基于车联网技术的无人驾驶汽车转向控制方法

Steering Control Method for Autonomous Vehicles Based on Internet of Vehicles Technology

目前,模型预测控制联合车联网技术已经成为汽车系统控制中的热门研究领域。针对传统控制方法下无人驾驶汽车转向控制精度低、延迟高等问题,研究将车联网技术、无人驾驶汽车、转向控制进行结合,首先利用车联网技术搭建无人驾驶控制系统,接着利用模型预测控制构建了汽车转向控制模型。研究结果表明,所构建的模型能够很好地控制车辆参数的变化,使其仿真轨迹基本与参考轨迹重合。相较于其他传统控制算法,模型预测控制算法的控制准确率为97.8%,误差率为1.05%,系统响应时间为1.01 s。综上,此次研究所设计的转向控制模型拥有较好的性能表现,能为优化无人驾驶汽车转向控制提供一定的参考价值。

Currently,model predictive control combined with vehicle networking technology has become a hot research field in automotive system control.In response to the problems of low accuracy and high delay in steering control of unmanned vehicles under traditional control methods,the study combines vehicle networking technology,unmanned vehicles,and steering control.Firstly,an unmanned driving control system is constructed using vehicle networking technology,and then a vehicle steering control model is constructed using model predictive control.The research results indicate that the constructed model can effectively control the changes in vehicle parameters,making its simulation trajectory basically coincide with the reference trajectory.Compared with other traditional control algorithms,the model predictive control algorithm has a control accuracy of 97.8%,an error rate of 1.05%,and a system response time of 1.01 s.In summary,the steering control model designed by this research institute has good performance and can provide certain reference value for optimizing the steering control of autonomous vehicles.