A revise on using surrogate safety measures for rear-end crashes

Abstract

Traffic safety is among the most serious topics of transportation engineering studies. Different methods have been proposed for safety evaluations. Applying surrogate safety measures (SSM) to predict the crash likelihood and severity is a relatively new approach, which needs microscopic traffic data instead of crash data. Numerous SSMs have been introduced in the literature. Now, it is somehow hard to decide about the selection of suitable SSMs for safety assessments based on microscopic traffic data. In this paper, first a review on SSMs relating to rear-end conflicts introduced in the high-quality papers is done. Then, with the help of microscopic traffic data of NGSIM in I-80 freeway, SSMs are calculated for each car-following scenario. Because of the diversity of SSMs and contradicting results it was tried to propose a method for combining the results of these indicators to report one number as the rear-end collision risk. The efficiency of the new indicator is evaluated in comparison to individual SSMs. The proposed methodology can be beneficial to improve the efficiency of In-vehicle collision avoidance warning system (IVCAWS) and enhancing highway safety evaluations based on SSMs.

Keywords

• Safety
• Surrogate safety measure
• Crash
• Collision avoidance