Frugal fleets: how AI and location intelligence can keep vehicles running longer

Out-of-service trucks cost businesses up to $760 a day per vehicle in lost earnings and repair costs. Maintenance costs for commercial vehicles are also increasing, significantly worsening the problem.

With the average truck in the United States covering 80,159 miles a year – and every one of those miles focused on maximizing return on investment – spotting problems before they happen can keep your fleet running for longer and reduce your repair and maintenance bills.

Thanks to advancements in artificial intelligence (AI) and location technology, it’s now possible to predict potential problems before they render vehicles inoperative and out of action for lengthy periods.

A Deloitte report into AI predictive maintenance said that replacing educated guesses with data-based knowledge is key to maintaining your fleet. The report added: “Avoiding downtime and driving efficiency in maintenance could help maximize asset usage and keep operations moving.”

That’s where AI-powered location technology comes in. This fusion of technologies is already revolutionizing the fleet and trucking industry. Combining real-time vehicle data, IoT sensors and predictive analytics, operators can spot potential issues before they escalate, allowing fleets to mitigate issues or have parts replaced during routine maintenance.

“More accurate predictions of machine failure can optimize maintenance schedules and decrease unplanned downtime and the associated costs,” wrote Mark Jackley in a post on AI predictive maintenance on Oracle’s blog. “They also extend the life of equipment by flagging issues and recommending maintenance actions.”

Key to enabling accurate AI prediction is being able to see where a vehicle travels and the types of environments it travels through. HERE’s geo-contextual insights help AI models correlate mechanical wear with terrain type, weather, route topology and traffic conditions to build up a picture of when a vehicle might need a repair.

Tiresome issues

For instance, Goodyear partnered with HERE for its advanced Tire Pressure Monitoring System, which uses advanced sensors and a predictive algorithm to alert drivers and fleet operators to tire issues. To date, it has helped fleets avoid up to 90% of tire-related breakdowns.

Using HERE location services, fleet operators can find a vehicle in need of service or road assistance down to just a few meters, and navigate them to the nearest maintenance station. Goodyear also developed a mobile app for commercial drivers using the HERE SDK.

“In the daily fleet operations, every minute counts and being able to locate a vehicle in a timely and precise manner is key to minimizing downtime,” said Grégory Boucharlat, Vice President for Commercial Europe at Goodyear.

Preventing a repair altogether is, obviously, the key to keeping fleets running longer. Bosch and Daimler Truck AG collaborated with HERE on its Predictive Powertrain Control. This Advanced driver assistance system (ADAS) for commercial vehicles uses the HERE ADAS Map and Bosch’s Electronic Horizon software to survey the road ahead taking into account topography, curvature, slope, intersections, traffic signs and speed limits.

The HERE ADAS Map links the precise position of a truck on the road to define an “electronic horizon” for which the driving style is then automatically adapted to. This allows the vehicle to plan and time gear shifts in advance as well as to predictively adjust the speed of the vehicle, minimizing unnecessary braking, acceleration and gear shifts to reduce the wear and tear on the vehicle, as well as fuel and battery consumption.

A to Z via AI

By fusing sensor data with HERE’s location intelligence, AI models can more accurately predict component fatigue such as remaining brake life based on where and how the vehicle operates. For instance, if it drives regularly on slopes and elevations, this is more likely to cause brake and transmission wear, while driving downhill can lead to brake overheating.

Maps and AI can also predict maintenance based on traffic patterns and road conditions. For example, vehicles driven regularly on congested stop-start routes could potentially have increased brake wear, increasing service needs. AI and location tech can also flag high-wear roads such as those with potholes and rough terrain that can damage a vehicle’s components and navigate away from these high-risk routes.

Central to this is accurate tracking and monitoring of vehicles using location data. When combined with AI, fleets can make informed decisions about maintenance and servicing, ensuring that vehicles are in perfect working order to maximize their lifespans and protect your business’s valuable assets.

“We’re just at the beginning of something massive,” said Gino Ferru, HERE’s Senior Vice President and General Manager EMEA. “Over time, machine learning will get even better at predictive maintenance, route optimization and anomaly detection, creating a hyper-intelligent supply chain.”