Montana is using research in an effort to beef up its truck safety and weight enforcement efforts and that could mean trucks with Canadian registration plates will be targeted.

That’s because a seven-year study of truck collisions in Montana, reported at this year’s Transportation Research Board in Washington, DC, found that trucks with Canadian registration plates have a higher risk of a severe collision than other trucks. The researchers who conducted the study aren’t quite sure why this is the case but speculate that: “An increased predicted crash severity for Canadian-based carriers may be due to a difference in trucking regulations between Canada and the United States; safety regulation, enforcement, vehicle size and weight limits and driver qualification requirements may vary enough to explain this noted difference in crash severity.” They go on to speculate, “a second explanation for this finding [that Canadian trucks have a greater chance of severe collisions] may relate to operational differences related to posted speeds, roadway design standards, etc.”

Jodi Carson, professor of civil engineering at Montana State University in Bozeman and one of the researchers, says that Montana Department of Transport has not yet implemented the results of the work. “Right now, Montana DoT has shifted focus to a second study that looked at using WIM [weigh-in-motion] scales to target weight enforcement more effectively.”

This second study was also reported at the Transportation Research Board meeting. In this case, two of the people working on the study were Montana DoT employees. That may explain the greater interest in the findings, although more likely it’s because the DoT spends millions every year on pavements and wants to protect this investment.

But the results of the first study are not going to be ignored. In the long run, this study of trucks with a higher than average risk of severe collisions will have a more profound influence on enforcement than the WIM study. Two major enforcement tools used in the U.S. currently are the Inspection Selection System (ISS) and SafeStat. ISS helps on-road enforcement officers decide which trucks to select for inspections. It does this when the officer taps into a central database that keeps track of things like out-of-service rates for particular carriers. If a carrier has a high OOS rate, its trucks are sure to be selected. SafeStat is a complicated mathematical process that takes into account a carrier’s history of collisions, violations and government audits of carrier safety-management practices. It tells federal inspectors which carriers represent the greatest risk to highway safety and, hence, which carriers to target for an audit (“Compliance Review” as they are called in the U.S.).

While Canadian provinces don’t have enforcement tools equivalent to ISS, the safety-rating systems in a few provinces are similar to SafeStat in the sense they tell the enforcement agencies who to target for an audit.

Evaluations of both ISS and SafeStat have shown they are effective in helping enforcement officers target their efforts where they do the most good. But both tools suffer from a common problem: they rely on a past history of information on carriers. And there are a lot of trucks out there on the road that don’t have a “history” at least in terms of government databanks. If you’ve never had a truck inspected, if you haven’t had a collision in quite a few years, if your drivers have fairly clean records and if no government auditor has knocked on your door, chances are that your record is a blank or almost blank sheet. (The vast majority of trucks in Canada are in one and two-truck fleets that operate locally; enforcement agencies have little information about the carriers operating these trucks.)

So what both research efforts with which Carson was involved attempt to do is develop predictive models of how enforcement efforts should be targeted. By figuring this out, enforcement agencies can be a lot more efficient than they are by just selecting trucks or carriers randomly.

In the first study, the one that examined all 6,524 commercial vehicle collisions in Montana between 1993 and 1999, Carson and her research team used elaborate statistical procedures to figure out what characteristics are most important in predicting trucks likely to have a higher risk of a severe collision than other trucks. Cutting through the complicated math, and the not inconsiderable problems they had in getting information, the three major findings are: two-axle straight trucks, trucks with Canadian registration plates and trucks operated by carriers that employ a large number of trip-lease drivers all have a greater chance of severe collisions than other trucks.

Montana enforcement officers can easily use the first two findings: the implications are that they should take a closer look at two-axle straight trucks and Canadian trucks. The third finding is more difficult to use because there is no easy way for an enforcement officer to identify trucks being driven by trip-lease drivers. But, whether these research findings are readily useable or not, as Carson points out, Montana has not yet decided to use them.

Her second study, conducted jointly with Jerry Stephens at Montana State University, also had data problems in the sense that data from WIM scales are not easy to obtain and analyze. But, putting these problems aside, the purpose and the results of the study are easy enough to understand. Based on information from a large number of WIM sites scattered throughout the state of Montana, the research team figured out a pattern for overweight trucks. The “pattern” classified the roads most likely to have overweight trucks, the months when most of these overweights occurred, the direction of travel of the overweight trucks, and the type of truck (number of axles). Armed with this information, Montana DoT dispatched its mobile enforcement crews to the selected areas in the 12-month period May 2001 to April 2002. The results show pretty clearly that this targeted approach to enforcement pays off. In the year preceding the targeted effort, 8.5 per cent of all trucks passing over a WIM scale were overweight and the average overweight was 7,100 pounds. In the year of targeted enforcement, only 6.8 per cent of trucks were overweight and the average infraction was only 5,300 pounds.

While the one-year pilot study using WIM data was successful, it still is not clear how Montana will continue with this type of targeted approach to weight enforcement. “They are considering their options,” says Carson.