摘要： 无人驾驶汽车根据自身获取信息进行决策,与人类驾驶缺乏有效的交互机制,在复杂交通环境下难以发挥优势,甚至会引起事故。为此,引入智能网联汽车的设计思想,针对车辆在行驶过程中的换道行为,基于博弈论构建一种包含车辆协同机制的换道模型。考虑驾驶员实施换道的行为特征,车辆在做出换道决策后观察分析其他车辆的驾驶风格,其结果会影响最终决策。根据安全前提下可能获得的加速空间决定支付函数,同时加入表征驾驶风格的参数,并量化得到驾驶风格分数。在SUMO仿真软件上的测试结果显示,使用博弈换道模型的车辆在不同车流密度环境下平均通行数量提高5.60%,平均通行时间减少8.44%,测试中未发生事故,表明模型具有感知、判断人类驾驶风格的能力,可在保证安全的前提下提高通行效率。

关键词: 换道模型, 博弈论, 智能网联汽车, 车辆协同, 驾驶风格

Abstract: The autonomous vehicles make decisions according to their own information and lack effective interaction with human driving vehicles.When the autonomous vehicle is in complex traffic environment,its advantage is hard to play and even causes accidents.Based on the thought of intelligent connected vehicle,aiming at the lane changing behaviors in the driving process,this paper puts forward a lane-changing model by using game theory.Firstly,it gives full consideration to the behavior characteristics of the human lane changing.After the vehicle makes lane changing decision,it observes and analyzes the driving style of other vehicles,which affects the final decision.Secondly,the payoff function is determined according to the accelerating space in the premise of safety while adding the parameters expressing the driving style and quantifying the driving style scores.Finally,through the simulation by SUMO,the experimental results show that,by using game lane-changing model,the vehicles passing through increases by 5.60% and driving time decreases by 8.44% on average under different traffic densities,and no accident happens in the test.With the ability of perception and judgments of human driving style,traffic efficiency under the premise of safety is optimized.

Key words: lane-changing model, game theory, Intelligent Connected Vehicle(ICV), vehicle collaboration, driving style

中图分类号: 

• TP391.9