Predicting collisions between aircraft through spatiotemporal data-driven simulation of airport ground operations

Unsafe ground air traffic operations remain as one of the major concerns in the aviation system performance and have significantly jeopardized airport safety. With the significantly increased air traffic demand, reducing accidents/incidents during ground operations is important to aviation systems safety. While the volume of air traffic surging, areas across an airport could become compact, especially in ramp areas. Cramped and rapidly changing ramp areas can lead to higher risks of conflicting trajectories of aircraft and ground objects. Advanced operational data collection, modeling, simulation, and intervention methods are thus necessary for comprehending airport operational risks and preventing collisions. Advanced instrumentation of airports enabled airport management agencies to collect detailed trajectory data of aircraft for operational process analysis and simulation. A typical example is the ASDE-X data. In this paper, the authors established a quantitative data-driven spatiotemporal modeling approach that can simulate three scenarios around ramp areas during air traffic peak time for helping airport operators aware of collision risks between aircraft in ramp areas. The results indicate that this framework has the potential of fully utilizing ASDE-X data for supporting simulation and prognosis of airport operations. The ultimate goal is to develop an advanced collision prevention system in ramp areas.