Traffic Prediction Based on Online Vehicle Position Information for Simulation, Validation and Controller Resource Allocation Purposes

In the context of the dynamic transportation system, advancements in modern technological elements have facilitated the real-time, online transmission of vehicle positional data across numerous transport subsectors. Such data can be made accessible in a format that underpins the validity of simulations aimed at accurately representing real-world processes. In response to the prevailing trends of automation within air traffic control, there is an increasing imperative to develop a testing environment that allows for the simulation of automated system operations. This encompasses not only the examination of conflict resolution algorithms but also the exploration of human–machine collaboration. While archival traffic data can be readily obtained, they primarily capture the current functioning of the transportation system as a result of past control processes. Therefore, to ensure reliable testing of automation, it is essential to generate traffic demand based on real data through estimation methodologies.