Collision Avoidance Systems explained

Some drivers have only a vague understanding of the Artificial Intelligence (AI) that drives car Collision Avoidance Systems (CAS) – leading to distrust. Time to lift the veil.

As Arthur C. Clarke once said, “Any sufficiently advanced technology is indistinguishable from magic.” That certainly applies to CAS. Since their emergence, they’ve been enthusiastically adopted by corporate fleets because of their proven, positive effect on the car collision rate and driver safety. But they also continue to baffle both drivers and fleet managers. Magic? No: the truth is even better.

CAS is based on the same principle that allows humans to drive – vision. Only, computers can do it better. On long drives (and on some shorter ones), we tend to get tired, bored or distracted. But CAS are as focused during the 8th hour of a long drive as during the first – and any time in between. They’re also never tempted to look at the text that just came in from their best friend.

But making a computer ‘see’ is not as simple as hooking it up to a camera. This is where CAS technology comes in. The company’s focus is on developing AI that can reliably tell the difference between a stopped vehicle and a moving one; between a pedestrian and a traffic sign; and between getting too close to the vehicle ahead and getting stuck in heavy traffic. 

That level of learning took 20 years to acquire; plus the collection of 200 million miles (322 million km) of driving footage against which to stress-test CAS algorithms. That incredible volume of real-life experience has been the AI’s education, its lessons now branded into the EyeQ® chip – part and parcel of CAS. 

Proven results have translated into deep trust and broad acceptance of its AI technology by the market. And, this technology is getting even better. CAS next-generation chips are expected to learn from each other and crowdsource that knowledge. For example: cars equipped with CAS would be able to share real-time information about traffic and weather conditions with other such cars via the cloud. 

In other words, CAS-equipped vehicles would quietly send data to the cloud, with no human intervention required (so drivers can stay focused on the road). Meanwhile, the AI would adjust for weather conditions, for example by taking into account that rainy weather implies greater stopping distances when braking. 

But AI benefits are about more than traffic and weather. AI can learn about driver behaviour and react appropriately. For example: following more lane departure warnings than usual, it might advise the driver to take a rest. AI is not magical, but something even more wonderful: road-tested, machine-learning high-tech, making drivers safer and their fleets more cost-effective.

Technology is just one factor to consider in a comprehensive fleet accident management programme. Not all incidents can be avoided, so it pays to have a robust support plan in place to ensure driver safety, minimise business disruption, and organise repairs so the asset’s integrity and value is protected. Talk to Crash Management now about a fully customised programme to suit your operational requirements and budget.