Motion Prediction Methods for Surrogate Safety Analysis

TRB 92nd Annual Meeting (2013), paper reference 13-4647

Mohamed Gomaa Mohamed and Nicolas Saunier

Abstract: Despite the rise in interest for surrogate safety analysis, little work has been done to understand and test the impact of the methods for motion prediction which are needed to identify whether two road users are on a collision course and to compute many surrogate safety indicators such as the time to collision (TTC). The default, unjustified method used in much of the literature is prediction at constant velocity. In this paper, a generic framework is presented to predict road users' future positions depending on their current position and their choice of acceleration and direction. This results in the possibility of generating many predicted trajectories by sampling distributions of acceleration and direction. Three safety indicators, the TTC, an extended version of predicted post encroachment time pPET and a new indicator measuring the probability that the road users attempting evasive actions fail to avoid the collision P(UAE), are computed over all predicted trajectories. These methods and indicators are illustrated on four case studies of lateral road user interactions. The evidence suggests that the prediction method based on the use of a set of initial positions seems to be the most robust. The last contribution of this paper is to make all the data and code used for this paper available (the code as open source) to enable reproducibility and to start a collaborative effort to compare and improve the methods for surrogate safety analysis.

The code and this page has been moved to a Github repository.