摘要
目前的行车安全场理论基于“人-车-路”三维构建势能函数,但忽略了复杂的天气因素对行车风险的复合影响,将道路状况(“路”)与天气情况(“环”)所产生的影响简单地归于一类。这低估了天气环境对行车风险的影响程度,并存在对极端天气的风险解算不够敏感的问题,使得方法的实际应用受到较大局限。因此基于行车安全场(driving safety field,DSF)理论,引入了新的环境场函数,实现“人-车-路-环”的风险因素全覆盖,分别构建行为场(behavior field)、动能场(kinetic energy field)、势能场(potential energy field)和环境场(environment field),以此提出针对恶劣天气下的行车安全场BKPE模型。基于中国道路交通安全数据集对原有行车安全场相关参数进行重新标定。同时分析天气因素对行车安全影响的指数变化特征,构建环境了影响因子,并提出环境场函数。在构建包含环境场的行车安全场模型的基础上,基于Car-100数据集,对具体实例计算其人工势能函数,进行微观分析。通过2个典型事件进行多类型风险的量化分析,同时与原有行车安全场模型进行比较分析,说明原有行车安全场模型对于天气环境形成的风险存在低估。随后基于Bootstrap抽样,6次采样计算所得人工势能函数对实际交通事件的描述平均准确率达到91.7%。最终,基于BKPE模型,提出相应的行车风险控制对策。
The current driving safety field(DSF)theory is based on a three-dimensional framework of"driver-vehi-cleroad"to construct the potential energy function.However,it overlooks the complex impact of weather condi-tions on driving risk,simplistically categorizing the influence of road conditions(“road”)and weather conditions(“environment”)into one category.This approach underestimates the extent of the impact of weather conditions on driving risk and exhibits insufficient sensitivity to the risk calculation associated with extreme weather conditions,thereby significantly limiting the practical application of the method.Therefore,based on the DSF theory,a new en-vironmental field function is introduced to achieve comprehensive coverage of risk factors in a“driver-vehi-cleroad-environment”framework.Specifically,the Behavior field,Kinetic energy field,Potential energy field,and Environmental field are constructed separately,and the BKPE model for driving safety field under adverse weather conditions is proposed.In this study,the relevant parameters of the original driving safety field are re-calibrated based on the Chinese road traffic safety dataset.Meanwhile,the exponential change characteristics of weather fac-tors on driving safety are analyzed,and an environmental impact factor is constructed,leading to the proposal of the environmental field function.On the basis of the driving safety field model incorporating the environmental field,the artificial potential energy function is calculated for specific cases using the Car-100 data set for micro-analysis.Two typical events are analyzed to quantify multiple types of risks,and a comparative analysis with the original driving safety field model is conducted,demonstrating that the original model underestimates the risks associated with weather conditions.Subsequently,based on Bootstrap sampling,the average accuracy rate of the artificial po-tential energy function in describing actual traffic events,calculated from six samples,reaches 91.7%.Finally,corre-sponding driving risk control strategies are proposed based on the BKPE model.
作者
李诚信
柳本民
廖晨非
王鹏飞
胡佳欣
刘鹏乾
涂辉招
LI Chengxin;LIU Benmin;LIAO Chenfei;WANG Pengfei;HU Jiaxin;LIU Pengqian;TU Huizhao(The Key Laboratory of Road and Traffic Engineering of Ministry of Education,Tongji University,Shanghai 201804,China;AI thrust,The Hong Kong University of Science and Technology(Guangzhou),Guangzhou 511466,China;School of Emergency Management and Safety Engineering,China University of Mining&Technology(Beijing),Beijing 100083,China)
出处
《交通信息与安全》
北大核心
2025年第2期177-186,共10页
Journal of Transport Information and Safety
基金
国家重点研发计划项目(2019YFE0108300)
云南公路资产管理项目(HAMP-CS-05)资助。
