Towards better information transparency in the air traffic landing system: A novel agent-based model with implicit interactions

With the ever-increasing demands of air traffic flow management, its landing system requires fundamental improvements to meet the future needs. For the current landing system, information gaps between parties (i.e. pilots and air traffic controllers) cause interaction conflicts, which hinder a system's risks detection and mitigation. Therefore, a well-implementation of data-links can promise a better information transparency, by facilitating the development of team cognition and the execution of implicit interaction between parties to predictively adapt to changing conditions. To achieve it, this research proposes a smart interaction system based on the two agent-based models (ABMs), and further compared them to examine the improvements of a system's reliability and efficiency. Results show that implicit interaction significantly reduces the reactive actions needed to cope with congestions and system errors. Moreover, the efficiency of resource utilization is also improved without causing significant delay, and hence characterizes a more reliable and efficient landing system.