Empowering driver management with fleet and video telematics innovation

For any fleet operator, managing drivers is a complex challenge in terms of safety, compliance and risk, which requires a comprehensive approach that incorporates robust processes and leverages advanced technology solutions. As such, telematics is playing a crucial role in driver management by providing valuable data and insights that enable better decision-making, while facilitating improved communication and collaboration between the fleet manager and drivers.

Photograph: Applied Driving

Driver data analysis and insight

While fleet technology has become a key component of effective driver management, it also represents a potential headache in terms of the amount of data it provides, often from multiple systems and hardware. For overstretched fleet management teams, there is often a lack of time and resource to use the available data and turn it into the required actionable insight.

The latest telematics innovation, increasingly using AI-powered tools and processes, has the potential to transform how critical data is analysed, providing much needed support to fleet managers. “AI-powered analysis will enable the telematics system to understand where issues exist and take the appropriate steps to resolve these exceptions,” believes Steve Thomas, managing director of Inseego UK Ltd.

“It can increasingly be used to interrogate a wide range of data and video sources – behaviour, incidents, near misses, fuel usage, speed limits, location, weather conditions – to create a holistic view of driver performance.”

By combining multiple data sets that would be impossible to analyse manually, a fleet manager can use a telematics system to create a true picture of fleet risk and pinpoint driver behaviour that requires attention. “Someone speeding, in the rain, outside a school is clearly a higher risk than someone marginally over the speed limit in dry conditions on a motorway, but most current systems would not differentiate, making it harder to prioritise intervention,” explains Thomas.

Vernon Bonser, UK sales director at Queclink Wireless Solutions, agrees that AI will undoubtedly enable fleets to analyse huge amounts of data quickly and effortlessly, to gain operational insight and trends that were previously impossible to compile: “The challenge for fleet and video telematics has always been how to best compile, review and then act on visible trends, which is where the risk reduction and return on investment sits.”

Vehicle cameras, for example, typically upload video clips based on g-force events, but often these are triggered by false positive events such as harsh driving, potholes and speed humps. For a fleet of 50 vehicles, if each generates four clips per day, the fleet manager would have 1,000 videos to watch a week, which is simply not workable. This is not just about having the time to view footage, but also being able to react quickly to situations that need immediate attention, both from a duty of care and insurance perspective.

“The time needed to simply examine daily driver behaviour events for a medium or large sized fleet is significant and would be impossible for a single person or even a small department to achieve efficiently. When you add video into the equation, imagine how much more resource is required to review the gathered vehicle and driver footage,” adds Bonser.

With post-event machine vision, telematics software can view the video clips and flag up those that need attention. This means a fleet manager can quickly focus on actual collisions or an incident where a vulnerable road user (pedestrian, motorcyclist or cyclist) was involved. AI technology of this kind has already been shown to reduce the number of videos needing review by as much as 99 per cent, leaving just a handful that can be checked in a matter of minutes.

The major problem facing organisations now is certainly information overload, especially as smart vehicle cameras now capture a growing range of driver risk events. “Fleet operators are struggling to handle the avalanche of alerts and video uploads generated by AI cameras, which is impairing their ability to best use the technology,” says Sam Footer, partnership director of SureCam. “These devices provide an added layer of risk detection – determining threats both in the vehicle and on the road – but this has created its own set of challenges. By embedding AI into a cloud-based platform, it’s possible to manage and resolve issues without needing excessive human oversight and intervention.”

Automated communication and engagement

Fleet telematics is rapidly evolving to enhance driver communication and management with ever greater levels of automation and engagement. This is already happening to a certain extent, according to Inseego’s Thomas, but moving forward the system will possess the ability to communicate with the drivers directly, which will massively reduce the burden on the fleet manager.

“We will start seeing telematics handle many aspects of fleet management including training, compliance, vehicle usage and working hours to take on much of the hard work. Many driver, vehicle and fleet processes will soon move from human intervention to automatic system management, leaving the fleet manager to deal with the 2–3 per cent that truly require their attention. For the rest, they will be able to oversee using reporting dashboards that intelligently measure ongoing performance,” he suggests.

There is automation occurring around driver behaviour monitoring and education, with some exciting developments in targeted training that provides engagement and coaching, triggered by specific recurring behaviour. “Fleets need to have a system in place to provide drivers with useful feedback, based on their performance,” comments Nigel Lawrence, director of Applied Driving. “The ability to share automated safety messages, performance reports and training modules – using both real-time and historical data – is helping address individual issues, change driver attitudes, and instil a responsible driving culture.”

There is also a growing number of intelligent dashcams that can not only capture footage but also engage directly with drivers regarding distraction and fatigue; detect nearby vulnerable road users; and understand fleet risk like never before. According to SureCam’s Footer: “Organisations can now identify risk-generating events behind the wheel and automatically prompt the driver to change their behaviour with real-time voice instructions. Event alerts with video are then sent back to base to ensure coaching and training is focused and relevant to their drivers.”

Queclink’s Bonser suggests that the continued advancements in edge-based computing and AI algorithms will lead to enhanced decision-making capabilities and the provision of highly accurate real-time insight. “With improved object detection, better understanding of driving scenarios and sophisticated behaviour analysis, driver communication and management is going to take a massive step forward.

“This could even include a way of predicting a person’s actions – based on age, direction, speed and distraction – which will enable far quicker and more accurate risk alerts than existing technology.”

For more information see:

queclink.com

surecam.com

applied-driving.com

inseego.com