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TCA Netradyne Driveri Adam Kahn Photo: Josh Fisher / Fleet Owner
Adam Kahn of Netradyne demonstrates the Driveri mapping system at TCA 2018.

Netradyne’s Driveri RiskMap aims to make fleet decisions less risky

Fleet managers can get a geographic and time-based look at the best and worst parts of their driver's routes with Netradyne's Driveri RiskMap.

When’s the best time to dispatch your drivers so they can get the most and safest miles out of their hours of service (HOS)? For years it has taken instinct and experience to make that decision. But San Diego-based Netradyne, a creator of artificial intelligence technology focused on driver and fleet safety, is launching Driveri RiskMap that looks to give fleet managers data-backed maps and information to make smart and safe decisions for their drivers. 

The new feature analyzes the comprehensive data captured through Netradyne's Driveri platform. This data is provided fleet managers with a complete view of how their drivers are driving by geography, Adam Kahn, vice president of fleet for Netradyne, told Fleet Owner during a demonstration of the technology at the 80th annual TCA Convention: The Future of Truckload

The RiskMap mapping feature recognizes and clusters specific driver behaviors that represent favorable or risky situations for the driver, fleet or public. This gives safety managers the power to review and evaluate identified areas and modify fleet operations and routes to increase safety for all parties involved.

In addition to identifying potentially dangerous roads, Driveri RiskMap uses Driveri's data visualization tool to relay other unfavorable road conditions such as heavy traffic congestion, reduced following distance, dangerous intersections, speed relative to traffic, and incidents of vehicle damage so fleet managers and drivers can efficiently plan their daily routes.

“So if I have a fleet and I am running across Eureka Road in Michigan and my fleet is just struggling with those red lights all day long,” Kahn said as an example. “From a planning perspective, I can say, ‘How do I either train better for traffic on Eureka Road? How do I go explore what’s happening on Eureka Road?’ Because I might actually want to go drive it and see if they’re timed right, do I need to have better training for my drivers, or do I just start to plan around Eureka Road?”

As Driveri collects more and more data on traffic, roads with habitual speeding, stop signs, “anywhere I can track an alert,” Kahn said, “I can start to geographically map that from a historical perspective.”

This risk map help fleets identify and prioritize risks associated with their business, as well as recognize roads that contain positive driving clusters so they can be used more often. Using artificial intelligence, machine learning, and edge computing, Driveri captures and analyzes every driving minute, providing fleets with deep data-backed insight into their entire workday. This includes capturing both potential risk and excellent driving behavior.   

If the average driver clocks 500 minutes per day and all that data is collected, that is a wealth of specific data – broken down by time and location – that will help any fleet plan and react better, Kahn said. “So now I know Eureka Road is bad. But is it bad at 3 a.m.? Or is it bad because there is a high school right there and at 8 a.m. and that's why it's really bad? So now if I can start to slice that by time, that’s super interesting to a fleet because when I am trying to manage my hours of service (HOS) dispatch window, I am going to look to see the best window for my drivers.”

While most legacy systems capture video once the system is triggered by actions such as hard breaking, Netradyne’s system captures and records every minute of driving. “The immediate byproduct of Driveri is now we can recognize good driving,” Kahn said. “I’ve changed the data from being a lagging indicator to being a leading indicator. My score of my driver changes every minute. So if the driver drives good, the score ticks up. If there’s an event I need to track, the score ticks down.”

If a driver’s score starts to drop significantly, the system can send a note to the fleet manager alerting him or her so the manager can intervene before the problem grows, Kahn said. The system also focuses on highlighting “great moments” by drivers, where they are driving safely and encourages recognizing good driving.

Netradyne's Driveri is a vision-based driver retention and safety platform for commercial vehicles, which captures and analyzes every minute of every driving day. The platform uses a Quad-HD camera to provide a complete view of the road, a TeraFLOP processor capable of one trillion calculations per second and artificial intelligence that analyzes driver behavior and relays data to fleet managers immediately.

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