New cars are in short supply, with delivery times stretching as long as a year because of the ongoing semiconductor shortage and other supply chain issues.
This is affecting customers of all kinds, but none more than fleet buyers. The shortage means many fleets, from rental car companies to police departments, are not able to replace vehicles as often, resulting in a growing reliance on older vehicles, and increased resources devoted to maintaining them.
Rather than simply replacing vehicles, which was often the strategy before because it was more cost-effective than making repairs or keeping up with ongoing maintenance, fleet managers need to invest more in inspections, monitoring and repairs.
One way they can ensure that the vehicles they do deploy remain safe and in the best conditions possible is by using artificial intelligence solutions that increase driver accountability, examine a vehicle’s performance, and determine ways to make sure that it remains up to the standards necessary in order to ensure safety and effectiveness — as well as recommend ways to bring vehicles up to code, or identify issues before they cause problems.
To many people, the term “fleet” brings to mind rental cars and taxis. But fleets include police and rescue vehicles, transportation for government safety inspectors and regulators carrying specialized equipment, delivery vans and trucks to bring much-needed supplies to consumers and institutions like schools and hospitals, and much more.
Operators of these fleets need vehicles they can truly rely on; and if they do fail, that could put lives at risk.
Until the supply chain backlog is cleared — and that could take years, according to experts — fleets of all kinds are going to have to make do with what they have. To do that, they are going to have to go beyond the usual inspection and repair procedures they have relied on in the past.
Artificial intelligence can help with these deep-dive inspections, utilizing easy to operate mobile apps along with standard vehicle equipment like security cameras to routinely document the condition of fleet vehicles.
This creates an objective and updated record. Apps can remind drivers to log an inspection report when they start and finish a shift, and cameras can record vehicles, and details about its condition, coming in and out of services. All this data can be uploaded to a central server, where advanced data analysis tools can process the images, cataloging them in an easy to use format for the review of fleet managers, body shops, inspectors, and other suppliers.
Meanwhile, sensors can keep track of data on driving habits, brake-use, wear and tear, and other internal vehicle data. Based on the analysis of all this data, AI tools can make recommendations on services needed or expected problems and repairs.
Tracking driving habits and ongoing vehicle conditions also makes drivers more accountable, ensuring that the vehicle is treated better, aware of its condition, and pick up and return it on time. This, too, can help extend the life of a vehicle, or at least keep it in better shape.
Widespread use of AI in these inspections will not only make for safer driving and safer vehicles, but it will also cut down on the labor required to ensure that vehicles are fit for the road.
Most such inspections now are still carried out manually, meaning that they are labor-intensive as well as being subject to human error. Automating the inspection process using advanced data analysis will help ensure that inspections are done on a regular basis — without the risk of fatigue-driven error.
Advanced AI analysis systems could make the difference between poor and ideal performance – perhaps even between life and death.