A Comprehensive joint econometric model of motor vehicle crashes arising from multiple sources of risk

This study first postulates, and then demonstrates empirically, that crash occurrence may be more complex than can be adequately captured by a single equation regression model. The total crash count recorded at a transport network location (e.g. road segment) may arise from multiple simultaneous and inter-dependent sources of risk, rather than one. Each of these sources may uniquely contribute to the total observed crash count. For instance, a site’s crash occurrence may be dominated by contributions from driver behaviour issues (e.g. speeding, impaired driving), while another site’s crashes might arise predominately from design and operational deficiencies such as deteriorating pavements and worn lane markings. Stated succinctly, this research hypothesises that the unobserved heterogeneity in the accumulation of motor vehicle crashes at transport network locations arises because multiple sources of risk, not one, better captures complexity in the crash occurrence process. A stochastic multiple risk source methodological approach is developed to correspond with and empirically test this hypothesis. A joint econometric model with random parameters and instrumental variables demonstrates the applicability of the proposed theory and the corresponding methodological approach. The proposed model assumes that complexity of crash occurrence is well approximated using three sources of risk comprised of engineering, unobserved spatial, and driver behavioural factors. It is empiric...
Source: Analytic Methods in Accident Research - Category: Accident Prevention Source Type: research