|Title:||Development of Safety Screening Tool for High Risk Rural Roads in South Dakota|
|Authors:||Xiao Qin and Adam Wellner|
|Publication Date:||Mar 2011|
|Keywords:||safety, rural transportation, transportation systems, geographic information systems|
|Type:||Research Report – MPC Publications|
Given the sparsely distributed crashes across various highway systems, this study designed an empirical Bayes (EB) based sliding window technique within a spatial context. By examining roadway safety spatially, the safety analysts are able to account for high-risk locations completely within longer predefined segments and locations, which may include multiple predefined roadway segments. Removing the dependence on predefined segmentation can also bring to the forefront safety issues previously ignored. The robustness of the EB method significantly improves the crash estimation accuracy. In conjunction with several different but complementary safety metrics, a complete view of rural highway safety performance can be presented.
To ease the use of such a new technique, the South Dakota GIS Highway Safety Review (GIS-HSR) Tools was developed, which provides a data-driven approach toward identifying high-risk locations.
Qin, Xiao, and Adam Wellner. Development of Safety Screening Tool for High Risk Rural Roads in South Dakota, MPC-11-231. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2011.