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

Ze Zhou; Claudio Roncoli

doi:10.1109/MT-ITS56129.2023.10241664

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 proceeding › Conference article in proceedings › Scientific › peer-review

4 Citations (Scopus)

156 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 language	English
Title of host publication	2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	978-1-6654-5530-5
DOIs	https://doi.org/10.1109/MT-ITS56129.2023.10241664
Publication status	Published - 11 Sept 2023
MoE publication type	A4 Conference publication
Event	IEEE International Conference on Models and Technologies for Intelligent Transportation Systems - Nice, France Duration: 14 Jun 2023 → 16 Jun 2023 Conference number: 8 https://mt-its2023.eurecom.fr/

Conference

Conference	IEEE International Conference on Models and Technologies for Intelligent Transportation Systems
Abbreviated title	MT-ITS
Country/Territory	France
City	Nice
Period	14/06/2023 → 16/06/2023
Internet address	https://mt-its2023.eurecom.fr/

Keywords

ridesharing
pricing fairness
user choice

Access to Document

10.1109/MT-ITS56129.2023.10241664

ENG_Zhou_and_Roncoli_A_fairness-aware_ joint_pricing_MI-ITS_2023Accepted author manuscript, 263 KBLicence: CC BY

Cite this

@inproceedings{a9dc84ab5dd74be3875b91dbc38a7c3c,

title = "A fairness-aware joint pricing and matching framework for dynamic ridesharing",

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{\textquoteright} shared rides. In simulation experiments where passengers can choose from different service types, we show that our method can significantly increase the system{\textquoteright}s profit without violating the fairness principles among co-riders.",

keywords = "ridesharing, pricing fairness, user choice",

author = "Ze Zhou and Claudio Roncoli",

note = "| openaire: EC/H2020/856602/EU//FINEST TWINS; IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS ; Conference date: 14-06-2023 Through 16-06-2023",

year = "2023",

month = sep,

day = "11",

doi = "10.1109/MT-ITS56129.2023.10241664",

language = "English",

booktitle = "2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023",

publisher = "IEEE",

address = "United States",

url = "https://mt-its2023.eurecom.fr/",

}

Zhou, Z & Roncoli, C 2023, A fairness-aware joint pricing and matching framework for dynamic ridesharing. in 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023. IEEE, IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, Nice, France, 14/06/2023. https://doi.org/10.1109/MT-ITS56129.2023.10241664

TY - GEN

T1 - A fairness-aware joint pricing and matching framework for dynamic ridesharing

AU - Zhou, Ze

AU - Roncoli, Claudio

N1 - Conference code: 8

PY - 2023/9/11

Y1 - 2023/9/11

N2 - 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.

AB - 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.

KW - ridesharing

KW - pricing fairness

KW - user choice

UR - https://www.scopus.com/pages/publications/85170651394

U2 - 10.1109/MT-ITS56129.2023.10241664

DO - 10.1109/MT-ITS56129.2023.10241664

M3 - Conference article in proceedings

BT - 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023

PB - IEEE

T2 - IEEE International Conference on Models and Technologies for Intelligent Transportation Systems

Y2 - 14 June 2023 through 16 June 2023

ER -

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

Abstract

Conference

Keywords

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-: FINEST TWINS GA856602Nieminen

ALCOSTO: Adaptive and Learning COntrol strategies for Sustainable future Traffic Operations

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

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

-: FINEST TWINS GA856602Nieminen

ALCOSTO: Adaptive and Learning COntrol strategies for Sustainable future Traffic Operations

Cite this