Forget hypercars! There are millions of emergency response vehicles globally, and these must be the fastest vehicles on public roads. I think we can all agree that saving lives is more important than showcasing a high life. Vehicle communication technologies, combined with a smart city infrastructure can give priority to doctors, firefighters and police officers more efficiently than roof mounted flashers and sirens.
Cities are connecting their traffic lights to central management centers and vehicle-to-everything – V2X – roadside units, so V2X-equipped vehicles can communicate with the infrastructure. This is all we need to do the magic and turn the lights green on the route of an ER unit.
Another advantage of V2X installed in ER vehicles is that it can send warnings to other vehicles. Car manufacturers can decide how to display alerts in the vehicle without distracting drivers. It’s up to the user experience experts to find the perfect combination of sounds and visible signals.
The point is to notify drivers of an approaching ER vehicle before they see it, or hear the sirens.
In the age of always-on digital entertainment, when roaring music from 20 speakers can drown out outside noises, it’s very important to find every opportunity to get the driver’s attention.
We can count on V2X, the technology will be more widespread in the next decade. The Euro NCAP (New Car Assessment Program) will require various V2X features in new vehicles for a top safety rating. (Read our blog post about NCAP’s efforts).
For those who may worry that affluent or skillful drivers will take advantage of the opportunities offered by the system can rest assured. Only special vehicles can acquire certificates to influence the infrastructure, and all suspicious V2X units are automatically denounced and disconnected from the whole V2X network.
Our view is that the V2X-based detection of emergency responders is more foolproof, efficient and accurate than a camera-based solution. It doesn’t require human labour, and radio communication requires much less computing power than an intelligent image recognition system.