电动自行车穿行对公交乘客进出站行为的安全影响分析

Analysis of the safety impact of E-bike passing through on the behavior of bus passengers entering and exiting bus stops

为深刻认知公交乘客在横穿非机动车道进出公交站台过程中与纵向穿行的电动自行车形成的交叉型碰撞冲突的特征并探究冲突严重程度的影响因素,提出电动自行车穿行对公交乘客进出站行为的安全影响分析方法。首先,依据航拍获取的电动自行车和公交乘客运行轨迹,将公交乘客-电动自行车冲突划分为公交乘客避险、电动自行车避险、双方均避险等3类;然后在交叉型冲突特征分析的基础上,提出相对碰撞时间(TTR)指标,联合后侵入时间(PET)、安全减速度(DST)构建基于改进K-means聚类的冲突严重程度评价模型;最后分别从公交乘客和电动自行车视角提取5个冲突严重程度影响因素,建立基于BP神经网络的冲突严重等级预测模型,并对模型有效性进行检验。结果表明:速度差和相对速度对冲突严重等级的影响最大;电动自行车主动避险对冲突双方的运动状态影响最小,相对碰撞能量最低;所提冲突严重等级预测模型的计算结果与实际冲突等级具有较高符合度,能够在一定程度预测冲突严重程度。

In order to deeply understand the characteristics of the cross-type collision conflict between bus passengers crossing the non-motorised road to enter and exit bus stops and the longitudinal crossing of E-bikes,and to explore the factors influencing the severity of the conflict,a method for analyzing the safety impacts of E-bike crossings on the entering and exiting behaviors of bus passengers was proposed.Based on the trajectories of E-bikes and bus passengers obtained from aerial photography,the bus passenger-E-bike conflict was divided into three categories:bus passenger avoidance,E-bike avoidance,and both sides avoidance.Based on the characterization of cross-type conflicts,the relative collision time(TTR)indicator was proposed,and the conflict severity evaluation model based on improved K-means clustering was constructed by combining the post-trespassing time(PET)and safety deceleration speed(DST).Finally,five conflict severity influencing factors were extracted from the perspectives of bus passengers and E-bikes respectively,and a conflict severity level prediction model based on BP neural network was established and tested for model validity.The results show that speed difference and relative speed have the greatest influence on the conflict severity level.E-bike active avoidance has the least influence on the motion state of both parties in the conflict,and the relative collision energy is the lowest.The calculation results of the proposed conflict severity level prediction model have a high degree of conformity with the actual conflict level,and can predict the conflict severity level to a certain extent.