Matching 5G Connected Vehicles to Sensed Vehicles for Safe Cooperative Autonomous Driving

Abstract

5G connected autonomous vehicles (CAVs) help enhance perception of driving environment and cooperation among vehicles by sharing sensing and driving information, which is a promising technology to avoid accidents and improve road-use efficiency. A key issue for cooperation among CAVs is matching communicating vehicles to those captured in sensors such as cameras, LiDAR, etc.. Incorrect vehicle matching may cause serious accidents. While centimeter level positioning is now available for autonomous vehicles, matching connected vehicles to sensed vehicles (MCSV) is still challenging and has rarely been studied. In this paper, we are motivated to investigate the MCSV problem for 5G CAVs, propose and assess solutions for the problem to bridge the research gap. We formulate the MCSV problem and propose two MCSV approaches to support cooperative driving. The first approach is based on vehicle registration number (VRN), which is unique to identify a vehicle and can be shared among CAVs for MCSV. VRN is hashed before sharing to protect privacy, and will be compared to the shared one for vehicle matching. The second MCSV approach is based on visual features of vehicle’s external views, which are shared with other CAVs and compared to those obtained from visual sensors to match the vehicles of interest. A new MCSV dataset is developed to assess the effectiveness of the proposed approaches. Experiment results show that both approaches are feasible and useful, and they achieve a very low false positive rate, which is critical for cooperative driving safety.

Publication DOI: https://doi.org/10.1109/mnet.2023.3321530
Divisions: College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Electronics & Computer Engineering
College of Engineering & Physical Sciences > Aston Centre for Artifical Intelligence Research and Application
Additional Information: Copyright © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Funding: 10.13039/501100004663-Ministry of Science and Technology, Taiwan (Grant Number: 109-2221-E-006-175-MY3, 109-2221-E-006-182-MY3)
Uncontrolled Keywords: Computer Networks and Communications,Hardware and Architecture,Information Systems,Software
Publication ISSN: 1558-156X
Last Modified: 27 Dec 2023 09:53
Date Deposited: 16 Oct 2023 09:55
Full Text Link:
Related URLs: https://ieeexpl ... cument/10273777 (Publisher URL)
PURE Output Type: Article
Published Date: 2023-10-06
Published Online Date: 2023-10-06
Accepted Date: 2023-07-22
Authors: Tang, Zuoyin (ORCID Profile 0000-0001-7094-999X)
He, Jianhua
Yang, Kun
Hsiao-HwaChen

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