Published In
Transportation Research Record
Document Type
Pre-Print
Publication Date
10-9-2025
Subjects
Crash frequency, Crash severity, Vehicle mix variables, Pooled model, Unobserved effects
Abstract
The current approaches for crash frequency and severity prediction in the Highway Safety Manual (HSM) do not employ vehicle mix information. In this research effort, we build advanced alternatives to HSM methods while incorporating vehicle mix information. Two model systems—(a) multivariate Poisson-lognormal model and (b) negative binomial-ordered probit fractional split model—are estimated by incorporating vehicle mix variables. The developed model systems can also capture the influence of observed and unobserved heterogeneity of different independent variables including vehicle mix variables. We estimate the models for three facility types including Urban Arterial 4-Lane Divided segments, Rural 3-Leg STOP-Controlled and Rural 4-Leg STOP-Controlled intersections using data from four Highway Safety Information System (HSIS) states including California, Illinois, Minnesota, Washington, and three non-HSIS states including Connecticut, Florida, and Texas. For modeling crashes at each facility level, we adopt a pooled modeling technique that accounts for state-specific observed and unobserved heterogeneity in the pooled datasets. A comprehensive set of independent variables including traffic volume, vehicle mix indicators, roadway characteristics, and state-specific indicators are considered in the analysis. The model comparison exercise is conducted based on a comprehensive set of quantitative and qualitative metrics. The study highlights how different methodological approaches perform better for different facilities. The study findings also underscore how capturing the observed and unobserved impacts of vehicle mix variables improves model performance in crash frequency and severity dimensions across the facility types.
Rights
© Copyright the author(s) 2025
DOI
10.1177/03611981251362781
Persistent Identifier
https://archives.pdx.edu/ds/psu/44201
Citation Details
Published as: Pervaz, S., Joshi, M., Bhowmik, T., Parvez, D. A., Wang, K., Ivan, J. N., & Eluru, N. (2025). Incorporating the Influence of Vehicle Mix on Crash Frequency and Severity. Transportation Research Record: Journal of the Transportation Research Board.
Description
This is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published as: Incorporating the Influence of Vehicle Mix on Crash Frequency and Severity. Transportation Research Record: Journal of the Transportation Research Board.