Pilot system for determining waiting times at border crossings
On the border between Slovenia and Croatia, especially during the tourist season, there are longer traffic jams. The main cause is administrative border control, which, even in the case of very fast and efficient work of the border authorities, with a large influx of vehicles, inevitably causes traffic jams. Several systems (FCD, traffic counters, bluetooth) have been tested in the past to estimate waiting times. When reviewing solutions for similar problems around the world, the technology of object recognition through video camera recordings was encountered. Therefore, the aim of this pilot project is to test such a system, which will be the basis for further planning of improving traffic information on the situation at border crossings.
The system will be able to transmit data on the actual waiting time in standard protocols via dedicated API web interfaces and in xml or JSON format, which will enable subsequent use in the client's systems. The system will not collect personal data, license plate data or other vehicle identification data.
The information about the wait before border crossings will be designed in such a way that it will provide information about the current waiting time every minute. In doing so, the system will not use other algorithms for estimating travel times in free traffic flow or on the open road, as these algorithms proved insufficient. The system will detect an individual vehicle and track the actual time (not estimated) that the vehicle takes over a certain distance. In doing so, it will be able to display vehicles that do not provide relevant travel times, such as e.g. static vehicles and vehicles that are eliminated or included in traffic on the section in question.
The proportion of vehicles in the total traffic that the system will detect will be large enough to make the data on waiting times reliable and to be able to detect and correct any errors. The system will have the ability to detect the object/vehicle in all conditions (rain, sun, night).