Observational models based on reported crash history are the most common measures for identifying unsafe sites for priority intervention. Observational models are good for predicting higher-severity crashes but ignore higher-risk vehicle interactions (e.g., near misses) that failed to result in crashes that are reported in historical data. Proponents of microscopic simulation models argue that failure to recognize these higher-risk interactions can significantly understate the safety problem at a given site and lead to misallocation of scarce treatment funds. This paper takes the position that a complete understanding of the safety problem at a given site can emerge only if both crash potential and traffic conflicts are taken into account. A priority-ranking model that integrates estimates from observational crash prediction models into an analysis of traffic conflicts is presented. Traffic conflicts were based on simulated vehicle interactions and deceleration requirements for different traffic scenarios. The suitability of the approach for priority ranking of sites was assessed with six ranking approaches: crash frequency, empirical Bayes, potential for safety improvement, conflict frequency, conflict rate (sum and cross product of traffic volume), and integrated model. Priority ranking was evaluated with five test criteria: site consistency, method consistency, rank difference, total rank score, and sensitivity and specificity. These models were applied to a sample of 58 signalized intersections from Toronto, Ontario, Canada, for the period from 1999 to 2006. The integrated model was found to yield better results for the five evaluation criteria; this result suggests that the proposed approach has promise.


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    Titel :

    Integrating Observational and Traffic Simulation Models for Priority Ranking of Unsafe Intersections


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:


    Erscheinungsdatum :

    2012-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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