Real-Time Crash Prediction Model for the Application to Crash Prevention in Freeway Traffic

The likelihood of a crash or crash potential is significantly affected by short-term turbulence of traffic flow. For this reason, crash potential must be estimated on a real-time basis by monitoring the current traffic condition. In this regard, a probabilistic real-time crash prediction model relating crash potential to various traffic flow characteristics which lead to crash occurrence, or “crash precursors”, was developed. However, several assumptions were made in the development of this previous model that had not been clearly verified from either theoretical or empirical perspectives. Therefore, the objective of this study is to (1) suggest the rational methods by which crash precursors included in the model can be determined on the basis of experimental results; and (2) test the performance of the modified crash prediction model. The study found that crash precursors can be determined in an objective manner eliminating a characteristic of the previous model that the model results were dependent on analysts’ subjective categorization of crash precursors.