Research Of The Influencing Factors Of Red-light Running Behavior Of E-bike

From 2013 to 2017,a total of 56,200 traffic accidents are arising from e-bike caused casualties in China.These traffic accidents directly resulted in 72,000 casualties and 111 million yuan in property losses.Because red-light running is one of the main illegal acts that result in these accidents,it is of great importance to reduce the number of traffic accidents for improving the traffic environment by reducing red-light running behavior.Furthermore,it is imperative to investigate these factors,which have important influence on the behavior red-light running,for improving traffic safety.Based on this,combining actual observations with related literatures,this article takes e-bike as the research object,and focus on analyzing the red-light running behavior of e-bike at urban signal intersections.Moreover,this work reveals the important factors and impact degree about red-light running behavior.More importantly,a model is established to predict the crossing of e-bike behavior.The specific research work is as follows:(1)Data about the behavior of e-bike red-light running.This article selects three typical city signal intersections in Shenzhen for video recording.Through descriptive statistical analysis of the data,it is found that the probability of e-bike red-light running is about 60%.(2)The distribution law of waiting time of e-bike riders.Based on the survey data,this paper uses the Kaplan-Meier non-parametric method in the survival analysis method to analyze the effects of weather,crossing areas,manned people,takeaways,and the same way illegal inducement on the rider's waiting time,further investigating these factors impact on the behavior of red-light running.The study shows that with the same waiting time,the survival rate of cyclists on rainy days and without people are higher than that of sunny days and with people,respectively.On sunny days,with the same waiting time,the survival rate of e-bike riders crossing the street in the zebra crossing area is significantly higher than that in the non-zebra crossing area,while this phenomenon is not obvious on rainy days.Due to the influence of the same-directed illegal inducement factors,the survival rate of other waiting e-bike riders is low on sunny days,while the survival rate of this group is higher on rainy days.(3)Cox risk model of e-bike red-light running and the corresponding influencing factors.According to the survey data,the Cox risk model about the waiting time of e-bike riders is constructed to investigate the impact degree of the influencing factors.The study indicate that the takeout and second crossing factors have insignificant effect on the waiting time of e-bike riders when crossing the street.However,the weather has relatively large influence on the waiting time.Obviously,the risk rate of sunny days is about twice that of rainy days.In addition,the crossing area and the manned factors have similar influence on the waiting time.(4)Analysis of the prediction model for crossing behavior of e-bike at signalized intersections.With the help of factor analysis,the public factors,including road factors,personal characteristic factors,environmental factors,inducing factors,and traffic factors,that affect the behavior of e-bike riders when they red-light running,are obtained.By virtue of these public factors,a Logistic regression model is established to predict the behavior of e-bike riders when they cross the street.According to the regression model,the influence intensity of road factors and personal characteristic factors on crossing behavior is relatively large,while the influence intensity of traffic factors and inducement factors is relatively small.