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The Nash Equilibrium Among Taxi Ridesharing Partners

Published: 07 November 2017 Publication History

Abstract

Ride sourcing services such as Uber and Lyft have become widespread in large cities for everyday mobility. When matching passengers, these services attempt to optimize cost savings at a global level. However, a possible scenario is that a passenger A is matched to passenger B even though if A were matched to passenger C, then both A and C would have saved more money. This introduces the concept of "fairness" in ride sharing, which consists of finding the Nash equilibrium in ridesharing. In this paper we compare optimum and fair ridesharing theoretically and experimentally. We show that although theoretically the gap between fair and optimum is large, in practice it is very small.

References

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Cited By

View all
  • (2023)Distributed Fair Assignment and Rebalancing for Mobility-on-Demand Systems via an Auction-based Method2023 International Symposium on Multi-Robot and Multi-Agent Systems (MRS)10.1109/MRS60187.2023.10416781(128-134)Online publication date: 4-Dec-2023
  • (2022)Fair Planning for Mobility-on-Demand with Temporal Logic Requests2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS47612.2022.9981291(1283-1289)Online publication date: 23-Oct-2022
  • (2021)Weighted Stackelberg Algorithms for Road Traffic OptimizationProceedings of the 29th International Conference on Advances in Geographic Information Systems10.1145/3474717.3483652(57-68)Online publication date: 2-Nov-2021
  • Show More Cited By

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Published In

cover image ACM Conferences
SIGSPATIAL '17: Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 2017
677 pages
ISBN:9781450354905
DOI:10.1145/3139958
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 November 2017

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Author Tags

  1. Dynamic
  2. Fairness
  3. Optimum
  4. Ridesharing
  5. Static

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  • Refereed limited

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SIGSPATIAL '17 Paper Acceptance Rate 39 of 193 submissions, 20%;
Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Cited By

View all
  • (2023)Distributed Fair Assignment and Rebalancing for Mobility-on-Demand Systems via an Auction-based Method2023 International Symposium on Multi-Robot and Multi-Agent Systems (MRS)10.1109/MRS60187.2023.10416781(128-134)Online publication date: 4-Dec-2023
  • (2022)Fair Planning for Mobility-on-Demand with Temporal Logic Requests2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS47612.2022.9981291(1283-1289)Online publication date: 23-Oct-2022
  • (2021)Weighted Stackelberg Algorithms for Road Traffic OptimizationProceedings of the 29th International Conference on Advances in Geographic Information Systems10.1145/3474717.3483652(57-68)Online publication date: 2-Nov-2021
  • (2020)Spatio-Temporal Hierarchical Adaptive Dispatching for Ridesharing SystemsProceedings of the 28th International Conference on Advances in Geographic Information Systems10.1145/3397536.3422212(227-238)Online publication date: 3-Nov-2020
  • (2020)Modeling travel mode choice of young people with differentiated E-hailing ride services in Nanjing ChinaTransportation Research Part D: Transport and Environment10.1016/j.trd.2019.10221678(102216)Online publication date: Jan-2020
  • (2020)A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand PredictionMultiple-Aspect Analysis of Semantic Trajectories10.1007/978-3-030-38081-6_8(100-116)Online publication date: 4-Jan-2020
  • (2019)Auction-Based Order Dispatch and Pricing in Ridesharing2019 IEEE 35th International Conference on Data Engineering (ICDE)10.1109/ICDE.2019.00096(1034-1045)Online publication date: Apr-2019
  • (2019)Optimum versus Nash-equilibrium in taxi ridesharingGeoInformatica10.1007/s10707-019-00379-6Online publication date: 24-Aug-2019
  • (2018)Spatio-Temporal Matching for Urban Transportation ApplicationsACM Transactions on Spatial Algorithms and Systems10.1145/31833443:4(1-39)Online publication date: 4-May-2018

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