Integrating Trip and Roadway Characteristics to Manage Safety in Traffic Analysis Zones
Mohamed Abdel‐Aty, Chowdhury Siddiqui, Helai Huang, Xuesong Wang
Abstract
Mohamed Abdel‐Aty, Chowdhury Siddiqui, Helai Huang, Xuesong Wang
Abstract
A transportation network is a conglomeration of road-traffic-environment modules and features multicategories of interdependent factors. This mix makes the management of safety in traffic analysis zones (TAZs) explicitly challenging. This study investigated the association between crash frequencies and various types of trip productions and attractions in combination with the road characteristics of 1,349 TAZs of four counties in the state of Florida. Crash safety management of these TAZs is emphasized through prioritizing them by examining the effects of trip and roadway factors on the aggregated crash frequencies. Models were developed separately for total crashes, severe crashes (fatal and severe injury crashes), total crashes during peak hours, and pedestrian- and bicycle-related crashes on the basis of various groups of estimators. It was found that the total crash model and the peak-hour crash model were best estimated by total trip productions and total trip attractions. The severe crash model was best fit by trip-related variables only, and the pedestrian- and bicycle-related crash model was best fit by road-related variables only. The results from this study pave the way for better safety management and the incorporation of safety measures in travel and network planning.
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A transportation network is a conglomeration of road-traffic-environment modules and features multicategories of interdependent factors. This mix makes the management of safety in traffic analysis zones (TAZs) explicitly challenging. This study investigated the association between crash frequencies and various types of trip productions and attractions in combination with the road characteristics of 1,349 TAZs of four counties in the state of Florida. Crash safety management of these TAZs is emphasized through prioritizing them by examining the effects of trip and roadway factors on the aggregated crash frequencies. Models were developed separately for total crashes, severe crashes (fatal and severe injury crashes), total crashes during peak hours, and pedestrian- and bicycle-related crashes on the basis of various groups of estimators. It was found that the total crash model and the peak-hour crash model were best estimated by total trip productions and total trip attractions. The severe crash model was best fit by trip-related variables only, and the pedestrian- and bicycle-related crash model was best fit by road-related variables only. The results from this study pave the way for better safety management and the incorporation of safety measures in travel and network planning.
Key concepts: Crash, Transport engineering, Pedestrian, Poison control, Engineering, Computer science, Environmental health, Programming language