多智能网联汽车轨迹规划：现状与展望

doi:10.3901/JME.2024.10.129

机械工程学报 ›› 2024, Vol. 60 ›› Issue (10): 129-146.doi: 10.3901/JME.2024.10.129

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多智能网联汽车轨迹规划：现状与展望

戢杨杰¹, 张馨雨¹, 杨紫茹¹, 周上航¹, 黄岩军¹, 曹建永², 熊璐¹, 余卓平¹

1. 同济大学汽车学院上海 201804;
2. 上海机动车检测认证技术研究中心有限公司上海 201800

收稿日期:2023-11-18 修回日期:2024-04-12 出版日期:2024-05-20 发布日期:2024-07-24
作者简介:戢杨杰,男,1994年出生,博士研究生。主要研究方向为智能网联汽车,智能汽车决策规划。
E-mail:jiyj20@tongji.edu.cn
张馨雨,女,2001年出生,硕士研究生。主要研究方向为智能网联汽车预测与规划。
E-mail:1878885913@qq.com
杨紫茹,女,1998年出生,硕士研究生。主要研究方向为多车规划。
E-mail:yangziru1029@163.com
周上航,男,2001年出生,硕士研究生。主要研究方向为多车规划。
E-mail:zsh1359821613@163.com
黄岩军(通信作者),男,1986年出生,博士,教授,博士研究生导师。主要研究方向为自动驾驶决策控制、车辆动力学控制、自动驾驶数据闭环、人机混合增强智能等。
E-mail:yanjun_huang@tongji.edu.cn
曹建永,男,1980年出生,博士,正高级工程师,博士研究生导师。主要研究方向为智能网联汽车安全测试与评估方法。
E-mail:jianyongc@smvic.com.cn
熊璐,男,1978年出生,博士,教授,博士研究生导师。主要研究方向为汽车系统动力学与控制、新能源汽车整车集成技术。
E-mail:xiong_lu@tongji.edu.cn
余卓平,男,1960年出生,博士,教授,博士研究生导师。主要研究方向为汽车系统动力学与控制。
E-mail:yuzhuoping@tongji.edu.cn
基金资助:
上海市自然科学基金资助项目(21ZR1465900)。

Trajectory Planning of Multi-intelligent Connected Vehicles: The State of the Art and Perspectives

JI Yangjie¹, ZHANG Xinyu¹, YANG Ziru¹, ZHOU Shanghang¹, HUANG Yanjun¹, CAO Jianyong², XIONG Lu¹, YU Zhuoping¹

1. School of Automotive Studies, Tongji University, Shanghai 201804;
2. Shanghai Motor Vehicle Inspection Certification Tech Innovation Center, Shanghai 201800

Received:2023-11-18 Revised:2024-04-12 Online:2024-05-20 Published:2024-07-24

摘要/Abstract

摘要： 轨迹规划是自动驾驶汽车的基本功能。随着车用无线通信技术(Vehicle to everything，V2X)技术的发展，自动驾驶汽车具备智能网联功能，这些汽车被称为智能网联汽车。智能网联技术可以为自动驾驶汽车带来大量信息，增强不同自动驾驶汽车之间的合作，并为轨迹规划提供额外的优化空间，以减少驾驶时间，提高驾驶舒适性和安全性。与传统的单车轨迹规划相比，多车轨迹规划可以充分利用智能网联汽车的技术优势，为多个自动驾驶汽车规划合适的轨迹。以结构化场景和非结构化场景的分类综述典型的多车轨迹规划应用场景，总结不同的多车轨迹规划合作规划策略和特点。总结用于多车轨迹规划的各种方法，包括传统的流水线规划方法和端到端方法，并对多车轨迹规划的试验进行归纳。基于当前研究现状，提出多车轨迹规划面临的挑战和未来的研究方向，为智能交通系统领域的研究人员提供启发和参考。

关键词: 自动驾驶汽车, 轨迹规划, 智能网联汽车

Abstract: Trajectory planning is a basic function of autonomous vehicles(AVs). With the development of vehicle-to-everything(V2X) technology, many AVs are equipped with intelligent connected capabilities, and these vehicles are called connected autonomous vehicles(CAVs). The intelligent connected technology can bring much information to AVs, enhance cooperation between different AVs and provide unprecedented opportunities for planning vehicle trajectories to reduce travel time, improve driving comfort and increase safety. Compared to traditional single-vehicle trajectory planning, multi-vehicle trajectory planning can fully utilize the technical advantages of CAVs and plan suitable trajectories for multiple AVs. Typical multi-vehicle trajectory planning application scenarios are overviewed according to structured and unstructured scenarios, and different cooperative planning strategies and characteristics of multi-vehicle trajectory planning are summarized. Various approaches used for multi-vehicle trajectory planning are summarized including traditional pipeline planning methods and end-to-end methods, and experiments on multi-vehicle trajectory planning are generalized. Based on the current research status, the challenges and future research directions of multi-vehicle trajectory planning are presented to provide inspiration and reference for researchers in the field of intelligent transportation systems.

Key words: autonomous vehicle, trajectory planning, connected automated vehicles

中图分类号:

U495

戢杨杰, 张馨雨, 杨紫茹, 周上航, 黄岩军, 曹建永, 熊璐, 余卓平. 多智能网联汽车轨迹规划：现状与展望[J]. 机械工程学报, 2024, 60(10): 129-146.

JI Yangjie, ZHANG Xinyu, YANG Ziru, ZHOU Shanghang, HUANG Yanjun, CAO Jianyong, XIONG Lu, YU Zhuoping. Trajectory Planning of Multi-intelligent Connected Vehicles: The State of the Art and Perspectives[J]. Journal of Mechanical Engineering, 2024, 60(10): 129-146.

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多智能网联汽车轨迹规划：现状与展望

Trajectory Planning of Multi-intelligent Connected Vehicles: The State of the Art and Perspectives

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