Identifying the Threshold Discrepancy of Rear-End Conflicts under Clear and Rainy Weather Conditions Using Trajectory Data

Abstract

The appropriate threshold selection is pivotal in near-crashes detections. Nevertheless, most cutting-edge warning systems utilize thresholds that are directly derived from general traffic scenarios. There is no evidence support that thresholds acquired from general scenarios can be applied to specific scenarios. Thus, the purpose of this study is to investigate whether thresholds of three surrogate measures of safety (SMoS) differ between the general clear scenario and the special rainy scenario. A total of 1048 rear-end events (724 in clear conditions and 324 in light rain conditions) were obtained from the CitySim dataset. Two threshold selection methods were used to recommend appropriate thresholds. The findings indicated that only MTTC had a statistical difference in two weather scenarios, hence, a threshold was recommended under each of two weather conditions. Furthermore, the MTTC threshold for rainy conditions was three times higher than for clear conditions. Contrarily, the threshold was statistically insignificant for the SPDRF and DRAC under two conditions, so only one integration threshold per SMoS was recommended, even in two scenarios. These findings could help safety-system designers set more targeted and appropriate thresholds when encounter specific characteristics (e.g., weather) for active safety systems or safety warning infrastructures in future smart cities.