SIMULATED PEAK HOUR CONFLICT BASED CRASH PREDICTION MODELS: ANALYSIS AND EVALUATION;

摘要

Road traffic crashes are one of the major causes of deaths worldwide. A safety prediction model is designed to estimate the safety of a road entity and to identify the hazardous locations. In most cases these models link traffic volumes to crashes. A major problem with such models is that crashes are rare events and that crash statistics do not take into account everything that may have contributed to the crashes. The use of traffic conflicts to measure safety can overcome these problems as conflicts occur more frequently than crashes and can be easily recorded using micro simulation models eliminating the need of waiting for substantial number of crashes to occur in order to develop a good model. For the purpose of this paper, simulated peak hour conflict based crash prediction models are developed for 113 Toronto signalized intersections and their predictive capabilities are evaluated. The effects of a hypothetical left turn treatment on crashes and conflicts are also explored and compared to a different study conducted for a group of similar Toronto intersections that actually underwent a change from permissive to protected-permissive left turn phasing. The results show that the conflict based crash prediction models provide a good alternative to the volume based models and that they can be used to evaluate the safety of a road entity comparably to volume-based models.