TABLE 1 Summary of Existing Macro-Level Crash Frequency Studies Independent Variable Considered Methodological Unit of Analysis Spatial Unit Crash level Approach Traffic network Measures measures Exposure Accessibility and Road environment characteristics characteristics characteristics Socio-economic Noland and Standard Pedestrian injury crashes, Quddus Negative binomial statistical --- Yes Yes Yes Yes --- Bicyclist Slight injury (2004a) regions crashes Wier et al. Ordinary least square Pedestrian crash Census tract Injury crashes --- Yes Yes Yes Yes Yes (2009) regression Wei et al. Traffic Negative binomial Bicycle crashes Yes Yes Yes Yes Yes Yes (2013) analysis zone Negative binomial, Total pedestrian Siddiqui et al. Pedestrian and Traffic Bayesian log-normal crashes, Total --- Yes Yes Yes Yes Yes (2012) bicycle crash analysis zone model bicycle crashes Cho et al. Pedestrian and Community Path analysis crashes Yes Yes --- --- Yes Yes (2009) bicycle analysis zones Bayesian spatial and Young (Age 0-25) MacNab Local health ecological regression pedestrian and Injury crashes --- Yes --- Yes Yes Yes (2004) areas model Bicyclist crash Random Effect Fatal crashes, Noland (2003) Crash State --- Yes Yes Yes Yes --- negative binomial Injury crashes Noland and crashes, Fatal Quddus Negative binomial County --- Yes Yes Yes Yes --- crashes (2004a) Total crashes, Karlaftis et al. Cluster analysis, Aged driver crash Urban crashes, --- Yes --- Yes Yes --- (1998) Negative binomial Rural crashes et al. Total crashes, Bayesian spatial model Crash County --- Yes Yes Yes Yes --- (2010) Severe crashes Amoros et al. Total crashes, Negative binomial Crash County --- --- --- --- Yes --- (2003) Fatal crashes Ukkusuri et Random parameter Pedestrian crash Census tract crashes Yes Yes Yes --- Yes Yes al. (2011) negative binomial
TABLE 1 Summary of Existing Macro-Level Crash Frequency Studies Methodological Approach Unit of Analysis Spatial Unit Crash level Independent Variable Considered Accessibility measures Exposure Measures characteristics Socio-economic characteristics Road network and Traffic characteristics environment Noland and Quddus (2004a) Negative binomial Pedestrian Bicyclist Standard statistical regions injury crashes, Slight injury crashes --- Yes Yes Yes Yes --- Wier et al. (2009) Ordinary least square regression Pedestrian crash Census tract Injury crashes --- Yes Yes Yes Yes Yes Wei et al. (2013) Negative binomial Bicycle Traffic analysis zone crashes Yes Yes Yes Yes Yes Yes Siddiqui et al. (2012) Negative binomial, Bayesian log-normal model Pedestrian and bicycle crash Traffic analysis zone Total pedestrian crashes, Total bicycle crashes --- Yes Yes Yes Yes Yes Cho et al. (2009) Path analysis Pedestrian and bicycle Community analysis zones crashes Yes Yes --- --- Yes Yes MacNab (2004) Bayesian spatial and ecological regression model Young (Age 0-25) pedestrian and Bicyclist crash Local health areas Injury crashes --- Yes --- Yes Yes Yes Noland (2003) Random Effect negative binomial Crash State Fatal crashes, Injury crashes --- Yes Yes Yes Yes --- Noland and Quddus (2004a) Negative binomial County crashes, Fatal crashes --- Yes Yes Yes Yes --- Karlaftis et al. (1998) Cluster analysis, Negative binomial Aged driver crash Total crashes, Urban crashes, Rural crashes --- Yes --- Yes Yes --- et al. (2010) Bayesian spatial model Crash County Total crashes, Severe crashes --- Yes Yes Yes Yes --- Amoros et al. (2003) Negative binomial Crash County Total crashes, Fatal crashes --- --- --- --- Yes --- Ukkusuri et al. (2011) Random parameter negative binomial Pedestrian crash Census tract crashes Yes Yes Yes --- Yes Yes
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