Abstract
To effectively reduce traffic violations that often cause severe crashes at signalized intersections, exploring their contributing factors seems hugely urgent and essential. This study attempted to investigate the influence factors of wrong-way driving (WWD), red-light-running (RLR), violating traffic markings (VTM), and driving in the inaccurate oriented lane (DIOL) at signalized intersections by using data collected from traffic enforcement camera in Hohhot, China. To this end, an ordinary multinomial logit model was developed. By considering the unobserved heterogeneity between observations, a random effects multinomial logit model was proposed as well. After that, the marginal effects of explanatory variables were computed. The outcomes showed that non-local vehicles were more likely to commit WWD and VTM than local vehicles. WWD and RLR frequently occurred in the daytime and evening (6:00–23:59), and on most days within a week. RLR and DIOL mainly happened in June and July. The left-turn lane ratio significantly increased RLR and DIOL. The cloudy, partly cloudy, and rainy days obviously increased WWD and VTM. The temperature from 21 to 30 degrees centigrade was apparently associated with the higher likelihoods of RLR and DIOL. According to the findings of this study, some intervention measures, targeting different vehicle types and considering temporal factors, road, and weather conditions, were recommended to reduce WWD, RLR, VTM, and DIOL at signalized intersections.
Highlights
Intersection safety has been becoming an international concern
The marginal effects of independent variables were applied to figure out the extent to which a particular factor affected traffic violations
The estimation results of ordinary multinomial logit model (OMLM) and REMLM of wrong-way driving (WWD), RLR and violating traffic markings (VTM) are presented in Table 4, Table 5, and Table 6, respectively
Summary
Intersection safety has been becoming an international concern. In Australia, almost 33% of major casualties are caused by intersection crashes [1]. The outcomes of this study manifested that local vehicle, time of day, day of week, month, leftturn lane ratio, channelization ratio, weather status, and temperature had varying influences on four types of traffic violations at signalized intersections.
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