Unobserved heterogeneity in ramp crashes due to alignment, interchange geometry and truck volume: Insights from a random parameter model

Abstract

This paper presents a negative binomial random parameter model with heterogeneity in means and variance to capture the effect of heterogeneous effect of ramp type, alignment, truck volume and interchange geometry and on freeway ramp crash frequency. Two years (2018–2019) of crash data on freeway ramps in Washington State were analyzed. Model estimation results show ramp type (directional, semi-directional and loop), alignment, and traffic characteristics significantly impact ramp crash frequency. The northwest loop ramp indicator has a random parameter. The minimum horizontal curve radius and the total number of vertical curves on the ramp appear to be statistically significant sources of heterogeneity in the mean of this parameter. Heterogeneity in the mean of the random effect is influenced by single truck percentage and the low AADT indicator (<=1,340 vehicles per day).

Heterogeneity in the variance of the northwest loop ramp random parameter appears to be associated with the southwest loop ramp indicator indicating unobserved effects due to same-side loop geometries.

Directional ramp indicators (on- and off-ramps) and interactions involving speed limit, AADT and horizontal curve radius are statistically significant (as fixed parameters) in their impact on ramp crash frequency.

Total centerline mile footprint of all ramps at the interchange is a continuous fixed parameter effect. Ramp-specific lengths (longer than 0.335 miles) also appear to be statistically significant. The findings in this study suggest that ramp and interchange design need to account for a holistic integration of spatial footprint, type of ramp and alignment factors, in addition to traffic flow variables.