基于元胞自动机的高速公路瓶颈交通演化仿真

为分析高速公路中道路瓶颈造成的堵塞现象，本文改进KKW (Kerner-Klenov-Wolf) 模型， 建立跟驰规则；综合考虑车间距和车速对车辆换道的影响，建立自由换道和强制性换道规则；并对高速公路中不同车流量条件下，道路瓶颈上游的堵塞区域分布、换道行为特征和车道上交通参数的变化情况进行仿真研究。结果表明：在给定的交通量条件下，汇流车道的拥堵区域长度处于动态平衡状态，不会随时间而变化，且道路瓶颈前的汇流行为会导致目标车道上严重的速度下降，汇流车道和目标车道上车辆速度变化趋同；从换道集群特征来看，道路瓶颈前因高交通流量形成的低速汇流车辆倾向于以小集团的方式统一进行换道，造成目标车道上剧烈的交通震荡；瓶颈消失后，交通恢复时间随进口交通流量的上升而线性增长。

Simulation of Highway Traffic Bottleneck Via Cellular Automata

To analyze the congestion caused by road bottlenecks on the highway, this paper uses the improved KernerKlenov-Wolf (KKW) model to establish car-following rules, and comprehensively considers the impacts of vehicle spacing and speed on vehicle lane-changing behaviors to establish free lane-changing and mandatory lane-changing rules. This paper also analyzes the distribution of the congestion area upstream of the road bottleneck, the characteristics of lane-changing behaviors, and the changes of traffic parameters on the lane through simulations under different traffic flow conditions. The results show that: with given traffic volume, the length of congested area in merging lane is in a dynamic equilibrium state and will not change with time. In addition, the convergence behavior upstream of the road bottleneck can lead to a severe speed drop on the target lane. The vehicle speed changes in the convergence lane and the target lane tend to be consistent. From the perspective of lane-changing cluster characteristics, the low-speed merging vehicles tend to change lanes in small groups in the upstream of the road bottleneck due to heavy traffic volumes, which would cause severe traffic shocks in the target lane. After the bottleneck disappears, the traffic recovery time increases linearly with the increase of the entering traffic flow.