High-Accuracy, High-Efficiency, and Comfortable Car-Following Strategy Based on TD3 for Wide-to-Narrow Road Sections

被引：1

作者：

Qin, Pinpin ^{[1
]}

Wu, Fumao ^{[1
]}

Bin, Shenglin ^{[1
]}

Li, Xing ^{[1
]}

Ya, Fuming ^{[2
]}

机构：

[1] Guangxi Univ, Sch Mech Engn, Nanning 530004, Peoples R China

[2] Guangxi Univ, Sch Comp Elect & Informat, Nanning 530004, Peoples R China

来源：

WORLD ELECTRIC VEHICLE JOURNAL | 2023年 / 14卷 / 09期

关键词：

car-following; twin delayed deep deterministic policy gradient (TD3); wide-to-narrow road sections; desired safety distance (DSD); traffic congestion; DECISION-MAKING; MODEL;

D O I：

10.3390/wevj14090244

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

To address traffic congestion in urban expressways during the transition from wide to narrow sections, this study proposed a car-following strategy based on deep reinforcement learning. Firstly, a car-following strategy was developed based on a twin-delayed deep deterministic policy gradient (TD3) algorithm, and a multi-objective constrained reward function was designed by comprehensively considering safety, traffic efficiency, and ride comfort. Secondly, 214 car-following periods and 13 platoon-following periods were selected from the natural driving database for the strategies training and testing. Finally, the effectiveness of the proposed strategy was verified through simulation experiments of car-following and platoon-following. The results showed that compared to human-driven vehicles (HDV), the TD3 and deep deterministic policy gradient (DDPG)-based strategies enhanced traffic efficiency by over 29% and ride comfort by more than 60%. Furthermore, compared to DDPG, the relative errors between the following distance and desired safety distance using TD3 could be reduced by 1.28% and 1.37% in simulation experiments of car-following and platoon-following, respectively. This study provides a new approach to alleviate traffic congestion for wide-to-narrow road sections in urban expressways.

引用

页数：14