Ordinal Discrete Choice Analyses of Wisconsin Cross-Median Crash Severities

Abstract

A cross-median crash (CMC), in which a vehicle crosses the median, is one of the most severe crashes because of the risk of colliding with an opposing vehicle. Ordinal discrete choice modeling efforts for investigating the nexus between the underlying severity propensity and miscellaneous roadway-safety-related factors for single- and multivehicle CMCs that occurred from 2001 to 2007 in Wisconsin are described. Ordinal logit (ORL) and probit (ORP) models were employed for the severity analyses. For multivehicle CMCs, the final ORP model found that road condition has a significant effect on severity. Adverse road conditions enhance the likelihood of a more severe consequence if a CMC occurs. Winter precipitation negatively affects CMC severity, and logically Wisconsin's geographical location plays a significant role. The final ORL model found that alcohol and drug use incurs more severe consequences when a CMC occurs. Both models found that more severe injuries occur on roadways posted with higher speed limits. The similarity and dissimilarity in findings by both models imply that it is necessary for safety researchers to apply distinct statistical methods when pursuing a comprehensive understanding of a study topic. The final ORP model for single-vehicle CMCs shows that alcohol and drug use, lane curvature, and unfriendly lighting conditions exacerbate the severity tendency if a CMC happens. A dry road surface is found to incur more severe consequences; this result implies that more severe single-vehicle CMCs are closely related to maintaining overly high speeds. All ORL regression models for single-vehicle CMCs were found statistically invalid. Median width and average daily traffic were found insignificant for both multivehicle and single-vehicle CMCs.

Evaluating Factors Influencing the Severity of Three-Plus Multiple-Vehicle Crashes using Real-Time Traffic Data

“…Poor nighttime lighting conditions lead to reduced visibility on the roadway. Given the high operating speeds on freeways, poor lighting could result in longer perception to reaction time, limiting the drivers’ collision avoidance ability and increasing the risk of severe multiple-vehicle crashes ( 8 ).…”

“…However, the definition of a multiple-vehicle crash has not been consistent across different studies. While most previous studies (3)(4)(5)(6)(8)(9)(10) have defined multiple-vehicle crashes as those that involve two or more vehicles, some of the previous studies have classified crashes involving three or more vehicles as multiplevehicle crashes (11)(12)(13). On the other hand, another study, conducted on I-94 in Michigan (14), defined multiple-vehicle crashes as those involving five or more vehicles.…”

“…First, the definition of a multiple-vehicle crash has not been consistent across different studies. While most previous studies have defined multiple-vehicle crashes as those that involve two or more vehicles (3)(4)(5)(6)(8)(9)(10), some have classified crashes involving three or more vehicles as multiple-vehicle crashes (11)(12)(13). Multiple-vehicle crashes involving three or more vehicles have to be analyzed separately since factors contributing to these crashes are different from the factors contributing to two-vehicle crashes.…”