STATISTICAL ANALYSIS OF ACCIDENT SEVERITY ON RURAL FREEWAYS

The growing concern about the possible safety-related impacts of Intelligent Transportation Systems (ITS) has focused attention on the need to develop new statistical approaches to predict accident severity. This paper presents a nested logit formulation as a means for determining accident severity given that an accident has occurred. Four levels of severity are considered: 1) property damage only; 2) possible injury; 3) evident injury; and, 4) disabling injury or fatality. Using a 5-year accident data from a 61 km section of rural interstate in Washington State, we estimated a nested logit model of accident severity. The estimation results provide valuable evidence on the effect that environmental conditions, highway design, accident type, driver characteristics and vehicle attributes have on accident severity. Our findings show that the nested logit formulation is a promising approach to evaluate the impacts that ITS or other safety-related countermeasures may have on accident severities.

Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
Corporate Authors:
Elsevier

The Boulevard, Langford Lane
Kidlington, Oxford United Kingdom OX5 1GB
Authors:
- Shankar, V
- Mannering, F
- Barfield, W
Publication Date: 1996-5

Language

English

Media Info

Features: Figures; References; Tables;
Pagination: p. 391-401
Serial:
- Accident Analysis & Prevention
- Volume: 28
- Issue Number: 3
- Publisher: Elsevier
- ISSN: 0001-4575
- Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

TRT Terms: Crash severity; Intelligent transportation systems; Logits; Rural highways; Statistical analysis
Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

Accession Number: 00723729
Record Type: Publication
Report/Paper Numbers: HS-042 305
Files: HSL, TRIS
Created Date: Jul 30 1996 12:00AM