Proactive empty vehicle rebalancing for Demand Responsive Transport services

被引:19
|
作者
Bischoff, Joschka [1 ]
Maciejewski, Michal [2 ]
机构
[1] Swiss Fed Railways, Passenger Div, Bern, Switzerland
[2] Tech Univ Berlin, Transport Syst Planning & Transport Telemat, Berlin, Germany
关键词
Demand Responsive Transport; MATSim; Vehicle Rebalancing; Ridesharing;
D O I
10.1016/j.procs.2020.03.162
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Worldwide, ridesharing business is steadily growing and has started to receive attention also by public transport operators. With future fleets of Autonomous Vehicles, new business models connecting schedule-based public transport and feeder fleets might become a feasible transport mode. However, such fleets require a good management to warrant a high level of service. One of the key aspects of this is proactive vehicle rebalancing based on the expected demand for trips. In this paper we model vehicle rebalancing as the Dynamic Transportation Problem. Results suggest that waiting times can be cut by around 30 % without increasing the overall vehicle miles travelled for a feeder fleet in rural Switzerland. (C) 2020 The Authors. Published by Elsevier B.V.
引用
收藏
页码:739 / 744
页数:6
相关论文
共 50 条
  • [21] Aggregation or Selection? Clustering Many Objectives for Vehicle Routing Problem with Demand Responsive Transport
    Mendes, Renan S.
    Wanner, Elizabeth F.
    Martins, Flavio V. C.
    Deb, Kalyanmoy
    [J]. 2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021), 2021, : 1257 - 1264
  • [22] Understanding the behavioral intention of the rural population to use demand-responsive transport services
    Schasche, Stephanie E.
    Wankmueller, Christian
    Hampl, Nina
    [J]. TRANSPORTATION RESEARCH INTERDISCIPLINARY PERSPECTIVES, 2023, 22
  • [23] A predictive chance constraint rebalancing approach to mobility-on-demand services
    Jacobsen, Sten Elling Tingstad
    Lindman, Anders
    Kulcsar, Balazs
    [J]. COMMUNICATIONS IN TRANSPORTATION RESEARCH, 2023, 3
  • [24] Demand-responsive rebalancing zone generation for reinforcement learning-based on-demand mobility
    Castagna, Alberto
    Gueriau, Maxime
    Vizzari, Giuseppe
    Dusparic, Ivana
    [J]. AI COMMUNICATIONS, 2021, 34 (01) : 73 - 88
  • [25] Estimating the demand for launch vehicle services
    Rusch, RJ
    Sharples, R
    [J]. COLLECTION OF THE 18TH AIAA INTERNATIONAL COMMUNICATIONS SATELLITE SYSTEMS CONFERENCE AND EXHIBIT, TECHNICAL PAPERS, VOLS 1 AND 2, 2000, : 72 - 80
  • [26] Optimization of the Vehicle Routing Problem with Demand Responsive Transport Using the NSGA-II Algorithm
    Mendes, Renan S.
    Wanner, Elizabeth F.
    Sarubbi, Joao F. M.
    Martins, Flavio V. C.
    [J]. 2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2016, : 2657 - 2662
  • [27] 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
  • [28] The importance of information flows temporal attributes for the efficient scheduling of dynamic demand responsive transport services
    Diana, M
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2006, 40 (01) : 23 - 46
  • [29] On demand forecasting of demand-responsive paratransit services with prior reservations
    Chandakas, Ektoras
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2020, 120
  • [30] Robust matching-integrated vehicle rebalancing in ride-hailing with uncertain demand
    Guo, Xiaotong
    Caros, Nicholas S.
    Zhao, Jinhua
    [J]. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2021, 150 : 161 - 189