High-risk driving is a threat to our lives and is a leading cause of death globally. In that case, why aren’t people prioritizing their safety on the roads? And why aren’t we, as a society, pushing safe driving as a health benefit? In today’s digital-first world, artificial intelligence (AI) has the power to revolutionize the way we look at driver safety and turn it into the next big fitness challenge.
Road crashes are a major cause of death among all age groups and the leading cause of death for children and young adults aged 5–29 years. Every year, approximately 1.3 million people die as a result of road traffic crashes. Up to 50 million more people suffer non-fatal injuries, with many incurring a disability as a result of their injury.[i] My own small hometown was left devastated recently when five men were killed in one crash. For every fatality, so many other lives are affected.
Unfortunately, road safety does not get the attention it deserves, despite it being one of the threats to health that we CAN do something about. Is it time to look at driver safety in the same way we look at other serious health threats? And can tackling high-risk driving be a challenge we can all get behind?
AI for good enables us to dig deep into the factors that contribute to crash probability. In fact, at Greater Than we convert GPS data into driving patterns, a revolutionary technique that enables us to identify whether patterns have been seen before, in real-life trips involving crashes.
We’ve determined that some of the most common contributory factors are focus, anticipation and speed control. And, importantly, these are factors we can measure and remedy. For example, small changes in driver attitude, such as avoiding distraction and planning ahead, can make a huge difference to crash probability.
While it’s a positive development to see a growing number of advanced safety systems in vehicles (everything from automatic emergency braking to collision warning), one researcher concluded that a combination of vehicle crash avoidance technologies reduces crash frequency only by about 3.5%[ii].
Some technology can make a significant difference to crash severity. For example, the Insurance Institute for Highway Safety (IIHS) and the Highway Loss Data Institute (HLDI) found that forward collision warning combined with automated emergency braking cuts front-to-rear crashes with injuries by more than half (56%). However, a survey discovered that, of the drivers whose vehicles had these optional features, 11% turned off forward collision warning and 17% turned off automated emergency braking.[iii]
It could be the time to increase the focus – and pressure – on the driver. But how do we empower drivers to want to make a difference to road safety by reducing high-risk driving behaviors?
Around the world, individuals invest time and effort in keeping themselves fit, active and healthy. In fact, the global fitness tracker market alone is projected to grow from $36.34 billion in 2020 to $114.36 billion in 2028[iv]. If individuals are so committed to tracking their fitness, should it be so difficult to encourage them to track their driving health?
With AI, any organization involved in mobility management, driver risk management or motor insurance, can turn safe driving into a fitness challenge. By uncovering real-time driving risk insights and incentivizing safer attitudes with feedback, gamification, rewards, and recognition, organizations can make a real difference.
In fact, insurance companies are particularly influential when it comes to driver safety and tackling high-risk driving behaviors. By adopting usage-based or risk-based pricing that increases/decreases according to risk level, insurers place the power in drivers’ hands. Quite simply, the drivers with the highest crash probability pay the most, and risk not having their policies renewed. Drivers with the lowest crash probability are recognized for their safe behavior.
Most of us are familiar with the gamification features that motivate us to reach our fitness goals. The same approach can be utilized in driver safety. A leader board, for example, where drivers can see how they compare with others in their company or division, or even their family. Feedback that highlights strengths and weakness. And recognition when they achieve a goal – such as a specific driving score or a high level of driving focus.
With AI for good, it’s easy to measure a driver’s risk level and incorporate these features into a program that turns driver safety into a fitness challenge. All that’s needed to get started is 1km of GPS data, which can be shared via a simple API connection.