低能见度条件下高速公路异构交通流建模及仿真

doi:10.13229/j.cnki.jdxbgxb.20250433

摘要/Abstract

摘要：

考虑到低能见度对人工驾驶车辆（HDV）的安全距离、加速度、视距及换道行为的影响，基于元胞自动机构建了HDV跟驰模型，采用Path实验室开发的跟驰模型刻画网联自动驾驶车辆（CAV）跟驰行为；构建了考虑能见度、驾驶风格等因素的HDV换道模型，根据前方车辆类型和换道条件刻画CAV的换道决策，开展低能见度条件下高速公路异构交通流仿真研究，基于仿真结果评估不同能见度及CAV渗透率下的通行能力、拥堵率、冲突严重程度、平均油耗及排放量。结果表明：随着能见度和CAV渗透率的增大，通行能力和平均车速均显著提高；相较于Nasch模型，本文构建的低能见度条件下高速公路异构交通流跟驰和换道模型在安全性方面提升约23.1%，平均油耗和氮氧化物排放分别降低了3.42%和1.5%。本文研究成果可丰富高速公路交通流理论，为研究异构交通环境下的相关交通问题提供基础模型。

关键词: 交通运输规划与管理, 高速公路, 交通流仿真, 跟驰模型, 异构交通, 低能见度, 元胞自动机仿真

Abstract:

Considering the impact of low visibility on the safety distance， acceleration， sight distance， and lane-changing behavior of human-driven vehicles （HDV）， a car-following model for HDV is developed based on cellular automata， while the car-following behavior of connected and automated vehicles （CAV） is characterized using a model developed by the Path Laboratory. A lane-changing model for HDV is constructed， incorporating factors such as visibility and driving style， whereas CAV lane-changing decisions are modeled based on the type of preceding vehicle and lane-changing conditions. Simulation studies on heterogeneous traffic flow under low visibility conditions are conducted， and the simulation results are used to evaluate capacity， congestion rate， conflict severity， average fuel consumption， and emissions under different visibility levels and CAV penetration rates.The simulation results demonstrate that as visibility and CAV penetration rates increase， both capacity and average speed significantly improve. Compared to Nasch models， the proposed car-following and lane-changing models for heterogeneous traffic flow under low visibility conditions enhance safety by approximately 23.1%， while reducing average fuel consumption and nitrogen oxide emissions by 3.42% and 1.5%， respectively. This study enriches the theoretical research on highway traffic flow and provides a foundational model for investigating traffic-related issues in heterogeneous traffic environments.

Key words: transportation planning and management, freeway, traffic flow simulation, car following model, heterogeneous traffic, low visibility, cellular automata simulation

中图分类号:

U495

程国柱,刘强,方丽庄,尤志栋,顾爽. 低能见度条件下高速公路异构交通流建模及仿真[J]. 吉林大学学报(工学版), 2026, 56(10): 2566-2577.

Guo-zhu CHENG,Qiang LIU,Li-zhuang FANG,Zhi-dong YOU,Shuang GU. Modeling and simulation of heterogeneous traffic flow on freeway under low visibility conditions[J]. Journal of Jilin University(Engineering and Technology Edition), 2026, 56(10): 2566-2577.

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能见度/m	模型	安全性（1/TTC）		平均油耗（L/100 km）		平均氮氧化物/（mg·s^-1）
能见度/m	模型	数值	提升比例/%	数值	提升比例/%	数值	提升比例/%
50	Nasch	0.042	26.2	20.343	4.08	118.00	1.7
50	本文	0.031	26.2	19.512	4.08	116.00	1.7
100	Nasch	0.033	24.0	17.537	3.50	110.68	1.5
100	本文	0.025	24.0	16.923	3.50	109.00	1.5
200	Nasch	0.021	19.2	11.012	2.68	67.90	1.3
200	本文	0.017	19.2	10.715	2.68	67.00	1.3
平均提升比例		-	23.1	-	3.42	-	1.5