考虑驾驶风格的闭环反馈车速引导方法研究

信号交叉口的车速控制不当会降低车辆的燃油经济性甚至引起追尾碰撞事故，车路协同环境下的车速引导系统可以有效提高信号交叉口处的通行效率和燃油经济性。现有车速引导研究大多忽略了驾驶员风格的差异性，将导致驾驶员无法准确跟踪引导速度。针对该问题，建立考虑驾驶风格的闭环反馈车速引导模型。首先，分析不同风格驾驶员车辆最大纵向加速度的概率分布；其次，研究闭环反馈车速引导方法，使驾驶员更准确地跟踪引导车速；然后，基于机会约束规划方法优化闭环反馈车速引导模型，使模型更加符合驾驶员的不同风格；最后，在MATLAB/ Simulink环境中设计仿真场景，对激进型、适中型和保守型3种闭环反馈车速引导模型进行仿真分析。仿真结果表明：相较于传统车速引导模型，本文模型可使不同风格的驾驶员更容易跟踪引导车速，其中，激进型和适中型车速引导模型可以使车辆以更短的时间通过交叉路口，保守型车速引导模型可以提高车辆在绿灯相位通过交叉口的概率。本文方法可以有效地提高信号交叉口的通行效率。

Closed-loop Feedback Speed Guidance Method Considering Driving Style

At signalized intersections, unreasonable speed control may increase the vehicle fuel consumption and may even cause a rear-end collision. Speed guidance systems can improve the efficiency of vehicle speed control. However, drivers cannot accurately follow the speed guidance during driving. This study proposes a closed-loop feedback vehicle speed guidance system by considering the driving styles of drivers. Firstly, the probability distribution of vehicle maximum acceleration with different driving styles is analyzed. The closed-loop feedback approachis then proposed for drivers to follow thespeed guidance more accurately. A chance constraint model is further developed to consider different driving styles. Finally, a simulation is conducted in MATLAB/Simulink to validate the proposed speed guidance models. The simulation results show that the model with different driving styles in this study is more effective and reliable compared with the traditional model. The aggressive and moderate speed guidance models can make vehicles get through signalized intersections efficiently, and the cautious speed guidance model can increase the probability of getting through signalized intersections in green light phases. This speed guidance model can improve the traffic efficiency at signalized intersections.