The current study contributes to safety literature both methodologically and empirically by developing a macro-level multivariate copula-based crash frequency model for crash counts. The multivariate model accommodates for the impact of observed and unobserved effects on zonal level crash counts of different road user groups including car, light truck, van, other motorized vehicle (including truck, bus and other vehicles) and non-motorist (including pedestrian and bicyclist). The proposed model is estimated using Statewide Traffic Analysis Zone (STAZ) level road traffic crash data for the state of Florida. A host of variable groups including land-use characteristics, roadway attributes, traffic characteristics, socioeconomic characteristics and demographic characteristics are considered. The model estimation results illustrate the applicability of the proposed framework for multivariate crash counts. Model estimation results are further augmented by evaluation of predictive performance and policy analysis.

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