Severity Distribution Functions for Freeway Segments
To date, the focus of modeling efforts for freeway safety has been on developing safety prediction functions and crash modification factors, with only limited consideration for crash severity distributions. As a result, relatively little is known about the safety effects of design elements such as l...
Saved in:
Published in | Transportation research record Vol. 2398; no. 1; pp. 19 - 27 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Los Angeles, CA
SAGE Publications
01.01.2013
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | To date, the focus of modeling efforts for freeway safety has been on developing safety prediction functions and crash modification factors, with only limited consideration for crash severity distributions. As a result, relatively little is known about the safety effects of design elements such as lane width, rumble strips, and longitudinal barriers on crash severity. In some cases, countermeasures are implemented with the intent to reduce fatal crashes, but the effect of these treatments on less severe crashes is not well understood. Research was conducted to develop severity distribution functions (SDFs) to predict the proportion of crashes in each severity category as a function of roadway geometric design elements and traffic control features. The SDFs were calibrated with freeway segment data from California, Maine, and Washington State. The findings from this research show that barrier presence, increased traffic volume, increased lane width, and urban area type reduce the proportion of high-severity crashes. At the same time, the presence of rumble strips and horizontal curvature increases the proportion of high-severity crashes. These SDFs can be applied along with safety prediction functions and crash modification factors to obtain more precise estimates of the safety effects of design decisions. |
---|---|
Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISBN: | 9780309294881 0309294886 |
ISSN: | 0361-1981 2169-4052 |
DOI: | 10.3141/2398-03 |