74: An Integrated Multivariate Econometric Modeling Framework for Risky Driving Behaviour Related Crashe

Thomas M. Menino Convention & Exhibition Center 

Rapid advancements in crash modeling have yet to fully integrate multiple behavior-driven crash types and their severity outcomes within a single, scalable framework, specially in a way that captures the sequential nature of these behaviors where one risky action may amplify another. This study proposed an integrated multivariate econometric framework to jointly model crash frequency and severity outcomes for three major behaviorally driven crash types: alcohol-related, distraction-related, and aggressive-driving-related crashes. Specifically, using Oregon's 2022 census block group-level crash data, we propose an Integrated Multivariate Negative Binomial – Generalized Ordered Probit Fractional Split (IMNB–GOPFS) model to analyze these dimensions simultaneously while accounting for the sequential nature of the behavioral crash types. A comparison exercise in terms of model fit and predictive performance reveals the superior performance of the proposed framework over traditional non-integrated approaches, thus highlighting the existence and importance of capturing such interdependencies among behaviorally driven crashes.

Behavioral Crash

Crash severity

Integrated Multivariate Model

Sequential Interdependencies

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Transportation Statistics Interest Group