V2X assisted co‐design of motion planning and control for connected automated vehicle

Abstract The rapid development of vehicle‐to‐everything (V2X) communication technologies significantly promotes the revolution of intelligent transportation systems. V2X communication is expected to play a critical role in enhancing the safety and efficiency of connected and automated vehicles (CAVs...

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Main Authors: Jiahang Li, Cailian Chen, Bo Yang
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:IET Intelligent Transport Systems
Subjects:
Online Access:https://doi.org/10.1049/itr2.12501
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author Jiahang Li
Cailian Chen
Bo Yang
author_facet Jiahang Li
Cailian Chen
Bo Yang
author_sort Jiahang Li
collection DOAJ
description Abstract The rapid development of vehicle‐to‐everything (V2X) communication technologies significantly promotes the revolution of intelligent transportation systems. V2X communication is expected to play a critical role in enhancing the safety and efficiency of connected and automated vehicles (CAVs), especially for mixed traffic scenarios. Additionally, the computational and storage capabilities of roadside units (RSUs) will be harnessed to effectively enhance the motion planning and control performance of CAVs within the constraints of limited on‐board computational resources. Thus, a V2X assisted co‐design of motion planning and control algorithm for CAVs to improve their situational awareness and computational efficiency is proposed. Under this architecture, a pre‐planning algorithm is proposed first to utilize the computational and storage capabilities of RSUs and generate feasible trajectories for different driving tasks. By analysing the relationship between driving risk index and motion planning performance, an online‐planning algorithm is derived to modify the pre‐planned trajectories in real‐time with static or dynamic obstacles. Furthermore, the lateral and longitudinal control of the vehicle using the Frenet coordinate system is decoupled. The lateral control employs an offline linear quadratic regulator (LQR) from RSUs to control the steering angle of the vehicle. The longitudinal control employs a dual‐loop PID to control the throttle opening of the vehicle. The performance of the proposed framework is evaluated and demonstrated by a Carsim‐Prescan simulation study in different mixed traffic scenarios. Compared with conventional methods, the proposed method improves the computational efficiency by 23% and reduces the collision rate by 13%.
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spelling doaj-art-d4657627f6f4422285a4854b5a9b4cb32024-12-06T05:51:13ZengWileyIET Intelligent Transport Systems1751-956X1751-95782024-12-0118122601261710.1049/itr2.12501V2X assisted co‐design of motion planning and control for connected automated vehicleJiahang Li0Cailian Chen1Bo Yang2Department of Automation and the Key Laboratory of System Control and Information Processing, Ministry of Education of China Shanghai Jiao Tong University Shanghai ChinaDepartment of Automation and the Key Laboratory of System Control and Information Processing, Ministry of Education of China Shanghai Jiao Tong University Shanghai ChinaDepartment of Automation and the Key Laboratory of System Control and Information Processing, Ministry of Education of China Shanghai Jiao Tong University Shanghai ChinaAbstract The rapid development of vehicle‐to‐everything (V2X) communication technologies significantly promotes the revolution of intelligent transportation systems. V2X communication is expected to play a critical role in enhancing the safety and efficiency of connected and automated vehicles (CAVs), especially for mixed traffic scenarios. Additionally, the computational and storage capabilities of roadside units (RSUs) will be harnessed to effectively enhance the motion planning and control performance of CAVs within the constraints of limited on‐board computational resources. Thus, a V2X assisted co‐design of motion planning and control algorithm for CAVs to improve their situational awareness and computational efficiency is proposed. Under this architecture, a pre‐planning algorithm is proposed first to utilize the computational and storage capabilities of RSUs and generate feasible trajectories for different driving tasks. By analysing the relationship between driving risk index and motion planning performance, an online‐planning algorithm is derived to modify the pre‐planned trajectories in real‐time with static or dynamic obstacles. Furthermore, the lateral and longitudinal control of the vehicle using the Frenet coordinate system is decoupled. The lateral control employs an offline linear quadratic regulator (LQR) from RSUs to control the steering angle of the vehicle. The longitudinal control employs a dual‐loop PID to control the throttle opening of the vehicle. The performance of the proposed framework is evaluated and demonstrated by a Carsim‐Prescan simulation study in different mixed traffic scenarios. Compared with conventional methods, the proposed method improves the computational efficiency by 23% and reduces the collision rate by 13%.https://doi.org/10.1049/itr2.12501automated driving & intelligent vehiclesvehicle automation and connectivity
spellingShingle Jiahang Li
Cailian Chen
Bo Yang
V2X assisted co‐design of motion planning and control for connected automated vehicle
IET Intelligent Transport Systems
automated driving & intelligent vehicles
vehicle automation and connectivity
title V2X assisted co‐design of motion planning and control for connected automated vehicle
title_full V2X assisted co‐design of motion planning and control for connected automated vehicle
title_fullStr V2X assisted co‐design of motion planning and control for connected automated vehicle
title_full_unstemmed V2X assisted co‐design of motion planning and control for connected automated vehicle
title_short V2X assisted co‐design of motion planning and control for connected automated vehicle
title_sort v2x assisted co design of motion planning and control for connected automated vehicle
topic automated driving & intelligent vehicles
vehicle automation and connectivity
url https://doi.org/10.1049/itr2.12501
work_keys_str_mv AT jiahangli v2xassistedcodesignofmotionplanningandcontrolforconnectedautomatedvehicle
AT cailianchen v2xassistedcodesignofmotionplanningandcontrolforconnectedautomatedvehicle
AT boyang v2xassistedcodesignofmotionplanningandcontrolforconnectedautomatedvehicle