网联车辆自适应巡航控制算法验证平台设计

自适应巡航控制系统是一种车辆高级辅助驾驶系统,不仅可以减轻驾驶员工作负担,还能增强车辆的行车安全和驾乘舒适性。基于MATLAB和Python混合编程,在网络协议环境下设计智能车巡航控制算法验证平台;该平台能够模拟多种不同典型行车场景,其实时的信息采集与动画演示功能能够直观有效地展现车辆状态。结合所开发的平台软件,设计出增量式模型预测控制器(IMPC)和智能驱动驾驶(IDM)控制器,所提出的IMPC算法不仅能综合考虑网联车巡航多目标的特点,同时还满足巡航系统快速性和准确性的要求。最后结合典型驾驶工况,开展智能车的车辆自适应巡航控制实验。实验结果表明,基于MATLAB和Python混合编程的软件系统能有效模拟各种驾驶情景,并能结合智能车验证该自适应巡航控制算法的结果。

Design of Verification Platform for Adaptive Cruise Control Algorithm of Connected Vehicles

Adaptive Cruise Control（ACC） is an intelligent automatic control system, which can be used to reduce drivers’ workload and also to improve driving safety and ride comfort. This paper designs the cruise control system of smart connected vehicles based on the MATLAB and Python mixed programming. The system can simulate multiple classical driving scenarios in order to test the performances of ACC algorithms, where the real-time information collection and animation demonstration can feedback state of smart car. Then the Incremental Model Predictive Control（IMPC） and Intelligent Driving Model（IDM） algorithms are designed to realize the adaptive cruise control of smart cars, which are illustrated by this presented software system. The proposed algorithm  has ability to take  the characteristics of the connected vehicles’ multi-objective into account and satisfy  the rapidity and accuracy requirements of the cruise system. Some experimental results show that the designed ACC software of connected vehicles can be used for the representative driving scenarios, which can effectively demonstrate the effects of multiple different ACC algorithms of connected vehicles.