An agent-based model for real-time bus stop-skipping and holding schemes

This paper develops a real-time agent-based simulation model to optimize the dynamic bus stop-skipping and holding schemes. The proposed agent-based simulation model is capable of modeling, schedul...

[1]  Konstantinos Gkiotsalitis,et al.  Robust Stop-Skipping at the Tactical Planning Stage with Evolutionary Optimization , 2019, Transportation Research Record: Journal of the Transportation Research Board.

[2]  Chen Zhou,et al.  Discrete and Dynamic Optimization Problems in Operation Management , 2013 .

[3]  Mark D. Hickman,et al.  An Analytic Stochastic Model for the Transit Vehicle Holding Problem , 2001, Transp. Sci..

[4]  David Bernstein,et al.  The Holding Problem with Real - Time Information Available , 2001, Transp. Sci..

[5]  Hai Le Vu,et al.  Optimizing multi-agent based urban traffic signal control system , 2018, J. Intell. Transp. Syst..

[6]  Washington Y. Ochieng,et al.  Agent-based day-to-day traffic network model with information percolation , 2017 .

[7]  Hu Zhang,et al.  Advantages of bus stop skipping and holding control in reducing schedule deviation , 2019 .

[8]  Ricardo Giesen,et al.  Analysis of real-time control strategies in a corridor with multiple bus services , 2015 .

[9]  Miaojia Lu,et al.  Improving the sustainability of integrated transportation system with bike-sharing: A spatial agent-based approach , 2018, Sustainable Cities and Society.

[10]  Chung-Hsing Yeh,et al.  A Multiobjective Model for Passenger Train Services Planning: Application to Taiwan's High-Speed Rail Line , 2000 .

[11]  Mei Chen,et al.  Optimal train scheduling under a flexible skip-stop scheme for urban rail transit based on smartcard data , 2016, 2016 IEEE International Conference on Intelligent Rail Transportation (ICIRT).

[12]  Michel Gendreau,et al.  REAL-TIME SCHEDULING ON A TRANSIT BUS ROUTE: A 0-1 STOCHASTIC PROGRAMMING MODEL. IN: PROCEEDINGS OF THE THIRTY-THIRD ANNUAL MEETING, TRANSPORTATION RESEARCH FORUM, OCTOBER 31 - NOVEMBER 2, 1991, NEW ORLEANS, LOUISIANA , 1991 .

[13]  Stephan Winter,et al.  Simulating Demand-responsive Transportation: A Review of Agent-based Approaches , 2015 .

[14]  Liping Fu,et al.  Optimization of headways with stop‐skipping control: a case study of bus rapid transit system , 2015 .

[15]  Ricardo Giesen,et al.  How much can holding and/or limiting boarding improve transit performance? , 2012 .

[16]  Hu Zhang,et al.  Sensitivity Analysis of Fleet Size for Dynamic Headway-Based Control Method Performance in terms of Passengers’ Experience , 2020 .

[17]  Vladimír Bures,et al.  Comparative analysis of selected path-planning approaches in large-scale multi-agent-based environments , 2018, Expert Syst. Appl..

[18]  G. F. Newell.  Control of Pairing of Vehicles on a Public Transportation Route, Two Vehicles, One Control Point , 1974 .

[19]  Stephen G. Ritchie,et al.  A multi-agent architecture for cooperative inter-jurisdictional traffic congestion management , 2002 .

[20]  Lei Zhang,et al.  AgBM-DTALite: An integrated modelling system of agent-based travel behaviour and transportation network dynamics , 2017, Travel Behaviour and Society.

[21]  David Meignan,et al.  Simulation and evaluation of urban bus-networks using a multiagent approach , 2007, Simul. Model. Pract. Theory.

[22]  Catherine Morency,et al.  Macro-, meso-, and micro-level validation of an activity-based travel demand model , 2017 .

[23]  Ricardo Giesen,et al.  Design of limited-stop services for an urban bus corridor with capacity constraints , 2010 .

[24]  Mark D. Abkowitz,et al.  IMPLEMENTING HEADWAY-BASED RELIABILITY CONTROL ON TRANSIT ROUTES , 1990 .

[25]  Keechoo Choi,et al.  Optimizing Skip-Stop Rail Transit Stopping Strategy using a Genetic Algorithm , 2014 .

[26]  Zhiyuan Liu,et al.  Bus stop-skipping scheme with random travel time , 2013 .

[27]  Yu Gu,et al.  A two-phase optimization model for the demand-responsive customized bus network design , 2020 .

[28]  Graham Currie,et al.  Modeling Dwell Time for Streetcars in Melbourne, Australia, and Toronto, Canada , 2012 .

[29]  Minh Tran,et al.  Performance Measurements on Mass Transit , 2009 .

[30]  Minghui Ma,et al.  A self-adaptive method to equalize headways: Numerical analysis and comparison , 2016 .

[31]  Huasheng Liu,et al.  A Dynamic Short-Turning Bus Control for Uncertain Demand , 2017 .

[32]  Martin N. Milkovits.  Modeling the Factors Affecting Bus Stop Dwell Time , 2008 .

[33]  Carlos F. Daganzo,et al.  Dynamic control of complex transit systems , 2015 .

[34]  Minghui Ma,et al.  Coordinated control method to self-equalize bus headways: an analytical method , 2019 .

[35]  Yanfeng Ouyang,et al.  Dynamic bus substitution strategy for bunching intervention , 2018, Transportation Research Part B: Methodological.

[36]  Ricardo Giesen,et al.  Generation and design heuristics for zonal express services , 2015 .

[37]  Michel Gendreau,et al.  Real-Time Dispatching of Public Transit Operations with and without Bus Location Information , 1995 .

[38]  Hong Zheng,et al.  A Primer for Agent-Based Simulation and Modeling in Transportation Applications , 2013 .

[39]  Dave Elliman,et al.  A New Intelligent Agent-based Strategy for Constrained Multiple Destination Routing Problems , 2004, Comput. J..

[40]  Shuai Li,et al.  Multi-objective optimal control formulations for bus service reliability with traffic signals , 2017 .

[41]  Xiaobo Qu,et al.  Dynamic headway control for high‐frequency bus line based on speed guidance and intersection signal adjustment , 2019, Comput. Aided Civ. Infrastructure Eng..

[42]  Zhiyuan Liu,et al.  Design of limited-stop bus service with capacity constraint and stochastic travel time , 2015 .

[43]  Javier Faulin,et al.  Agent-based simulation for horizontal cooperation in logistics and transportation: From the individual to the grand coalition , 2018, Simul. Model. Pract. Theory.

[44]  G. F. Newell,et al.  Control Strategies for an Idealized Public Transportation System , 1972 .

[45]  Dewei Li,et al.  Estimation method for a skip-stop operation strategy for urban rail transit in China , 2014 .

[46]  Wei Wang,et al.  Cellular automaton simulations of a T-shaped unsignalised intersection with refined configurations , 2014 .

[47]  Carlos F. Daganzo,et al.  Reducing bunching with bus-to-bus cooperation , 2011 .

[48]  Tarek Sayed,et al.  Validation of an agent-based microscopic pedestrian simulation model in a crowded pedestrian walking environment , 2018, Transportation Planning and Technology.

[49]  Ahmed M El-Geneidy,et al.  The Effects of Articulated Buses on Dwell and Running Times , 2011 .

[50]  Hussein Dia,et al.  An agent-based approach to modelling driver route choice behaviour under the influence of real-time information , 2002 .

[51]  Nigel H. M. Wilson,et al.  Real-time holding control for high-frequency transit with dynamics , 2016 .