Modeling Morning Commute Problem with Real-time Ridesharing Services
ID:2030 View Protection:ATTENDEE Updated Time:2021-12-03 15:36:36 Hits:284 Poster Presentation

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Abstract
The development of on-demand ridesharing platforms has reshaped commuters' travel behavior, enabling commuters to decide whether to become ridesharing drivers or passengers in real time. To examine the impact of commuters' decisions and ridesharing platform's strategies on the equilibrium state in the morning commute problem, this paper formulates an equilibrium framework to characterize commuters' mode choice and travel time choice behavior based on the bottleneck model. The mismatch problem and commuters' heterogeneous preference for the ridesharing mode are considered. An analytical sensitivity analysis is conducted to discuss how the market share of ridesharing mode changes with the platform's pricing strategies based on the equilibrium state. The optimal strategies for profit and market share maximization are also studied. Under derived conditions, we find that the supply of ridesharing drivers must be coordinated with the passenger demand when the optimal state is achieved. The numerical results are further demonstrated to verify the analytical findings. Our analyses provide insights for pricing strategies of the ridesharing platform.
Keywords
CICTP
Speaker
Xiqun Chen
Zhejiang University

Submission Author
Xiqun Chen Zhejiang University
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  • Conference Date

    Dec 17

    2021

    to

    Dec 20

    2021

  • Dec 16 2021

    Contribution Submission Deadline

  • Dec 24 2021

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Chinese Overseas Transportation Association
Chang'an University
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