The principle of reporting traffic restrictions by smartphones deserves to retire. It has been with us for decades, but makes little sense nowadays. There is a solution, which is fully automatic and several times more effective at the same time.
Most of us have a smartphone in our pockets. It contains a large number of sensors keeping track of the current state, and on the basis of mathematical calculations, they can even “predict the future.“
Imagine you regularly commute to work by car. Your mobile phone, thanks to a GPS and motion sensors, knows that it usually takes you between 20 and 30 minutes and you only stop at crossroads. If you deviate from this “habit“ and slow down, there might be a road accident ahead, for example. Your mobile phone can easily detect this and suggest a better road in real time.
The real power lies in big data
It is not very difficult to assume that, in fact, there is a number of such drivers/owners of smartphones on the road at any given moment. There are thousands of cars on the roads in a moderately sized city at any given time. Understandably, one driver slowing down cannot be evaluated as a traffic restriction, she might have stopped to have a burger.
But if the flow of the entire traffic gets slower on a specific road and this incident is detected in real time by hundreds of smartphones, probably a problem has occurred on the road. Whether it is a road accident, traffic jam or drunken pedestrian can be specified by drivers within an application (such as Waze for example), but the core of the matter is that a drive on the given road takes longer than usually – and this can be detected irrespective of how many of the drivers are using apps such as Waze.
This mass of data from a lot of individual users and their subsequent statistical evaluation constitute the basis of „crowdsourcing“. When a huge volume of individual independent data provides a unified picture of a certain situation. This principle to determine a degree of road congestion is also used by Google Maps or the popular application mentioned before – Waze.
On the basis of findings resulting from the analysis of anonymised data, each driver can be warned about any troublesome situation in advance. This would enable them to avoid the respective road, potentially averting an even problem. All this is actually possible without anyone having to report the problem physically or other drivers hearing about it on the radio.
In order to ensure security and anonymity of all participants and provide reliability of the entire system, it is inevitable to make use of advanced algorithms of population analysis such as Market Locator. After employing these, nothing stands in the way of actually everyone profiting from the system.