01153415

Component

https://doi.org/10.3141/2148-06

http://scholar.google.com...oyce&publication_year=2010

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.

01164464

10-1337

English

pp 47-58

2010

Transportation Research Record: Journal of the Transportation Research Board

9780309142793

Print

Figures (1) ; References (34) ; Tables (9)

Crash severity; Drunk driving; Frontal crashes; Highway curves; Highway safety; Logits; Medians; Multiple vehicle crashes; Probits; Single vehicle crashes; Snow; Speed; Traffic crashes; Visibility distance; Weather conditions

Cross median accidents; Discrete choice analysis; Road conditions

Wisconsin

Highways; Safety and Human Factors; I82: Accidents and Transport Infrastructure; I83: Accidents and the Human Factor

TRIS, TRB, ATRI

Jan 25 2010 10:36AM

• County-Level Crash Risk Analysis in Florida: Bayesian Spatial Modeling
• Crash Generation Models: Forecasting Crashes in Urban Areas
• Evaluating Trauma Management Performance in Europe: A Multiple-Layer Data Envelopment Analysis Model
• Exploratory Study of Mechanisms by Which Exposure Influences Accident Occurrence
• Fatality Risk of Intersection Crashes on Rural Undivided Highways in Alberta, Canada
• Full Bayes Approach to Before-and-After Safety Evaluation with Matched Comparisons: Case Study of Stop-Sign In-Fill Program
• Impact of Rumble Strips on Collision Reduction on Highways in British Columbia, Canada: Comprehensive Before-and-After Safety Study
• Implementation Road Map for In-Vehicle Safety Systems in China
• Logistic Models in Crash Severity Classification Based on Road Characteristics
• Model-Based Application of Abbreviated Injury Scale to Police-Reported Crash Injuries
• Property Damage Crash Equivalency Factors to Solve Crash Frequency–Severity Dilemma: Case Study on South Korean Rural Roads
• Rethinking Electronic Crash Data Collection Transmission Model: Conceptual Framework for Centralized Web-Based Crash Data Collection System
• Revisiting Variability of Dispersion Parameter of Safety Performance for Two-Lane Rural Roads