Optimal matching for coexisting ride-hailing and ridesharing services considering pricing fairness and user choices
Loading...
Access rights
openAccess
publishedVersion
URL
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Date
2023-11-01
Department
Major/Subject
Mcode
Degree programme
Language
en
Pages
23
Series
Transportation Research Part C: Emerging Technologies, Volume 156
Abstract
Mobility-on-demand (MoD) has the potential to revolutionise the patterns of urban mobility. Typically, an MoD platform provides both ride-hailing and ridesharing services, exacerbating the challenges of operating a city-scale real-time MoD system. Existing studies assume that travellers are fully compliant with the platform’s decisions regarding pricing and vehicle assignments, whereas, in reality, travellers can choose different modes based on monetary costs and travel experience, which may conflict with the results derived from the system perspective. In this study, we relax this assumption by accounting for pricing fairness and the travellers’ modal choices within a framework designed to optimise vehicle–traveller matching when both ride-hailing and ridesharing services are provided by an MoD platform. Six fairness principles are defined to characterise fair pricing for shared rides. Computationally efficient optimisation problems are formulated accounting for co-existing ride-hailing and ridesharing services. In numerical experiments, we assess the effectiveness of our method and compare it with state-of-the-art ones using a dataset of taxi requests for New York City. The results show that our optimisation strategy can significantly increase the service ratio and profit without sacrificing the service quality.Description
| openaire: EC/H2020/856602/EU//FINEST TWINS
Keywords
Ridesharing, Fairnes, pricing
Other note
Citation
Zhou, Z, Roncoli, C & Sipetas, C 2023, ' Optimal matching for coexisting ride-hailing and ridesharing services considering pricing fairness and user choices ', Transportation Research Part C: Emerging Technologies, vol. 156, 104326 . https://doi.org/10.1016/j.trc.2023.104326