Time-varying Analysis of Traffic Conflicts at the Upstream Approach of Toll Plaza

This study investigates the traffic conflict risks at the upstream approach of toll plaza during the vehicles’ diverging period from the time of arrival at the diverging area to that of entering the tollbooths. Based on the vehicle's trajectory data extracted from unmanned aerial vehicle (UAV) videos using an automated video analysis system, vehicles’ collision risk is computed by extended time to collision (TTC). Then, two time-varying mixed logit models including time-varying random effects logistic regression (T-RELR) model and time-varying random parameters logistic regression (T-RPLR) are developed to examine the time varying effects of influencing factors on vehicle collision risk, and four models including the standard random effects logistic regression (S-RELR) model, standard random parameters logistic regression (S-RPLR) model, distance-varying random effects logistic regression (D-RELR) model and distance-varying random parameters logistic regression (D-RPLR) are developed for model performance comparison. The results indicate that the T-RPLR model has the highest prediction accuracy. Eight influencing factors including following vehicle's travel distance, following vehicle's initial lane, following vehicle's toll collection type, leading vehicle's toll collection type, distance between two vehicles’ centroids, and following vehicle's speed, are found to have time-varying effects on collision risk. Meanwhile, the first six factors are found to exhibit heterogeneous effects over the travel time. Another important finding is that the vehicle that comes from the innermost lane has an increasing trend to be involved in traffic conflicts, whereas the collision risks of other vehicles decrease as the travel time increases. Moreover, vehicles with higher speed have a decreasing probability to be involved in crashes over the travel time. Interestingly, the results of D-RPLR model are similar with that of T-RPLR model. These findings provide helpful information for accurate assessment of collision risk, which is a key step toward improving safety performance of the toll plazas’ diverging areas.