摘要
考虑当前车路云一体化的发展趋势,人工驾驶车辆(HDV)和智能网联自动驾驶车辆(CAV)构成的人机混驾交通流将是未来交通的主要组成方式。为探索偶发事故下CAV类人行驶策略以及感知信息能力对人机混驾交通流的影响机理,改进KKW(Kerner-Klenov-Wolf)模型框架下的元胞自动机规则,引入考虑CAV类人行驶策略的同步因子,针对不同跟驰模式构建HDV和CAV跟驰规则;基于事故场景车辆换道需求,构建考虑中间车道选择意愿的HDV和CAV多车道自由换道策略,建立考虑换道压力的CAV强制换道规则,分析不同换道压力参数的敏感性;经过数值模拟仿真,分析不同交通量、CAV渗透率、CAV事故信息感知范围、CAV类人行驶策略对人机混驾交通流的影响。研究结果表明:CAV的增加可以有效缓解偶发事故后交通流的拥堵,限制拥堵时空范围,且CAV渗透率由0增加到1时,低交通量的平均速度和平均流量分别提高11.74%和6.32%,提升程度低于中、高交通量;在渗透率大于0.4的中、高交通量情形下,随着CAV事故信息感知范围的增加,合流区的拥堵空间逐渐分散,交通效率得到提高;CAV类人行驶策略由激进型过渡到保守型的过程中,人机混驾交通流的流量逐渐降低,排队缓行范围扩大,交通拥堵逐渐恶化,且随着时间的推移,各车道速度波动趋势逐渐趋同。
With the ongoing development of integrated vehicle-road-cloud systems,mixed traffic flow composed of human-driven vehicles(HDVs)and connected and autonomous vehicles(CAVs)is expected to become the dominant form of future transportation.To explore the influence mechanism of CAV human-like driving strategy and sensing information capability on human-machine mixed driving traffic flow under occasional accident,this paper improved the cellular automata rules under the framework of the KKW(Kerner-Klenov-Wolf)model,introduced the synchroni⁃zation factor to consider the CAV human-like driving strategy,and constructed the HDV and CAV car-following rules for different following modes.Considering the lane-changing demand in accident scenarios,a multi-lane dis⁃cretionary lane-changing strategy incorporating the lane preference of HDVs and CAVs was constructed,along with a mandatory lane-changing rule for CAVs based on lane-changing pressure.Sensitivity analysis was conducted on different lane-changing pressure parameters.Through numerical simulations,the effects of varying traffic volume,CAV penetration rate,CAV perception range of accident information,and CAV human-like driving strategies on mixed traffic flow were analyzed.The results show that the increase of CAVs can effectively alleviate the congestion of traffic flow after occasional accident and limit the spatial and temporal scope of congestion,and the average speed and average traffic volume of the low traffic volume are increased by 11.74%and 6.32%,respectively,when CAV penetration rate is increased from 0 to 1.The enhancement is lower than that of medium and high traffic volume.In the case of medium and high traffic volume with CAV penetration rate greater than 0.4,with the increase of CAV accident information sensing range,the congestion space in the merging area is gradually dispersed,and traffic effi⁃ciency is improved.With the transition of the CAV human-like driving strategy from aggressive to conservative,the flow of the human-machine mixed driving traffic flow is gradually reduced,and the range of slow queues expands,traffic congestion gradually worsens,and the trend of speed fluctuations in each lane gradually converges over time.
作者
张文会
施鑫涛
周舸
ZHANG Wenhui;SHI Xintao;ZHOU Ge(School of Civil Engineering and Transportation,Northeast Forestry University,Harbin 150040,Heilongjiang,China)
出处
《华南理工大学学报(自然科学版)》
北大核心
2025年第8期61-72,共12页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金项目(51638004)。
关键词
智能网联自动驾驶车辆
偶发事故
元胞自动机
人机混驾交通流
connected and autonomous vehicles
occasional accident
cellular automata
human-machine mixed driving traffic flow
