汽车工程 ›› 2025, Vol. 47 ›› Issue (9): 1647-1654.doi: 10.19562/j.chinasae.qcgc.2025.09.001

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自动驾驶汽车车速跟随空间预瞄跟随方法研究

管欣,李思深,贾鑫()   

  1. 吉林大学,汽车底盘集成与仿生全国重点实验室,长春 130025
  • 收稿日期:2024-11-22 修回日期:2025-01-04 出版日期:2025-09-25 发布日期:2025-09-19
  • 通讯作者: 贾鑫 E-mail:jiaxin@jlu.edu.cn
  • 基金资助:
    国家重点研发计划项目(2023YFB2504500);吉林省自然科学基金(SKL202302014)

Study on Spatial Preview Tracking Method for Autonomous Vehicle Speed Tracking

Xin Guan,Sishen Li,Xin Jia()   

  1. Jilin University,National Key Laboratory of Automotive Chassis Integration and Bionics,Changchun 130025
  • Received:2024-11-22 Revised:2025-01-04 Online:2025-09-25 Published:2025-09-19
  • Contact: Xin Jia E-mail:jiaxin@jlu.edu.cn

摘要:

车速跟随是自动驾驶汽车的重要功能之一,为了提高自动驾驶汽车在指定空间位置处的速度跟随精度,本文提出了一种自动驾驶汽车车速跟随空间预瞄跟随方法。与其它方法相比,本文重点研究如何在空间域而非时间域进行汽车车速预瞄跟随。首先,建立基于运动基元的空间多段车速预瞄方法,本方法以运动基元对目标车速进行空间预瞄,根据误差确定分段点,动态调整每段的距离,保证预瞄误差处于容许误差范围内。根据预瞄结果确定预期纵向加速度。然后,建立纵向加速度跟随方法对预期纵向加速度进行跟随。最后,在仿真环境下,验证本文提出的方法的有效性,并与多种方法进行对比。试验结果表明,本文提出的方法与其他对比方法相比具有更高的空间跟随精度。

关键词: 空间预瞄, 多段预瞄, 车速跟随, 自动驾驶汽车

Abstract:

Speed tracking is one of the most important function of autonomous vehicles. In order to improve the spatial speed tracking accuracy of autonomous vehicles at the designated spatial position, in this paper a spatial preview method for autonomous vehicles speed tracking is proposed. Compared with other methods, this paper focuses on spatial preview rather than temporal preview. Firstly, a motion primitives based spatial multi-segment speed preview method is established. The target speed is spatially previewed by motion primitive, and the segmentation points are determined according to the preview tracking error. The distance of each segment is adjusted dynamically to ensure that the preview tracking error within the allowable deviation range. The expected longitudinal acceleration is determined according to the preview result. Then, a longitudinal acceleration tracking method is established to track the expected longitudinal acceleration. Finally, the effectiveness of the method proposed in this paper is verified and compared with various currently widely used methods in the simulation environment. The test results show that the method proposed in this paper has higher spatial tracking accuracy compared with other methods.

Key words: spatial motion preview, multi segment preview, speed tracking, autonomous vehicle