Traffic signals are often implemented to provide for efficient movement and to improve traffic safety. Nevertheless, severe crashes still occur at signalized intersections. This study aims to improve understanding of signalized intersection safety by identifying crash types, locations, and factors associated with signalized intersections. For this purpose, 1,295 police-reported crashes at 87 signalized intersections were analyzed on the basis of detailed crash descriptions, that is, crash data and collision diagrams. The information from the collision diagrams was used to distinguish six crash types and to create a crash location typology to divide the signalized intersection into 13 detailed typical segments. Logistic regression modeling techniques were used to identify relations between crash types, their crash location on certain signalized intersection segments, the crash severity, and the different features that affected crash occurrence. Four dominant crash types were identified: rear-end, side (i.e., left-turn plus right-angle), head-on, and vulnerable road user crashes. The results of the logistic regression models showed that the location of these crash types was related to specific signalized intersection segments. The results also revealed important signalized intersection features that affected the crash occurrence. As a result, connections between certain signalized intersection crash types, their crash location, and signalized intersection design characteristics were found. The combination of intersection features with detailed signalized intersection segments provided valuable insights into the nature of signalized intersection crashes and the safety impact of signalized intersection design.


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    Title :

    Crash Patterns at Signalized Intersections


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2015-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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