Fleet managers are working with an ever growing volume of data, and Artificial Intelligence (AI) is becoming more prevalent in using that data in the ongoing push for efficiency, sustainability and safety.
In combination with 5G connectivity, cloud services and the Internet of Things, AI is emerging at the top of the technology stack for fleet managers both for autonomous and self-driving vehicles.
In the micro-mobility segment, for example, Indian EV company Zypp Electric is using AI-enable rider route optimization for its services as a key-last mile delivery provider for essentials such as medicines and daily groceries.
Zypp operates 10 hubs operating over 7000 EVs making 40,000 deliveries a day across six cities. The company has been a leader in implementing IoT and data, and is using API integration for AI-enabled chat support for customers and drivers, which it says is delivering time savings of up to 20% on deliveries.
Zypp’s technology converges in an advance platform for order placement and tracking, in-depth analytics and a live feed of the progress of a delivery to the customer.
The platform also delivers scores on driver behaviour and performance, and the data is harnessed to enable more timely battery charging and swapping in addition to creating ‘vehicle life data’ which is shared with manufacturers.
Another AI application is in Singapore, where public bus operator Go-Ahead is set to trial an AI enabled safe driving system which detects abnormal driving patterns.
Using technology from German company Continental and the local Nanyang Technological University, the Go-Ahead buses will be equipped with a solution which will pick up data from sensors monitoring bus drivers, combining human data on heart rate and blood pressure with telematics recording vehicle behaviour such as acceleration and braking.
US company Helbiz is another leader in mobility technology, and released a product called HelmetChecker which uses AI and computer vision to ensure that a rider is wearing a helmet and has the strap secured.
Micro-mobility operators are able to use HelmetChecker to stop a vehicle from unlocking until it confirms helmet use or provide incentives to riders.
A more recent product release from Helbiz used AI in parking verification. ParkSense is an AI powered tool which allows fleet operators to be compliant with local regulations.
Instead of relying on location data, ParkSense relies on a picture of the parked vehicle taken from the rider at the end of the trip.
The tool, which has no hardware requirement and is able to return an answer in less than a second, takes into account multiple conditions such as if the vehicle is secure, if it impedes a path or road of the entrance to a business – all information which cannot be registered with a GPS device.
“We approached a problem with technology first, built the AI in-house and deployed it successfully,” said Helbiz chief technology officer Nemanja Stancic.
Greater Than describes itself as an “insurtech” company which uses AI “to predict driver risk and understand car drivers’ impact on road safety and energy consumption.”
In a recent blog, the company’s Global Director Fleet, Jim Noble, said AI had the ability to bring data together “to create an individual risk picture for each driver.”
“Our AI providers fleet operators with predictive risk insights for every driver, across the entire fleet,” Noble said.
“Because our data works in real time it ensures continuous validation of risk to help prevent incidents before they happen. In other words, our score is correlated to actual outcomes.”
This individualised driver data enabled fleet operators to obtain tailored insurance pricing, if they shared the data with their insurers.
“By being able to see a real driver score, and how their score compares to others’, drivers are encouraged to adapt their driving style to climb the leader board,” said Noble.
“This is good for a fleet’s safety performance, and good for road safety in general.”
There was also a link between driver safety and sustainability, Noble said.
“Our AI is not only trained with real driving claims, but also with fuel consumption and CO2 output,” Noble said.
“The AI is therefore an enabler to help fleets reduce their CO2 and environmental footprint.”