John Baxter is senior associate editor of Commercial Carrier Journal. E-mail
A crash analyst for the federal government assured the truck safety community recently that while a study of truck crash causation may be long in coming, the insights it delivers will make the effort worthwhile. “We will find some interesting and surprising things,” predicted Ralph Craft, Ph.D., a crash data analyst in the analysis division of the Federal Motor Carrier Safety Administration, in a presentation at the Commercial Vehicle Safety Alliance Fall Workshop in Boston. Ultimately, the study could lead to a new approach toward enforcement of truck safety rules.
Most of the data is in, but the final results and conclusions won’t be available for more than a year. Data collection is only one element of the overall task. Once compiled, the data must be crunched in a lengthy and tedious process.
Craft offered some insights into the study’s methodology, which lies at the heart of why the study is so complex. He outlined the “crash coding” process, which will enable researchers to narrow down and categorize the causes of crashes. Crash causes may consist of any of as many as 1,000 elements, all of which will be included in the data.
Crashes occur, Craft says, because of a critical event that makes a crash inevitable. This event will be “coded” or categorized without regard to who had the right of way. Rather, coding is based entirely on the physical movements of the vehicles involved. Critical events result from one or more critical reasons.
Critical reasons include driver error or other driver factors, such as alcohol consumption, inattention or fatigue; a significant vehicle problem, such as overheated brakes; or the environment, such as poor road design or snow. In the study, critical reasons are linked to each vehicle involved.
Sounds simple, right? Hardly. Determining the presence of a critical reason isn’t always easy. “Fatigue is a tough issue,” Craft says. “The problem is that even a fatigued driver will be fully alert after a crash.” Data will be gathered on sleep for every driver for seven days before the crash. If the driver has been moonlighting in addition to driving or running hot loads without stopping to rest, those facts will be obvious and will be factored into the data. All data will be gathered on an 11-page form for each crash.
How will the researchers make sense of all the data? Consider, for example, crashes where the vehicle fails to round a curve and goes off the road. “If we study many crashes of that type, we can determine the relative importance of each of the factors,” Craft says. So researchers ultimately will divide the factor totals by totals for each type of crash. Then they will be able to see, for example, whether or not going off the road on a curve is more prevalent when the driver is unfamiliar with the road.
FMCSA is already seeing some trends in the data. Driver factors were much more predominant than all others were. For example, in a batch of single truck crash factors, there were five environmental factors, 13 roadway factors and 93 driver factors.
“In most cases, it’s obvious that the driver causes the accident,” Craft concludes. That’s not too surprising. But some critical reasons for driver error are a bit unexpected. For example, the driver being unfamiliar with the road is often a critical factor, Craft says. Another frequent contributor is a particular combination of drugs that are all perfectly legal.
“All this could have a profound impact on the allocation of enforcement resources,” Craft concludes. That is, of course, if federal and state governments truly apply the insights gleaned from this major effort and don’t just stick the truck crash causation study on a shelf.