Selection and assessment of the relevant data for reducing the number of red-light running

Abstract

Although traffic light controlled intersections separate, the traffic flows by time and space, road traffic accidents still occur, usually due to Red-Light Running (RLR). In order to define countermeasures to solve this problem, it is necessary to collect and analyze certain data that will indicate type of measures, which should be applied. In this paper, it was done on the example of one 3-leg and one 4-leg intersection where citizens provided information about frequent RLR to the City Administration of Belgrade (Serbia). The statistical significance of differences between the collected data was tested by ANOVA analysis and by PostHoc Tukey test, which showed that forecasting of second of RLR after red-light onset could effectively be conducted by Cubic distribution. In order to define the so-called RLR risk indicator for the intersection, the use of the Danger Degree (DD) indicator, that presents the rate between the number of dangerous situations caused by RLR and the total number of RLR, was proposed.