Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148345
Title: BEHT : blockchain-based efficient highway toll paradigm for opportunistic autonomous vehicle platoon
Authors: Ying, Zuobin
Yi, Longyang
Ma, Maode
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Ying, Z., Yi, L. & Ma, M. (2020). BEHT : blockchain-based efficient highway toll paradigm for opportunistic autonomous vehicle platoon. Wireless Communications and Mobile Computing, 2020. https://dx.doi.org/10.1155/2020/8868656
Project: IAF-PP WP5
Journal: Wireless Communications and Mobile Computing
Abstract: Autonomous vehicle platoon is a promising paradigm towards traffic congestion problems in the intelligent transportation system. However, under certain circumstances, the advantage of the platoon cannot be fully developed. In this paper, we focus on the highway Electronic Toll Collection (ETC) charging problem. We try to let the opportunistic platoon pass the ETC as a whole. There are three main issues in this scenario. Firstly, the opportunistic platoon is temporarily composed; vehicles do not trust each other. Secondly, single vehicle may try to escape from the ETC charging by following the platoon. Finally, platoon members may collude with each other and try to underreport the number of vehicles in the platoon so as to evade payment. To solve these challenges, we propose a blockchain-based efficient highway toll paradigm for the opportunistic platoon. The driving history, credential information of every registered vehicle, is recorded and verified from the blockchain. A roadside unit (RSU) is adopted to distinguish the single vehicle from the platoon and in charge of lane allocation. Additionally, an aggregate signature is introduced to accelerate the authentication procedure in the RSU. We analyse the potential security threats in this scenario. The experimental result indicates that our scheme is efficient and practical.
URI: https://hdl.handle.net/10356/148345
ISSN: 1530-8669
DOI: 10.1155/2020/8868656
Rights: © 2020 The Author(s). This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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