考虑可变时距和多车信息的混合交通流跟驰模型

A Car-following Model of Mixed Traffic Flow Considering Variable Time Headway Strategy and Multiple Vehicles Information

考虑到未来智能网联小汽车和卡车的落地应用及可能出现的混行状态,文章提出一种智能网联环境下考虑可变时距和多前车信息的卡车-小汽车混合流跟驰模型。为提升道路利用率和安全性,将制动时间和制动时间差引入可变时距策略,在此基础上,基于车车通信建立考虑多车信息的改进智能驾驶员模型(Intelligent Driver Model,IDM)并推导其线性稳定性条件。最后,基于数值仿真分析混合交通流的稳定性、通行能力以及卡车编队对混合交通流的影响。结果表明,考虑多车信息和可变时距的混合流模型相对于仅考虑时距策略的改进IDM模型、IDM模型非稳定域面积降低16.3%、20.0%以上,通行能力提升6.7%、10.3%以上;卡车编队车辆数量增加有助于提升混合流稳定性和通行能力,当编队数量达到4时提升幅度缓慢。

A car-following model of car and truck mixed flow under connected and automated environment are studied.In order to improve utilization rate and safety level of the road,braking distance is introduced to the variable time headway strategy.Based on this,the improved intelligent driver model(IDM)considering multiple front vehicles on the basic of vehicle to vehicle communications is established.The linear stability of the proposed car-following model is analyzed.Finally,the mixed flow stability,capacity,and the effect of truck platoon is studied by numerical simulation.The results show that compared with IDM,improved IDM only considering variable time headway strategy,the car-following model considering variable time headway strategy and multiple vehicles information non-stable domain area is reduced by more than 16.3%,20.0%respectively,capacity is improved by more than 6.7%,10.3%respectively.An increase in the number of vehicles in the truck platoon helps improve mixed flow stability and capacity,with a slow improvement when the number of formations reaches 4.