Smart Traffic Lights, Smooth Traffic Flow
Smart traffic lights determine traffic flow in several ways, which can enable traffic to run more smoothly and even lower emissions.
Light to Vehicle
Based on predictive analyses of the traffic flow, the driver or vehicle could be advised to anticipate on the upcoming traffic light. Communication could go directly to the vehicle, or via an application to the driver, and reduce unnecessary acceleration, and braking; with lower emissions as a result.
Another application of smart traffic lights is currently in a test phase in York (UK). The traffic lights would advise drivers on the speed they should drive at in order to arrive at the next traffic lights when they turn green. This would put an end to stop-go driving, make traffic flow smoother while also reducing emissions.
Further on, traffic lights could anticipate on traffic congestion and alter their pattern; or prioritise ambulances, buses and cyclists. In Cambridge, for example, lights at the end of the bus lanes hold back traffic to give buses priority; this system applies in over 250 towns and cities throughout Europe. Zurich, Braundschweig and Potsdam, even use it to co-ordinate all traffic in the city.
Vehicle to Light
It can work the other way around as well. In various projects in Arizona, California, New York City, Tampa and Florida vehicles share their real-time location and speed with traffic lights, which can be used to optimise the traffic timing in coordination with the real-time traffic demand.
Vienna goes even further, and developed a system that recognises if a pedestrian or cyclist is actually trying to cross at the intersection, or not. In case of the latter the traffic lights does not have to turn green unnecessarily. This system would not have a higher cost than conventional pedestrian traffic lights with push buttons.
Mind the Fraud
However, smart traffic lights are vulnerable to cyber criminals. A car can send out false information to cause traffic jams, and a group of cars could even shut down whole areas, according to the Robust Net Research Group and the Michigan Traffic Laboratory. They consider the algorithm as the weakest point, because it assumes that the received information is ‘honest’. Nevertheless, this kind of information can be a fraud, by making the vehicle lie about its position and speed. The solution might be the validation of the received data before the algorithm starts calculating, for example by the additional use of in-road sensors.
With various smart traffic light projects already on the road, and the possibilities still expanding, it becomes clear that transport worldwide has given the green light for the new layer of smart cities, on top of smart street lighting.