Integrating Trip and Roadway Characteristics to Manage Safety in Traffic Analysis Zones

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.

Support vector machine in crash prediction at the level of traffic analysis zones: Assessing the spatial proximity effects

“…One of the main objectives of macro-level crash prediction analysis is to explain observed cross-sectional variations in safety using zone-level covariates at different spatial scales (e.g., states, counties, traffic analysis zones, and census wards) (Washington et al, 2006;Quddus 2008;. These macro-level CPMs may aid transportation agencies in more effectively incorporating safety consideration into transportation planning and management (Abdel-Aty et al, 2011;Huang et al, 2013;Xu and Huang, 2015).…”

Evaluating the road safety effects of a fuel cost increase measure by means of zonal crash prediction modeling

“…Hadayeghi et al 2010a, 2010b, Lovegrove 2005 or NOTs (e.g. Abdel-Aty et al 2011a, 2011b, Naderan and Shahi 2010 and NOCs per TAZ. The only exception was observed where VKT on motorways was negatively associated with "Car-Slowmode" crashes.…”

Application of Geographically Weighted Regression Technique in Spatial Analysis of Fatal and Injury Crashes

“…Reviewing the literature for different model forms showed that the following model has been widely used in different studies (Abdel-Aty et al, 2011;Hadayeghi, 2009;Lovegrove, 2005):…”

“…ZCPMs have been initially introduced by Levine et al based on Linear Regression models (Levine et al 1995a). However, the most common modeling framework for ZCPMs is the Generalized Linear Modeling (GLM) framework (Abdel-Aty et al, 2011;Aguero-Valverde and Jovanis, 2006;Hadayeghi et al, 2010Hadayeghi et al, , 2007Hadayeghi et al, , 2003; Khondakar et al, 2010;Lord and Mannering, 2010;Lovegrove andSayed, 2007, 2006;Lovegrove et al, 2010;Lovegrove and Litman, 2008;Naderan and Shahi, 2010;Pirdavani et al, 2013). Within a GLM framework, fixed coefficient estimates explain the association between the dependent variable and the explanatory variables.…”