Principal Investigator(s):
Michael Wade, Former Professor and Director, Kinesiology
Project summary:
In this study, a database was constructed based on crash data from Martin County, Minnesota. This database included information on crash characteristics and locations, as well as information on signage, weather, and other factors. A descriptive analysis of the data to determine the general frequency rates of accidents was first carried out on the database. A second analysis identified dangerous roadways. Counting the number of crashes on specific roadways and dividing this number by the average ADT on a roadway generated crash rates for those roadways, including county state aid highways (CSAHs), county highways, and township roads. Roadways with the highest five percent were considered significantly dangerous. Crash rates were generated for specific locations. This method identified 15 dangerous locations, nine on CSAHs, three on county highways, and two on township roads. There were only 235 cases where no improper driving was indicated. The remaining 1,554 cases suggested that driver error was the major cause. The most likely factor in causing an accident on a highway with an ADT of less than 400 is a crash involving an animal. Road design factors such as number of lanes and the speed limit seem to be the factors related to these accidents.
Project details:
- Project number: 2002008
- Start date: 09/2001
- Project status: Completed
- Research area: Transportation Safety and Traffic Flow
- Topics:
Data and modeling, Safety