How telematics will resolve traffic congestion
Ever notice how you sometimes run into heavy congestion on motorways that causes traffic to come to a standstill, even for long periods of time, but it seems to have no cause? There is no accident up ahead, no construction work; there is nothing on the opposite side of the road that could have caused curious drivers to slow down and take a look, no traffic lights of course, nothing. And yet you were stuck in traffic for 10 or 20 minutes, before suddenly the road suddenly seems completely clear and everyone is moving along again at a normal speed. It’s what we often refer to as a phantom traffic jam.
This seemingly elusive phenomenon, which can be caused by just a few drivers suddenly braking and giving rise to a wave-effect of repetition amongst vehicles arriving from behind, has been widely studied by statisticians and scientists. This curious – and vexing – effect, however, is not simply solved. In fact, as the driver who has caused the initial braking to begin accelerates again, the chain-reaction does not dissipate, but moves backwards down the highway.
The term “jamiton” was first coined by researchers at the UK National Science Foundation in 2009. However, independent teams of researchers around the world have come to the same conclusion using computer simulations. Phantom traffic jams – or jamitons – have a striking resemblance with the physical phenomenon of soliton waves, as well as revealing striking similarities with equations used to describe the detonation waves caused by explosions.
Reducing Traffic Congestion
The first solution proposed to reduce this phantom menace is based in common sense along with the application of varying speed limits. There is no advantage in speeding and then braking. The best solution to avoid such congestion is to maintain a constant speed and safe distance from other cars that will prevent vehicles from having to slow down. That’s driving school 101 material.
The oldest solution to this problem is queue warnings, which are often used on highways to alert drivers to slow down. Some European countries have introduced safety patrol cars that enter the traffic fray to slow down cars and prevent the congestion wavefrom propagating backwards. Similarly, adaptive cruise controls that maintain vehicles at a steady speed can also help dissipate this issue.
However, safer and slower driving is not enough. If there are a sufficient number of vehicles on the road, traffic congestion becomes inevitable, at least with human drivers.
Connected cars that share a range of information on weather, road visibility and conditions and traffic through interconnected telematics systems can make a big difference.
A vehicle that needs to brake, for example, could transmit this information to other drivers on the road, recommending they slow down. Moreover, the same could be accomplished by smart highway and city infrastructure. And the promise is that the more data is shared, the greater possibility we have of avoiding the formation of phantom traffic jams. However, the real issue at this stage remains the driver: will he/she heed the warnings and slow down?
The true solution to this problem will be provided by artificial intelligence and autonomous vehicles.
Once human drivers are completely out of the equation and can no longer override alerts, sophisticated sensors, data analysis, and algorithms and the real-time communication between smart infrastructure and the AI systems governing fully autonomous vehicles will be able to adapt solutions in real-time to avoid the formation of jamitons.
And that is another strong point in favour of self-driving cars.
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