Cellular automata for the investigation of navigation dynamics and aircraft mix in terminal arrival traffic

Investigating the impact of traffic mix and route flexibility on the arrival traffic dynamic within the terminal maneuvering area (TMA) is challenging, mainly due to the spatial constraints and wake turbulent separation requirements. In this study, we capture the dynamism of complex interactions and non-linearity in traffic by using a cellular automaton that is modified to enable more realistic representation of air traffic movements. Our results show that route flexibility makes traffic less sensitive to changes caused by size-based traffic mix and demonstrate the emergence of an organized flow zone in the fundamental diagram of the flexible strategies. When a gentle TMA saturation behavior is preferred, however, less flexible routes are deemed more suitable. As a general principle, we propose to adopt a mixed strategy that uses a fixed routing strategy at low TMA occupancies and a flexible routing strategy at medium to high TMA occupancies. • Weighted cell values facilitate the dynamic representation of agent sizes. • System condition modeling using neighborhood state-based transition probability. • Flexible agent navigation enabled by specialized cells and dynamic transition rules. • Identification of organized flow zone in flexible route selection strategies. • Improved system throughput through tactical strategy mix and condition awareness.