Transportation Fleets Leverage Video, Big Data to Mitigate Risk

The freight transport industry is leveraging video intelligence to protect companies from the threat of litigation.

PITTSBURGH – The combination of video and Big Data, or video intelligence, has already transformed several industries. Commercial transportation could be next, reports Commercial Carrier Journal (CCJ).

Fleet owners in the high-risk, low-margin freight transport business industry see the technology as a way to protect themselves and their drivers from the ever-present threat of litigation.

The University of Michigan Transportation Research Institute – a leader in truck-related crash research – studied 8,309 fatal car-truck crashes to determine fault. Car drivers were assigned fault 81 percent of the time versus 27% for truck drivers, CCJ reports. Without video evidence, the odds are unlikely to be this favorable towards trucks.

Pitt Ohio, a transportation solutions provider specializing in trucking services, began using video intelligence in 2012. The merits of the SafetyDirect system from Bendix were validated when one of its trucks was involved in an accident on the Pennsylvania Turnpike soon after, CCJ reports.

An SUV crashed into a concrete barrier on the left side and then crossed into the right lane, striking the Pitt Ohio truck and taking out its steering axle. The truck crashed into a barrier on the right side. The passengers in the SUV were injured and looking for a scapegoat, CCJ reports.

“They were coming after us,” Jeff Mercadante, vice president of safety for Pitt Ohio, told CCJ. “Three people were trying to say we hit them.”

Pitt Ohio showed a video of the event to the insurance company representing the SUV owner. The case was settled quickly and Pitt Ohio received $34,000 in damages.

Video intelligence platforms are designed to capture a short clip of incidents before and after a trigger event. They also continuously monitor and capture the speed, swerving, sudden deceleration and other data from such events to deliver an efficient way to manage risk using this three-step process. It includes creating a risk profile, turning data into action and expanding visibility around the vehicle to detect risk.

To read more detail about each step in the process, read the full article here.

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