计算机与现代化 ›› 2021, Vol. 0 ›› Issue (06): 54-60.

• 人工智能 • 上一篇    下一篇

基于道路结构的无定位车辆出库转向控制方法

  

  1. (1.武汉科技大学计算机科学与技术学院,湖北武汉430065; 2.智能信息处理与实时工业系统湖北省重点实验室,
    湖北武汉430065; 3.武汉科技大学信息科学与工程学院/人工智能学院,湖北武汉430081)
  • 出版日期:2021-07-05 发布日期:2021-07-05
  • 作者简介:熊莹(1978—),女,湖北汉川人,工程师,硕士,研究方向:车联网,智能驾驶路径规划,高速大容量网络,E-mail: xiongying78@wust.edu.cn; 周亚琪(1997—),女,湖北荆州人,硕士研究生,研究方向:智能驾驶路径规划,车载激光雷达,E-mail: 498902522@qq.com; 通信作者:毛雪松(1975—),男,教授,博士,研究方向:道路环境信息感知,智能驾驶路径规划和智能光设备,E-mail: xsmao@wust.edu.cn。
  • 基金资助:
    国家自然科学基金资助项目(51774219)

Road Structure Based Steering Control Without Localization for Vehicle out of Garage

  1. (1. School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430065, China; 
    2. Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan 430065, China; 
    3. School of Information Science and Engineering/School of Artificial Intelligence,  Wuhan University of Science and Technology, 
    Wuhan 430081, China)
  • Online:2021-07-05 Published:2021-07-05

摘要: 针对地下车库内定位信号差,无人驾驶车辆不能获得自身位置信息来完成在全局参考系中路径规划的问题,提出利用道路边沿的几何结构,从理论上推导转向控制的方法以完成车辆的出库。首先,给出车辆的驾驶场景和用于仿真的低速车辆模型;然后根据道路边沿数据,从理论上推导车辆相对于道路的位姿以及转弯处的转向曲率,并给出车辆在各路段的转向角控制方法;最后,在获取理想与非理想的道路边沿数据情况下,分别仿真采用该方法的车辆行驶状况。仿真结果表明,在道路边沿测量误差小于±20 cm的情况下,方法可以实现无定位的自主驾驶。

关键词: 无人驾驶, 路径跟随, 立体视觉, 转向控制

Abstract: To solve the problem that unmanned vehicles cannot acquire their positions for planning a path in global reference frame when they are driving in an underground garage where the localization signal is weak, a steering control method was deduced theoretically by considering geometry of the road edge for aiding vehicles out of garage. Firstly, driving scene of the vehicle and low speed vehicle model were given. Then, vehicle pose relative to road edge and turning curvature at turning point were deduced theoretically, in addition to the steering angle control method at each road segment. Finally, driving behavior by the method was simulated under the condition that road edge data are ideal and non-ideal, respectively. Simulation results show that the method can realize self-driving without using location if the road edge measurement error is limited.

Key words: unmanned driving, path following, stereoscopic vision, steering control