Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/89257
Title: Ridesharing user equilibrium problem under OD-based surge pricing strategy
Authors: Ma, J
Xu, M 
Meng, Q
Cheng, L
Issue Date: Apr-2020
Source: Transportation research. Part B, Methodological, Apr. 2020, v. 134, p. 1-24
Abstract: Ridesharing is one of the effective urban traffic supply and demand management policies to reduce car ownership and mitigate traffic congestion. The origin-destination (OD) based surge pricing strategy is widely adopted by ridesharing service operators in practice due to its fairness and effectiveness. In this study, we aim to investigate the ridesharing user equilibrium (RUE) problem for an urban transportation network under the OD-based surge pricing strategy. We first build a variational inequality (VI) model for the proposed RUE problem. In particular, we explicitly formulate the necessary ride-matching constraints for the participants of multiple ridesharing services and rigorously demonstrate the existence and uniqueness of the RUE solution under some mild conditions. A parallel self-adaptive projection method (PSPM) incorporating column generation is developed to find an RUE solution for the large-scale problems. Finally, numerical experiments are conducted to provide valuable insights and examine the effectiveness of the proposed solution method. The results quantitatively show that the ridesharing under the OD-based surge pricing strategy reduces not only the travel cost for travelers but also the deliberate detours. Traffic congestion is significantly mitigated by ridesharing. Moreover, the proposed solution method has satisfactory computational efficiency for solving the large-scale problems.
Keywords: Ridesharing user equilibrium (RUE)
OD-based pricing strategy
Ride-matching constraints
Variational inequality (VI)
Parallel projection methods
Publisher: Pergamon Press
Journal: Transportation research. Part B, Methodological 
ISSN: 0191-2615
EISSN: 1879-2367
DOI: 10.1016/j.trb.2020.02.001
Appears in Collections:Journal/Magazine Article

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Embargo End Date 2022-04-30
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