AI, or artificial intelligence, is one of the most exciting areas of technology being developed right now. The possibilities of what could be achieved with advanced AI is extensive. One area which has already been impacted, and continues to be impacted, by AI is fleet management. Fleet management is the process of organising and controlling a group of vehicles, often commercial vehicles such as vans or trucks so that they can perform their duties in the most efficient and productive way.
One of the most important areas of running a commercial fleet is making sure the vehicles in that fleet are taking the most time efficient routes during the day when out on the road. Having vehicles stuck in traffic can be detrimental in several key ways. Firstly, it can delay the vehicle from arriving at its destination on time. In specific industries, such as construction, the delivery of materials to a site can cause financial losses if they don’t arrive on time. Similarly, if a vehicle is delivering an order which has been purchased online, making the customer wait past their delivery time will not produce high customer satisfaction levels. Secondly, sitting in traffic can be harmful to the fuel efficiency of a vehicle as often the engine is left idling.
Engine idling can significantly contribute to fuel wastage and should be avoided where possible. There are two ways of avoiding this. In-cab coaching telematics systems can be installed which alert drivers to engine idling and have been proven to improve fuel usage. Also, AI within navigation systems can advise drivers of traffic delays and adjust their routes to always keep them on the predicted fastest route to their destination. This demonstrates a significant change as without these tools available, route planning and driver behaviour were much harder to control and plan correctly.
Another area which often causes problems for fleet managers is taking vehicles off the road to conduct maintenance work. Whenever a fleet is without even one of its vehicles, the productivity of the overall fleet is reduced. This can cause delays for customers which neither the fleet manager or the customer would be happy with.
AI can help avoid this by providing fleet managers with predictive maintenance requirements. By alerting fleet managers before a problem occurs, this can help keep a vehicle on the road. Without prior warning that a mechanical problem is developing within a vehicle, a fleet manager may have to remove a vehicle from operation for a considerable period of time while the issue is fixed. Furthermore, without warning, the issue could develop into a significant problem which could cost the business a lot of money to fix. However, with prior warning, it can be the case that the problem can be solved before it develops, and far less time is lost with a vehicle off the road.
Overall, AI’s impact on fleet management will likely increase in the coming years. With the advancements being made in autonomous vehicles, with highly integrated AI systems, fleet management could well go through even bigger changes. Safety is one of the areas where AI within commercial vehicles could have the most significant impact. Features such as lane detection and auto-braking could prove vital to avoiding accidents with other road users.