Surrogate Safety Measures from Traffic Simulation: Validation of Safety Indicators with Intersection Traffic Crash Data

Abstract

The traditional analysis of road safety is based on statistical methods that are applied to crash databases to understand the significance of geometrical and traffic features on safety, or in order to localize black spots. These classic methodologies, which are based on real crash data and have a solid background, usually do not explicitly consider the trajectories of vehicles at any given location. Moreover, they are not easily applicable for making comparisons between different traffic network designs. Surrogate safety measures, instead, may enable researchers and practitioners to overcome these limitations. Unfortunately, the most commonly used surrogate safety measures also present certain limits: Many of them do not take into account the severity of a potential collision and the dangers posed by road-side objects and/or the possibility of drivers being involved in a single-vehicle crash. This paper proposes a new surrogate safety indicator founded on vehicle trajectories, capable also of considering road-side objects. The validity of the proposed indicator is assessed by means of comparison between the calculation of surrogate safety measures on micro-simulated trajectories and the real crash risk obtained with data on real crashes observed at several urban intersection scenarios. The proposed experimental framework is also applied (for comparison) to classical indicators such as TTC (time to collision) and PET (post-encroachment time).