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A Multi-Modal Route Choice Model with Ridesharing and Public Transit

Author

Listed:
  • Meng Li

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Guowei Hua

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Haijun Huang

    (School of Economics and Management, Beihang University, Beijing 100191, China)

Abstract

With the extensive use of smart-phone applications and online payment systems, more travelers choose to participate in ridesharing activities. In this paper, a multi-modal route choice model is proposed by incorporating ridesharing and public transit in a single-origin-destination (OD)-pair network. Due to the presence of ridesharing, travelers not only choose routes (including main road and side road), but also decide travel modes (including solo driver, ridesharing driver, ridesharing passenger, and transit passenger) to minimize travelers’ generalized travel cost (not their actual travel cost due to the existence of car capacity constraints). The proposed model is expressed as an equivalent complementarity problem. Finally, the impacts of key factors on ridesharing behavior in numerical examples are discussed. The equilibrium results show that passengers’ rewards and toll charge of solo drivers on main road significantly affect the travelers’ route and mode choice behavior, and an increase of passengers’ rewards (toll) motivates (forces) more travelers to take environmentally friendly travel modes.

Suggested Citation

  • Meng Li & Guowei Hua & Haijun Huang, 2018. "A Multi-Modal Route Choice Model with Ridesharing and Public Transit," Sustainability, MDPI, vol. 10(11), pages 1-14, November.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:4275-:d:183822
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    References listed on IDEAS

    as
    1. Xiaolei Wang & Hai Yang & Daoli Zhu, 2018. "Driver-Rider Cost-Sharing Strategies and Equilibria in a Ridesharing Program," Transportation Science, INFORMS, vol. 52(4), pages 868-881, August.
    2. Frederick A. Armah & David O. Yawson & Alex A. N. M. Pappoe, 2010. "A Systems Dynamics Approach to Explore Traffic Congestion and Air Pollution Link in the City of Accra, Ghana," Sustainability, MDPI, vol. 2(1), pages 1-14, January.
    3. Catherine Morency, 2007. "The ambivalence of ridesharing," Transportation, Springer, vol. 34(2), pages 239-253, March.
    4. Athanasios K. Ziliaskopoulos, 2000. "A Linear Programming Model for the Single Destination System Optimum Dynamic Traffic Assignment Problem," Transportation Science, INFORMS, vol. 34(1), pages 37-49, February.
    5. Fukushima, Masao, 1984. "A modified Frank-Wolfe algorithm for solving the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 18(2), pages 169-177, April.
    6. Oren Bahat & Shlomo Bekhor, 2016. "Incorporating Ridesharing in the Static Traffic Assignment Model," Networks and Spatial Economics, Springer, vol. 16(4), pages 1125-1149, December.
    7. Xu, Huayu & Pang, Jong-Shi & Ordóñez, Fernando & Dessouky, Maged, 2015. "Complementarity models for traffic equilibrium with ridesharing," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 161-182.
    8. Larsson, Torbjörn & Patriksson, Michael, 1999. "Side constrained traffic equilibrium models-- analysis, computation and applications," Transportation Research Part B: Methodological, Elsevier, vol. 33(4), pages 233-264, May.
    9. Yuanyuan Zhang & Yuming Zhang, 2018. "Examining the Relationship between Household Vehicle Ownership and Ridesharing Behaviors in the United States," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    10. Agatz, Niels A.H. & Erera, Alan L. & Savelsbergh, Martin W.P. & Wang, Xing, 2011. "Dynamic ride-sharing: A simulation study in metro Atlanta," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1450-1464.
    11. Torbjörn Larsson & Michael Patriksson, 1992. "Simplicial Decomposition with Disaggregated Representation for the Traffic Assignment Problem," Transportation Science, INFORMS, vol. 26(1), pages 4-17, February.
    12. de Palma, André & Kilani, Moez & Lindsey, Robin, 2005. "Congestion pricing on a road network: A study using the dynamic equilibrium simulator METROPOLIS," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 588-611.
    13. Ma, Rui & Zhang, H.M., 2017. "The morning commute problem with ridesharing and dynamic parking charges," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 345-374.
    14. Masoud, Neda & Jayakrishnan, R., 2017. "A decomposition algorithm to solve the multi-hop Peer-to-Peer ride-matching problem," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 1-29.
    15. Stiglic, Mitja & Agatz, Niels & Savelsbergh, Martin & Gradisar, Mirko, 2015. "The benefits of meeting points in ride-sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 36-53.
    16. Xiao, Ling-Ling & Liu, Tian-Liang & Huang, Hai-Jun, 2016. "On the morning commute problem with carpooling behavior under parking space constraint," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 383-407.
    17. Furuhata, Masabumi & Dessouky, Maged & Ordóñez, Fernando & Brunet, Marc-Etienne & Wang, Xiaoqing & Koenig, Sven, 2013. "Ridesharing: The state-of-the-art and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 28-46.
    18. Agatz, Niels & Erera, Alan & Savelsbergh, Martin & Wang, Xing, 2012. "Optimization for dynamic ride-sharing: A review," European Journal of Operational Research, Elsevier, vol. 223(2), pages 295-303.
    19. Nie, Yu (Marco), 2010. "A class of bush-based algorithms for the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 73-89, January.
    20. Yitian Wang & Zixuan Peng & Keming Wang & Xiaolin Song & Baozhen Yao & Tao Feng, 2015. "Research on Urban Road Congestion Pricing Strategy Considering Carbon Dioxide Emissions," Sustainability, MDPI, vol. 7(8), pages 1-20, August.
    21. Todd Litman & David Burwell, 2006. "Issues in sustainable transportation," International Journal of Global Environmental Issues, Inderscience Enterprises Ltd, vol. 6(4), pages 331-347.
    22. Lawphongpanich, Siriphong & Hearn, Donald W., 1984. "Simplical decomposition of the asymmetric traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 18(2), pages 123-133, April.
    23. Stiglic, M. & Agatz, N.A.H. & Savelsbergh, M.W.P. & Gradisar, M., 2015. "The Benefits of Meeting Points in Ride-sharing Systems," ERIM Report Series Research in Management ERS-2015-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    24. Hou, Liwen & Li, Dong & Zhang, Dali, 2018. "Ride-matching and routing optimisation: Models and a large neighbourhood search heuristic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 143-162.
    25. Dial, Robert B., 2006. "A path-based user-equilibrium traffic assignment algorithm that obviates path storage and enumeration," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 917-936, December.
    26. Masoud, Neda & Jayakrishnan, R., 2017. "A real-time algorithm to solve the peer-to-peer ride-matching problem in a flexible ridesharing system," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 218-236.
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