Abstract: In order to describe the phenomenon of “high speed car-following” in traffic, based on the NaSch model, it establishes a high speed car-following traffic flow model considering the dynamic effect of the preceding vehicle（DPM） by taking into account the movement characteristics of the preceding vehicle and combining the driver’s driving behavior. Through the numerical simulation, it obtains high speed car-following rule, when the density of road traffic is 0.18, the high speed car-following rate on the driveway is 4.93%. At the same time, by analyzing the space-time characteristics of the traffic flow, the model can simulate free flow, synchronized flow and wide moving jam in traffic flow. The model also shows the speed-flow-density relationship when driver proportions are different. The fluctuation of the speed and the headway distance of the vehicle are obtained, which has higher traffic stability than the NaSch model. Finally, the NGSIM data and the measured data in China are used to verify the DPM model, which proves the validity and practicability of the model.

Key words: numerical simulation, high speed car-following, traffic flow, dynamic effect of preceding vehicle, cellular automata

摘要： 为描述交通中存在的“高速跟驰”现象，在NaSch模型的基础上，考虑了前车的运动特性，并结合驾驶员的驾驶行为差异，建立了考虑前车动态效应的高速跟驰交通流模型（DPM）。通过数值模拟得到了高速跟驰规律，当道路车流密度为0.18时，车道上的高速跟驰率为4.93%；同时，通过分析车辆运动的时空特性，模拟出交通流中自由流、同步流以及宽幅运动阻塞现象；还得出了不同驾驶员占比下的速度-流量-密度的关系；并分析了车辆随时间变化的速度及车头间距波动情况，较NaSch模型有更高的交通稳定性。通过NGSIM数据集及国内实测数据验证了DPM模型的有效性和实用性。

关键词: 数值模拟, 高速跟驰, 交通流, 前车动态效应, 元胞自动机