An RSU Deployment Scheme for Vehicle-Infrastructure Cooperated Autonomous Driving

Lingyu Zhang, Li Wang, Lili Zhang (), Xiao Zhang and Dehui Sun
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Lingyu Zhang: Beijing Key Lab of Urban Intelligent Control Technology, North China University of Technology, Beijing 100144, China
Li Wang: Beijing Key Lab of Urban Intelligent Control Technology, North China University of Technology, Beijing 100144, China
Lili Zhang: College of Information Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
Xiao Zhang: Hebei Vocational College of Politics and Law, Shijiazhuang 050064, China
Dehui Sun: Beijing Key Lab of Urban Intelligent Control Technology, North China University of Technology, Beijing 100144, China

Sustainability, 2023, vol. 15, issue 4, 1-16

Abstract: For autonomous driving vehicles, there are currently some issues, such as limited environmental awareness and locally optimal decision-making. To increase the capacity of autonomous cars’ environmental awareness, computation, decision-making, control, and execution, intelligent roads must be constructed, and vehicle–infrastructure cooperative technology must be used. The Roadside unit (RSU) deployment, a critical component of vehicle–infrastructure cooperative autonomous driving, has a direct impact on network performance, operation effects, and control accuracy. The current RSU deployment mostly uses the large-spacing and low-density concept because of the expensive installation and maintenance costs, which can accomplish the macroscopic and long-term communication functions but fall short of precision vehicle control. Given these challenges, this paper begins with the specific requirements to control intelligent vehicles in the cooperative vehicle–infrastructure environment. An RSU deployment scheme, based on the improved multi-objective quantum-behaved particle swarm optimization (MOQPSO) algorithm, is proposed. This RSU deployment scheme was based on the maximum coverage with time threshold problem (MCTTP), with the goal of minimizing the number of RSUs and maximizing vehicle coverage of communication and control services. Finally, utilizing the independently created open simulation platform (OSP) simulation system, the model and algorithm’s viability and effectiveness were assessed on the Nguyen–Dupuis road network. The findings demonstrate that the suggested RSU deployment scheme can enhance network performance and control the precision of vehicle–infrastructure coordination, and can serve as a general guide for the deployment of RSUs in the same application situation.

Keywords: autonomous driving; vehicle–infrastructure coordination; human–machine driving; roadside unit (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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