An Ohio State University statistics expert used the powerful machines of the Ohio Supercomputer Center to design a program that identifies traffic accident hotspots on Ohio’s roadways. Christopher Holloman, Ph.D., produced color-coded computer models to tell state troopers where fatal and injury accidents, especially those from speeding and drunk driving, are most likely to occur.
“We started out evaluating a couple of hundred miles worth of roadway in five major cities in Ohio,” said Dr. Holloman. “The Highway Patrol found the information I provided extremely helpful, so it asked me to include all of Ohio.”
“Crashes are going to occur — it’s a matter of when and where,” said Lt. Anthony Bradshaw of the Ohio State Highway Patrol. “If we’re able to predict a crash, then we’re better able to prevent it.”
“We already had the code, we just needed a more powerful computer that would fit such a large model. We basically had two options — either go to OSC or start from scratch and rewrite the program.” –Christopher Holloman, Ph.D.
Dr. Holloman’s program analyzed every traffic accident in the Highway Patrol’s databases that occurred on Ohio highways over a five-year period. Predictions were made under two types of road conditions: good or bad. Also, each roadway had predictions for each of five different categories of days: Monday through Thursday, Friday,
Saturday and Sunday, the day before a long weekend, and holidays. In addition, Dr. Holloman’s program breaks out results by factors such as age group, alcohol status, speed and class of vehicle.
The Ohio State Highway Patrol used the program to help position its cruisers during major holidays. The research team also combined the program with Google Earth, which Dr. Holloman said makes the tool even easier to use.
Project lead: Christopher Holloman, Ph.D., The Ohio State University
Research title: Predicting crashes and crash causes on Ohio roadways
Funding source: Statistical Consulting Service at The Ohio State University Department of Statistics