考虑自动驾驶的混合交通流路段阻抗函数

Cost Function of Mixed Traffic Flow with Autonomous Driving

为解决未来自动驾驶专用车道的规划设计问题,本文提出了一种自动驾驶车与人工驾驶车混合交通流路段阻抗函数模型。首先,分析了自动驾驶专用车道的设置对混合交通流中车辆跟驰模式的影响;其次,在此基础上,引入微观跟驰驾驶模型,推导了不同自动驾驶车辆渗透率条件下的路段通行能力函数,分析了自动驾驶车辆对路段通行能力的影响;然后,将混合交通流通行能力引入经典的BPR函数,推导了考虑自动驾驶的混合交通流路段阻抗函数模型;最后,设计了数值实验讨论了自由流速度(自由流行程时间)、自动驾驶车辆的渗透率和安全车头时距对路段阻抗的影响。结果表明:(1)当路段流量较小时,自动驾驶车辆的引入对路段阻抗行程时间的影响较小;(2)当自动驾驶车的渗透率为30%时,设置自动驾驶专用车道对行程时间的改善最为明显;(3)当流量较小时,自动驾驶车辆渗透率对路段阻抗行程时间的影响较小,而随着路段流量的增大,自由流速度和自动驾驶车辆渗透率将共同决定路段的行程时间。相关成果可为未来自动驾驶专用车道的规划与设计提供理论支撑。

To solve the planning and design problems of automated dedicated lanes(ADLs),this study proposes a cost function model for mixed traffic flow of connected automated vehicles(CAVs)and human-driven vehicles.First,the influence of the ADL setting on car-following modes in mixed traffic flow is analyzed.Second,a car-following driving model is adopted to derive the traffic capacity function under different penetration rates of CAVs,and the effects of CAVs on traffic capacity are analyzed.The capacity of mixed traffic flow is then introduced into the classic Bureau of Public Roads function,and a cost function model of mixed traffic flow that considers autonomous driving is derived.Finally,numerical experiments are conducted to examine the effects of free-flow velocity(free travel time),penetration rates of CAVs,and safe headway on the cost function.The results showed that:(1)when the traffic volume was low,the effects of the application of CAVs on travel time were small;(2)when the penetration rate of CAVs was 30%,the improvement in travel time was the most obvious when the ADL was set;and(3)when the traffic volume was low,the penetration rates of CAVs had little effect on the travel time.With an increase in traffic volume,the free-flow velocity and penetration rates of CAVs jointly determine the travel time.The relevant findings can provide theoretical support for future planning and design of automated dedicated lanes.