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S096585642030714X | Passenger activities in terminals can be understood better in the current era when sensors are pervasive throughout airports . This study demonstrated the usefulness of combining multiple source data to investigate passenger behavior in airports . Objective time use and terminal activity participation data of 266 air passengers behavior at Taipei Songshan International Airport were collected from beacons a self developed mobile application and questionnaires . The study first investigated recall errors generated from self report questionnaires an approach commonly used in previous studies with a retrospective design . The study then assessed the participation and duration of terminal activities conducted by passengers with standard nested and mixed multiple discrete continuous extreme value models . The analysis results revealed that recall errors were associated with activity choice and duration and passenger characteristics . These errors were not random but systematic and could potentially lead to biased results in retrospective studies solely based on self report questionnaires . The estimation results of extreme value models generally confirmed the expected association of terminal activity choice with passenger characteristics such as more frequent retail store visits in female passengers than in male passengers . However the associations of passenger characteristics with activity duration could be consistent with or opposite to those with activity choice for example frequent flyers tended to consume food and beverages more frequently and spend a longer time in restaurants whereas passengers having a long free dwell time were less likely than those having a short free dwell time to consume F B but the duration was relatively long on average . Managerial implications for airports and retailers and recommendations for future air passenger behavioral studies were provided . | Passenger behaviors in airports are examined using data collected from beacons mobile phones and questionnaires. Recall errors in air passenger data with a retrospective design are not merely inaccurate but also biased. Passenger behaviors in terminals are intercorrelated and could be grouped into moving and sedentary activities. Passengers time budgets are crucial to the choice of sedentary activities because of their relatively long duration. |
S0965856420307217 | Ramp metering is known to be an effective freeway control measure that ensures the overall efficiency and safety of a highway system by regulating the inflow traffic on ramps . Therefore agencies are required to frequently assess the performance of their ramp meters . However one major challenge for the agencies conducting ramp metering performance assessments is the lack of knowledge about data requirements . Data requirements consist of the information regarding the duration of data collection for accommodation time and for the evaluation time . In this paper a non parametric statistic approach is proposed that is robust to the underlying distribution of the random variable . Meaning that the accuracy of the model is insensitive to the data distribution . For validation purposes three active ramps along State Route 51 in the Phoenix Metropolitan area Arizona are selected as the case study . ADOT altered their ramp control strategy from fixed time to responsive control and is attempting to know the extent of data required for assessing its new ramp metering strategy . For this particular case study the results suggest that two months worth of data is the minimum data sufficient for a ramp metering assessment . The proposed assessment approach can be transferred to other ramp metering applications to help traffic engineers efficiently tune up ramp metering strategies . | Examine how much data is enough for before and after studies. Proposed a non parametric statistic approach for ramp metering evaluation procedure. Two month is the minimum data collection period for robust ramp metering evaluation. Proposed a methodology that only considers a few assumptions. |
S0965856420307229 | A claimed benefit of real time information apps in public transit systems is the reduction of waiting time by allowing passengers to appropriately time their arrivals at transit stops . Although previous research investigated the overall impact of RTI on waiting time few studies examine the mechanisms underlying these claims and variations in its effectiveness over time and space . In this paper we theorize and validate the sources of RTI based users waiting time penalties | Public transit agencies publish real time information for use in mobile apps. We benchmark several strategies using empirical transit system performance data. Overall real time information does not outperform simply following schedule. Real time information can reduce waiting time for some users based on location. Including a time buffer improves the greedy approach used by popular apps. |
S0965856420307230 | This paper investigates the impacts of high speed rail development on regional equity in China during 20072017 . The equity in terms of economic output and HSR service is characterized at national divisional and provincial levels . The Gini indices associated with prefectures gross regional product per capita HSR connectivity and accessibility are measured to assess disparity from different aspects . Instead of measuring the effect of HSR entry by a dummy variable representing the presence of HSR service only this paper estimates the effects of HSR by various terms regarding the HSR presence network coverage service quality and equity of HSR development . In particular the HSR network coverage is captured by the number of prefectures connected to HSR . Service quality is characterized by the HSR connectivity and accessibility . The frequency and accessibility related metrics are further decomposed into two sub variables representing the intra and inter provincial metrics to differentiate the service availability and travel time between prefectures in a same or different province . The influence between neighboring or adjoining provinces on each others economic equity is identified by spatial autocorrelation effect . Our main findings include 1 National equity is gradually improved in terms of both GRP and HSR developments in China between 2007 and 2017 the provinces or divisions with larger GRP tend to be less equitable 2 The inauguration of HSR has positive correlation with provincial equity however the positive effect diminishes with the spread of HSR coverage 3 HSR accessibility has more significant effect on provincial economic equity than frequency 4 Effects of intra provincial accessibility and connectivity dominate inter provincial metrics 5 The prosperous and balanced HSR development in neighboring provinces helps promote provincial economic equity of one another . | Impact of HSR on regional disparity examined. Multiple disparity metrics for GRP HSR coverage travel time frequency. Inauguration of HSR has a positive correlation with provincial equity. Positive effect diminishes with the spread of HSR coverage. HSR accessibility has more significant effect on economic equity than frequency. |
S0965856420307242 | Attitudes towards travel mode choice have been regarded as bi polar evaluations of travel options that remain stable across time and context . Intra personal attitudes can be variable becoming more or less salient and changing in strength or valence across decisional contexts . This study draws on theoretical underpinnings of attitudinal ambivalence which proposes that a person can hold two dimensional evaluations about one attitude object simultaneously . The present research aimed to explore attitudinal ambivalence in relation to travel modes and examine the variability of attitudes in different contexts . Thirty semi structured interviews explored above average mileage car users and non car users experiences of attitudinal ambivalence in relation to various transport modes and under which circumstances . Thematic analysis found support for attitudinal ambivalence and context dependent attitude variability in relation to travel mode evaluations . Discussions of an a priori questionnaire confirmed the malleability of transport relevant attitudes . Transport relevant attitudes are complex and ambivalent . Attitudinal ambivalence and context dependent attitude variability has implications for transport research design interventions targeting travel related attitudes and policies aimed to reduce single occupancy driving . | Semi structured in depth interviews explored attitudinal complexity of above average mileage car users and non car users. Thematic analysis revealed attitudinal ambivalence and context dependent variability of transport relevant evaluations. Identified specific situations in which ambivalence is salient. Highlighted the complexity of aspects of transport convenience and inconvenience. Findings suggest that specific survey questions may be prone to ambiguity. |
S0965856420307291 | During the last decade the use of free floating carsharing systems has grown rapidly in urban areas . However little is known on the effects free floating carsharing offerings have on car ownership in general . Also the main drivers why free floating users sell their cars are still rarely analysed . | Survey of free floating carsharing users carried out in 11 European cities. Each SHARE NOW car replaces up to 20 private cars. The probability of selling private cars increases with kilometres by this service. City specific characteristics affect private car sales. The car fleet was reduced due to free floating carsharing in all cities. |
S0965856420307321 | This study examines the relationship between transport logistics foreign direct investment and economic growth in developing countries over the period 20002016 . A global panel data comprising of 46 developing countries were collected and divided into three sub panels European and Central Asian countries Middle East North African and Sub Saharan countries and East Asian Pacific and South Asian countries . Using GMM estimators we found that all underlying variables influence each other in the long run . The direction of causal relationship between the variables tended to vary across panels with different levels of significance . The results arising out of empirical analysis imply that transport and logistics infrastructure do contribute to FDI attractiveness and sustainable economic growth . These results would be of particular interest to policymakers working in developing countries and help them design and develop modern transportation and logistics coupled with interlinked technological factors which could possibly be used for sustainable economic development and which in turn would attract FDI . | We study the dynamic linkages among transport logistics FDI and economic growth. Empirical investigation considers 46 developing countries between 2000 and 2016. The 46 countries have been divided into three sub groups. We use the GMM estimators for econometric investigation. Positive and significant causal relationships are found between the variables. |
S0965856420307357 | The tourism industry is rapidly growing and the massification of certain areas is jeopardising the environment . Certain roads in protected areas or near tourist attractions are experiencing an increase in traffic volumes leading to higher pollution and noise levels and greater discomfort in the travel experience . To recommend measures intended to ensure a sustainable tourism industry without compromising the environment it is necessary to obtain further knowledge regarding tourists travel behaviour as it may differ from that of other travellers i.e . tourists might choose a route based on variables other than time and cost such as landscape or tourist attractions . | Survey of vehicle based tourists conducted in 2018 in Norway. Route features trip and socioeconomic characteristics were observed. Tourist route choice estimated using a path size correction logit model. Travel time road width and road scenery were significant. Sightseeing places outdoor activities and facilities were significant. |
S0965856420307370 | Understanding how traffic flows respond to fuel price changes is useful for traffic management . This study uses a dataset of 11.9 million hourly observations from 118 traffic count stations over 20102017 to investigate the relationship between gasoline prices and traffic flows in the state of New South Wales Australia . The findings suggest that higher gasoline prices reduce traffic flows with an average effect size of 0.04 in the hourly estimates . The elasticity is particularly pronounced during off peak periods both on weekdays and weekends . In contrast a positive effect of gasoline prices on traffic flows is observed for peak periods on weekdays . Evidence is also obtained that afternoon peak hour speeds are faster when gasoline prices are higher consistent with a lowering of traffic density . The research also finds a negative price elasticity of gasoline demand and that people are more likely to use public transport when gasoline prices are higher . The findings suggest that fuel excise plays a role in both reducing overall road dependence and alleviating the severity of some peak hour traffic jams . | The effect of fuel prices on traffic flows in New South Wales is studied. The dataset consists of 11.9 million observations. The average gasoline price elasticity of hourly traffic flows is 0.04. The gasoline price elasticity of weekday peak period traffic flows is positive. Higher fuel prices lead to faster travel speeds in peak afternoon periods. |
S0965856420307400 | As a special case of multitasking travel based multitasking typically refers to conducting a set of in vehicle activities while traveling . Travel based multitasking has an indisputable influence on offering a pleasant travel experience to transit users during their rides given that they can use their travel time to perform desirable activities and gain benefits in various form . For instance the in activities could help the rider free up time from his her schedule for the day . In this study we investigate how the worthwhileness of a travel based multitasking could be under the influence of the transit users lifestyle and socio demographics and the characteristics of the transit trip . Towards this we conducted an intercept survey focusing on the transit trips in the Chicago metropolitan area and analyzed it using latent class modeling approach . Per the results two classes of transit users could be identified | We explored latent lifestyles underlying travel based multitasking habits in transit. Implications for fostering transit oriented lifestyles in the future are discussed. Implications for manufacturing future autonomous transit systems are discussed. |
S0965856420307412 | Air cargo is vital to the modern supply chain because it provides efficient and timely delivery . In the past decade the development of high speed rail in China has resulted in significant impacts on air cargo traffic which has long been neglected by the existing studies . In this research we quantify such impacts using HSR entry dummy variables and employ a panel regression approach to capture the impacts specifically the impacts on air cargo volumes and flight frequencies . We conduct a case study using quarterly air cargo traffic data in China which contains 321 city pairs and spans between January 2011 and December 2017 . We separately analyze the impacts on belly hold cargo traffic and freighter cargo traffic . We first capture the general impacts on belly hold cargo traffic and freighter cargo traffic for all city pairs . Then to quantify the distance level impacts on belly hold cargo traffic we categorize city pairs into multiple groups according to their distance and apply the panel regression approach in each group . Our main results include The entry of HSR services reduces the belly hold cargo volumes and flight frequencies by 21.9 and 19.4 respectively The strongest impacts on belly hold cargo volumes and flight frequencies are observed in the medium haul group within a distance of 8001300km After the entry of HSR services the cargo volumes and flight frequencies of freighter cargo generally increase by 22.3 and 20.9 respectively The whole air cargo traffic in the measurement of cargo volumes and flight frequencies decreases after the entry of HSR and the impacts on whole air cargo volumes are relatively smaller than the belly hold cargo volumes in the short haul and long haul groups . | We investigate the impacts of HSR entry on air cargo traffic in China. We quantify the distance level impacts of HSR entry on air belly hold cargo traffic. We utilize Chinese air cargo traffic data from January 2011 to December 2017. The impacts of HSR on belly hold cargo traffic are stronger among medium haul flights Freighter cargo volumes and frequencies increase after the entry of HSR. |
S096585642030745X | With the rise of smart cities a number of new mobility services have emerged to drive changes in built environment policies . Up to date demand models are needed to capture the impact of these policies on emerging mobility enabled travel patterns . The study explores modeling requirements to assess the impact of such built environment policies . A synthetic population of New York City with a tour based nested logit mode choice model was developed with accessibility to bikesharing and ride hail services via smartphone ownership . The model results suggest Manhattanites have a value of time of 29 h consistent with the literature . Smartphone ownership is positively influenced by income and negatively influenced by age and in turn negatively impacts Citi Bike ridership relative to other modes available . The synthetic population is also applied to analyze two city scale built environment scenarios a hypothetical Amazon headquarter deployment and a Citi Bike service expansion . If Amazon succeeded in Long Island City it would have increased the number of trips to from that neighborhood by 239 of which FHVs would grow by over 441 and transit by 294 . It would have led to an increase of peak morning trips from 5000 up to at least 8000 . Citi Bikes expansion plan would grow ridership by 92 and if they were able to expand efficiently throughout NYC this would grow further to 210 over the baseline . | A synthetic population is created for NYC that includes emerging mobility. Mode choice is simulated with a tour based nested logit model. Emerging mobility choices include smartphone ownership model. Manhattan and non Manhattan market segments simulated. Scenarios include Amazon HQ in LIC and Citi Bike expansion. |
S0965856420307473 | China is now a global leader in the construction of high speed railways . However few studies have focused on the actual operational performance of Chinas HSR system which is revealed by high speed train services . This paper investigates the spatial distribution of Chinas HST services and the influencing factors are analyzed by using multiple stepwise regression . The results indicate that the total HST services in China have sharply increased in a short period but there are significant disparities in HST services available to different regions and cities . At the regional level Central and East China and Chinas major urban agglomerations have received more HST services while the HST services in West China have achieved faster growth . At the city level most cities in the southeastern coastal provinces and middle reaches of the Yangtze River have received more services largely due to the highly developed HSR infrastructure network there . The results of the stepwise regression show that the dominant factors in HST service allocation in China vary greatly at different spatial levels and in different regions . At the national level the urban socio economic performance and nature of the HSR infrastructure has a significant impact on the distribution of HST services . Additionally at the regional level the primary determinants of HST service allocation vary across regions which are closely associated with the disparity in socio economic development and the HST extension stages in different regions . | Investigate the spatiotemporal allocation and evolution of Chinas high speed train services. A multiple stepwise regression is perform to explore the determinants of HST service allocation. The results contribute to understanding the actual operational performance of Chinas HSR system. Implications are raised for Chinas future HSR development. |
S0965856420307497 | We explored the structure of public attitudes on whether self driving vehicles should be allowed on public roads through a four way typology of attitudes . We segmented participants based on a single item according to which participants allocated themselves to one of the four attitudinal groups and characterized the demographic and psychological profiles of the four groups in a paper and pencil survey in Tianjin China | We surveyed positive negative ambivalent and indifferent attitudes to whether SDVs are allowed on roads. Nearly half of the participants were in the ambivalent group followed by the positive group. Perceived benefit and risk ambivalence and interest in SDVs were not sufficient to describe the differences between the four groups. The four groups clearly differed on behavioral intention and willingness to pay. |
S0965856420307503 | Traffic engineers are making efforts to mitigate congestion and to improve efficiency at intersections . The symmetric intersection can increase the capacity of intersections and is economical practical efficient and convenient . The pedestrians crossing patterns tailored for SI has not yet been studied . This paper not only develops three pedestrian crossing patterns but also analyzes crossing patterns from the aspects of efficiency and safety . For efficiency delay models are proposed by considering through and diagonal pedestrian movements . For safety exposure conflicts and the number of potential traffic accidents are analyzed . Then delay and potential accidents are converted into money value respectively and the total cost is calculated . The case study results show that SI performs better in terms of increasing capacity and decreasing pedestrian delay compared with conventional intersection . Crossing pattern 1 is efficient but unsafe while the total delay and safety cost of pattern 3 is usually the highest . The sensitivity analysis indicates that cycle length has a negative impact on average pedestrian cost and if critical flow ratio increases the average pedestrian cost of pattern 1 and pattern 3 will increase and decrease respectively . Furthermore the best pedestrian pattern choice under different values of cost per accident and cost of pedestrian delay is also studied . | Designing and comparing three pedestrian crossing patterns for SI. Considering both through and diagonal pedestrians delay. Integrating forty eight delays models into three categories. |
S0965856420307515 | User perception plays a critical role in pedestrian infrastructure usage . Indeed the perceptional influence varies across individuals and it is imperative to consider their response heterogeneity in modelling individual travel intentions . The present study develops a novel framework to understand the pedestrian perception and further identify their impact on future travel decisions . In this framework the individual pedestrian perception of an area is captured using a Level of Service index and the overall set of LOS is categorized using a clustering methodology . The future travel behavior is modelled using a single step estimation that incorporates the effect of both response heterogeneity and latent individual correlation . The proposed framework is utilized in estimating the LOS categorization and the future willingness to walk in the city of Coimbatore India . The results found a significant response heterogeneity among respondents in Coimbatore and consequently emphasized the need for incorporating these taste variations in the travel behavior models . An increase in LOS encouraged the respondents to walk and further walk longer . Moreover females were willing to pursue walking and or walk more distance compared with males . The positive ordinal interval for LOS A to C indicated an acceptability for this LOS range among pedestrians compared with LOS E to F having a negative range . In the individual assessment of LOS variables almost all study areas were found requiring an improvement with respect to the management of footpath vendors and footpath cleanliness . | Framework incorporating latent individual correlation in choice models. Incorporation of response heterogeneity in choice models. A PLOS categorization based on LOS index. Need to incorporate response heterogeneity and response correlation. Need to reduce pedestrian conflict with motor vehicles |
S0965856420307539 | The aviation industry is one of the fastest growing sectors in producing carbon emissions . In order to reduce its carbon footprint and to respond to the increasing number of people concerned about the impact caused by air transport on climate change the International Civil Aviation Organization has recently passed the carbon neutral growth from 2020 resolution requiring that the global net CO | The WTP ranges between 12 and 38 per ton and between 14 and 66 per flight. It is higher for projects aimed at forest protection afforestation reforestation. It is significantly lower if the description of the project financed is missing. Gender occupational status and education degree influence the WTP. Also travel habits and environmental consciousness influence the WTP. |
S0965856420307606 | The current paper contributes to the literature on the relationship between economic growth fuel prices and the demand for gasoline and diesel within the transportation sector by assembling a wide panel dataset of fuel consumption and prices for 35 OECD and 83 Non OECD countries . The unbalanced data spans 19782016 with the full 39years of data for 36 countries . In addition our dynamic panel estimates address nonstationarity heterogeneity and cross sectional dependence . The OECD panel price elasticity for gasoline is around 0.7 or about three times that for the non OECD panel whereas the OECD price elasticity for diesel is only modestly larger than the non OECD elasticity . For gasoline the non OECD GDP elasticity is around 1.0 or about twice that for OECD countries . For the OECD panel the diesel GDP elasticity is about three times that of the OECD GDP elasticity for gasoline whereas for the non OECD panel the two GDP elasticities are about the same . For non OECD countries subpanels based on geography and income produced mostly similar results . We found no evidence of GDP or price asymmetric effects for the 19782016 period . Lastly the large and statistically significant transportation price elasticities reported here provide stark contrast to the economy wide energy price elasticities calculated in Liddle and Huntington . | Gasoline price elasticity for OECD is 0.7 three times that for non OECD . Diesel price elasticity for OECD is 0.35 modestly larger than that for non OECD . Gasoline GDP elasticity for non OECD is around 1.0 twice that for OECD . For OECD diesel GDP elasticity is considerably larger than that for gasoline. For non OECD diesel GDP elasticity is similar to that for gasoline. |
S0965856420307618 | Safety is always the first concern for a ships navigation in the Arctic . Ships navigating in the Arctic may face two main accident scenarios i.e . getting stuck in the ice and ship ice collision . More specifically excessive speed may cause severe hull damage while a very low speed may lead to a high probability of getting stuck in the ice . Based on this multi risk perspective an integrated risk assessment model was proposed to obtain the overall risk using the Bayesian Network in which the probabilities of accident occurrence and the severities of the possible consequences for ships getting stuck in the ice and for ship ice collision could be estimated . Then the voyage data collected from Yong Shengs Arctic sailing in 2013 were inputted into the integrated risk assessment model to perform a case study . A sensitivity analysis was performed to validate the proposed model and reveal the inherent mechanisms behind these two accidental scenarios . The proposed model can be applied to identify the safe speed for Arctic navigation under various ice conditions a duty that is traditionally performed by well trained crew members but which entails too many uncertainties . The results can to some extent provide useful suggestions for navigators . They are imperative in supporting decision making to shape the Arctic policy and to enhance the safety of Arctic shipping . | The risks of getting stuck in ice and ship ice collision are analyzed. Bayesian Network is used to construct the risk assessment model. A case study of Chinese merchant vessel Yong Sheng is carried out. A safe speed identification method for ships in ice covered waters is proposed. |
S0965856420307667 | To relieve road congestion a variety of transport demand management measures have been implemented all over the world . The success of these measures has been found to depend at least partially on users perception about them . Several articles have jointly addressed the acceptability of public transport improvement and road pricing . However these research works have not considered discounts on existing toll roads to relieve congestion on free alternative expressways . The objective of this paper is to study the combined acceptance of different congestion calming policies at the suburban level including the promotion of toll roads and measures to foster the use of transit . To that end a survey was conducted among travelers on a commuting transport corridor in the region of Madrid aimed at exploring their perceptions towards four TDM measures and a choice modeling framework was conducted . The scenarios considered are carrot policies and the results of the analysis indicate that enhancing public transportation enjoys more support among respondents than toll promotions . Motorists using the free highway are more willing to use transit improvements than to opt for a toll road as an alternative regardless of the proposed toll discounts . Among the TDM measures explored the least supported is the promotion of toll discounts associated with non household carpooling . Furthermore according to the results the adoption of these TDM measures is more influenced by trip related factors in particular the trip frequency and the mode of transport than by socio economic characteristics of the traveler . Finally some geodemographic attributes of the residential location are also found to be statistically significant . | This article compares the acceptance of transit improvements and incentives to use an underutilized toll road. Toll discounts are less acceptable than transit improvements especially those related to carpooling. Incentives to use the toll road are not enough to attract free highway drivers. Socioeconomic factors play a smaller role compared to trip related variables. |
S0965856420307680 | This paper studies the impact of offices on urban freight traffic . Research on freight activity generated by offices is very limited because they are not seen as important contributors to urban freight traffic and because the amount of deliveries per office is very small compared to the number of deliveries per establishment in freight intensive sectors . However the number of offices in cities is so large that altogether they represent a significant share of urban deliveries and generate a nonnegligible share of urban freight traffic . Hence the relevance of quantifying their freight trip generation . This paper uses the City of Stockholm as a case study . The author collected data from offices and other establishments estimated regression models and applied them to the city . The results show that offices represent 36 of establishments in Stockholm 62 of employees and are responsible for 15 of freight trips generated in the city . | This paper proposes a set of models to quantify freight trip generation of offices. This paper applies the model to assess the contribution of offices to the overall freight traffic of the city of Stockholm. Policy implications and applications for public authorities and other stakeholders are presented. |
S0965856420307710 | Several studies have made manifest that involvement with public transport play a key role in the intentions of its use . However conflicting models exist in the literature about involvements role in the relationship between service quality satisfaction and behavioral intentions or loyalty . Previous studies suggest all possible roles antecedent mediator moderator and direct effects . A structural equation modeling approach is applied here to further understand the role of involvement with public transport comparing eight alternative models and using data from a single survey carried out in five European cities . Later the study uses a multiple indicators and multiple causes structural equation modeling approach to analyze the effect of heterogeneity present in the data over the four constructs considered . This comprehensive methodological approach provides a number of noteworthy findings including the empirical verification that satisfaction is a full mediator between service quality and involvement and involvement is a full mediator between satisfaction and behavioral intentions . The results further suggest that involvement is the factor that contributes most to behavioral intentions or loyalty followed by service quality perceptions and satisfaction . Lastly this study demonstrates the relevance of controlling for heterogeneity in users perceptions so as to obtain more robust relations among factors and identify significant differences among market segments which could prove useful for public transport operators or policy makers . | The relationship among SQ SA INV and BI is analyzed using 8 models and 5 samples. Results suggest that INV is a complete mediator between SA and BI or loyalty. Results also suggest that SA is a complete mediator between SQ and INV towards PT. INV is the factor with the highest effect on BI followed by SQ and SA. The following sociodemographic characteristics produce heterogeneity in the factors. City household location gender age travel frequency education and income level. |
S0968090X18307769 | An important component of airport landside operations involves providing assistance to passengers with reduced mobility . These operations are typically managed by third party contractors which leverage a team of escorts and a set of wheelchairs to provide mobility assistance services . The performance of these systems relies critically on the dispatch of escorts and wheelchairs to serve each traveler request . Sub optimal dispatch can lead to negative individual and system wide implications such as long passenger wait times customer dissatisfaction or added delays in flight departures . This paper reports the outcomes of a collaboration with the Pittsburgh International Airport that involved three steps . First the collection and digitization of data provided visibility into demand for mobility assistance services and historical performance of the system . Second we propose an original integer programming model to optimize and support the assignment of escorts to traveler requests and we develop an efficient solution approach based on a rolling algorithm to enable the implementation of the model with realistic problem sizes . We verify that the models outputs are consistent with insights obtained from the historical records of operations and identify opportunities to enhance the level of service without increasing system capacity . In particular the results suggest that improvements in information flows and in communication between airlines the central dispatcher and passenger escorts can result in significant dispatch improvements . Third we leveraged these insights by developing a tablet application to provide real time visibility into traveler requests dispatch recommendations and data visualizations for continued performance assessment and enhancement . | Mobility assistance services are becoming key components in landside management. Real world data on escort operations are acquired digitized and analyzed. An integer programming model optimizes escort dispatch to minimize wait times. Level of service is improved with elevated escort utilization rates. Web based applications are developed to store visualize and forecast demand. |
S0968090X18308179 | In vehicle longitudinal control improved comfort and reduced operation workload for human drivers are achieved with the ACC which still requires the driver to maintain full attention on monitoring meanwhile the risk of distraction and fatigue rises resulting from the long term supervising task which has a strong impact on the successful takeover . The key point to make full use of ACC advantages and make up humans weakness on supervising task is the reasonable arrangement of control time of ACC and human driver . In this paper an MPC based optimized switching strategy of longitudinal driving authority transition is proposed which aims to provide proper advice for human drivers to handover and takeover control authority through minimizing the overall index consisted of the operation workload fuel consumption takeover risk and tracking errors . In addition a new driver longitudinal model considering actual reaction time delay and insensitive distance perception of human drivers is proposed as well which combines with ACC to constitute a typical switched control system called the switched driving model as the predictive model for MPC . The stable condition of the new driver longitudinal model is derived by using describing function method and a sufficient condition to ensure steady switched system is given by using the Lyapunov method and LMI approach . The results of simulator experiments show that the new driver model describes the car following behavior of real human driver better . Whats more the simulation results demonstrate that the performance index of switched driving is smaller than the human driving and ACC driving only and the optimization time is short enough to meet the requirement of engineering practice . | A new driver model is developed from the view of human factors. An MPC based optimized switched driving strategy is proposed. The simulator experiment is conducted to verify the new driver longitudinal model. The performance index of switched driving is smaller than the human and ACC driving. The real time of algorithm can meet the requirement of engineering practice. |
S0968090X1830857X | The problem of operating exclusive bus corridors that have segments with bidirectional lanes is treated . On these lanes only one direction of movement is allowed when a bus is present . Such construct requires less road space which is a scarce resource in dense urban areas and thus may be the only feasible alternative for the installation of exclusive bus corridors . The system model includes limits on bus passenger capacity . The control method for real time operation integrates bus headway corrections and bus priority through signalized intersections while enforcing mutual exclusion of opposing buses on the bidirectional lanes . Effectively the control avoids bus bunching over the entire corridor and coordinates the passage of opposing buses on bidirectional lanes . The objective is to minimize the total waiting time of passengers both onboard and at stops . Simulation results indicate the applicability of the integrated holding and priority bidirectional lane control method . | Integrated headway and bus priority control for bidirectional lane segments. May represent in many cases the only feasible way for system deployment. Relationship between the headway and bus travel time in the bidirectional segments. |
S0968090X18310660 | Unmanned Aerial Vehicles are being increasingly deployed in humanitarian response operations . Beyond regulations vehicle range and integration with the humanitarian supply chain inhibit their deployment . To address these issues we present a novel bi stage operational planning approach that consists of a trajectory optimisation algorithm and a hub selection routing algorithm that incorporates a new battery management heuristic . We apply the algorithm to a hypothetical response mission in Taiwan after the Chi Chi earthquake of 1999 considering mission duration and distribution fairness . Our analysis indicates that UAV fleets can be used to provide rapid relief to populations of 20 000 individuals in under 24h . Additionally the proposed methodology achieves significant reductions in mission duration and battery stock requirements with respect to conservative energy estimations and other heuristics . | A framework to model UAV based humanitarian logistics missions is defined. A mixed integer programming formulation for the problem is presented. An effective Large Neighbourhood Search approach is proposed to solve this problem. The algorithm optimises trajectories depot location and battery allocation. |
S0968090X18310684 | This paper considers the problem of measuring spatial and temporal variation in driver productivity on ride sourcing trips . This variation is especially important from a drivers perspective if a platforms drivers experience systematic disparities in earnings because of variation in their riders destinations they may perceive the pricing model as inequitable . This perception can exacerbate search frictions if it leads drivers to avoid locations where they believe they may be assigned unlucky fares . To characterize any such systematic disparities in productivity we develop an analytic framework with three key components . First we propose a productivity metric that looks two consecutive trips ahead thus capturing the effect on expected earnings of market conditions at drivers drop off locations . Second we develop a natural experiment by analyzing trips with a common origin but varying destinations thus isolating purely spatial effects on productivity . Third we apply a spatial denoising method that allows us to work with raw spatial information exhibiting high levels of noise and sparsity without having to aggregate data into large low resolution spatial zones . By applying our framework to data on more than 1.4 million rides in Austin Texas we find significant spatial variation in ride sourcing driver productivity and search frictions . Drivers at the same location experienced disparities in productivity after being dispatched on trips with different destinations with origin based surge pricing increasing these earnings disparities . Our results show that trip distance is the dominant factor in driver productivity short trips yielded lower productivity even when ending in areas with high demand . These findings suggest that new pricing strategies are required to minimize random disparities in driver earnings . | Current ride sourcing dispatching and pricing schemes do not adequately ensure driver equity. Drivers at the same origin enjoyed different continuation payoffs after getting dispatched on trips to different locations. Origin based surge pricing increased these disparities in drivers earnings. Trip distance is a major predictive factor on driver productivity. New pricing strategies are required to guarantee driver equity |
S0968090X18311148 | This paper investigates optimal parking pricing with parking permit management in a many to one park and ride network in which each origin is connected to the destination by an auto path a parallel rail transit path and a P R path . First we revisit the parking pricing scheme at P R parking facility with parking restraint and find that it fails to eliminate extra costs arising from competition for inadequate parking spots . Fortunately competition for inadequate parking spots can be eliminated by a strategy of parking permits distribution . Then we investigate the optimal number of parking permits distributed to each OD pair in a many to one park and ride network . The problem is formulated as a mixed integer linear program . However parking permit management is less efficient than parking pricing at P R facility when parking provision is sufficient . Therefore we propose two hybrid management schemes with parking pricing and parking permit to reduce system travel cost . Joint implementation of parking pricing and parking permit not only alleviates the traffic congestion but also eliminates the competition for inadequate parking space . Next the bi level programming models are proposed to determine the optimal parking fees at P R parking facilities in the hybrid management schemes . In the bi level programming models the number of parking permits assigned or held by each OD pair is an implicit function with respect to parking fee . A global optimum oriented solution algorithm and simulated annealing algorithm are used to solve the MILP and bi level programming models respectively . Numerical examples are carried out to show that the hybrid schemes with parking pricing and parking permits are more effective than both pure parking pricing scheme and pure parking permits management scheme . | Optimal parking pricing with parking permits management in a many to one park and ride P R network. A hybrid management with parking pricing and parking permit to reduce system travel cost. A mixed integer linear program MILP to determine system optimum parking permits distribution. Comprehensive parking management in response to inadequate parking space. |
S0968090X18311574 | The technological barriers to automated driving systems are being quickly overcome to deploy onroad vehicles that do not require a human driver onboard . ADS have opened up possibilities to improve mobility productivity logistics planning and energy consumption . However further enhancements in productivity and energy consumption are required to reach CO | Automated Driving Systems ADS affect optimum setup of propulsion system in battery electric heavy vehicles BEHV . ADS makes BEHVs profitable in longer travel ranges. ADS dedicated BEHVs have lower optimal speeds than vehicles with a human driver. Driving slow is cheaper in ADS dedicated BEHVs than in conventional heavy vehicles. Vehicle infrastructure optimization reduces the total cost of ownership of BEHVs. |
S0968090X18311872 | In this paper a new multi class urban traffic model is proposed based on the features of a single class urban traffic model and the characteristics of a multi class freeway traffic model . The heterogeneous traffic flow is represented using the concept of Passenger Car Equivalent for congestion and free flow regimes separately . The proposed multi class urban traffic model is intended for model based control applications . The single class model and the proposed multi class traffic model are compared with microscopic simulation data obtained using the SUMO open source simulator . The two models are calibrated through optimal parameter estimation and their performance is evaluated and compared by taking into account the error index between the models and the simulation data . Simulation results show that the multi class model gives a significantly better fit . | The multi class S model describes the heterogeneous flow of vehicles. The performance of multi class S model is compared with the single class S model using microsimulation as a reference. The computation time of the macroscopic models does not depend on the number of vehicles. |
S0968090X18312117 | Multi day activity travel patterns help create potential vehicle usage profiles that contain vehicle operations and battery status under different scenarios with varying location based charging opportunities based on travel needs and charging availability behaviors . Utilizing a multi day data sampling method analyses of scenarios are designed to provide insights on bounds of potential BEV market under different charging opportunities including level 2 activity charging and level 3 trip charging . Single day data results tend to overestimate travelers BEV feasibility assuming that multi day sample data provides accurate estimations . Facility utilization can be improved without affecting travelers charging demand under correct pricing scheme for most cost sensitive users . Smart grid charging strategy can greatly reduce the total number of operating chargers during the same time in a day and BEV users charging behaviors have minor impact on this improvement . Our numerical results indicate that an appropriate number of chargers installed in shopping and leisure locations should be more profitable and have higher charger utilization rate since those chargers help cover BEV users trips . | We perform a multi day scenario analysis on potential uses feasibility and charging requirements of Battery Electric Vehicles BEVs . It is shown that single day analysis overestimates BEV feasibilities compared to multi day analysis. We employ detailed activity based charging behaviors and assumptions and derive managerial policy and planning insights of charging stations deployment. Four different charging demand management strategies immediate charging optimal charging factional average charging and fractional optimal charging are studied and results indicate that these charging strategies reduces infrastructure requirements. |
S0968090X18312129 | Network travel time reliability can be represented by a relationship between network space mean travel time and the standard deviation of network travel time . The primary objective of this paper is to improve estimation of the network travel time reliability with network partitioning . We partition a heterogeneous large scale network into homogeneous regions with well defined Network Fundamental Diagrams using directional and non directional partitioning approaches . To estimate the network travel time reliability a linear relationship is estimated that relates the mean travel time with the standard deviation of travel time per unit of distance at the network level . The impact of different partitioning approaches as well as the number of clusters on the network travel time reliability relationship are also explored . To estimate individual vehicle travel times we use two distinct approaches to allocate vehicle trajectories to different time intervals namely trajectory and sub trajectory methods . We apply the proposed framework to a large scale network of Chicago using a 24 h dynamic traffic simulation . Partitioning and travel time reliability estimation are conducted for both morning and afternoon peak periods to demonstrate the impacts of travel demand pattern variations . The numerical results show that the sub trajectory method for the network travel time reliability estimation and the directional partitioning with three clusters have the highest performance among other tested methods . The analyses also demonstrate that partitioning a heterogeneous network into homogeneous clusters may improve network travel reliability estimation by estimating an independent relationship for each cluster . Also comparing morning and afternoon peak periods suggests that the estimated parameter for the linear network travel time reliability relationship is directly related to the coefficient of variation of density as a measure of spatial distribution of congestion across the network . | Exploring network partitioning impacts on the reliability relation in large networks. Proposing a modified dynamic methodology to partition a large scale network. Comparing two proposed approaches in literature to define the reliability relation. Results show that sub trajectory method is more consistent with network partitioning. Positive impacts of partitioning on the reliability parameter estimation for clusters. |
S0968090X18312749 | We introduce the Stochastic Maintenance Fleet Transportation Problem for Offshore wind farms in which a maintenance provider determines an optimal medium term planning for maintaining multiple wind farms while controlling for uncertainty in the maintenance tasks and weather conditions . Since the maintenance provider is typically not the owner of a wind farm it needs to adhere minimum service requirements that specify the required service . We consider three of such settings perform all maintenance tasks allow for a fraction of unscheduled tasks and incentivize to perform maintenance rather quickly . We provide a two stage stochastic mixed integer programming model for the three SMFTPO settings and solve it by means of Sample Average Approximation . In addition we provide an overview of the what we discovered non aligned modeling assumptions in the literature regarding operational decisions . By providing a series of special cases of the second stage problem resembling the different modeling assumptions we aim to establish a common consensus regarding the key modeling decisions to be taken in maintenance planning problems for offshore wind farms . We provide newly constructed and publicly available benchmark sets . We extensively compare the different SMFTPO settings and its special cases on those benchmark sets and we show that the special case reformulations are very effective for solving the second stage problems . In addition we find that for particular cases established modeling techniques result in overestimations and increased running times . | A tactical maintenance planning model in offshore wind is introduced. Uncertainty of weather conditions and maintenance tasks is included. Three distinct minimum service requirements are introduced within this context. It is shown that different modeling decisions impact the computational efficiency. With Sample Average Approximation we provide solutions to the stochastic problem. |
S0968090X18312750 | Customer booking prediction is essential for On Demand Transport services especially for those in rural and suburban areas where the demand is low variable and often regarded as unpredictable . Existing literature tends to focus more on the prediction of demand for traffic classical public transport and urban On Demand Transport service such as taxi Uber or Lyft in areas with higher and less variable demand in which popular time series prediction methods can be employed . This paper proposes an ensemble learning framework to predict the customer booking behaviour and demand using the observed data of a suburban On Demand Transport service where data scarcity is a challenge . The proposed method which is called as Class specific Soft Voting is found to be the most accurate prediction method when compared to popular supervised classification methods such as Logistic Regression Random Forest Support Vector Machine and other ensemble techniques . | A new ensemble algorithm to combine results form multiple predictors. Prediction of customer booking behaviour in on demand transport. An analysis of customer booking behaviour from a real data |
S0968090X18313408 | Pre tactically managing the imbalances of the network and organizing the resources of the airspace is one of the main objectives of Dynamic Demand Capacity Balancing . Introducing Short term Air Traffic Flow and Capacity Management measures such as minor ground delays or slight speed adjustments applied to a selected number of flights on the day of operations supports the dDCB process by reducing the traffic complexity and the probability of Air Traffic Controllers interventions . This paper introduces a rolling horizon methodology for detecting concurrence events analysing their trajectory interdependencies and applying a strategic mitigation measure that shifts the Estimated Take Off Time within the assigned Calculated Take Off Time window . The methodology proposes a collaborative decision making process for a better coordination of departures from airports feeding airspace volumes with high air traffic demand . The experimental part of this paper aims at showing the potential benefits of such a STAM procedure by applying the methodology to distribute the demand of a sector located in the London Terminal Manoeuvring Area . Experiments have considered regulated traffic scenarios where ETOT were allocated in order to reduce departure time uncertainties . Lastly it is analysed the impact of the parameters used by the methodology to calculate the mitigation measures safe separation criteria look ahead time and number of coordinated airports . | New departure synchronization mechanism in a Multi Airport system to reduce the probability of separation minima infringement. Airspace digitalization for efficient potential concurrence event detection and mitigation. New interdependency metrics for reducing downstream domino effects in ATM. Rolling horizon methodology for detecting concurrence events analysing their trajectory interdependencies and applying a strategic mitigation measure that shifts the Estimated Take Off Time ETOT within the assigned Calculated Take Off Time CTOT window. Use Constraint Programming models supporting optimal mitigation measures. Experimental work showing the potential benefits of such a STAM procedures by applying the methodology to distribute the demand of a sector located in the London Terminal Manoeuvring Area LTMA . |
S0968090X18313767 | Although mixed traffic including both autonomous vehicles and human driven vehicles is expected to prevail in the foreseeable future our current understanding of the longitudinal characteristics of mixed traffic is limited and in particular lacks evidence from field experiments . To bridge this gap we designed and conducted a set of field experiments to reveal differences in car following behaviors between a human driver following AV and following HV on both constant speed traffic characteristics with discrete speeds and dynamic car following behaviors with continuous speeds in both the indifferentiable and differentiable appearance settings of the AV . We recruited 10 drivers for the experiment 14 runs for each driver and collected position and speed data of the tested vehicles along their complete trajectories based on vehicle gaps headways and standard deviations of vehicle speed . A K means clustering algorithm was applied to classify drivers based on their responses in following AV vs. following HV with both constant speed and dynamic speed characteristics . The analyses of the differentiable appearance setting show that different drivers exhibit different behaviors in following AV vs. following HV some are AV believers some are AV skeptics and the others are insensitive . Yet in the indifferentiable appearance setting there is no significant difference between following a lead AV and following a lead HV . This reveals that drivers response to the lead vehicle depends on their subjective trusts on AV technologies rather than the actual driving behavior . The results suggest that depending on the characteristics and composition of the drivers classic car following behavior in pure HV traffic may need to be updated for modeling mixed traffic in the near future . | Revealing differences between a human driver following AV and following HV. Considering both constant speed traffic and dynamic car following behaviors. Proposing a driver classification approach to separate different driving behaviors. |
S0968090X18313810 | The area based heterogeneous traffic has significant differences from the lane based homogeneous traffic . In area based traffic drivers generally ignore the lane markings and perceive the entire road space while progressing longitudinally . The traditional car following and lane changing models are not directly applicable to model such driving behaviour . | A novel microscopic modelling framework for area based non lane based heterogeneous traffic flow. MNL model for the area selection of the vehicle movement. Modified IDM model for the movement of the vehicle. Model is throughly tested and applied on real trajectory data from India. |
S0968090X18314578 | The electrification of city bus systems is an increasing trend with many cities replacing their diesel buses with battery electric buses . Due to limited battery capacities and to random battery discharge rateswhich are affected by weather road and traffic conditionsBEBs often need daytime charging to support their operation for a whole day . The deployment of charging infrastructures as well as the number of stand by buses available has a significant effect on the operational efficiency of electric bus systems . In this work a stochastic integer program has been developed to jointly optimise charging station locations and bus fleet size under random bus charging demand considering time of use electricity tariffs . The stochastic program is first approximated by its sample average and is solved by a customised Lagrangian relaxation approach . The applicability of the model and solution algorithm is demonstrated by applications to a series of hypothetical grid networks and to a real world Melbourne City bus network . Managerial insights are also presented . | Optimize the battery electric bus charging facility location and fleet size problem. Consider stochastic charging demand and time of use electricity tariffs. Develop a stochastic integer program and a customized Lagrangian Relaxation algorithm. |
S0968090X1831564X | Express bus services are services that skip some of the stops along their routes to provide a faster ride for particularly demanded trips on a corridor . There is a growing literature on express services that focuses on route design and performance evaluation . In this work we study a simplified transit corridor where a regular service operates in tandem with an end to end express service . Assuming that passengers minimize their expected travel and waiting times we show that even if the system has enough aggregate capacity it may present a specific range of frequencies for the express service where it attracts more demand than it can actually fulfill . We call this range the danger zone of express services . When frequencies fall within the danger zone a queue of passengers will form at the station . Applying queuing theory we obtain expressions to estimate these queues and the associated waiting times expected travel times and social costs of the system . We show that even when the station has unlimited passenger capacity the performance of the system can be greatly affected in the danger zone . If the station has indeed limited capacity the scenario can be much worse if the queue grows to the point of saturating the station a vicious circle ensues that amplifies the negative effects of the danger zone . | We identify a new phenomenon we call the danger zone of express services. Raising express service frequencies can damage the level of service in a corridor. Under certain conditions this effect occurs in a specific range of frequencies. The effect happens when the express draws in more demand than it can carry. We use queuing theory to model and measure this effect on an idealized corridor. |
S0968090X18315791 | The advent of autonomous driving technologies has created a crucial need for upgrading conventional traffic control and lane management strategies in large cities . In this research we design an optimal lane management strategy for corridors with a heterogeneous demand of human driven autonomous and communicant autonomous vehicles . In a monocentric city setting we dynamically control the inflow of the network by optimizing the size of CAV platoons in the corridors based on the instantaneous condition of the integrated system . These corridors can potentially have three types of lanes for vehicles with different levels of automation technology . We model the multiple lane type corridors as sets of parallel bottlenecks with general distributions of multiclass demand . The dynamics of the congestion in the network is also modeled using the macroscopic network fundamental diagram . To study the impacts of the rise in the penetration rate of AVs and CAVs on the performance of the system we derive a closed form representation of the model . We show that the increase of the delay in the network with the rise in the penetration rate of AVs and CAVs can have a stable an unstable or a hybrid pattern . To optimize the system we minimize a weighted summation of the experienced delay in the corridors and the total travel time in the urban network by optimizing the number of lanes of each type and the dynamic size of the CAV platoons . The results of the San Francisco case study show that implementing an optimal lane management strategy can reduce the experienced delay in the corridors up to 78 with a rise in the AV CAV penetration rate . By dynamically controlling the size of the CAV platoons in the automated highway of the Bay Bridge we limit the increase of the travel time in the downtown network as low as 5 . | We design an optimal lane management strategy for a heterogeneous traffic condition. We dynamically control the network inflow by optimizing the size of the CAV platoons. The multiple lane type corridors are modeled as sets of parallel bottlenecks. The dynamics of the congestion in the network is modeled using the MNFD. We solve the optimization problem for the city of San Francisco CA. |
S0968090X18315870 | This paper proposes a methodology to characterize and evaluate the performance of the aircraft operation in complex systemized terminal manoeuvring area based on the study of its standard routes structure and their actual traffic . | Trajectory analysis could be used to determine the deviation of aircraft trajectories. Predicting deviation patterns in the airspace helps to improve air traffic control. Determining where when are conflicts produced help to release the airspace. London s terminal airspace contains high adherence and low adherence routes. |
S0968090X1831622X | In the era of smart cities Internet of Things and Mobility as a Service private operators need to share data with public agencies to support data exchanges for living lab ecosystems more than ever before . However it is still problematic for private operators to share data with the public due to risks to competitive advantages . A privacy control algorithm is proposed to overcome this key obstacle for private operators sharing complex network oriented data objects . The algorithm is based on information theoretic k anonymity and using tour data as an example where an operators data is used in conjunction with performance measure accuracy controls to synthesize a set of alternative tours with diffused probabilities for sampling during a query . The algorithm is proven to converge sublinearly toward a constrained maximum entropy under certain asymptotic conditions with measurable gap . Computational experiments verify the applicability to multi vehicle fleet tour data they confirm that reverse engineered parameters from the diffused data result in controllable sampling error and tests conducted on a set of realistic routing records from travel data in Long Island NY demonstrate the use of the methodology from both the adversary and user perspectives . | A privacy control mechanism is proposed to allow mobility operators to share data. An algorithm is proposed to generate a tour set and diffusion to maximize entropy. The algorithm tests illustrate how to control the tour diffusion by accuracy tolerance. The algorithm is illustrated in a case study of shared taxi tours from Long Island trips. |
S0968090X18316577 | Vacant taxi drivers passenger seeking process in a road network generates additional vehicle miles traveled adding congestion and pollution into the road network and the environment . This paper aims to employ a Markov Decision Process to model idle e hailing drivers optimal sequential decisions in passenger seeking . Transportation network companies or e hailing drivers exhibit different behaviors from traditional taxi drivers because e hailing drivers do not need to actually search for passengers . Instead they reposition themselves so that the matching platform can match a passenger . Accordingly we incorporate e hailing drivers new features into our MDP model . The reward function used in the MDP model is uncovered by leveraging an inverse reinforcement learning technique . We then use 44 160 Didi drivers 3 day trajectories to train the model . To validate the effectiveness of the model a Monte Carlo simulation is conducted to simulate the performance of drivers under the guidance of the optimal policy which is then compared with the performance of drivers following one baseline heuristic namely the local hotspot strategy . The results show that our model is able to achieve a 17.5 improvement over the local hotspot strategy in terms of the rate of return . The proposed MDP model captures the supply demand ratio considering the fact that the number of drivers in this study is sufficiently large and thus the number of unmatched orders is assumed to be negligible . To better incorporate the competition among multiple drivers into the model we have also devised and calibrated a dynamic adjustment strategy of the order matching probability . | Imitation learning is applied to estimate the reward function. The first to calibrate a dynamic adjustment strategy of order matching probability. E hailing drivers performance can be improved in comparison to other strategies. |
S0968090X18316759 | This paper proposes a new hyperpath based dynamic trucking equilibrium assignment model . Unlike existing freight assignment models we focus on the interactions between individual truck operators that solely compete for loads advertised on an online freight exchange . The competitors are assumed to follow optimal bidding and routing strategies represented using a hyperpath to maximize their expected profit . The proposed DTE model predicts system wide truck flows identifies efficiency improvements gained by network wide visibility and lays the foundation for building a system optimal model . We rewrite the DTE conditions as a variational inequality problem and discuss the analytical properties of the formulation including solution existence . A heuristic solution algorithm is developed to solve the VIP which consists of three modules a dynamic network loading procedure for mapping hyperpath flows onto the freight network a column generation scheme for creating hyperpaths as needed and a method of successive average for equilibrating profits on existing hyperpaths . The model and the solution algorithm are validated by numerical experiments constructed from empirical data collected in China . The results show that the DTE solutions outperform with wide margin the benchmark solutions that either ignore inter truck interactions or operate trucks according to suboptimal routing and bidding decisions . | A hyperpath based dynamic trucking equilibrium DTE assignment model is proposed. The model predicts system wide truck flows and identifies efficiency improvements. A variational inequality problem VIP model is formulated and solved heuristically. The model is validated by experiments constructed from data collected in China. The DTE solutions generate diverse and fair routing bidding strategies. |
S0968090X18316760 | This study proposes a state space model that estimates traffic states over a two dimensional network with alternative routes available by a data assimilation technique that fuses probe vehicle data with a traffic flow model . Although a number of studies propose traffic monitoring methods based on physical flow dynamics using sensing data such as probe vehicle and traffic detector data they are basically limited to traffic monitoring along a simple road section . This study extends the analysis to a two dimensional network in which several alternative routes exist for each OD with consideration of the route choice behaviours of users . Our proposed method employs sequential Bayesian filtering with a cell transmission model for the flow model and probe vehicle data . From the probe vehicle data not only cell densities but also diverging ratios are assumed to be measured and these measurements are assimilated into the flow model . The model validation in a hypothetical network reveals the potential of the model and discloses future issues . | A state space model estimating traffic states on a 2 dimensional network is proposed. SSM consists of CTM and probe vehicle measurements of densities and diverging ratios. Particle filtering is used to estimate the traffic states as well as model parameters. The model validation is made on a hypothetical network. |
S0968090X18316875 | A hybrid fare scheme is proposed in this paper that combines a fare reward scheme and a non rewarding uniform fare scheme by considering the heterogeneity in transit commuters scheduling flexibility . It aims at reducing peak hour congestion in the urban transit system with alternative options catering for various commuters . In the H FRS a commuter will be rewarded with a free ride during the periods preceding or following a given shoulder period after taking a certain number of paid rides during the central period in peak hours . In the H UFS a commuter needs to pay a different but uniform fare during peak hours . Commuters will have the opportunity to join either of the sub schemes according to their scheduling flexibility of departure time choice . The hybrid fare scheme determines the free fare intervals the rewarding ratio and the new fares for the sub schemes . Our results demonstrate that the proposed HFS is not only revenue preserving but also Pareto improving . Depending on the original fare an optimally designed hybrid fare scheme can achieve a reduction in total time costs by at least 25 with the optimal free fare interval . | The hybrid fare scheme HFS consists of a fare reward and a uniform fare scheme. We capture the heterogeneity in commuters arrival time flexibility interval. The optimal hybrid fare scheme can be achieved with multiple solutions. Individual trip costs reduction depends on the degree of the heterogeneity. All commuters are no worse off and the transit operator is revenue neutral. |
S0968090X18316966 | This paper presents a doubly dynamic day to day traffic assignment model with simultaneous route and departure time choices while incorporating incomplete and imperfect information as well as bounded rationality . Two SRDT choice models are proposed to incorporate imperfect travel information One based on multinomial Logit model and the other on sequential mixed multinomial nested Logit model . These two variants serving as base models are further extended with two features bounded rationality and information sharing . BR is considered by incorporating the indifference band into the random utility component of the MNL model forming a BR based DTD stochastic model . A macroscopic model of travel information sharing is integrated into the DTD dynamics to account for the impact of incomplete information on travelers SRDT choices . These DTD choice models are combined with within day dynamics following the Lighthill Whitham Richards fluid dynamic network loading model . Simulations on large scale networks illustrate the interactions between users adaptive decision making and network conditions with different levels of information availability and user behavior . Our findings highlight the need for modeling network transient and disequilibriated states which are often overlooked in equilibrium constrained network design and optimization . The MATLAB package and computational examples are available at | Doubly dynamic day to day traffic assignment models are proposed and implemented on large scale networks. Simultaneous route and departure time SRDT choices are modeled. Deterministic processes with random probabilistic choice models are considered. Bounded rationality is incorporated into SRDT choices in the doubly dynamic model. A macroscopic sub model is proposed to capture the effect of varying levels of information sharing among travelers. |
S0968090X1831708X | Optimal cordon metering rates are obtained using Macroscopic Fundamental Diagrams in combination with flow conservation laws . A model predictive control algorithm is also used so that time varying metering rates are generated based on their forecasted impacts . Our scalable algorithm can do this for an arbitrary number of cordoned neighborhoods within a city . Unlike its predecessors the proposed model accounts for the time varying constraining effects that cordon queues impose on a neighborhoods circulating traffic as those queues expand and recede over time . The model does so at every time step by approximating a neighborhoods street space occupied by cordon queues and re scaling the MFD to describe the state of circulating traffic that results . The model also differentiates between saturated and under saturated cordon metering operations . Computer simulations of an idealized network show that these enhancements can substantially improve the predictions of both the trip completion rates in a neighborhood and the rates that vehicles cross metered cordons . Optimal metering policies generated as a result are similarly shown to do a better job in reducing the Vehicle Hours Traveled on the network . The VHT reductions stemming from the proposed model and from its predecessors differed by as much as 14 . | Neighborhood MFDs are re scaled to account for effects of cordon queues. Simulation experiments reveal that re scaled MFDs better predict traffic performance. Cordon metering plans are found to be more effective as well. |
S0968090X18317121 | This paper proposes a methodology to estimate the passenger macroscopic fundamental diagram for bi modal urban corridors while accounting for the stochastic nature of bus operations . The proposed framework extends the existing variational theory approaches by introducing a probabilistic VT graph where the costs are computed using an efficient stochastic shortest path algorithm capturing the effects of stochastic moving bus bottlenecks and the correlation of bus arrival times incorporating a macroscopic passenger model that reflects the passenger dynamics for the different modes and accounting for the effects that the traffic conditions might have on bus operations . | Introducing a probabilistic VT graph where the costs are computed using an efficient stochastic shortest path algorithm. Capturing the effects of stochastic moving bus bottlenecks and the correlation of bus arrival times. Incorporating a macroscopic passenger model that reflects the passenger dynamics for the different modes. Accounting for the effects that the traffic conditions might have on bus operations. Introducing an innovative application example for the evaluation of different bus lane layouts. |
S0968090X18317133 | Emergent cooperative adaptive cruise control strategies being proposed for platoon formation in the connected autonomous vehicle context mostly assume idealized fixed information flow topologies for the platoon implying guaranteed vehicle to vehicle communications for the IFT assumed . In reality V2V communications are unreliable due to failures resulting from communication related constraints such as interference and information congestion . Since CACC strategies entail continuous information broadcasting communication failures can occur in congested CAV traffic networks leading to a platoons IFT varying dynamically . To explicitly factor IFT dynamics and to leverage it to enhance the performance of CACC strategies this study proposes the idea of dynamically optimizing the IFT for CACC labeled the CACC OIFT strategy . Under CACC OIFT the vehicles in the platoon cooperatively determine in real time which vehicles will dynamically deactivate or activate the send functionality of their V2V communication devices to generate IFTs that optimize the platoon performance in terms of string stability under the ambient traffic conditions . The CACC OIFT consists of an IFT optimization model and an adaptive Proportional Derivative controller . Given the adaptive PD controller with a two predecessor following scheme and the ambient traffic conditions and the platoon size just before the start of a time period the IFT optimization model determines the optimal IFT that maximizes the expected string stability in terms of the energy of speed oscillations . This expectation is because each IFT has specific degeneration scenarios whose probabilities are determined by the communication failure probabilities for that time period based on the ambient traffic conditions . The optimal IFT is deployed for that time period and the adaptive PD controller continuously determines the car following behaviors of the vehicles based on the unfolding degeneration scenario for each time instant within that period . The effectiveness of the proposed CACC OIFT is validated through numerical experiments in NS 3 based on NGSIM field data . The results indicate that the proposed CACC OIFT can significantly enhance the string stability of platoon control in an unreliable V2V communication context outperforming CACCs with fixed IFTs or with passive adaptive schemes for IFT dynamics . | Propose the CACC OIFT strategy to dynamically optimize information flow topology IFT for CACC. Under CACC OIFT vehicles dynamically deactivate activate send functionality of their V2V communication devices. CACC OIFT consists of an IFT optimization model and an adaptive Proportional Derivative controller. CACC OIFT enhances string stability of platoon control in an unreliable V2V communication context. |
S0968090X18317248 | The objective of this paper is to develop a micro economic modeling approach for car following behaviors that may capture different risk taking tendencies when dealing with different traffic conditions . The proposed framework allows for the consideration of perception subjectivity and judgement errors that may lead to unsafe acceleration driving maneuvers with the possibility of real end collisions . The modeling approach relies on a generalized utility based formulation with three specific types of subjective utility functions Prospect Utility subjective utility function Constant Relative Risk Aversion subjective utility function and an Exponential Constant Relative Risk Aversion subjective utility function . The formulation is assessed in terms of its homogeneous macroscopic properties and its non homogeneous microscopic properties . | A generalized utility based formulation of a car following is offered. This includes Prospect Utility and two variants of Constant Relative Risk Aversion. The macroscopic and microscopic properties of the different functions are derived. The model was calibrated and validated using 1000 individual trajectory sets. The model s characteristics are analyzed via simulation and sensitivity analysis. |
S0968090X18317273 | This study develops and analyses the centralised and decentralised solution procedures for urban network traffic management through an optimal control framework . The optimal control is formulated based upon the Hamilton Jacobi formulation of kinematic wave model . Following the problem decomposition under the decentralised scheme we introduce the use of semi analytical performance derivatives when developing the decentralised solution algorithm . The proposed control strategies are applied to a set of test scenarios constructed from a real road network in Central London in the UK . Specific interests in the investigation include comparison of the performance gain and computational effort of the two strategies under different circumstances . We also investigate effect of network decomposition strategies on the performance of the solution algorithm . This study generates insight on urban traffic management with use of traffic flow theory decentralised optimisation and network decomposition techniques . | Centralised and decentralised algorithms with optimal control formulation. Sensitivity based decentralised signal optimisation algorithms. Comparison with distributed backpressure control policy. Investigation of different network decomposition schemes. Case study of optimisation algorithms on Central London networks. |
S0968090X18317285 | This study presents an adaptive railway traffic controller for real time operations based on approximate dynamic programming . By assessing requirements and opportunities the controller aims to limit consecutive delays resulting from trains that entered a control area behind schedule by sequencing them at a critical location in a timely manner thus representing the practical requirements of railway operations . This approach depends on an approximation to the value function of dynamic programming after optimisation from a specified state which is estimated dynamically from operational experience using reinforcement learning techniques . By using this approximation the ADP avoids extensive explicit evaluation of performance and so reduces the computational burden substantially . In this investigation we explore formulations of the approximation function and variants of the learning techniques used to estimate it . Evaluation of the ADP methods in a stochastic simulation environment shows considerable improvements in consecutive delays by comparison with the current industry practice of First Come First Served sequencing . We also found that estimates of parameters of the approximate value function are similar across a range of test scenarios with different mean train entry delays . | Development of an adaptive control system to manage railway traffic in real time. Application of approximate dynamic programming to railway traffic management. Application of reinforcement learning to approximate railway traffic states. A computationally efficient approach to manage the stochastic nature of railways. |
S0968090X18317339 | This paper proposes a new dynamic user equilibrium traffic assignment model using reservoir based network reduction techniques and surrogate dynamic network loading models . A traffic network is decomposed into a reservoir structure and the DUE problem is formulated as a variational inequality with an embedded surrogate model for the path delay operator to describe traffic dynamics at the reservoir level . The surrogate model is further enhanced by the reproducing kernel Hilbert space and adaptive sampling to reduce approximation error and improve computational efficiency . To solve the proposed surrogate based DUE problem on reduced networks we develop a customized algorithm that integrates the kernel trick with the generalized projection framework . A pre computation scheme is proposed which calculates and stores the of kernel matrices and vectors could further reduce the computational burden . Numerical experiments of the proposed methods show significant reduction of the computational times by up to | A surrogate based variational inequalities formulation of DUE problem is proposed. We introduce the kernel trick and weighting scheme to train the surrogate model by high order functions. Reservoir based traffic model is introduced to further reduce the number of features. Proposed model is tested by various numerical experiments and achieved reduction in computation time while maintaining low approximation error. |
S0968090X18317340 | The rise of e hailing taxis has significantly altered urban transportation system and led to a competitive taxi market with both traditional street hailing and e hailing taxis . The various taxi services provide similar door to door rides thus compete with each other . Meanwhile the expanding fleet size of e hailing taxis together with considerable number of traditional taxicabs influence the urban road network performance which can also in turn affect taxi mode choice and operation . In this study we propose an innovative modeling structure for the competitive taxi market and capture the interactions not only within the taxi market but also between the taxi market and urban road system . | Model the e hailing taxi system using queuing modeling. Empirically show that the arrivals of taxi and service rate can be approximated as a Poisson process. Propose an algorithm to match the vehicles to passengers in the queue. Compute various performance metrics of the e hailing system using queuing models. Conduct various tests using real world data from New York City. |
S0968090X18317364 | Recently the employment of different types of incentives in transportation systems to form advanced transportation congestion management solutions has garnered significant attention . Instead of using presumed or fixed amount incentives this paper develops an integrated and personalized traveler information and incentive scheme to incentivize toward a more energy efficient travel and mobility decisions . We have developed a behavior research and empirical modeling system to quantify the personalized monetary incentives . Then it is integrated with a control optimizer for optimized incentive allocation . This scheme innovatively integrates behavioral modeling and optimization for travel incentive design . Through a demonstrative case study for a large scale transportation system in the Washington D.C. and Baltimore regions the capability of the proposed scheme is highlighted with significant system level energy savings reasonable insights on individual travel behavior responses as well as superior computational efficiency . | Developed an integrated and personalized traveler information and incentive scheme. Developed an empirical model to quantify the personalized monetary incentives. The scheme integrated behavioral modeling and optimization of incentive allocation. Demonstrated the effectiveness of control in a large scale transportation system. |
S0968090X18317388 | The fundamental challenge of the origin destination matrix estimation problem is that it is severely under determined . In this paper we propose a new data driven OD estimation method for cases where a supply pattern in the form of speeds and flows is available . We show that with these input data we do not require an iterative dynamic network loading procedure that results in an equilibrium assignment nor do we need an assumption on the kind of equilibrium that emerges from this process . The minimal number of ingredients which | New data driven framework for OD matrix estimation. No equilibrium assignment nor network loading model needed. Scalable for large networks using dimensionality reduction techniques. Supervised learning to estimate production and attraction from 3D supply patterns. Results on small and large network promising. |
S0968090X1831739X | We develop a personalized system to modify individual travel behaviors by offering personalized incentives . Individual preferences are learned to provide personalized incentives so that the promoted alternative is likely accepted . Using knowledge from control theories and state estimation we model travelers choice making behaviors with the random utility theory and responses from the individuals are mined by a particle filter for learning individual preferences to promote sustainable behaviors . The discrete nature of travel behavior naturally leads to limited observability . We overcome this problem by designing a measurement function from which additional information can be solicited . Additionally the inherent trade offs between factors that affect travel choices result in an infinite set of solutions . We thus propose two solutions the divide and conquer strategy in which a multi dimensional conditional probability function is proposed and use of domain knowledge to restrict that preference values fall in certain ranges and are consistent with certain distributions . The performance of preference learning with these two solutions applied is shown via simulation tests and an online experiment involving human participants . For departure time choices we show an average acceptance ratio of 0.68 for all participants when being promoted with alternatives with personalized incentives . We also show that changes in individual departure time choices will lead to 48 reduction in total travel time on a simple transportation network . | We develop a personalized incentive system to promote sustainable travel behaviors. The proposed approach allows individual preference tracking over time. The proposed approach permits learning from limited data. The proposed approach achieves multi dimensional learning. Our online experiment with humans shows an average acceptance ratio of 68 . |
S0968090X18317418 | This paper examines the time dependent bus dispatching problem in a multi modal context . Traditional studies along this line often optimize the bus frequency or schedule . However they may fail as the realized bus frequency or schedule is constrained by the time varying traffic congestion on the road . Adding more buses to service does not necessarily increase the service frequency . Given this we look into the time dependent bus dispatching when taking into account complex multi modal and multi directional flow interactions on the road . In particular the traffic dynamics over clock time is modeled through an aggregate traffic representation with flow interactions between cars and buses and interactions between traffic in opposite moving directions . Instead of explicitly optimizing the size of dispatched bus fleet we propose an adaptive fleet size adjustment mechanism where we have a target level of bus loading factor . This adaptive or responsive approach by taking advantage of the doubly dynamical system proposed in Liu and Geroliminis adjusts the size of dispatched bus fleet over calendar time and accommodates day to day variations of mode choices and traffic patterns . Numerical studies show that the proposed approach can help bus operator to reduce operating cost and improve net benefit while maintaining comparable user costs for passengers . This study offers a new perspective for dynamic bus dispatching strategy and improves our understanding of multi modal traffic dynamics . | The time dependent bus dispatching problem is examined in a doubly dynamic context. Adding more buses to service does not necessarily increase the service frequency. An adaptive bus fleet size adjustment approach is proposed with a target loading factor. The approach reduces bus operating cost while maintaining comparable user costs for passengers. |
S0968090X1831742X | This paper elucidates the impacts of vehicle heterogeneity on traffic dynamics and throughput of mixed traffic consisting of connected automated vehicles and regular vehicles . The main premise is that the heterogeneity in preferred acceleration rate desired speed and car following behavior will change traffic properties in ways that can undermine traffic flow throughput . This paper first decomposes the mechanism into two elements one driven by acceleration and one by time varying CF response to disturbances and then investigates their compounded effect . This paper also provides unifying frameworks to analyze the behavior of RVs and CAVs to facilitate analytical investigations . The results reveal how heterogeneous acceleration and CF behavior may create persistent voids and diminish traffic throughput . Integrating all the elements throughput reduction is quantified via numerical simulations . | Investigate impacts of heterogeneity in driving behavior on traffic dynamics. Unifying framework to analyze RV and CAV behavior in mixed traffic. Mechanism for heterogenous acceleration and CF leading to void creation. Simulation for compounded effects of heterogeneity in mixed traffic platoons. |
S0968090X18317431 | Randomness affecting the operation of public transport systems generates significant increments in waiting times . A strategy to deal with this randomness is bus injection in which buses are kept in specific points along the route ready to be dispatched when an event such as an extremely long headway occurs . In this work a stochastic model based on the second moment of the headways distribution is developed to determine if one or more buses are worth reserving for injection in a public transport service . A single stop approach is initially used to determine an expression for the optimal headway threshold triggering the injection . Then a model for the complete service is developed and used to determine when the empty bus should be injected within the headway once the decision to inject it has been taken . We show that the bus should be injected approximately when 57 of the headway has passed . Simulations with real data are used to test the proposed model proving its accuracy in terms of measuring the impact on waiting times . The results show that reserving a bus to be injected can be better than operating the entire fleet continuously . | An injection stochastic model based on the headway distribution second moment is proposed. An expression for the optimal headway threshold triggering the injection is proposed. A model to determine when a bus should be injected within the headway was developed. We identify at which moment within the headway a bus should be injected. Simulations with real data are used to test the proposed model proving its accuracy. |
S0968090X18317443 | Sags and tunnels are major bottlenecks where the road capacity is reduced and the capacity drop phenomenon occurs however there is no simple model or theory that can explain the formation and other characteristics of capacity drop . This paper presents a car following model which is equivalent to a continuum model in the Lagrangian coordinates . The model is built on two main assumptions inhomogeneous fundamental diagrams with location dependent time gaps and bounded acceleration . We first demonstrate that the stationary speed profiles the low acceleration rates the dropped capacity and the approximate time duration of the capacity drop formation in the model are consistent with empirical observations . Then the impacts on the stationary states and dropped capacity of the numerical viscosity caused by the discretization method are investigated and it is shown that the dropped capacity converges to the theoretical value . Further a one dimensional iterated function system is proposed to model the formation mechanism of the capacity drop which is derived by investigating the spatial pattern of equilibrium and bounded acceleration traffic states that arises in a lead vehicle problem . Utilizing this model we uncover a set of properties of the capacity drop such as existence uniqueness global convergence and convergence speed . Finally the model is applied to analyze the impacts of heterogeneous drivers . The model and insights in this study will help to develop control and management schemes to alleviate capacity drop effects with connected and autonomous vehicles in the future . | Present a continuum car following model of capacity drop at sag and tunnel bottlenecks. Demonstrate the occurrence of the capacity drop and compare its characteristics to the known empirical observations. Analyze the effects of a numerical viscosity on the capacity drop and the consistency with the KW model. Devise an iterated function system model to analyze the temporal formation and stabilized mechanisms of capacity drop. Apply the model to analyze the impacts of heterogeneous drivers. |
S0968090X18317455 | Reducing the number of transfers and improving the operating speed are key factors in enhancing the competitiveness of urban rail transit systems . This paper proposes an integrated optimization with tactical cross line planning and an operational express train mode to fully utilize line capacities and reduce the total trip time without additional operating costs and investments . In this paper a new mixed integer non linear programming model is proposed for systemically exploring the benefits of cross line express trains to achieve both passenger travel time and operation cost savings in this model the frequencies stopping patterns and operation zones of cross line express trains and local trains are simultaneously optimized . The characteristics of same line trips and cross line trips under various stopping patterns are investigated . Additionally a genetic algorithm is developed based on the MINLP model . Finally the effectiveness of the proposed model and heuristic algorithm is verified through a set of real life instances based on the Beijing URT network . The results show that the number of transfers can be reduced by 78 with a 3.34 savings of travel time and a 4.66 savings of operating costs when the cross line express operating mode is properly adjusted . | Transfer routes choice and in vehicle time saver under the variable stopping patterns and turn back stations for cross line trains. Frequency setting requirements on both lines caused by headway constraints between cross line trains and local trains running on the same track. The established model ISPOM can be applied to most real world URT networks to quantify the effectiveness of the cross line express operation mode in practice due to no requirements on overtaking facilities equipped. |
S0968090X18317595 | Aggressive driving amongst all driving behaviors is largely responsible for leading to traffic accidents . With the objective to improve road safety this paper develops an on line approach for vehicle running state monitoring and aggressive driving identification using kinematic parameters captured by the in vehicle recorder under naturalistic driving conditions . To characterize the roads in reality a novel road conceptual model is proposed . It accounts for not only the curve on the horizontal plane but also the slope on the vertical plane as well as the cross slope . For each position where the vehicle is driving the vehicle motion is decomposed into two circular motions on the horizontal and vertical planes . On each plane the vehicle maneuver is first identified . Then aggressive driving is identified according to the limit equilibrium of driving safety or comfortability . Based on the proposed method called three elements the vehicle maneuver radius and slope angle on the vertical plane can be solved in an on line manner . The novel approach is an elaborate analytical model with clear physical meaning but small computation load and therefore is potential to be implemented in the mobile devices to assist in real time aggressive driving identification and labeling . The developed approach is applied to a real case on the curved and sloped route in Nanjing China . Empirical results of extensive experiments based on the kinematic parameters collected from the in vehicle data recorder under naturalistic driving conditions demonstrate that aggressive driving behaviors are mostly found on the pavements with curve and slope and can be identified by the developed approach . | A concept road model characterizing the road in reality is presented. Analyzing aggressive driving on both the horizontal and vertical planes. Identifying aggressive driving considering both driving safety and comfortability. Aggressive driving is identified in a dynamic and on line manner. The proposed model is evaluated by a real case in Nanjing China. |
S0968090X18317625 | This paper proposes a new probabilistic treatment path dependence model for budget allocation within pavement network management problems . During the evaluation of treatment alternatives for a segment in a pavement network the model considers benefits of both the evaluated treatment and its following actions . It also incorporates the influence of treatment cost and deterioration uncertainties . Treatments are selected for each segment in the pavement network using a risk based optimization model . Three case studies are presented to illustrate the application and benefits of this new model . Results of the first two cases show that the risk aversion coefficient in the model influences segment level treatment selections and pavement network performance . The third case shows that the PTPD model performs better than a benefit cost ratio model due to the incorporation of uncertainties and treatment path dependence . To obtain a similar performance level the conventional model requires a 10.4 higher annual budget for the given case study . The results presented here suggest that elements of this model notably consideration of uncertainty in deterioration and cost treatment path dependency and explicit risk trade offs could be incorporated into asset management tools to improve the cost effectiveness of pavement network planning . | A methodology to consider treatment cost uncertainty and path dependence is developed. Risk trade offs are considered during decision making for treatment selections. A treatment is evaluated by benefits of both itself and its following treatments. A backtrack algorithm is developed to find the optimal treatment path for a segment. |
S0968090X18317728 | Providing quality transit service to travelers in low density areas particularly travelers without personal vehicles is a constant challenge for transit agencies . The advent of fully autonomous vehicles and their inclusion in mobility service fleets may allow transit agencies to offer better service and or reduce their own capital and operational costs . This study focuses on the problem of allocating resources between transit patterns and operating shared use AV mobility services in a large metropolitan area . To address this question a joint transit network redesign and SAMS fleet size determination problem is introduced and a bi level mathematical programming formulation and solution approach are presented . The upper level problem modifies a transit network frequency setting problem formulation via incorporating SAMS fleet size as a decision variable and allowing the removal of bus routes . The lower level problem consists of a dynamic combined mode choice traveler assignment problem formulation . The heuristic solution procedure involves solving the upper level problem using a nonlinear programming solver and solving the lower level problem using an iterative agent based assignment simulation approach . To illustrate the effectiveness of the modeling framework this study uses traveler demand from Chicago along with the regions existing multimodal transit network . The computational results indicate significant traveler benefits in terms of improved average traveler wait times associated with optimizing the joint design of multimodal transit networks and SAMS fleets compared with the initial transit network design . | Integrates shared autonomous vehicle service with conventional public transit. Method to jointly determine autonomous vehicle fleet size and transit route frequencies. Develops best allocation of resources to provide mobility to urban residents. Bi level problem formulation explicitly considers user response demand in the design process. Methodology applied to Chicago multimodal transit network. |
S0968090X18317996 | This paper proposes a two dimensional car following model to tackle traffic flow problems where considering continuum lateral distances enables a simpler or more natural mathematical formulation compared to traditional car following models . These problems include the effects of lateral friction often observed in HOV lanes and diverge bottlenecks the relaxation phenomenon at merge bottlenecks the occurrence of accidents due to lane changing and traffic models for autonomous vehicles . We conjecture that traditional car following models where the lateral dimension is discretized into lanes struggle with these problems and one has to resort to ad hoc rules conceived to directly achieve the desired effect and that are difficult to validate . | A microscopic traffic flow model incorporating the lateral dimension is formulated. The model includes non instant lane changes and a multi directional repulsive force. The model reproduces lateral friction and the relaxation phenomenon at on ramp merges. The model handles collision avoidance during distracted aggressive lane changing. Autonomous vehicles should consider the lateral dimension and be modeled in 2D. |
S0968090X1831814X | GPS based campaigns have been hailed as an alternative to transportation surveys that promise relatively high accuracy at a relatively low burden on the participants and fewer forgotten trips . However they still necessitate the recruitment of participants and are thus potentially biased and certainly not encompassing significant parts of the population . Given the high penetration of mobile phones passive tracking by telephone providers would alleviate those two shortcomings at the cost of reduced sampling frequency and positional accuracy . The trade off in quality has not yet been quantified and therefore recommendations on sensible thresholds are not yet available . In this study therefore instead of presenting yet another method for mode of transport classification we therefore compare the performance of existing mode detection schemes under deteriorating sampling rates and positional accuracies . As a possibility to compensate for the deteriorating signal we also calculate features from users positional histories that could be beneficial if their behaviour is repetitive . The evaluation is not only based on pointwise accuracy but includes quality measures that pertain to trips as a whole . We find that the necessary accuracy and sampling rate for applications will depend on whether the information of whole trajectories can be used or whether only the current information is available . The former being relevant to ex post analyses while the latter situation appears more frequently in near time analyses . For segmentwise classification there is no major impact on the quality of the classification by the tested levels of spatial accuracies as long as the sampling intervals can be kept at or below a minute whereas for point based classification the sampling interval should be between 30 s and a minute and increasing spatial accuracy always improves the classification . | Segmentation based classification is robust enough for today s passive tracking. Improper training and testing split can significantly distort reported accuracies. Point based online classification underperforms segment based classification. Recurrent Neural Networks yield better label accuracies but worse label sequences. |
S0968090X18318175 | Rapid urbanization and modern civilization require sound integration with public transportation systems . In the same time the volume and complexity of public transportation network are increasing making it harder to understand the public transportation dynamics . As a first step understanding the similarity among subway stations is imperative . In this paper we proposed a semantic framework inspired from natural language processing to interpret subway stations as compound words . Specifically we transplanted context and literal meaning of compound words into mobility and location attributes of stations . Using smart card data we trained stacked autoencoders with designed flow matrices as an embedding method to learn the mobility attributes . Subsequently to discover the location attributes we have applied affinity propagation clustering to classify 9 point of interest categories . Combined with urban planning knowledge we manage to comprehend the land use meanings of 9 POI clusters . The location semantics is chosen from those categories reflecting its urban land use pattern . By choose meaningful combination of mobility and location semantics for stations similarity case studies we summarized potential applications of this semantic framework . | A new concept to understand the mobility and location features of subway stations. Transplant Language Processing to understand subway stations as compound words. Obtain mobility and location semantics from neural net and affinity propagation. Interpretsemantic results in an urban planning aspect. |
S0968090X18318254 | This paper develops a flexible real time traffic signal control algorithm to optimize both phase durations and phase sequences at four approach intersections with conflicting left turns based on information obtained from connected vehicles . Vehicle to infrastructure communications are assumed to provide the location of all connected vehicles near the signalized intersection at regular time intervals and this information is used to identify the presence of non connected vehicles that are stopped at the intersection . All detected and identified vehicles are used to identify naturally occurring platoons in the traffic stream . The signal control algorithm then selects the optimal sequence that these platoons should discharge through the intersection to minimize average delay of all identified vehicles . Since all possible departure sequences for platoons of vehicles are considered the problem is computationally difficult . Hence several heuristic methods are proposed to determine optimal platoon departure sequences . These heuristics include an intelligent tree search and multiple types of genetic algorithms including a newly developed genetic algorithm that perserves phase order sequence that is vital to this problem . Comparisons between these heuristics and the global optimal solution suggest that the heuristics are able to provide similar operational performance with significant reductions in total computation time required such that the algorithm can be applied in real time . In general the intelligent tree search appears to outperform the genetic algorithm approaches in terms of operational performance but has computational requirements that increase exponentially with the number of platoons identified at the intersection . Meanwhile the genetic algorithm methods tend to be more scalable but slightly less efficient . Overall the results are promising for the application of the proposed flexible signal control algorithm at real intersections . | Flexible connected and autonomous vehicle signal control algorithm. Algorithm works for penetration ratios of CAVs less than 100 . Algorithm allows for complete flexibility in phase order and duration. Algorithm can be solved in real time. |
S0968090X18318436 | In recent years several perimeter control strategies have been proposed for traffic management in cities . The common factor found in these works is the use of Macroscopic Fundamental Diagram models to describe the dynamics of the network and optimize traffic inside the perimeter by manipulating perimeter inflows . Perimeter gating control strategies are attractive for traffic management inside the inner city . However it inevitably creates a negative impact on the traffic outside . Most of the works in this research area have neglected vehicle re routing outside the controlled perimeter i.e . they do not consider demand elasticity to the central region resulting from gating and the related queues . In this paper we propose a global modeling framework capable of assessing the effect of perimeter gating control on the full network considering demand elasticity resulting from Dynamic User Equilibrium . Classical Proportional Integral control scheme is used to control traffic congestion inside a central region . The modeling framework is comprised of an accumulation based MFD model to reproduce traffic dynamics inside the reservoir point queue model to represent queuing vehicles on inbound links to the gating points and a time dependent travel time profile based on a steady state approximation of MFD dynamics to characterize the alternative road network . DUE is then implemented considering instantaneous predicted travel time . This determines how the demand to the inner region is affected by the gating . The functioning of the global system is assessed by total time spent and NOx and CO | Designing a macroscopic modeling framework for perimeter gating control and dynamic user equilibrium. Designing a routing scheme with instantaneous dynamic user equilibrium and predictive travel time. Application of Proportional Integral PI controller for traffic control. Investigating the impact of perimeter gating control on routing inside and outside the reservoir. Analysis of emissions in the traffic network. |
S0968090X18318679 | Forward collision warning systems function by alerting drivers to upcoming hazards ahead and have been shown to help drivers respond more quickly under emergency situations . As FCW directly affects how vehicles interact longitudinally with one another it may also influence car following behavior such as reaction time which has been little researched . To investigate these effects driving data were collected from the Shanghai Naturalistic Driving Study . Five data collecting vehicles were equipped with Mobileye systems which included an FCW function with headway display and warning system . Participants drove the vehicles for two months with the Mobileye system activated the second month only . From the 161 055km of naturalistic driving data collected from 60 drivers 3 000 car following events were selected and the effects of FCW on car following headway and reaction time and on the parameter values of the Gazis Herman Rothery model were examined . Results showed that drivers tended to maintain shorter headway with FCW enabled while the proportion of time in short headways did not increase FCW reduced car following reaction time when the lead vehicle was accelerating and when the relative speed between the lead and following vehicle was large and a reduction in the space headway exponent of the GHR was observed when FCW was enabled indicating that drivers follow more closely with FCW because the system increases drivers sensitivity to changes in following gaps . Results of this study suggest that an FCW system with a headway monitoring function may increase traffic efficiency and stability without degrading safety . | Impacts of a forward collision warning FCW system on car following behavior were investigated. Five vehicles equipped with Mobileye FCW systems were used to collect driving data. Participants drove the vehicles for two months with the Mobileye system activated for the second month only. The FCW system resulted in a reduction in headway and a conditional reduction in reaction time. Drivers follow more closely because the system increased their sensitivity to the change of following gaps. |
S0968090X19300075 | A dynamic ridesharing system is a platform that connects drivers who use their personal vehicles to travel with riders who are in need of transportation on a short notice . Since each driver rider may have several potential matches to achieve a high performance level the ridesharing operator needs to make the matching decisions based on a global view of the system that includes all active riders and drivers . Consequently the ride matching problem that needs to be solved can become computationally expensive especially when the system is operating over a large region or when it faces high demand levels during certain hours of the day . This paper develops a graph partitioning methodology based on the bipartite graph that arises in the one to one ride matching problem . The proposed method decomposes the original graph into multiple sub graphs with the goal of reducing the overall computational complexity of the problem as well as providing high quality solutions . We further show that this methodology can be extended to more complex ride matching problems in a dynamic ride sharing system . Using numerical experiments we showcase the advantages of the new partitioning method for different forms of ride matching problems . Moreover a sensitivity analysis is conducted to show the impact of different parameters on the quality of our solution . | A new methodology to partition the bipartite graph in the ride matching problem. The partitioning forms sub problems that are uniform within tolerance in size. An entire trip is considered to be the object in partitioning. The iterative solution algorithm terminates in a finite number of steps. The iterative solution algorithm obtains strictly superior partitions with iterations. |
S0968090X19300361 | Blockchain has the potential to render the transaction of information more secure and transparent . Nowadays transportation data are shared across multiple entities using heterogeneous mediums from paper collected data to smartphone . Most of this data are stored in central servers that are susceptible to hacks . In some cases shady actors who may have access to such sources share the mobility data with unwanted third parties . A multi layered Blockchain framework for Smart Mobility Data market is presented for addressing the associated privacy security management and scalability challenges . Each participant shares their encrypted data to the blockchain network and can transact information with other participants as long as both parties agree to the transaction rules issued by the owner of the data . Data ownership transparency auditability and access control are the core principles of the proposed blockchain for smart mobility data market . In a case study of real time mobility data sharing we demonstrate the performance of BSMD on a 370 nodes blockchain running on heterogeneous and geographically separated devices communicating on a physical network . We also demonstrate how BSMD ensures the cybersecurity and privacy of individual by safeguarding against spoofing and message interception attacks and providing information access management control . | Blockchain framework for mobility data transactions is proposed. Framework is designed to secure the data and maintain individuals privacy. Six layered model is developed that defines the flow of mobility information. Smartphone based mobility data blockchain on geographically separated 370 nodes. Open Sourced code is made available for transportation community to build upon. |
S0968090X19300737 | Network state degradation probabilities increase with traffic density . Specifically at critical or congested densities any over input traffic flow may cause degradation local traffic jams and even hysteresis of the road network . Existing macroscopic traffic control methods usually target the maximum capacity or minimum delay to improve the road network efficiency and do not consider the negative effect of perimeter control on the state transfer of the road network . This study provides a method to prevent the transfer of the network state when implementing boundary control . First according to the data detected for the road network the concept of a conditional value at risk is used to establish a risk decision model that considers the influence of the boundary input flow rate on sub region state degradation . Then based on the risk decision model we propose a state transfer risk decision perimeter control method for a large scale traffic network with multiple sub regions . This perimeter control method predicts the traffic demand of every sub region selects an acceptable traffic flow range at the sub region boundary by risk interval regards the maximum trip completion flow and the minimum total travel time as the decision making objectives and controls multiple sub region boundaries . The simulation results show that compared with proportional integral control and no STRD control the STRD control scheme can effectively prevent the state transfer of all sub regions improve the trip completion flow and decrease the travel delay of the network . | Propose a state transfer risk decision STRD method for a large scale traffic network. This method is based on the conditional risk decision model. This method provides an acceptable traffic flow range at the sub region boundary by risk interval. Proposed method improves the state stability compared to PI and NSTRD. |
S0968090X1930083X | Automated monitoring of pedestrians on non motorized facilities with high pedestrian flows is challenging . Several automated sensor solutions are commercially available that have been evaluated in the literature including traditional point based sensors such as inductive loop detectors for bicycles and infrared sensors for pedestrians . More recently image based systems based on video cameras or thermal video cameras have been developed . Despite the various options some key limitations of existing solutions exist in particular the lack of low cost solutions using embedded systems capable of performing in real time under high volume conditions . This work aims at developing and evaluating the performance of a novel real time counting system developed for environments with high pedestrian flows . The proposed system is based on emerging LiDAR technology . As an input the system uses the distance measurements from a two dimensional LiDAR sensor with a set of distinct laser channels and a given angular resolution between each channel . The developed system processes those measurements using a clustering algorithm to detect count and identify the direction of travel of each pedestrian . The systems performance is evaluated by comparing its directional counting outputs with manual counts using disaggregate and aggregate counts at two different monitoring locations . The results demonstrate that the system accurately counts more than 97 of the pedestrians at the disaggregate level with a false direction detection rate of 1.1 . The over counting error is 0.7 and the under counting errors are 1.3 and 2.7 for the two selected sites . At the aggregate level the average absolute percentage deviations are 1.6 and 4.3 while the weighted AAPDs are 1.5 and 3.5 for the first and second sites respectively . The accuracy of the proposed system is higher than the traditional technologies used for the same purpose . | A novel real time counting system is developed for monitoring high pedestrian flows. The proposed system uses distance measurements from a two dimensional LiDAR sensor. Clustering algorithm is developed to count pedestrians and identify their direction. The results show that the system accurately counts more than 97 of the pedestrians. The accuracy of the proposed system is higher than the traditional technologies. |
S0968090X19300841 | The emergence of data driven demand analysis has led to the increased use of generative modelling to learn the probabilistic dependencies between random variables . Although their apparent use has mostly been limited to image recognition and classification in recent years generative machine learning algorithms can be a powerful tool for travel behaviour research by replicating travel behaviour by the underlying properties of data structures . In this paper we examine the use of generative machine learning approach for analyzing multiple discrete continuous travel behaviour data . We provide a plausible perspective of how we can exploit the use of machine learning techniques to interpret the underlying heterogeneities in the data . We show that generative models are conceptually similar to the choice selection behaviour process through information entropy and variational Bayesian inference . Without loss of generality we consider a restricted Boltzmann machine based algorithm with multiple discrete continuous layers formulated as a variational Bayesian inference optimization problem . We systematically describe the proposed machine learning algorithm and develop a process of analyzing travel behaviour data from a generative learning perspective . We show parameter stability from model analysis and simulation tests on an open dataset with multiple discrete continuous dimensions from a data size of 293 330 observations . For interpretability we derive the conditional probabilities elasticities and perform statistical analysis on the latent variables . We show that our model can generate statistically similar data distributions for travel forecasting and prediction and performs better than purely discriminative methods in validation . Our results indicate that latent constructs in generative models can accurately represent the joint distribution consistently on MDC data . | Data driven interpretable machine learning for large scale multiple discrete continuous data. Analytical methods for conditional probability elasticity latent variables and fore casting. Incorporate variational Bayesian inference into travel behaviour model estimation. Validation performed on a dataset consisting over 293 330 trip trajectories from Montral. |
S0968090X19300981 | In the future autonomous vehicles are expected to safely move people and cargo around . However as of now automated entities do not necessarily outperform human drivers under all circumstances particularly under certain road and environmental factors such as bright light heavy rain poor quality of road and traffic signs etc . Therefore in certain conditions it is safer for the driver to take over the control of the vehicle . However switching control back and forth between the human driver and the automated driving entity may itself pose a short term elevated risk particularly because of the out of the loop issue for humans . In this study we develop a mathematical framework to determine the optimal driving entity switching policy between the automated driving entity and the human driver . Specifically we develop a Markov decision process model to prescribe the entity in charge to minimize the expected safety cost of a trip considering the dynamic changes of the road environment during the trip . In addition we develop a partially observable Markov decision process model to accommodate the fact that the risk posed by the immediate road environment may only be partially observed . We conduct extensive numerical experiments and thorough sensitivity and robustness analyses where we also compare the expected safety cost of trips under the optimal and single driving entity policies . In addition we quantify the risks associated with the policies as well as the impact of miss estimating road environment condition risk level by the driving entities and provide insights . The proposed frameworks can be used as a policy tool to identify factors that can render a region suitable for level four autonomy . | Switching between driving entities in semi autonomous vehicles improves safety. Regardless of trip length switching between driving entities holds benefit. Forgo a planned entity change as late as possible in a dynamic driving environment. Location environment and switching risks are quantified in semi autonomous vehicles. Miss estimating road environment condition risk level by the driving entities may reduce the safety of navigation. |
S0968090X19301093 | One of the key challenges towards more automation in Air Traffic Control is the resolution of en route conflicts . In this article we present a generic framework for the conflict resolution problem that clearly separates the trajectory and conflict models from the resolution . It is able to handle any kind of maneuver and detection models though we propose our own realistic 3D maneuvers and conflict detection that takes into account uncertainties on the positioning of aircraft . Based on these models realistic scenarios are built for which potential conflicts are detected using an efficient GPU based algorithm . The resulting instances of the conflict resolution problem are provided to the community as a public benchmark . | Generic conflict resolution framework to provide benchmark to scientific community. GPU based conflict detection fast enough to enable real time applications. 2 phase Memetic Algorithm able to handle feasibility and optimization. Aggregation of ILP model constraints dramatically increases efficiency. Cooperation of exact algorithm and metaheuristic outperforms both on large instances. |
S0968090X19301238 | The availability of automated data for urban metro systems allows operators to accurately measure journey time reliability . However there remains limited understanding of the causes of journey time variance and how journey time performance can be improved . In this paper we present a semiparametric regression modelling framework to determine the underlying drivers of journey time variance in urban metro systems using the London Underground as a case study . We merge train location and passenger trip data to decompose total journey times into three constituent parts access times as passengers enter the system on train times and egress times as passengers exit at their destinations . For each journey time component we estimate non linear functional relationships which we then use to derive elasticity estimates of journey times with respect to service supply and demand factors including operational and physical characteristics of metros as well as passenger demand and passenger specific travel characteristics . We find that the static fixed physical characteristics of stations and routes have the greatest influence on journey time followed by train speeds and headways for which the average elasticities of total journey time are 0.54 and 0.05 respectively . The results of our analysis could inform operators about where potential interventions should be targeted in order to improve journey time performance . | AFC and AVL data are merged to assign passengers to trains. Total journey times decomposed into sub components to enable disaggregate analysis. Non linear elasticities of journey times derived via semiparametric regression. Physical characteristics of systems have greatest influence on journey times. Most influential dynamic factors elasticity train speed 0.54 headway 0.05 . |
S0968090X19301482 | In this work we adapt the rolling horizon approach of Eberlein et al . for adjusting the dispatching times of buses at each rolling horizon . The industry practice is to adjust the dispatching time of a bus once it departs from the first stop while considering that future trips will operate as planned . In contrast a rolling horizon approach adjusts simultaneously the dispatching times of all trips that operate during a pre determined time interval resulting in a coordinated effort to maintain the target headways . Due to the increased number of dispatching time decisions this coordinated effort increases the computational burden . To reduce the computational cost we introduce a nonlinear program and we propose a novel reformulation that limits the recursive relations of the optimization problem . Our program is proved to be convex and can be solved to global optimality under a limited computational cost . In addition it outperforms myopic methods that adjust the dispatching time of each bus trip in isolation . The sensitivity of our method to travel time and passenger demand fluctuations is investigated on a simulation scenario of bus line 15L in Denver . | Exact model for the bus dispatching in rolling horizons. Proof of convexity and global optimality. Reproducible numerical experiments. Identify dispatching times that can adjust to operational variations. Significant improvements for control horizons with 412 trips. |
S0968090X19301652 | This paper develops a model based hierarchical control method for coordinated ramp metering on freeway networks with multiple bottlenecks and on and off ramps . The controller consists of two levels where at the upper level a Model Predictive Control approach is developed to optimize total network travel time by manipulating total inflow from on ramps to the freeway network . The lower level controller distributes the optimal total inflows to each on ramp of the freeway based on local traffic state feedback . The control method is based on a parsimonious aggregated traffic model that relates the freeway total outflow to the number of vehicles on the freeway sections . | We propose a hierarchical ramp metering approach that is based on the freeway MFD. The effect of heterogeneity and capacity drop on freeway MFD are investigated. The presented control approach is tested using different models as the plant. The presented control approach is compared with other optimal control approaches. |
S0968090X1930172X | Advances in communications technology have made the development of connected and automated vehicle applications that may potentially replace traditional gantry operated lane control signals possible . This paper develops the concept of a prototype CAV enabled LCS application and provides a preliminary assessment of the potential improvement it offers over traditional LCS . Real world data obtained from an LCS on I 66 in Northern Virginia was used to calibrate and validate a baseline simulation model . Further the current lane control scenarios utilized in the Northern Virginia LCS were identified and relevant data resulting from implementation of those scenarios were collected to model the LCS in a simulation environment . The performance of real world LCS was then compared to a prototype CAV enabled LCS application developed in this research . The CAV enabled LCS application consistently outperformed the traditional LCS with increased throughput and speeds . On average an increase of 18.4 9.6 and 12.8 in throughput was observed for three selected scenarios under the best case of a 1 sec headway . Furthermore the CAV enabled LCS application was also found to reduce volatility represented by variation in acceleration and deceleration regimes by an average of 25.6 and 49.6 . The reduction in turbulence in the traffic stream may indicate potential improved safety with the CAV system . | Develop a prototype cooperative lane control LCS application for connected and automated vehicles under multiple platoons. The novel concept represents the future of Active Traffic Management and replaces traditional gantry deployed LCS. Analyze the operational impacts of cooperative lane control in terms of improvement in freeway throughput. Utilize the concept of volatility to infer variations in acceleration and deceleration regimes with CAVs. |
S0968090X19301901 | Autonomous Vehicles may become widely diffused as a road transport technology around the world . However two conditions of successful adoption of AVs are that they must be synchronously shared to avoid negative transport network and environmental consequences and that high levels of public acceptance of the technology must exist . The implications of these two conditions are that travellers must accept sharing rides with unfamiliar others in Shared Autonomous Vehicles . Two factors that have been identified as being positive influencers of acceptance are comfort and trust . The present paper undertakes a novel examination as to how comfort and trust ratings are affected by specific attributes of the ride experience of travelling in a fully automated real world shared vehicle . To this end 55 participants experienced riding in an SAV shuttle under experimental conditions at a test facility . Each experimental run involved two unrelated participants accompanied by a safety operative and a researcher undertaking four trips in the SAV during which two conditions were presented for each of the independent variables of direction of face and maximum vehicle speed . Order of presentation was varied between pairs of participants . After each run participants rated the dependent variables trust and comfort . Expected and evaluative ratings were also obtained during pre experimental orientation and debriefing sessions . Statistically significant relationships | Novel contribution analysing user trust and comfort in a shared autonomous vehicle. Statistically significant relation between trust and speed and direction of face. Strong correlation between comfort and trust. Car drivers in particular showed increased favourability after the experience. |
S0968090X19302505 | This paper considers a last mile delivery system in which a delivery truck operates in coordination with a fleet of unmanned aerial vehicles . Deploying UAVs from the truck enables customers located further from the depot to receive drone based deliveries . The problem is first formulated as a mixed integer linear program . However owing to the computational complexity of this problem only trivially sized problems may be solved directly via the MILP . Thus a heuristic solution approach that consists of solving a sequence of three subproblems is proposed . Extensive numerical testing demonstrates that this approach effectively solves problems of practical size within reasonable runtimes . Additional analysis quantifies the potential time savings associated with employing multiple UAVs . The analysis also reveals that additional UAVs may have diminishing marginal returns . An analysis of five different endurance models demonstrates the effects of these models on UAV assignments . The model and heuristic also support anticipated future systems that feature automation for UAV launch and retrieval . | A new extension to the ying sidekick TSP is presented. This problem assigns one truck and multiple heterogeneous drones to deliver parcels. Queueing of drone launch and retrieval activities is included in the formulation. A three phase heuristic solves problems with 100 customers and 4 drones. Numerical analysis provides insights into system behaviors and heuristic performance. |
S0968090X19302803 | This paper studies the trajectory planning problem for multiple aircraft in converging arrival routes in the presence of a multi cell storm in development . Storm avoidance constraints are enforced by approximating each cell of the storm as a moving and size changing ellipsoid . Besides storm avoidance constraints operational constraints such as following an arrival procedure or time based separation between aircraft are also considered . The problem is solved using nonlinear model predictive control based on hybrid optimal control with logical constraints in disjunctive form . Logical constraints in disjunctive form arise in modelling of both storm avoidance and operational constraints and also in modelling general decision making processes during flight such as establishing which among two or more actions should be taken to solve a contingency . The evolution of the storms is tackled using the nonlinear model predictive control scheme which iteratively re plans the trajectories as a new estimation of the state of the storms is available . The presence of this feedback mechanism in the trajectory planning scheme makes it substantially different from open loop trajectory planning methods . Since it is intended for trajectory planning with very short time horizon before the departure or during the flight it has been herein called online trajectory planning . An embedding approach is employed to transform logical constraints in disjunctive form into inequality and equality constraints which involve only continuous auxiliary variables . In this way the hybrid optimal control problem is converted into a smooth optimal control problem thereby reducing the computational complexity of finding the solution . The effectiveness of the approach is demonstrated through several numerical experiments . | Storm avoidance constraints are modelled using moving and size changing ellipsoid. Besides storm avoidance constraints operational constraints are also considered. Nonlinear model predictive control based on hybrid optimal control has been used. An embedding approach is employed to tackle logical constraints. The evolution of the storms is handled using the nonlinear model predictive control. |
S0968090X19303122 | Energy efficiency of train operations is influenced largely by the speed control and the scheduled running time in the train timetable . In practice the running time of a train is often determined in the train timetabling process at the macroscopic level while the energy efficient speed control of a train on a segment is often determined at the microscopic level with the given timetable . They are usually optimized separately due to limited computational resources which however may result in sub optimal solutions . To address this issue this paper proposes a novel integrated micro macro approach for better incorporating train energy efficient speed control into the railway timetabling process . Firstly we formulated the integrated train timetabling and speed control optimization problem as a nonlinear mixed integer programming model . Due to its complexity we reformulate it on the basis of flow conservation theory in a spacetime speed network and solve the problem in two steps . In the first step a set of pre solved energy efficient train trajectory templates is generated by a segment level optimization approach with consideration of train travel time entry speed and exit speed to save computation time . In the second step a near optimum train energy efficient timetable solution is found by a fast algorithm which consists of the shortest generalized cost path algorithm conflict detection and resolution algorithm and calculation of dynamic headways between two successive trains . The numerical experiments demonstrate that the developed approach provides better outcomes than the benchmark case in terms of both train journey time and energy consumption . | Integrate train trajectory optimization with timetabling. Pre solved segment level train trajectory is to improve computational efficiency. Consider dynamic headways between two successive trains. A fast algorithm is proposed to find the near optimum solution. |
S0968090X19303213 | Optimization of on demand transportation provisions and ride sharing services in evacuations may provide increased network capacity and enhanced evacuation performance to transportation systems and improve equity and disaster preparedness for community and society . This paper proposes a two phase model for optimizing trip planning and operations by integrating a ride sharing process in short notice evacuations to allow a joint optimization of driver rider matching and necessary transfer connections among shared vehicle trips . In the first phase following network topology information and personal requests a vehicle space time hyper dimensional network is developed by constructing vehicle space time vertexes and arcs . In the second phase based on the constructed vehicle space time network a new time discretized multi rider multi driver network flow model is built to formulate ride sharing with connecting transfers . A Lagrangian relaxation solution approach is designed to solve the model in a real world network scenario . Numerical analyses are conducted with considerations given to the three operating parameters in the method and the analysis results show that the proposed model can not only meet the evacuation trip needs of the participating parties but it also supports personalized requests and on demand accesses . A small sample network is used to theoretically test the whole model and the underlying concepts and solution strategy to show each step implemented in details and finally the applicability of the method is demonstrated using the Chicago City network . | Propose a solution to the media question Where is the app for escaping a hurricane . Model ride sharing with transfers in a vehicle space time network. Consider trip time window detour tolerance transfer time and vehicle parking time in the ride sharing framework. Develop a Lagrangian relaxation algorithm for the multi dimensional network flow program. Improve the performance of ondemand mobility services in short notice evacuations. |
S0968090X19303493 | The actions of autonomous vehicle manufacturers and related industrial partners as well as the interest from policy makers and researchers point towards the likely initial deployment of autonomous vehicles as shared autonomous mobility services . Numerous studies are lately being published regarding Shared Autonomous Vehicle applications and hence it is imperative to have a comprehensive outlook consolidating the existing knowledge base . This work comprehensively consolidates studies in the rapidly emerging field of SAV . The primary focus is the comprehensive review of the foreseen impacts which are categorised into seven groups namely Traffic Safety Travel behaviour Economy Transport supply Landuse Environment Governance . Pertinently an SAV typology is presented and the components involved in modelling SAV services are described . Issues relating to the expected demand patterns and a required suitable policy framework are explicitly discussed . | This work comprehensively consolidates studies in the rapidly emerging field of SAV. Foreseen SAV impacts are categorised into seven groups. An SAV typology is presented and the components involved in modelling SAV services are described. Issues relating to the expected demand patterns and a required suitable policy framework are explicitly discussed. |
S0968090X19303572 | An ACC based traffic control strategy is presented which improves the motorway traffic flow efficiency by changing in real time the driving behaviour of ACC equipped vehicles in motorway sections according to the corresponding traffic conditions . The control strategy comprises three distinct actions gradual decrease of ACC time gaps at near capacity traffic in order to increase capacity minimum time gaps and acceleration increase both at the very vicinity of active bottlenecks in order to increase the discharge flow . The behaviour and impact of the control strategy and of each of its parts separately are demonstrated for different ACC penetration rates via microscopic simulation applied to a real motorway stretch . The simulation results show that even for low penetration rates of ACC vehicles the proposed strategy leads to sensible improvements regarding the average vehicle delay and fuel consumption by delaying the onset of congestion and by speeding up its dissolution . | A real time traffic control strategy changes the driving behavior of ACC vehicles. Capacity and discharge flow of the motorway are increased where and when needed. Changing ACC time gap and acceleration improves the traffic flow efficiency. |
S0968090X19303717 | It is a common practice for transit lines with fluctuating passenger demands to use demand driven bus scheduling to reduce passenger waiting time and avoid bus overcrowding . However current literature on the demand driven bus scheduling generally assumes fixed bus capacity and exclusively optimizes bus dispatch headways . With the advent of connected and autonomous vehicle technology and the introduction of autonomous minibus shuttle the joint design of bus capacity and dispatch headway holds promises to further improving the system efficiency while reducing operating and passenger costs . This paper formulates this problem as an integer nonlinear programming model for transit systems operating with mixed human driven and autonomous buses . In such mixed operating environment the model simultaneously considers dynamic capacity design of autonomous bus i.e . autonomous buses with varying capacity can be obtained by assembling and or dissembling multiple autonomous minibuses trajectory control of autonomous bus i.e . autonomous bus can dynamically adjust its running time as a function of its forward and backward headways and stop level passenger boarding and alighting behavior . The objective of the model is designed to balance the trade off between the operating costs of dispatching different types of bus and the costs of increased passenger waiting time due to inadequate bus dispatching . The model is solved using a dynamic programming approach . We show that the proposed model is effective in reducing passenger waiting time and total operating cost . Sensitivity analysis is further conducted to explore the impact of miscellaneous factors on optimal dispatching decisions such as penetration rate of autonomous bus bus running time variation and passenger demand level . | We jointly optimize the scheduling and capacity of mixed human driven and autonomous buses. An integer nonlinear programming model is developed to consider both bus operating cost and passenger cost. The model can be solved efficiently using a dynamic programming approach. Simulation and empirical tests prove that autonomous buses are beneficial to both operators and passengers. |
S0968090X19303821 | We propose a novel approach for network wide traffic state prediction where the statistical time series model ARIMA is used to postprocess the residuals out of the fundamental machine learning algorithm MLP . This approach is named as NN ARIMA . Neural Network MLP is employed to capture network scale co movement pattern of all traffic flows and ARIMA is used to further extract location specific traffic features in the residual time series out of Neural Network . The experiment results show that the postprocessing the residuals of Neural Network by the ARIMA analysis helps to significantly improve accuracy of traffic state prediction by 8.913.4 in term of mean squared error reduction . In order to verify the efficiency of the ARIMA analysis in the postprocessing Multidimensional Support Vector Regression model is also employed to replace the role of Neural Network in the comparative experiment . Two streams of comparisons NN vs. NN ARIMA and MSVR vs. MSVR ARIMA are performed and show consistent results . The proposed approach not only can capture network wide co movement pattern of traffic flows but also seize location specific traffic characteristics as well as sharp nonlinearity of macroscopic traffic variables . The case study indicates that the accuracy of prediction can be significantly improved when both network scale traffic features and location specific characteristics are taken into account . | We sequentially concatenate Neural Network with ARIMA for traffic state prediction. Neural Network captures network scale co movement pattern of all traffic flows. ARIMA postprocesses the NN residuals to extract location specific traffic features. The postprocessing significantly improves the accuracy of prediction. |
S0968090X1930395X | This paper proposes a new optimization model for the network design problem of the demand responsive customized bus . The proposed model consists of two phases inserting passenger requests dynamically in an interactive manner and optimizing the service network statically based on the overall demand . In the dynamic phase we propose a hierarchical decision making model to describe the interactive manner between operator and passengers . The CB network design problem is formulated in a mixed integer program with the objective of maximizing operators revenue . The CB passengers travel behavior is measured by a discrete choice model given the trip plan provided by the operator . A dynamic insertion method is developed to address the proposed model in the dynamic phase . For the network design problem in the static phase the service network is re optimized based on the confirmed passengers with strict time deviation constraints embedded in the static multi vehicle pickup and delivery problem . An exact solution method is developed based on the branch and bound algorithm . Numerical examples are conducted to verify the proposed models and solution algorithms . | Propose an integrated decision making framework for the demand responsive customized bus network design. Formulate the network design problem as a two phase optimization model. Formulate the interactive mechanism between the operator and passengers in a hierarchical decision making model. |
S0968090X19304048 | In this paper we study the dial a ride problem of ride sharing automated taxis in an urban road network considering the traffic congestion caused by the ATs . This shared automated mobility system is expected to provide a seamless door to door service for urban travellers much like what the existing transportation network companies do but with decreased labour cost and more flexible relocation operations due to the vehicles automation . We propose an integer non linear programming model that optimizes the routing of the ATs to maximize the system profit depending on dynamic travel times which are a non linear function of the ATs flows . It is important to involve traffic congestion in such a routing problem since for a growing number of ATs circulating in the city their number will lead to delays . The model is embedded within a rolling horizon framework which divides a typical day into several horizons to deal with the real time travel demand . In each horizon the routing model is solved with the demand at that interval and assuring the continuity of the trips between horizons . Nevertheless each horizon model is hard to solve given its number of constraints and decision variables . Therefore we propose a solution approach based on a customized Lagrangian relaxation algorithm which allows identifying a near optimal solution for this difficult problem . Numerical experiments for the city of Delft The Netherlands are used to demonstrate the solution quality of the proposed algorithm as well as obtaining insights about the AT system performance . Results show that the solution algorithm can solve the proposed model for hard instances . Ride sharing makes the AT system more capable to provide better service regarding delay time and the number of requests that can be attended by the system . The delay penalty on the profit objective function is an effective control parameter on guaranteeing the service quality while maintaining system profitability . | An optimization model is formulated to maximize the automated taxi systems profit. The effect of traffic congestion is considered in automated taxis dial a ride problem. A customized Lagrangian relaxation algorithm can solve the model for hard instances. Ride sharing contributes more served requests and less delay. The automated taxis service quality is sensitive to the delay penalty. |
S0968090X19304061 | Because of zero emissions and other social and economic benefits electric vehicles are currently being introduced in more and more transit agencies around the world . One of the most challenging tasks involves efficiently scheduling a set of EVs considering the limited driving range and charging requirement constraints . This study examines the battery electric transit vehicle scheduling problem with stationary battery chargers installed at transit terminal stations . Two equivalent versions of mathematical formulations of the problem are provided . The first formulation is based on the deficit function theory and the second formulation is an equivalent bi objective integer programming model . The first objective of the math programming optimization is to minimize the total number of EVs required while the second objective is to minimize the total number of battery chargers required . To solve this bi objective BET VSP two solution methods are developed . First a lexicographic method based two stage construction and optimization solution procedure is proposed . Second an adjusted max flow solution method is developed . Three numerical examples are used as an expository device to illustrate the solution methods together with a real life case study in Singapore . The results demonstrate that the proposed math programming models and solution methods are effective and have the potential to be applied in solving large scale real world BET VSPs . | Focused on the battery electric transit vehicle scheduling problem BET VSP . Providing two equivalent mathematical formulation versions of BET VSP. Proposing a lexicographic method based two stage solution procedure. Developing an adjusted max flow solution method. Case study results demonstrate the efficacy and efficiency of the solution methods. |
S0968090X19304218 | At present en route flight traffic is carried out on a system of predefined routes with a low number of intersections between aircraft trajectories . This enables the air traffic controllers to control and supervise the traffic especially around these intersections . Consequently the route system leads to a low ratio of used to unused airspace where not necessarily the shortest route is used for each flight . To reduce trajectory length the idea of free routing has been developed whereby each aircraft uses the direct connection between origin and destination airport generating a traffic distribution which uses nearly the entire available airspace . As a consequence many intersections between flight trajectories occur making it more difficult for controllers to handle . We use these intersections as the basis of a so called main flow system with trajectories consisting of intersection points instead of waypoints . The intersections of all trajectories of a traffic sample are clustered and the resulting cluster centres are used as nodes in a route system . Additional processing is applied to identify a system of main flows and reduce the number of intersections to an acceptable amount . Our approach is able to identify major traffic flows within unstructured great circle traffic and to create a main flow system which is a compromise between the flexibility of free routing and the easier surveillance by controllers in the case of a predefined route network . To prove the ability of the proposed method to identify main flows it was applied to a scenario of planned flights following the standard route structure . Subsequent tests with two different free routing scenarios led to new route systems where the median adapted trajectory length for flights of the traffic sample is merely 0.9 higher than the direct connections . Furthermore structural complexity is lower for intersections of the new main flow system compared to those of direct or great circle scenarios . | Efficient method to identify main traffic flows in unstructured free route traffic. Usability enhancement of free routing by structural adaptations. Intersections of trajectories used as main characteristic of traffic flows. Efficient adaptation of free route traffic to a structured main flow system. Development of a new metric to quantify the structural complexity of traffic flows. |
S0968090X19304267 | This paper proposes a deep architecture called residual spatio temporal network for short term travel demand forecasting . It comprises fully convolutional neural networks and a hybrid module consisting of an extended Conv LSTM that can achieve trade off of convolutional operation and LSTM cells by tuning the hyperparameters of Conv LSTM convolutional neural networks and traditional LSTM . These modules are combined via residual connections to capture the spatial temporal and extraneous dependencies of travel demand . The end to end trainable RSTN redefines the traditional prediction problem as a learning residual function with regard to the travel density in each time interval . Further more a dynamic request vector based data representation scheme is presented which catches the intrinsic characteristics and variation of the trend to improve the performance of forecasting . Simulations with two real word data sets show that the proposed method outperforms the existing forecasting algorithms reducing the root mean square error by up to 17.87 . | An improved LSTM which is the fusion of convolutional technique and the traditional LSTM cell in a effective way termed CE LSTM is proposed in this paper. A novel architecture named RSTN is constructed which is an end to end trainable model that can capture the exogenous dependences and spatio temporal correlations of travel demand adequately. A residual connection fashion is introduced to RSTN yielding an easy training approach by reformulating a traditional prediction problem as a learning residual function with regard to the travel density in each time interval. A novel representation of the historical travel demand is proposed in this paper. It enables deeper and more logical representation of historical data and reflects the more detailed dynamics of travel requests. |
S0968090X19304322 | With an increasing number of automated vehicles appearing on roads and interacting with conventional traffic there is a need for improved simulation approaches to replicate and forecast the resulting effects . Interactions between AVs and their drivers and interaction with other human drivers involve new types of complex behavioural processes . There is an increasing necessity to explicitly incorporate these human factor processes in simulation which can not be properly accounted for with most current models . In this paper we present an extended conceptual simulation framework based on human factors processes and applicable for automated driving that does this . The framework makes use of previously constructed constructs to include the effects of driver task demand situation awareness and fundamental diagrams of task demand to extend to automated driving . This is especially considered for the case of transition of control as an important aspect of vehicle driver interaction . The framework is demonstrated in two experimental cases that consider different ToC situations and is found to be face valid within the applied assumptions . Challenges remain in regard to a lack of quantitative evidence from traffic psychology automated vehicle dynamics control and human vehicle interaction . With increasing amounts of research on going in these areas the extended framework will act as a valuable approach to further study and quantify the effects of AVs in mixed traffic in the future . | Interactions with driver and automated vehicles involve new types of complex behavioural processes. Modelling these processes requires explicit inclusion of human factors in simulation. An extended modelling framework is presented for mixed traffic that includes these behavioural interactions. This novel approach explicitly considers driver cognitive loading and related performance with automated vehicles. Two experimental cases considering transition of control demonstrate the face validity of the approach. |
S0968090X19304577 | The recent technological innovations in various ICT platforms have given rise to innovative mobility solutions . Such systems could potentially address some of the inherent shortcomings of a line schedule based public transport system . Previous studies either assumed that flexible on demand services are used as an exclusive door to door service or offered as a feeder connection to high capacity public transport services . However users may combine line schedule based public transport systems and on demand services so that their travel impedance is minimized . To this end we propose a multimodal route choice and assignment model that allows users combining Fixed and Flexible PT or use them as individual modes while demand for these services is endogenously determined . The model takes into account the dynamic demandsupply interaction using an iterative learning framework . Flexible public transport can be used to perform any part of the trip ranging from a first last mile service to an exclusive direct door to door connection . The developed model is implemented in an agent based simulation framework . The model is applied to a network centered around the city of Amsterdam The Netherlands . Scenarios where Fixed PT and Flexible PT are offered as mutually exclusive modes or can be combined into a single journey are analysed . Results indicate that Flexible PT is predominantly used for covering | Combined passenger route choice for fixed and flexible PT services. Demand for fixed and flexible services is endogenously determined. Agent based simulation applied to the network of Amsterdam. Decrease in share of fixed services while increase in overall share of PT. Level of service barely improves for fleet size 5 of the travel demand. |
S0968090X19305078 | Often serving as the backbone for public transport any serious metro incident will have a severe impact on passengers . In the aftermath of a disruption establishing alternative transport means to carry the affected metro passengers such as via substitute bus service is critical . After a particular routing and scheduling plan of SB service is determined the question is how to assemble the SB fleet which has different options . Few studies have addressed the issue of designing the contract with a bus company for the provision of SB including SB availability and service start time guarantee and pricing schemes under uncertain metro system recovery time . This paper attempts to fill this gap . We investigated both the bus companys profit in providing the SB service and the metro companys gain in passenger loss reduction after a metro disruption for setting up the SB service contract . Two payment schemes were considered fixed payment and linear payment . The objective is to design the SB service contract which defines the payment scheme and guaranteed SB service start time from both the perspective of the metro company and that of the bus company to explore feasible solutions . In addition the scenarios of collaborative decision between the bus and metro companies nonlinear passenger demand drop fleet size arrivals of new passengers and passengers waiting time are investigated . | Uncertain recovery time is considered in Substitute Bus SB deployment study. Cost benefit analysis is conducted of both the metro and bus companies. The bus companys profit from providing the SB service is examined. The metro companys gain of calling for the SB service is evaluated. Passenger optimal solution is proposed to determine payment rate and SB arrival time. |
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