基于轮胎特征点的并行大型车辆朝向角计算

Calculation of Heading Angle of Parallel Large Vehicle Based on Tire Feature Points

针对自动驾驶环境感知中并行大型车辆朝向角预测结果稳定性差的问题,本文中提出一种新的方法进行并行大型车辆朝向角计算。首先,基于相机逆投影模型提出根据轮胎特征点图像位置计算目标车辆朝向角的计算方法。然后,在现有单目3D目标检测模型上增加并训练子分支用于进行大型车辆轮胎特征点的检测。最后,对本文算法进行可视化验证。结果表明,该方法可得到准确的并行大型车辆朝向角,具有比单目3D目标检测模型更好的稳定性。

For the poor stability of the prediction results of heading angle of parallel large vehicles in auton‐omous driving environment perception,this paper proposes a new method for the calculation of heading angle of par‐allel large vehicle.Firstly,a method based on camera inverse projection model to calculate the heading angle of tar‐get vehicle according to the location of feature points of tires in the image is proposed.Subsequently,a sub-branch is added and trained on the existing monocular 3D object detection model for the detection of feature point of tire of large vehicles.Finally,the algorithm in this paper is visually verified.The results show that the method can obtain accurate heading angle of parallel large-scale vehicle,and has better stability than the monocular 3D object detec‐tion model.