01153444

Component

https://doi.org/10.3141/2148-10

http://scholar.google.com...+Lee&publication_year=2010

Safety interventions (e.g., median barriers, photo enforcement) and road features (e.g., median type and width) can influence crash severity, crash frequency, or both. Both dimensions—crash frequency and crash severity—are needed to obtain a full accounting of road safety. Extensive literature and common sense both dictate that crashes are not created equal, with fatalities costing society more than 1,000 times the cost of property damage crashes on average. Despite this glaring disparity, the profession has not unanimously embraced or successfully defended a nonarbitrary severity weighting approach for analyzing safety data and conducting safety analyses. It is argued here that the two dimensions (frequency and severity) are made available by intelligently and reliably weighting crash frequencies and converting all crashes to property-damage-only crash equivalents (PDOEs) by using comprehensive societal unit crash costs. This approach is analogous to calculating axle load equivalents in the prediction of pavement damage: for instance, a 40,000-lb truck causes 4,025 times more stress than does a 4,000-lb car and so simply counting axles is not sufficient. Calculating PDOEs using unit crash costs is the most defensible and nonarbitrary weighting scheme, allows for the simple incorporation of severity and frequency, and leads to crash models that are sensitive to factors that affect crash severity. Moreover, using PDOEs diminishes the errors introduced by underreporting of less severe crashes—an added benefit of the PDOE analysis approach. The method is illustrated with rural road segment data from South Korea (which in practice would develop PDOEs with Korean crash cost data).

01164464

10-1867

English

pp 83-92

2010

Transportation Research Record: Journal of the Transportation Research Board

9780309142793

Print

Maps (1) ; References (25) ; Tables (5)

Case studies; Costs; Crash rates; Crash severity; Rural highways; Traffic crashes

Accident costs; Property damage; Property-damage-only crash equivalents

South Korea

Highways; Safety and Human Factors; I81: Accident Statistics

TRIS, TRB, ATRI

Jan 25 2010 10:52AM

• 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
• Ordinal Discrete Choice Analyses of Wisconsin Cross-Median Crash Severities
• 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