Abstract Title

Identifying Secondary Crashes and Analyzing Associated Factors

Authors' Class Standing

Nadia Correa, Senior Yuan Tian, Senior

Lead Presenter's Name

Nadia Correa

Faculty Mentor Name

Dr. Hongyun Chen

Abstract

Traffic safety and congestion are the two major challenges facing today’s highway systems. According to the Federal Highway Administration (FHWA) traffic incidents account for almost 60% of the delay which has notable impact on mobility and safety of urban highways. The main purpose of this study is to magnify the research of secondary crashes on the spatial-temporal boundary to a more microscopic level in order to identify prone spatial locations, temporal relationships, and patterns with primary incidents; in addition this study aims to characterize secondary crashes and identify factors associated with highly prone crash locations. Crash data was obtained from Florida Department of Transportation (FDOT). Both static and dynamic methods are used in this study. The static method defines fixed values as spatial and temporal criteria, which are easy and convenient to process. The dynamic method uses spatial criteria varying with temporal criteria and tends to be more accurate when compared to static methods. The applications used in this study are Arc GIS, SPSS 19, Auto CAD and Matlab.

Location

Center for Faith & Spirituality

Start Date

9-4-2014 1:00 PM

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Apr 9th, 1:00 PM

Identifying Secondary Crashes and Analyzing Associated Factors

Center for Faith & Spirituality

Traffic safety and congestion are the two major challenges facing today’s highway systems. According to the Federal Highway Administration (FHWA) traffic incidents account for almost 60% of the delay which has notable impact on mobility and safety of urban highways. The main purpose of this study is to magnify the research of secondary crashes on the spatial-temporal boundary to a more microscopic level in order to identify prone spatial locations, temporal relationships, and patterns with primary incidents; in addition this study aims to characterize secondary crashes and identify factors associated with highly prone crash locations. Crash data was obtained from Florida Department of Transportation (FDOT). Both static and dynamic methods are used in this study. The static method defines fixed values as spatial and temporal criteria, which are easy and convenient to process. The dynamic method uses spatial criteria varying with temporal criteria and tends to be more accurate when compared to static methods. The applications used in this study are Arc GIS, SPSS 19, Auto CAD and Matlab.