Identification of Intersections' Crash Profiles/Patterns
Mohamed Abdel‐Aty, Chris Lee, Xuesong Wang, Piyush Nawathe, Joanne Keller, Smitha Kowdla, Hari Prasad
Abstract
Mohamed Abdel‐Aty, Chris Lee, Xuesong Wang, Piyush Nawathe, Joanne Keller, Smitha Kowdla, Hari Prasad
Abstract
The approach proposed in this research is to identify the crash profiles for the major intersection types based on geometric/configuration and traffic volume factors combination. In other words, there is a need to first identify the different intersection configurations that are present in Florida; second, associate these configurations with the different traffic volumes on these intersections; and third, analyze these intersections to identify the crash patterns for each type of intersection. The most extensive data collection effort for signalized intersections in Florida has been conducted as part of this project. Geometric, traffic and crash data were collected for 1562 signalized intersections. Crash profiles for 45 different types of intersections based on configuration and traffic volume have been developed. The 45 intersection crash profiles will be very useful to engineers and would serve as a crash profile manual that could be used as reference values that would assist in identifying intersections with specific problems, e.g., high number of fatal crashes or high number of angle crashes. A practical approach was developed to identify the expected number of crashes based on the total number of lanes which is a surrogate measure for the size of the intersection and volume. This method is simple to apply and could be used in identifying the expected number of crashes by type given that the number of lanes is known.
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The approach proposed in this research is to identify the crash profiles for the major intersection types based on geometric/configuration and traffic volume factors combination. In other words, there is a need to first identify the different intersection configurations that are present in Florida; second, associate these configurations with the different traffic volumes on these intersections; and third, analyze these intersections to identify the crash patterns for each type of intersection. The most extensive data collection effort for signalized intersections in Florida has been conducted as part of this project. Geometric, traffic and crash data were collected for 1562 signalized intersections. Crash profiles for 45 different types of intersections based on configuration and traffic volume have been developed. The 45 intersection crash profiles will be very useful to engineers and would serve as a crash profile manual that could be used as reference values that would assist in identifying intersections with specific problems, e.g., high number of fatal crashes or high number of angle crashes. A practical approach was developed to identify the expected number of crashes based on the total number of lanes which is a surrogate measure for the size of the intersection and volume. This method is simple to apply and could be used in identifying the expected number of crashes by type given that the number of lanes is known.
Key concepts: Intersection (aeronautics), Crash, Identification (biology), Traffic volume, Transport engineering, Geometric design, Computer science, Data collection