基于联合仿真的智能车辆路径跟踪控制研究
发布时间：2019-05-28 12:32
【摘要】：智能车辆作为智能交通控制领域中一项主要的研究内容,其将多种现代电子信息技术集成于一体。随着当前社会对于现代车辆的智能化、安全化的需求越来越高,智能车辆成为世界上各个国家在交通领域竞相研究的热点问题和技术前沿。在国家自然科学基金项目(编号61104165)的资助下,本文主要针对智能交通公路系统中,智能车辆的路径跟踪联合仿真控制问题进行了研究分析。 为了使建立的车辆动力学结构模型尽可能接近实车的机械系统动力学,本文首先对车辆的复杂结构进行了简化分析,然后以ADAMS/Car为仿真分析平台建立了智能车辆的各子系统模型,最后将各子系统组装成整车虚拟样机模型并定义了系统仿真时的输入变量和输出变量。 为了降低路径跟踪过程中的横向偏差与方向偏差,本文设计了一种基于车辆横摆角速度反馈方法的路径跟踪控制策略。基于车辆的运动学模型和位姿误差模型,通过对车辆实际位置与预瞄点之间虚拟路径的跟踪来生成期望横摆角速度,并采用滑模算法和RBF神经网络算法相结合的控制方法设计了车辆的路径跟踪控制器,从而使智能车辆能够较好地跟踪期望的运动轨迹。 经过大量的实验表明,在车辆行驶过程中遭遇突发状况时,驾驶员的最优操作是采用转向而不是刹车来避开障碍物,本文针对城市道路交通中车辆主动防碰撞进行了研究分析,基于车辆和障碍物之间的临界安全距离设计了避障决策曲面,并通过对几种避障轨迹进行了比较分析设计了等速偏移轨迹和正弦函数加权叠加的避障轨迹。 针对不同道路曲率的期望路径,本文在ADAMS/Car和Matlab/Simulink软件平台下对车辆路径跟踪控制系统进行了联合仿真分析研究,解决了控制参数在线调整的问题。仿真分析结果表明,本文所设计的智能车辆路径跟踪控制系统能够控制车辆准确地跟踪不同曲率的期望运动轨迹,整个控制过程运行平稳,具有较好的动态特性和鲁棒性,并且本文的控制算法提高了系统的控制精度,改善了系统的跟踪性能。
[Abstract]:As a main research content in the field of intelligent traffic control, intelligent vehicle integrates a variety of modern electronic information technology. With the intelligence of modern vehicles and the increasing demand for safety in the current society, intelligent vehicles have become a hot issue and technical frontier in the field of transportation in the world. With the support of the National Natural Science Foundation of China (No. 61104165), this paper mainly studies and analyzes the joint simulation control problem of intelligent vehicle path tracking in intelligent transportation highway system. In order to make the established vehicle dynamic structure model as close as possible to the mechanical system dynamics of the real vehicle, the complex structure of the vehicle is simplified and analyzed in this paper. Then each subsystem model of intelligent vehicle is established with ADAMS/Car as the simulation analysis platform. Finally, each subsystem is assembled into the virtual prototype model of the whole vehicle and the input variables and output variables of the system simulation are defined. In order to reduce the lateral deviation and direction deviation in the process of path tracking, a path tracking control strategy based on vehicle yaw angular velocity feedback method is designed in this paper. Based on the kinematic model and pose error model of the vehicle, the desired yaw angular velocity is generated by tracking the virtual path between the actual position of the vehicle and the preset point. The path tracking controller of the vehicle is designed by using the control method of sliding mode algorithm and RBF neural network algorithm, so that the intelligent vehicle can track the desired trajectory well. A large number of experiments show that when the driver encounters a sudden situation in the process of driving, the optimal operation of the driver is to use steering instead of braking to avoid obstacles. In this paper, the active collision prevention of vehicles in urban road traffic is studied and analyzed. Based on the critical safe distance between the vehicle and the obstacle, the obstacle avoidance decision surface is designed, and several obstacle avoidance trajectories are compared and analyzed, and the equal velocity migration trajectory and the weighted superposition of sinusoidal function are designed. In this paper, the vehicle path tracking control system is simulated and studied under ADAMS/Car and Matlab/Simulink software platform for the expected path of different road curvature, and the problem of on-line adjustment of control parameters is solved. The simulation results show that the intelligent vehicle path tracking control system designed in this paper can control the vehicle to track the desired trajectory with different curvature accurately, and the whole control process runs smoothly and has good dynamic characteristics and robustness. The control algorithm in this paper improves the control accuracy and tracking performance of the system.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495
本文编号：2487063
[Abstract]:As a main research content in the field of intelligent traffic control, intelligent vehicle integrates a variety of modern electronic information technology. With the intelligence of modern vehicles and the increasing demand for safety in the current society, intelligent vehicles have become a hot issue and technical frontier in the field of transportation in the world. With the support of the National Natural Science Foundation of China (No. 61104165), this paper mainly studies and analyzes the joint simulation control problem of intelligent vehicle path tracking in intelligent transportation highway system. In order to make the established vehicle dynamic structure model as close as possible to the mechanical system dynamics of the real vehicle, the complex structure of the vehicle is simplified and analyzed in this paper. Then each subsystem model of intelligent vehicle is established with ADAMS/Car as the simulation analysis platform. Finally, each subsystem is assembled into the virtual prototype model of the whole vehicle and the input variables and output variables of the system simulation are defined. In order to reduce the lateral deviation and direction deviation in the process of path tracking, a path tracking control strategy based on vehicle yaw angular velocity feedback method is designed in this paper. Based on the kinematic model and pose error model of the vehicle, the desired yaw angular velocity is generated by tracking the virtual path between the actual position of the vehicle and the preset point. The path tracking controller of the vehicle is designed by using the control method of sliding mode algorithm and RBF neural network algorithm, so that the intelligent vehicle can track the desired trajectory well. A large number of experiments show that when the driver encounters a sudden situation in the process of driving, the optimal operation of the driver is to use steering instead of braking to avoid obstacles. In this paper, the active collision prevention of vehicles in urban road traffic is studied and analyzed. Based on the critical safe distance between the vehicle and the obstacle, the obstacle avoidance decision surface is designed, and several obstacle avoidance trajectories are compared and analyzed, and the equal velocity migration trajectory and the weighted superposition of sinusoidal function are designed. In this paper, the vehicle path tracking control system is simulated and studied under ADAMS/Car and Matlab/Simulink software platform for the expected path of different road curvature, and the problem of on-line adjustment of control parameters is solved. The simulation results show that the intelligent vehicle path tracking control system designed in this paper can control the vehicle to track the desired trajectory with different curvature accurately, and the whole control process runs smoothly and has good dynamic characteristics and robustness. The control algorithm in this paper improves the control accuracy and tracking performance of the system.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495
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