中文摘要：

为了减少，象停车那样的外部骚乱的影响加速在驾驶 kinematics 存在的变化和模型无常，这份报纸论述基于预览背繁殖(BP ) 为车辆追踪方法的一条平行路径神经网络 PID 控制器。前面的 BP 神经网络能在实时调整 PID 控制器的参数。预览时间被考虑路径弯曲，在弯曲的变化和道路边界优化。就障碍和不同道路条件而言的一个模糊控制器被造选择开始的位置。另外，计划技术的一种路径令人满意障碍回避的要求被介绍。以便解决不连续的弯曲的问题，立方的 B 花键曲线被用于弯曲适合。模拟结果和真实车辆测试验证计划并且追踪方法的建议路径的有效性。

英文摘要：

In order to diminish the impacts of extemal disturbance such as parking speed fluctuation and model un- certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on pre- view back propagation （BP） neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting po- sition. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods.