Can Data Analysis Prevent Truck Accidents?

Truck and tractor-trailer accidents are the cause of many personal injury and wrongful death civil cases. Long-haul and over-the-road (OTR) trucking are vital to the economy of the United States, but they are also dangerous endeavors. Accidents involving big rigs occur everywhere in Georgia, from large metropolitan areas like Atlanta to small rural towns like Emerson in Bartow County. In 2007, the Federal Motor Carrier Safety Administration released its landmark Large Truck Crash Causation Study, which analyzed crash data statistics from 2001 to 2003. That study revealed that about 10 percent of all traffic fatalities in the U.S. involved long-haul trucks. The high rate of death resulting from large truck accidents has prompted researchers to go beyond statistics. Real-time analytical tools are now being used by truck fleet safety managers to predict road driver and vehicle performance.

How this technology works

Real-time data gathering is now possible thanks to telemetry instruments like GPS and in-vehicle computer modules capable of wireless data transmission. The predictive modeling takes into account the behavior of drivers and their reactions when dealing with factors such as truck performance, road conditions, weather, traffic patterns and more. If the analytics modeling returns a prediction indicating a high risk, the driver is not allowed to get on the road. Using an investigative script, fleet managers can now interview drivers in order to validate the computer prediction. If fleet managers find stressors or any other issues that may compromise the safety of OTR assignments, drivers are not sent out on the road. Should this type of predictive analysis become standard in the future, personal injury law firms could request such documentation to be entered as evidence in a truck accident lawsuit.

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