考虑多车响应的网联混行车流跟驰模型及稳态分析

doi:10.13229/j.cnki.jdxbgxb.20221645

摘要/Abstract

摘要：

为研究网联混行车流跟驰特性，本文建立网联混行车流跟驰模型帮助理解其跟驰特性，从而提高混行车流稳定性。考虑前后车头间距最优速度与最优速度记忆项，多前车速度差与加速度差，构建适用于智能网联汽车（CAV）与人工驾驶车辆（HV）交互渗透的混行车流跟驰模型（MFROVCM）。对模型进行稳定性分析，结果显示，MFROVCM模型与OVCM模型相比，不稳定区域减少53.17%；与BL-OVCM模型相比，不稳定区域减少15.44%，模型稳定性优于其他对比模型。数值仿真结果显示：相同扰动条件下，MFROVCM模型具有更好的交通流致稳性能，随着CAV渗透率的增大，整体交通流速度波动幅度减小，且恢复稳定的时间逐渐减小。该模型可应用于CAV与HV混行的车流跟驰仿真，为网联混合车流的交通控制策略提供理论依据与模型基础。

关键词: 交通工程, 网联混行车流, 跟驰模型, 数值仿真, 多车响应, 最优速度记忆

Abstract:

In order to study the car-following characteristics of Internet connected mixed traffic flow， the establishment of Internet connected mixed traffic flow car-following model can help to understand its car-following characteristics and improve the stability of mixed traffic flow. Considering the optimal velocity and optimal velocity changes with memory based on front and rear headway space， the velocity difference and acceleration difference of multiple front vehicles， a car-following model named multiple front and rear optimal velocity changes with memory （MFROVCM ） which is suitable for the interactive penetration of mixed traffic flow with connected and autonomous vehicles （CAV） and human-driven vehicles （HV） was constructed. The stability analysis of the model shows： Compared with OVCM model， the unstable area is reduced by 53.17%； compared with BL-OVCM model， the unstable area is reduced by 15.44%， and the stability of MFROVCM model is better than other comparison models. The simulation results show that under the same disturbance conditions， MFROVCM model has better traffic flow stabilization performance. With the increase of CAV permeability， the fluctuation amplitude of overall traffic flow velocity decreases， and the time to restore stability gradually decreases. The model can be applied to the car-following simulation of CAV and HV mixed traffic flow， and provides a theoretical basis and model basis for the traffic controlstrategy of networked mixed traffic flow.

Key words: traffic engineering, connected mixed traffic flow, car-following model, numerical simulation, multiple vehicles response, optimal velocity changes with memory

中图分类号:

U491

宋慧,曲大义,王少杰,王韬,杨子奕. 考虑多车响应的网联混行车流跟驰模型及稳态分析[J]. 吉林大学学报(工学版), 2024, 54(11): 3220-3230.

Hui SONG,Da-yi QU,Shao-jie WANG,Tao WANG,Zi-yi YANG. Connected mixed traffic flow car-following model and stability analysis considering multiple vehicles response[J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(11): 3220-3230.

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项目	α_I	λ_I	k_I	γ_I	τ	P
I=1	0.8	0.10	0.00	0.10	0.2	0.9
I=2	0.9	0.15	0.05	0.15	0.2	0.9
I=3	1.0	0.20	0.10	0.20	0.2	0.9

模型	α	λ	k	γ	τ	P
OV	1.0	0.0	0.0	0.0	0.0	1.0
FVD	1.0	0.2	0.0	0.0	0.0	1.0
OVCM	1.0	0.2	0.0	0.2	0.2	1.0
BLVD	1.0	0.2	0.0	0.0	0.0	0.9
BL-OVCM	1.0	0.2	0.0	0.2	0.2	0.9
MFROVCM	1.0	0.2	0.1	0.2	0.2	0.9