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Hauptverfasser: Liang, Kaier, Vasile, Cristian-Ioan
Format: Preprint
Veröffentlicht: 2024
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Online-Zugang:https://arxiv.org/abs/2402.04972
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author Liang, Kaier
Vasile, Cristian-Ioan
author_facet Liang, Kaier
Vasile, Cristian-Ioan
contents In this paper, we consider fair assignment of complex requests for Mobility-On-Demand systems. We model the transportation requests as temporal logic formulas that must be satisfied by a fleet of vehicles. We require that the assignment of requests to vehicles is performed in a distributed manner based only on communication between vehicles while ensuring fair allocation. Our approach to the vehicle-request assignment problem is based on a distributed auction scheme with no centralized bidding that leverages utility history correction of bids to improve fairness. Complementarily, we propose a rebalancing scheme that employs rerouting vehicles to more rewarding areas to increase the potential future utility and ensure a fairer utility distribution. We adopt the max-min and deviation of utility as the two criteria for fairness. We demonstrate the methods in the mid-Manhattan map with a large number of requests generated in different probability settings. We show that we increase the fairness between vehicles based on the fairness criteria without degenerating the servicing quality.
format Preprint
id arxiv_https___arxiv_org_abs_2402_04972
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Distributed Fair Assignment and Rebalancing for Mobility-on-Demand Systems via an Auction-based Method
Liang, Kaier
Vasile, Cristian-Ioan
Formal Languages and Automata Theory
Computer Science and Game Theory
In this paper, we consider fair assignment of complex requests for Mobility-On-Demand systems. We model the transportation requests as temporal logic formulas that must be satisfied by a fleet of vehicles. We require that the assignment of requests to vehicles is performed in a distributed manner based only on communication between vehicles while ensuring fair allocation. Our approach to the vehicle-request assignment problem is based on a distributed auction scheme with no centralized bidding that leverages utility history correction of bids to improve fairness. Complementarily, we propose a rebalancing scheme that employs rerouting vehicles to more rewarding areas to increase the potential future utility and ensure a fairer utility distribution. We adopt the max-min and deviation of utility as the two criteria for fairness. We demonstrate the methods in the mid-Manhattan map with a large number of requests generated in different probability settings. We show that we increase the fairness between vehicles based on the fairness criteria without degenerating the servicing quality.
title Distributed Fair Assignment and Rebalancing for Mobility-on-Demand Systems via an Auction-based Method
topic Formal Languages and Automata Theory
Computer Science and Game Theory
url https://arxiv.org/abs/2402.04972