基于车辆社会行为的无人车混合模型预测控制研究

项目名称： 基于车辆社会行为的无人车混合模型预测控制研究

项目编号： No.61473209

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 自动化技术、计算机技术

项目作者： 王峻

作者单位： 同济大学

项目金额： 81万元

中文摘要： 车辆社会行为是车辆在交通网络中表现出的群体属性，对行车安全及交通顺畅至关重要。无人车驾驶研究不仅需要考虑车辆自身的动力学特性，而且需要分析周边社会车辆与之产生的一系列交互行为。本课题研究基于车辆社会行为的无人车混合模型预测控制。首先，提出基于贝叶斯网络模型的马尔科夫链预测方法，识别周围车辆社会行为；其次，建立基于车辆社会行为的无人车混杂模型，设计混合模型预测控制律；最后，提出控制算法实时性的优化机制，实现无人车嵌入式控制器。通过本课题的深入研究，实现融合车辆社会行为的无人车混合模型预测控制方法，完善控制方法的嵌入式实现技术。

中文关键词： 无人车；模型预测控制；混合模型；社会行为

英文摘要： The social behavior of vehicles refers to the interactions among a swarm of vehicles in a traffic network, and it is vital to safe driving and smooth traffic. In the research of autonomous vehicles, not only does vehicle dynamics need to be considered, but also the interactive behavior among surrounding vehicles should be analyzed. This research studies the hybrid model predictive control of autonomous vehicles based on their social behavior. Firstly, the Markov chain model combined with a Bayesian network model is applied to recognize surrounding vehicles' social behavior. Secondly, a hybrid model is established based on the vehicles' social behavior, and its control law is designed by the theory of hybrid model predictive control. Finally, the real-time optimization mechanism is developed for the control law and its embedded controller is implemented for autonomous vehicles. Through the in-depth research, the hybrid model predictive control is achieved for autonomous vehicles based on their social behavior and the embedded techniques for the control method is further improved.

英文关键词： Autonomous Vehicle;Model Predictive Control;Hybrid Model;Social Behavior