Abstract:
This research examines weather and road conditions relation to traffic crashes on Bureau
of Land Management (BLM) and U.S. Forest Service (FS) land in three states:
Idaho, Oregon and California. Crash data for Idaho and Oregon were supplied by the
state transportation departments while the California data were obtained from the Federal
Highway Administration’s Highway Safety Administration (FHWA) .
The results are mixed, probably because of the different methods of data collection: Idaho
seems to have particularly severe crashes during bad weather on these public lands when
all roads on the public lands are compared with other rural Idaho state and federal
highways. Oregon's comparable weather-related crashes do not show such severe crashes
in poor weather or road conditions, but Oregon on these federal lands crashes in good
weather are very severe as are the “non-weather” crashes on lightly traveled rural
highways in the State.
California’s FHWA Highway Safety Information System data offered a much more
objective test of crashes on the public domain, based on federal and state roadways
versus private, rural land roads during "weather" and “non-weather” conditions. In the
aggregate, weather-related crash differences appear non-significant for California’s
public and private lands. The salient finding in California is that on average, "nonweather"
crashes on BLM and USFS land are significantly more severe than on
comparable rural roadways in the State. Using FHWA projections of crash costs, the
BLM and FS crashes produce about 30 percent greater losses.) The latter finding may be
a result of more speed with good weather conditions, adverse roadside environments and
the increased time required for emergency response to public land crashes.
Future deployments of Intelligent Weather technology for rural California roadways
could benefit from the database assembled for this research, especially the weatherrelated
crash analysis for roadway/county/federal or rural land contingencies in Appendix
A. Dramatic differences in local crash costs were observed in the limited fine-scale
analysis done in this study. Providing weather and location crash cost in a Geographical
Information System would further assist management and policy-makers in efforts to
reduce rural crash risk.
