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Incentive-compatible mechanisms for online resource allocation in Mobility-as-a-Service systems.

Authors :
Xi, Haoning
Liu, Wei
Waller, S. Travis
Hensher, David A.
Kilby, Philip
Rey, David
Source :
Transportation Research Part B: Methodological. Apr2023, Vol. 170, p119-147. 29p.
Publication Year :
2023

Abstract

In the context of Mobility-as-a-Service (MaaS), the transportation sector has been evolving towards user-centric business models, which put the user experience and tailored mobility solutions at the center of the offer. The emerging concept of MaaS emphasizes that users value experience-relevant factors, e.g., service time, inconvenience cost, and travel delay, over segmented travel modes choices. This study proposes an auction-based mechanism and tractable optimization models for the demand-side management of MaaS systems wherein users' trip requests are represented as mode-agnostic mobility resources. Users' requests arrive dynamically in the MaaS system and users compete for mobility resources by bidding for mobility services based on their willingness to pay and experience-relevant preferences. We take the perspective of a MaaS platform regulator who aims to maximize social welfare by optimally allocating mobility resources to users in real-time. The MaaS regulator first decides whether to offer each user a MaaS bundle and identifies the optimal allocation of mobility resources for the selected users. Users have the possibility to accept or reject offered MaaS bundles by comparing the associated utility obtained from MaaS with a reserve utility obtained from other travel options. We introduce mixed-integer programming formulations for this online mobility resource allocation problem. We show that the proposed MaaS mechanism is incentive-compatible, individually rational, budget balanced, and computationally efficient. We propose a polynomial-time online algorithm and derive its competitive ratio relative to an offline algorithm. We also explore rolling horizon configurations with varying look-ahead policies to implement the proposed mechanism. Extensive numerical simulations conducted on large-scale instances generated from realistic mobility data highlight the benefits of the proposed mechanism. • Consider a MaaS system where users value experience over segmented travel modes. • Users' trip requests are mode-agnostic and represented as mobility resources. • The MaaS platform regulator aims to maximize social welfare in real-time. • Develop an auction-based mechanism for allocating mobility resources as MaaS bundles. • The mechanism is incentive compatible, individually rational and budget balanced. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01912615
Volume :
170
Database :
Academic Search Index
Journal :
Transportation Research Part B: Methodological
Publication Type :
Academic Journal
Accession number :
162504586
Full Text :
https://doi.org/10.1016/j.trb.2023.02.011