RL Automotive has partnered with the European Space Agency to develop AutoTrust, a data analytics solution that will see the pair quantify the accuracy of big data gleaned from vehicles.
RL Automotive Pushes Connected Mobility
RL Automotive is using machine learning technology to scrutinise the increasing levels of information supplied by 5G and satellite communications networks, both for data quality and cyber-attack, as part of fault management and predictive maintenance services for connected vehicles, particularly in the Transport and Logistics sector.
“AutoTrust’s data analytics increases the confidence that you have in the data you’re getting, ensuring that critical issues are managed effectively,” explains RL Automotive’s founder and CEO, Mark Longden. “We establish that by pushing the data through our machine learning algorithms, looking at patterns and saying ‘yes, this appears to be a genuine piece of data’ and ‘no, that doesn’t.
“Say you have a truck with 10 wheels and tyres with a normal inflation pressure of 100-120psi. If the real-time data we receive from the vehicle shows pressure reducing to 80psi, 60psi, then 0psi, how do you know this is good data? Even the driver may not notice the difference on just one wheel. However, the safety of the vehicle and other road users is seriously compromised. Chances are that the data is good and the vehicle should be pulled over immediately. However, there are other possibilities, such as a faulty sensor or data manipulation causing perhaps a high-value cargo-carrying vehicle to be stopped unnecessarily. AutoTrust is a cloud-based data analytics module that provides users and fleet managers with a level of confidence in data authenticity for their connected vehicles.”
RL Automotive also has a Vehicle Management Platform, which uses connected vehicle data to make further decisions by automatically sending messages to dispatch a repair agent when the vehicle reaches its destination. It can also request additional information directly from the vehicle if the existing data is not considered strong enough to make an instantaneous decision.
Trials will start in early 2023 with leading UK Transport and Logistics operators, each of whom will supply data from a portion of its fleet of HGVs, trailers, and buses for further analysis and to fine-tune the algorithms. The Universities of Surrey and Hertfordshire are also partners in the development of AutoTrust.
“Many systems or companies stop at one application,” adds Longden, “you might, for example, have a telematics company that’s the gateway to getting the data out of the vehicle and reporting this on a dashboard, but that’s as far as it goes. We are very much on the analytics side for preventative and predictive maintenance. Our USP is the analysis of vehicle data, the ability to identify corrective actions for events and ensuring that these can be rectified. Rather than just telling someone that five of their vehicles are poorly maintained or about to break down, we have the systems in place and the processes to ensure the problem gets fixed before it gets worse. It is both predictive and reactive technology.”
RL Automotive has a history in advanced tyre analysis. It previously developed a laser scanning system to determine the condition of tread profiles and wear, which was employed by major Formula 1 teams. It then moved to tyre analysis for commercial fleets and became one of the earliest automotive tech firms to establish consistent remote analysis of vehicle data via the cloud.