Vehicle-oriented ridesharing package delivery in blockchain system

Xuefei Zhang; Junjie Liu; Yijing Li; Qimei Cui; Xiaofeng Tao; Ren Ping Liu; Wenzheng Li

Digital Communications and Networks (Aug 2024)

Vehicle-oriented ridesharing package delivery in blockchain system

Xuefei Zhang,
Junjie Liu,
Yijing Li,
Qimei Cui,
Xiaofeng Tao,
Ren Ping Liu,
Wenzheng Li

Affiliations

Xuefei Zhang: Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China; Corresponding author.
Junjie Liu: Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China
Yijing Li: Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China
Qimei Cui: Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China
Xiaofeng Tao: Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China
Ren Ping Liu: Department of Electrical and Data Engineering, University of Technology Sydney, Sydney, Australia
Wenzheng Li: Department of Information Technology, Beijing University of Technology, Beijing, 100876, China

Journal volume & issue: Vol. 10, no. 4
pp. 1014 – 1023

Abstract

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Package delivery via ridesharing provides appealing benefits of lower delivery cost and efficient vehicle usage. Most existing ridesharing systems operate the matching of ridesharing in a centralized manner, which may result in the single point of failure once the controller breaks down or is under attack. To tackle such problems, our goal in this paper is to develop a blockchain-based package delivery ridesharing system, where decentralization is adopted to remove intermediaries and direct transactions between the providers and the requestors are allowed. To complete the matching process under decentralized structure, an Event-Triggered Distributed Deep Reinforcement Learning (ETDDRL) algorithm is proposed to generate/update the real-time ridesharing orders for the new coming ridesharing requests from a local view. Simulation results reveal the vast potential of the ETDDRL matching algorithm under the blockchain framework for the promotion of the ridesharing profits. Finally, we develop an application for Android-based terminals to verify the ETDDRL matching algorithm.

Published in Digital Communications and Networks

ISSN: 2352-8648 (Online)
Publisher: KeAi Communications Co., Ltd.
Country of publisher: China
LCC subjects: Technology: Technology (General): Industrial engineering. Management engineering: Information technology
Website: https://www.keaipublishing.com/en/journals/digital-communications-and-networks/

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