Coalitional Double Auction For Ridesharing With Desired Benefit And QoE Constraints

Author:

Huang Jiale1,Wu Jigang1,Chen Long1,Wu Yalan1,Li Yidong2

Affiliation:

1. School of Computer Science and Technology, Guangdong University of Technology , Guangzhou, 510006 , China

2. School of Computer and Information Technology, Beijing Jiaotong University , Beijing, 100044 , China

Abstract

Abstract Ridesharing is an effective approach to alleviate traffic congestion. In most existing works, drivers and passengers are assigned prices without considering the constraints of desired benefits. This paper investigates ridesharing by formulating a matching and pricing problem to maximize the total payoff of drivers, with the constraints of desired benefit and quality of experience. An efficient algorithm is proposed to solve the formulated problem based on coalitional double auction. Secondary pricing based strategy and sacrificed minimum bid based strategy are proposed to support the algorithm. This paper also proves that the proposed algorithm can achieve a Nash-stable coalition partition in finite steps, and the proposed two strategies guarantee truthfulness, individually rational and budget balance. Extensive simulation results on the real-world dataset of taxi trajectory in Beijing city show that the proposed algorithm outperforms the existing ones, in terms of average total payoff of drivers while meeting the benefits of passengers.

Funder

National Natural Science Foundation of China

Guangdong Natural Science Foundation

Huangpu International Sci & Tech Cooperation Fundation

Publisher

Oxford University Press (OUP)

Subject

General Computer Science

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