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作 者:Haozhan Ma Bocheng An Linheng Li Zhi Zhou Xu Qu Bin Ran
机构地区:[1]School of Transportation,Southeast University,Nanjing 210096,China
出 处:《Journal of Intelligent and Connected Vehicles》2023年第2期79-90,共12页智能网联汽车(英文)
基 金:sponsored by the National Key R&D Program of China(Grant No.2018YFB160220600);MOE(Ministry of Education in China)Project of Humanities,National Natural Science Foundation of China(Grant No.52202408);Social Sciences23(Project No.20YJAZH083).
摘 要:Potential field theory,as a theory that can also be applied to vehicle control,is an emerging risk quantification approach to accommodate the connected and self-driving vehicle environment.Vehicles have different risk impact effects on other road participants in each direction under the influence of road rules.This variability exhibited by vehicles in each direction is not considered in the previous potential field model.Therefore,this paper proposed a potential field model that takes the anisotropy of vehicle impact into account:(1)introducing equivalent distances to separate the potential field area in the different directions before and after the vehicle;(2)introducing co-virtual forces to characterize the effect of the side-by-side travel phenomenon on vehicle car-following travel;(3)introducing target forces and lane resistance,which regress the control of desired speed to control the acceptable risk of drivers.The Next Generation Simulation(NGSIM)dataset is used in this study to create the model's initial parameter values based on the artificial swarm algorithm.The simulation findings indicate that when the vehicle is given the capacity to perceive the surrounding traffic environment,the suggested the anisotropic safety potential field model(ASPFM)performs better in terms of driving safety.
关 键 词:connected and automated vehicles car-following model potential field ANISOTROPY trajectory estimation
分 类 号:U46[机械工程—车辆工程] U49[交通运输工程—载运工具运用工程]
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