Empirical assessment of the impact of highway design exceptions on the frequency and severity of vehicle accidents

Abstract

Compliance to standardized highway design criteria is considered essential to ensure roadway safety. However, for a variety of reasons, situations arise where exceptions to standard-design criteria are requested and accepted after review. This research explores the impact that such design exceptions have on the frequency and severity of highway accidents in Indiana. Data on accidents at carefully selected roadway sites with and without design exceptions are used to estimate appropriate statistical models of the frequency and severity of accidents at these sites using recent statistical advances with mixing distributions. The results of the modeling process show that presence of approved design exceptions has not had a statistically significant effect on the average frequency or severity of accidents - suggesting that current procedures for granting design exceptions have been sufficiently rigorous to avoid adverse safety impacts. However, the findings do suggest that the process that determines the frequency of accidents does vary between roadway sites with design exceptions and those without.

A Study of Sex Differences on Road Crash Severity

“…With regard to the type of roads, this study determined that accidents which occur at intersections tend to be more severe for both males and females which was consistent with findings of other studies (38,46,58,71). This factor increases the probability of injuries/fatalities among males and females groups, by 84.0% and 1.2%, respectively.…”

Hierarchical Bayesian random intercept model-based cross-level interaction decomposition for truck driver injury severity investigations

“…Random parameters models and finite-mixture (latent-class) models are two major types of models that are widely used in traffic safety analysis to address unobserved heterogeneity in crash data resulting from roadway features, driver demographic and behavior information, spatial and temporal variations, etc. (Anastasopoulos et al, 2012a,b;Chen and Tarko, 2014;Flask et al, 2014;Haleem and Gan, 2013;Islam and Mannering, 2006;Kim et al, 2013;Malyshkina and Mannering, 2010;Xiong and Mannering, 2013). In this study, the cross-level interaction effects between crash-level and vehicle level variables are generally not observed in crash data, but may have significant influence on driver injury severity outcomes in traffic crashes.…”

“…Unobserved heterogeneity is defined as the unobservable factors or data that affect crash potential or severity, and they may generate biased estimations if their correlations with observed variables are not accounted for in model design (Mannering and Bhat, 2014). The unobserved heterogeneity could be attributed from different types of factors, including roadways (Flask et al, 2014;Haleem and Gan, 2013;Malyshkina and Mannering, 2010;Morgan and Mannering, 2011), drivers' demographic and behavior characteristics (Haleem and Gan, 2013;Islam and Mannering, 2006;Kim et al, 2013Kim et al, , 2010Morgan and Mannering, 2011;Ulfarsson and Mannering, 2004), spatial and temporal variations Ukkusuri et al, 2011;Xiong et al, 2014;Xu and Huang, 2015), etc. For instance, Kim et al (2010) evaluate pedestrian injury severity patterns in pedestrian-vehicle crashes considering the unobserved pedestrian heterogeneity regarding health, strength and behavior.…”

Analyzing pedestrian crash injury severity at signalized and non-signalized locations

“…This model is characterized by a random error term that allows the parameter estimates to randomly vary across the crash observations for more reliable parameter estimates (McFadden and Train, 2000;Train, 2009;Malyshkina and Mannering, 2010).…”