2009Unpublished venueRequires access

Identification of Intersections' Crash Profiles/Patterns to Include Unsignalized Intersections and Expand the Safety/Traffic Database. Part I

Mohamed Abdel‐Aty, Patrick Kerr, Kirolos Haleem, Helai Huang

Open publisher page 1 citations

Abstract

This research identified the geometric and traffic-related factors affecting crashes at unsignalized intersections, and hence identified major types of unsignalized intersections to be studied. Once identified, crash profiles for those identified types of unsignalized intersections are developed. Those crash profiles act as a manual that could be used as reference values assisting in identifying intersections with specific problem(s) (e.g., high number of fatal crashes or high number of rear-end crashes, etc.). This will indeed help in developing countermeasures tailored to the specific problem(s). To accomplish the project objectives, an extensive data collection effort for collecting unsignalized intersections in Florida was conducted. A sample of 2500 unsignalized intersections distributed among six counties (Orange, Seminole, Brevard, Hillsborough, Leon and Miami-Dade) was collected. This sample mainly includes unsignalized intersections located on state roads, and to broaden the data collection procedure, all-way stop-controlled intersections (i.e., three and four-way stops) were collected as well. Sixty categories were identified based on the collected sample, and the annual crash profile tables for these categories were developed. Those categories nearly represent all possible types of existing unsignalized intersections.

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What this paper is about

This research identified the geometric and traffic-related factors affecting crashes at unsignalized intersections, and hence identified major types of unsignalized intersections to be studied. Once identified, crash profiles for those identified types of unsignalized intersections are developed. Those crash profiles act as a manual that could be used as reference values assisting in identifying intersections with specific problem(s) (e.g., high number of fatal crashes or high number of rear-end crashes, etc.). This will indeed help in developing countermeasures tailored to the specific problem(s). To accomplish the project objectives, an extensive data collection effort for collecting unsignalized intersections in Florida was conducted. A sample of 2500 unsignalized intersections distributed among six counties (Orange, Seminole, Brevard, Hillsborough, Leon and Miami-Dade) was collected. This sample mainly includes unsignalized intersections located on state roads, and to broaden the data collection procedure, all-way stop-controlled intersections (i.e., three and four-way stops) were collected as well. Sixty categories were identified based on the collected sample, and the annual crash profile tables for these categories were developed. Those categories nearly represent all possible types of existing unsignalized intersections.

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Available abstract

This research identified the geometric and traffic-related factors affecting crashes at unsignalized intersections, and hence identified major types of unsignalized intersections to be studied. Once identified, crash profiles for those identified types of unsignalized intersections are developed. Those crash profiles act as a manual that could be used as reference values assisting in identifying intersections with specific problem(s) (e.g., high number of fatal crashes or high number of rear-end crashes, etc.). This will indeed help in developing countermeasures tailored to the specific problem(s). To accomplish the project objectives, an extensive data collection effort for collecting unsignalized intersections in Florida was conducted. A sample of 2500 unsignalized intersections distributed among six counties (Orange, Seminole, Brevard, Hillsborough, Leon and Miami-Dade) was collected. This sample mainly includes unsignalized intersections located on state roads, and to broaden the data collection procedure, all-way stop-controlled intersections (i.e., three and four-way stops) were collected as well. Sixty categories were identified based on the collected sample, and the annual crash profile tables for these categories were developed. Those categories nearly represent all possible types of existing unsignalized intersections.

Key concepts: Crash, Transport engineering, Miami, Sample (material), Data collection, Identification (biology), Computer science, Geography

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Identification of Intersections' Crash Profiles/Patterns to Include Unsignalized Intersections and Expand the Safety/Traffic Database. Part I — Research Paper | ScholarLens