Longitudinal Speed Control Method of Unmanned Vehicle Under Undulating Road Conditions

被引：0
|
作者：
Li J. [1 ]
Xu Y. [1 ]
Qi Y. [1 ]
Xie D. [1 ]
Li H. [1 ]
机构：
[1] Institute of Military Transportation, Army Military Transportation University, Tianjin
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2024年 / 24卷 / 03期
关键词：
intelligent transportation; slope preview detection; speed control accuracy; undulating roads; unmanned vehicles;
D O I：
10.16097/j.cnki.1009-6744.2024.03.005
中图分类号：
学科分类号：
摘要：
To improve the accuracy of the speed control of unmanned vehicles under undulating road conditions, a method for preview detection of road slopes on the target trajectory was proposed. Firstly, the response delay parameters of the vehicle speed control system were measured by experiments to determine the preview time. The lidar point cloud was stored in a circle with the diameter of the vehicle width, and the number of circles and the center coordinates of the stored point cloud were determined according to the preview time, the vehicle speed, the detection blind area of the lidar, and the length of the target trajectory. According to the Euclidean distance between the center of the circle and the center of the front axle of the vehicle, the preview time, and the vehicle speed, the circles of the stored point cloud are dynamically updated and extracted, and the slope of the road surface in the preview area relative to the vehicle attitude is calculated by the trigonometric function method. Finally, the absolute slope of the road surface in the preview area is obtained by superimposing the pitch angle of the vehicle provided by the inertial navigation system. Experimental results show that the proposed road slope preview detection method can improve the accuracy of the speed control of unmanned vehicles under undulating road conditions. According to the analysis of the minimum speed of unmanned vehicles in the process of going uphill, compared with the control method that ignores the road slope and uses the pitch angle provided by inertial navigation as the road slope, the accuracy of speed control is increased by 5.9% and 2.5% respectively when passing through a 4° ramp, and the accuracy of speed control is increased by 85% and 17.5% when passing a 16° ramp, respectively. © 2024 Science Press. All rights reserved.
引用
收藏
页码：43 / 52
页数：9
相关论文
共 11 条
  • [1] HOFFMANN G M, TOMLIN C J, SEBASTIAN T, Et al., Proceedings of the 2007 American control conference, (2007)
  • [2] CHRISTIAN G J, KARL H J., Vehicle speed and spacing control via coordinated throttle and brake actuation, IFAC Proceedings Volumes, 29, 1, pp. 7879-7884, (1996)
  • [3] ALOMARI K, MENDOZA R, SUNDERMANN S, Et al., Proceedings of the international conference on robotics, computer vision and intelligent systems, (2020)
  • [4] WANG Y J, DENG Y X, WANG H Y, Et al., Terminal constraint-free model predictive longitudinal control for unmanned ground vehicles with driving force table, IEEE Transactions on Vehicular Technology, 72, 3, pp. 3051-3062, (2023)
  • [5] WANG J, SUN Z, XU X, Et al., Adaptive speed tracking control for autonomous land vehicles in all-terrain navigation: An experimental study, ALV speed control, Journal of Field Robotics, 30, 1, pp. 102-128, (2013)
  • [6] MING T Y., Research on trajectory tracking control for intelligent vehicles, (2016)
  • [7] XU D, FANG S E, CHEN Y R., Influencing factors of truck operating speed at high altitude area, Journal of Transportation Systems Engineering and Information Technology, 19, 4, pp. 246-251, (2019)
  • [8] XIE H, LIU S S., Lateral and longitudinal motion control of unmanned vehicles using model predictive control, Journal of Automotive Safety and Energy, 10, 3, pp. 326-333, (2019)
  • [9] XU S B, PENG H, SONG Z Y, Et al., Design and test of speed tracking control for the self-driving lincoln MKZ platform, IEEE Transactions on Intelligent Vehicles, 5, 2, pp. 324-334, (2020)
  • [10] LIU B N., Research on longitudinal speed control for autonomous vehicles adaptive with road grade and vehicle mass, (2015)
12