Towards an Agent-based Model for Demand-Responsive Transport Serving Thin Flows

被引:2
|
作者
Cich, Glenn [1 ]
Knapen, Luk [1 ]
Galland, Stephan [2 ]
Vuurstaek, Jan [1 ]
Neven, An [1 ]
Bellemans, Tom [1 ]
机构
[1] Hasselt Univ, Transportat Res Inst IMOB, Wetenschapspk 5 Bus 6, B-3590 Diepenbeek, Belgium
[2] Univ Bourgogne Franche Comte, UTBM, UMR CNRS 6306 LE2I, 13 Rue Ernest Thierry Mieg, F-90010 Belfort, France
关键词
Demand-Responsive Transport; Thin Flows; Micro-Simulation; Agent-Based Modeling; Organizational Modeling; MULTIAGENT SYSTEMS;
D O I
10.1016/j.procs.2016.04.191
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Low volume traveler flows cause problems for public transportation (PT) providers. The Smart-PT project aims to find out how such flows can be combined to increase the service provider viability. The capability to conceive multi-modal trips is fundamental in that context and is modeled by the Trip Sequence Composer (TSC) concept. A TSC is an essential component of the traveler's brain, of the customer support operated by collective transport providers, of trip advisers in websites etc. We present a simulation model design to evaluate the effect of cooperating TSCs on the viability of demand responsive collective transport providers. While obeying specific regulations, specialized services targeting mobility impaired people can also serve regular requests in order to save fleet and personnel costs. All stakeholders are assumed to optimize their private objectives and none of them has global perfect knowledge. (C) 2016 The Authors. Published by Elsevier B.V.
引用
收藏
页码:952 / 957
页数:6
相关论文
共 50 条
  • [1] Accelerating agent-based demand-responsive transport simulations with GPUs
    Saprykin, Aleksandr
    Chokani, Ndaona
    Abhari, Reza S.
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2022, 131 : 43 - 58
  • [2] Simulating Demand-responsive Transportation: A Review of Agent-based Approaches
    Ronald, Nicole
    Thompson, Russell
    Winter, Stephan
    [J]. TRANSPORT REVIEWS, 2015, 35 (04) : 404 - 421
  • [3] An Agent-Based Model for Dispatching Real-Time Demand-Responsive Feeder Bus
    Li, Xin
    Wei, Ming
    Hu, Jia
    Yuan, Yun
    Jiang, Huifu
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2018, 2018
  • [4] A Multi-agent Based Model for Urban Demand-responsive Passenger Transport Services
    Jin, Xu
    Abdulrab, Habib
    Itmi, Mhamed
    [J]. 2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8, 2008, : 3668 - 3675
  • [5] Fixed-Route vs. Demand-Responsive Transport Feeder Services: An Exploratory Study Using an Agent-Based Model
    Calabro, Giovanni
    Le Pira, Michela
    Giuffrida, Nadia
    Inturri, Giuseppe
    Ignaccolo, Matteo
    Correia, Goncalo H. de A.
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2022, 2022
  • [6] A Multi-agent Based Model for Urban Demand-responsive Transport System Intelligent Control
    Jin, Xu
    Abdulrab, Habib
    Itmi, Mhamed
    [J]. 2008 IEEE INTELLIGENT VEHICLES SYMPOSIUM, VOLS 1-3, 2008, : 350 - 355
  • [7] Agent-Based Simulation Approach to Determine Safety Impacts of Demand-Responsive Transport (DRT) in Wayne County, Michigan
    Feizi, Ahmad
    Twumasi-Boakye, Richard
    Djavadian, Shadi
    Fishelson, James
    [J]. TRANSPORTATION RESEARCH RECORD, 2022, 2676 (10) : 361 - 375
  • [8] An Intelligent Model for Urban Demand-responsive Transport System Control
    Jin, Xu
    Wang, Dianhong
    [J]. 2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION WORKSHOP: IITA 2008 WORKSHOPS, PROCEEDINGS, 2008, : 151 - 154
  • [9] Effectiveness of Dynamic Insertion Scheduling Strategy for Demand-Responsive Paratransit Vehicles Using Agent-Based Simulation
    Torkjazi, Mohammad
    Nathan Huynh
    [J]. SUSTAINABILITY, 2019, 11 (19)
  • [10] Assessing the introduction of regional driverless demand-responsive transit services through agent-based modeling and simulation
    Patricio, Anne S.
    Santos, Goncalo Goncalves Duarte
    Antunes, Antonio Pais
    [J]. TRANSPORTATION, 2023,