MOBILITY-ON-DEMAND SERVICE IN MASS TRANSIT: HYPERCOMMUTE OPTIONS

被引:0
|
作者
Kayikci, Yasanur [1 ]
机构
[1] Turkish German Univ, Dept Ind Engn, Istanbul, Turkey
关键词
Mobility-on-demand; mobility; HyperCommute; dynamic ridesharing; public transportation; digitization; route analytics;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Digitization, increasing automation and new business models like shared mobility have revolutionized transportation and mobility. Ridesharing companies like Uber and Lyft provide technological platforms and support to connect drivers and riders on the basis of demand-response services. Although the most improvements in on-demand applications have been experimented in private transit services, there is no any implementation in public transportation to connect public transit services and passengers each other. On-demand is still vague. However, providing on-demand services in public transportation is complicated because of the big capacity problem in mass transit, its application in public transit services can enable flexible mobility for riders and provide personalized mobility experience. This paper presents the concept of mobilityon-demand service and its application in public transit services with an technological innovation of FM/LM pilot project represented by HyperCommute. The paper starts with introduction, then the business model of mobility-on-demand service is described and the most used algorithms are explained, then an illustrative example of HyperCommute mobility-on-demand service is given. Also, the applicability of mobility-ondemand service in Istanbul is discussed. The paper ends up with conclusion and future directions.
引用
收藏
页码:447 / 460
页数:14
相关论文
共 50 条
  • [41] Vehicle Rebalancing for Mobility-on-Demand Systems with Ride-Sharing
    Wallar, Alex
    van der Zee, Menno
    Alonso-Mora, Javier
    Rus, Daniela
    [J]. 2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2018, : 4539 - 4546
  • [42] Rebalancing Shared Mobility-on-Demand Systems: a Reinforcement Learning Approach
    Wen, Jian
    Zhao, Jinhua
    Jaillet, Patrick
    [J]. 2017 IEEE 20TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2017,
  • [43] Dynamic Pricing Mechanism Design for Electric Mobility-on-Demand Systems
    Ni, Liang
    Sun, Bo
    Wang, Su
    Tsang, Danny H. K.
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (08) : 11361 - 11375
  • [44] Hierarchical Control for Vehicle Repositioning in Autonomous Mobility-on-Demand Systems
    Zhu, Pengbo
    Ferrari-Trecate, Giancarlo
    Geroliminis, Nikolas
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2024,
  • [45] A Double-Layered MPC of Autonomous Mobility-on-Demand Systems
    Wang, Yujie
    Lou, Yuanyuan
    Li, Shaoyuan
    [J]. 2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 2670 - 2675
  • [46] Towards Online Electric Vehicle Scheduling for Mobility-On-Demand Schemes
    Gkourtzounis, Ioannis
    Rigas, Emmanouil S.
    Bassiliades, Nick
    [J]. MULTI-AGENT SYSTEMS, EUMAS 2018, 2019, 11450 : 94 - 108
  • [47] Congestion Management for Mobility-on-Demand Schemes that Use Electric Vehicles
    Rigas, Emmanouil S.
    Tsompanidis, Konstantinos S.
    [J]. MULTI-AGENT SYSTEMS AND AGREEMENT TECHNOLOGIES, EUMAS 2020, AT 2020, 2020, 12520 : 52 - 66
  • [48] On the Interaction between Autonomous Mobility-on-Demand and Public Transportation Systems
    Salazar, Mauro
    Rossi, Federico
    Schiffer, Maximilian
    Onder, Christopher H.
    Pavone, Marco
    [J]. 2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2018, : 2262 - 2269
  • [49] 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
  • [50] Multi-Objective Analysis of Ridesharing in Automated Mobility-on-Demand
    Cap, Michal
    Alonso-Mora, Javier
    [J]. ROBOTICS: SCIENCE AND SYSTEMS XIV, 2018,