Road safety is increasingly coming under the spotlight across the U.S. – at both a state and national level. Latest statistics from the National Highway Traffic Safety Administration (NHTSA) estimate 20,175 people died in motor vehicle traffic crashes in 1H 2022, an increase of about 0.5% compared to 20,070 fatalities estimated by the NHTSA for the first half of 2021. The human cost is huge, but the additive cost of overall motor vehicle crashes to American society is a worrying $340 billion per year according to recent insights from the NHTSA.
Reducing these overall figures is very much in the sights of the U.S. Department for Transportation. In the words of Secretary Pete Buttigieg: “These deaths are preventable, not inevitable, and we should act accordingly. Safety is our guiding mission at the Department of Transportation, and we will redouble our efforts to reduce the tragic number of deaths on our nation’s roads."
The safety policies are being put in place
At a city-by-city level more than 45 communities have committed to “Vision Zero” in the U.S. – a strategy to eliminate all traffic fatalities and severe injuries, while increasing safe, healthy, equitable mobility for all. Vision Zero acknowledges that many factors contribute to safe mobility - including roadway design, speeds, behaviors, technology, and policies - and sets clear objectives to achieve a shared goal by engaging stakeholders that span local traffic planners and engineers, policymakers, and public health professionals.
Technology aids road safety – fleets need to get “on board” with AI
But policymaking alone will not deliver on the journey to shrink road deaths. It needs buy-in from fleet operators and the helping hand of some tech-led innovations. Of course, we aren’t talking driverless vehicles yet but the NHTSA sees driver assisted technologies next on its Road to Full Automation.
Artificial Intelligence (AI) is already having an ever-greater influence on our everyday lives, so it’s no surprise that it has a growing role to play within the fleet sector to help improve driver performance, support duty of care and cut costs. Particularly in new developments, AI video telematics is expected to transform how vehicle operations approach road safety. In the broadest sense, AI is about using machines to perform tasks that would typically have required some form of human intervention and demonstrate behaviors associated with human intelligence. Powerful in-vehicle AI video telematics will make it easy to identify key areas of risk, reduce collisions and near misses, and ensure employees get home safely.
AI-enabled cameras go beyond the cab
AI-powered vehicle cameras, using Advanced Driver Assist Systems (ADAS), Driver Status Monitoring (DSM) and Blind Spot Detection (BSD) technologies, are now enabling fleet operators to maintain safety levels for both their drivers and other road users. By automatically monitoring hazards on the road and high-risk behaviors, these devices make it possible to provide real-time feedback straight to the driver.
Distractions such as cell phone use, eyes away from road, smoking, eating and drinking, can be detected alongside other fleet risk, such as fatigue, tailgating, and nearby vulnerable road users, so drivers can be encouraged to change potentially dangerous habits. In fact, in one international deployment of AI-powered video telematics, installed across 16,000 public sector vehicles, there was a reduction in risky driver behavior of over 80% within the first three months.
The latest intelligent detection cameras can even identify and track vulnerable people where driver visibility is poor, and risk of injury high. These devices can establish the severity of risk dependent on the proximity of a worker, pedestrian, or cyclist to the vehicle, activating internal and external alarms when they enter virtual exclusion zones. This provides the driver with increased time to react and warns other road users of the potential risk.
Humanized AI at work
Moving forward, advances in Vulnerable Road User (VRU) perception technology will enable AI-powered cameras to provide a nuanced understanding of human behavior. Using machine learning techniques, it will be possible to train devices to accurately predict a person’s actions, and as such, provide drivers with potential collision warnings that give them vital moments to avoid an incident. Backed by a dataset of hundreds of millions of human behaviors, the edge-based software analyzes age, direction, speed and distraction to deliver a much higher degree of accuracy than traditional ADAS technology.
Real-time analysis and decision making when incidents occur
Fleet managers can use the added insight provided by AI video telematics to better understand risk within their vehicle operations, and take steps to address issues before they result in a driving incident. However, no vehicle operation has the time and resources to manually review every triggered collision, near miss or driving event, when video uploads can exceed hundreds per day. Due to the size and weight of many vehicles – especially vans, trucks and specialist vehicles – dashcams require highly-sensitive g-force settings to detect a collision, which results in large levels of generated events data.
Computer vision algorithms can now be used to review huge amounts of data, which means fleet managers are only being presented with information that requires immediate intervention. AI post analysis can, for example, help overcome the challenge of manually checking hours of downloaded footage by automatically validating in seconds whether a collision occurred and determining if any action is required. The technology will continue to evolve in the future to detect, monitor and analyze near misses and driver behavior, which will support data-driven safety decision-making and problem-solving.
AI post analysis uses advanced object recognition software to identify different types of vehicles, cyclists and pedestrians, making it possible to distinguish between collisions and false positives that can be generated by harsh driving, potholes or speed humps. This added layer of analysis enables rapid intervention and the ability to quickly summon emergency assistance, resulting in enhanced duty of care and driver welfare, as well as reduced insurance claims costs.
The tech delivery
There are two types of technology – edge-and cloud-based – that will see AI delivery become increasingly embedded in video telematics hardware and software. For edge-based solutions the processing takes place close to the data source, such as a connected camera device, to provide real-time insight. Cloud-based solutions collect and process information in a centralized data center for powerful post analysis.
Driving towards a safer future
The new generation of AI video telematics will ensure fleet operators can access the right information at the right time, presented in a way that enables them to achieve significant change and encourage drivers to operate in the most responsible manner. By automating management processes, data analysis and incident detection, they can take advantage of intelligent solutions to keep drivers, road users and pedestrians safe and reduce the number of collisions.
The U.S. DOT Fatality Analysis Reporting System (FARS) show large trucks account for nearly 13% of fatalities on the nation’s roads, so there is an opportunity to embrace AI innovation and immediately save lives – and we must not ignore its ability to reduce cost to society as well. We all want a future where no one is killed or injured on U.S. roads and fleet technology such as AI has a significant role to play in safer transportation for all.