基于动态轨迹规划的自动驾驶车辆协同换道方法

doi:10.16097/j.cnki.1009-6744.2024.05.007

交通运输系统工程与信息 ›› 2024, Vol. 24 ›› Issue (5): 65-78.DOI: 10.16097/j.cnki.1009-6744.2024.05.007

• 智能交通系统与信息技术 • 上一篇下一篇

基于动态轨迹规划的自动驾驶车辆协同换道方法

刘淼淼^{*1a, 1b}，刘晓晨^{1a, 1b}，朱明月^{1a, 1b}，魏泽平^1b，邓辉²，姚民坤^{1a, 1b}，吴思霖^1a，李昂^1a，石赞^1a，龚筱萸^1a

1. 北京航空航天大学，a. 交通科学与工程学院，b. 车路协同与安全控制北京市重点实验室，北京 100191；2. 中电信数字城市科技有限公司，河北保定 071700

出版日期:2024-10-25 发布日期:2024-10-22
作者简介:刘淼淼(1986- )，女，山东潍坊人，副教授，博士。
基金资助:
国家自然科学基金青年基金(52102393)；科技部雄安新区科技创新专项课题(2022XAGG0126)。

Collaborative Lane Change Method for Autonomous Vehicles Based on Dynamic Trajectory Planning

LIU Miaomiao^{*1a, 1b}, LIU Xiaochen^{1a, 1b}, ZHU Mingyue^{1a, 1b}, WEI Zeping^1b, DENG Hui²,YAO Mingkun^{1a, 1b}, WU Silin^1a, LI Ang^1a, SHI Zan^1a, GONG Xiaoyu^1a

1a. School of Transportation Science and Engineering, 1b. Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, Beihang University, Beijing 100191, China; 2. China Telecom Digital City Technology Co Ltd, Baoding 071700, Hebei, China

Online:2024-10-25 Published:2024-10-22
Supported by:
The National Natural Science Foundation of China (52102393)；The Xiongan New Area Science and Technology Innovation Project (2022XAGG0126)。

摘要/Abstract

摘要： 传统的多车协同缺乏对目标队列和换道车辆信息的有效利用，为考虑动态信息变化对换道过程的影响，本文提出基于动态轨迹规划的自动驾驶车辆协同换道控制方法。首先，针对自动驾驶环境下单车进入车辆队列的研究场景，提出基于实时动态信息的协同换道控制框架，在考虑换道车辆与目标队列车辆的合作以及换道行为给目标队列带来影响的基础上，构建非换道期间和换道期间的纵向协同控制模型；之后，在换道车辆发出换道请求并满足换道触发条件后，考虑队列纵向协同目标，根据纵向速度变化动态规划每一时刻的期望轨迹，提出基于正弦曲线的动态换道轨迹规划方法，得到安全和可靠的轨迹曲线，并采用模型预测控制的轨迹跟踪控制算法，实现实时轨迹跟踪；最后，通过搭建Prescan-Simulink联合仿真平台，设计多组不同速度工况下的仿真实验，以及设置传统基于前车—跟随策略的控制算法与本文的控制策略进行对比，综合分析换道触发时间、队列稳定时间和速度波动幅度这3项指标，验证本文控制策略的有效性和可行性。仿真结果表明：本文所设计的协同换道控制策略和传统方法相比，队列的平均稳定时间缩短了34%，队列的速度波动幅度保持稳定，并在不同相对速度的工况下，均能够实现车辆安全和高效地换道。

关键词: 智能交通, 协同换道, 动态轨迹规划, 网联自动驾驶车辆, 协同换道控制架构

Abstract: Traditional multi-vehicle coordination lacks effective utilization of information about target platoons and lane-changing vehicles. To address the impact of dynamic information changes on the lane-changing process, this paper proposes a collaborative lane-changing control method for autonomous vehicles based on dynamic trajectory planning. First, focusing on the scenario of a single vehicle merging into vehicle platoons in autonomous driving environments, a collaborative lane change control framework based on real-time dynamic information is proposed. Considering the cooperation between the lane-changing vehicle and the target platoon vehicles, and the impact of the lane-changing behavior on the target platoon, longitudinal collaborative control models are established for both non-lane changing and lane-changing periods. Second, after the lane-changing vehicle sends a lane-change request and satisfies the lane-change triggering conditions, a dynamic lane-change trajectory planning method using a sinusoidal curve is employed to derive a safe and reliable trajectory. Vertical coordination goals are considered. And based on the dynamic planning of longitudinal speed changes, a sine-curve-based dynamic lane change trajectory planning approach is introduced to derive safe and reliable trajectories. Then, a model predictive control-based trajectory tracking control algorithm is used to achieve real-time trajectory tracking. Finally, by constructing a joint simulation platform of Prescan and Simulink, several sets of simulation experiments under different speed conditions are designed. And traditional control algorithms based on vehicle tracking strategies are compared with the proposed control strategy by analyzing three key indicators: lane change trigger time, train stabilization time, and speed fluctuation amplitude. This comprehensive analysis validates the effectiveness and feasibility of the proposed control strategy. Simulation results show that, compared with traditional methods, the average stable time of the platoon is reduced by 34%, and the speed fluctuation amplitude of the platoon remains stable. In addition, safe and efficient lane changes can be achieved under different relative speed conditions.

Key words: intelligent transportation, coordinated lane change, dynamic trajectory planning, networked self-driving vehicles, collaborative lane change control architecture

中图分类号:

U495

刘淼淼, 刘晓晨, 朱明月, 魏泽平, 邓辉, 姚民坤, 吴思霖, 李昂, 石赞, 龚筱萸. 基于动态轨迹规划的自动驾驶车辆协同换道方法[J]. 交通运输系统工程与信息, 2024, 24(5): 65-78.

LIU Miaomiao, LIU Xiaochen, ZHU Mingyue, WEI Zeping, DENG Hui, YAO Mingkun, WU Silin, LI Ang, SHI Zan, GONG Xiaoyu. Collaborative Lane Change Method for Autonomous Vehicles Based on Dynamic Trajectory Planning[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(5): 65-78.

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链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2024.05.007

http://www.tseit.org.cn/CN/Y2024/V24/I5/65

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基于动态轨迹规划的自动驾驶车辆协同换道方法

Collaborative Lane Change Method for Autonomous Vehicles Based on Dynamic Trajectory Planning

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