An Innovative Cooperative Driving Strategy for Signal-Free Intersection Navigation with CAV Platoons

被引：1

作者：

Gao, Jian ^{[1
]}

Tian, Jin ^{[1
]}

Gong, Li ^{[2
,3
]}

Zhang, Yujin ^{[1
]}

机构：

[1] Shanghai Univ Engn Sci, Sch Elect & Elect Engn, Shanghai 201620, Peoples R China

[2] East China Normal Univ, Inst Global Innovat & Dev, Shanghai 200062, Peoples R China

[3] East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China

来源：

APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 08期

基金：

上海市自然科学基金;

关键词：

signal-free intersection; connected and automated vehicles; hybrid electric vehicles; cooperative driving strategies; AUTOMATED VEHICLES; TRACES; MODEL;

D O I：

10.3390/app14083498

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

We present an innovative cooperative driving strategy known as Dynamic Resequencing and Platooning (DRP) designed to ensure the safe and efficient traversal of Connected and Automated Vehicles (CAVs) through signal-free intersections. By employing a Resequencing and Platooning Algorithm (RPA) grounded in state transition networks and CAV platooning, the optimal crossing sequence for CAVs is ascertained within a finite time. Through the utilization of a decentralized energy-optimal control framework, optimal trajectories are devised for CAVs, thereby facilitating optimal coordination among them. Simulation results underscore the substantial performance benefits of the DRP strategy compared to traffic light, First-In-First-Out (FIFO), and Local Dynamic Resequencing (LDR) strategies, with notable reductions observed in both travel delay and fuel consumption.

引用

页数：20