In our rapid world, the number of traffic jams - caused by the continously growing traffic – is steadily increasing. There is a high demand on services providing adequate information about the actual status of the traffic, allowing participants to avoid jams.
In the course of my work, I developed and applied a complex, social traffic information system related traffic-estimating method. By using this method, the system became adapted for describing the actual traffic circumstances.
The traffic-estimating algorithm generates the final data by analysing and processing the incoming localization information, based on the average speed of the sender cars. This information is linked by a well-developed map matching algorithm to the corresponding part of the map. The system as a whole is able to trustworthily represent the traffic by synchronizing the incoming information and the map database.
The traffic information – generated by the monitoring system – can be displayed like a map on several platforms (IPTV, webpages, smartphones), ensuring that the information reaches the user, allowing them to avoid traffic jams. What’s more, reaching the optimal user number and distributing the traffic in a balanced way makes it possible to prevent obstructions.