A fairness-aware joint pricing and matching framework for dynamic ridesharing

Ze Zhou*, Claudio Roncoli

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)
27 Downloads (Pure)

Abstract

Enabled by the prevailing mobile devices, novel mobility services, such as ridesharing, have a great potential to change the mobility pattern of metropolis inhabitants. In this study, we focus on the pricing and matching challenges faced by a mobility service platform when both ridesharing and non-shared mobility services are provided. A joint pricing and matching framework is proposed to efficiently dispatch vehicles and deliver explicit trip time and fare information in real-time. Besides, we define six principles to evaluate the fairness of pricing methods and develop a discount function considering the features of passengers’ shared rides. In simulation experiments where passengers can choose from different service types, we show that our method can significantly increase the system’s profit without violating the fairness principles among co-riders.
Original languageEnglish
Title of host publication2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-6654-5530-5
DOIs
Publication statusPublished - 11 Sept 2023
MoE publication typeA4 Conference publication
EventIEEE International Conference on Models and Technologies for Intelligent Transportation Systems - Nice, France
Duration: 14 Jun 202316 Jun 2023
Conference number: 8
https://mt-its2023.eurecom.fr/

Conference

ConferenceIEEE International Conference on Models and Technologies for Intelligent Transportation Systems
Abbreviated titleMT-ITS
Country/TerritoryFrance
CityNice
Period14/06/202316/06/2023
Internet address

Keywords

  • ridesharing
  • pricing fairness
  • user choice

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