Simulation models for accident section on freeway are built in microscopic traffic flow simulation environment. In these models involving 2-lane,3-lane and 4-lane freeway,one detector is set every 10 m to measure sect...Simulation models for accident section on freeway are built in microscopic traffic flow simulation environment. In these models involving 2-lane,3-lane and 4-lane freeway,one detector is set every 10 m to measure section running speed. According to the simulation results,speed spatial distribution curves for traffic accident section on freeway are drawn which help to determine dangerous sections on upstream of accident section. Furthermore,the speed spatial distribution models are obtained for every speed distribution curve. The results provide theoretical basis for determination on temporal and spatial influence ranges of traffic accident and offer reference to formulation of speed limit scheme and other management measures.展开更多
轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成...轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成乘客特征—时序(FeatureTemporal,F-T)矩阵;通过改进的欧氏距离计算F-T矩阵间的相似性,实现F-T矩阵的相似性度量;提出一种基于相似度矩阵的K-Means聚类和层次聚类相结合的两步聚类方法(Two-step Clustering of K-Means Clustering and Hierarchical Clustering,KMHC)划分乘客影响群体,分析影响乘客出行转移的因素;以新冠肺炎疫情期间上海轨道交通11号线昆山段停运作为实例,对本文方法进行验证。研究结果表明:昆山段停运后,常乘客呈现出5种主要的出行转移影响群体,占常乘客总数的94.4%;各影响群体的转移距离、通勤时间和出行频率差异明显,是影响区段停运后常乘客出行选择的重要因素。本文方法可为其他计划性停运场景提供借鉴和参考,也可为区段停运后的网络客流变化预测,行车和客运组织方案优化提供支撑。展开更多
基金Sponsored by the Fundamental Research Funds for the Central Universities(Grant No.DL12BB16)the National Natural Science Foundation of China(Grant No.51305181)
文摘Simulation models for accident section on freeway are built in microscopic traffic flow simulation environment. In these models involving 2-lane,3-lane and 4-lane freeway,one detector is set every 10 m to measure section running speed. According to the simulation results,speed spatial distribution curves for traffic accident section on freeway are drawn which help to determine dangerous sections on upstream of accident section. Furthermore,the speed spatial distribution models are obtained for every speed distribution curve. The results provide theoretical basis for determination on temporal and spatial influence ranges of traffic accident and offer reference to formulation of speed limit scheme and other management measures.
文摘轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成乘客特征—时序(FeatureTemporal,F-T)矩阵;通过改进的欧氏距离计算F-T矩阵间的相似性,实现F-T矩阵的相似性度量;提出一种基于相似度矩阵的K-Means聚类和层次聚类相结合的两步聚类方法(Two-step Clustering of K-Means Clustering and Hierarchical Clustering,KMHC)划分乘客影响群体,分析影响乘客出行转移的因素;以新冠肺炎疫情期间上海轨道交通11号线昆山段停运作为实例,对本文方法进行验证。研究结果表明:昆山段停运后,常乘客呈现出5种主要的出行转移影响群体,占常乘客总数的94.4%;各影响群体的转移距离、通勤时间和出行频率差异明显,是影响区段停运后常乘客出行选择的重要因素。本文方法可为其他计划性停运场景提供借鉴和参考,也可为区段停运后的网络客流变化预测,行车和客运组织方案优化提供支撑。