摘要
剧烈的急减速行为是影响交通运行安全和效率的重要因素之一.基于控制器局域网络(controller area network,CAN)总线设备获得的机动车行驶轨迹数据,设计了基于阈值条件的小汽车急减速行为诊断方法.随后,从初始速度、减速持续时间、平均减速度等角度分析了小汽车急减速的基本特征,并挖掘了小汽车急减速行为与交通拥堵状态的关联特征.最后,进行了急减速风险路段诊断与急减速行为聚类分析的案例讨论.结果表明:急减速的持续时间越短,其平均减速度越大;而初始速度越大,其平均减速度越大.急减速发生概率与道路交通拥堵状态具有显著的正相关关系;同时急减速发生的空间位置与道路交通节点密切相关.而K-means聚类分析表明不同类型的驾驶员的急减速频率特征差异显著.
The rapid deceleration behavior is an important factor affecting safety and efficiency.Based on the vehicle trajectory data obtained by the controller area network(CAN)equipment,this paper designed a threshold method for diagnosing the rapid deceleration behavior.Then,the characteristics of the vehicle rapid deceleration were analyzed from the perspectives of initial speed,deceleration duration,and average deceleration.Further,the correlation characteristics between the rapid deceleration and the traffic state were excavated.Finally,the hot-spot identification of the rapid deceleration and the clustering analysis of rapid deceleration behavior were discussed.Results show that the shorter the duration of the rapid deceleration,the greater the average deceleration;the greater the initial speed,the greater the average deceleration.There is a significant positive correlation between the occurrence probability of the rapid deceleration and the traffic congestion;besides,the spatial location of the rapid deceleration is closely related to road traffic nodes.The K-means cluster analysis shows that the rapid deceleration characteristics of different driver types are significantly different.
作者
张建波
孙建平
温慧敏
宋国华
ZHANG Jianbo;SUN Jianping;WEN Huimin;SONG Guohua(School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;Beijing Key Laboratory of Urban Transport Simulation and Decision Making Support,Beijing Transport Institute,Beijing 100073,China;Beijing International Science and Technology Cooperation Base of Urban Transport,Beijing Transport Institute,Beijing 100073,China)
出处
《北京工业大学学报》
CAS
CSCD
北大核心
2021年第12期1360-1366,共7页
Journal of Beijing University of Technology
基金
国家重点研发计划资助项目(2018YFB1600700)。
关键词
驾驶行为
轨迹数据
急减速
关联分析
风险评价
驾驶员类型
driving behavior
trajectory data
rapid deceleration
correlation feature
risk evaluation
driver types
