Airport Taxiway Traversal and Safety Optimization using Combinatorics
Rasmussen, Thore Groenlund
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The demand for air travel has increased dramatically in the last decade, putting large strain on airports and their limited resources. Expanding the available resources at an airport is not always an option either due to location, budget or time. This forces the administrators of an airport system to use the limited resources as efficiently as possible. This thesis proposes a tool for air traffic controllers and pilots that can be used when planning taxiway systems. Taking inspiration from Dijkstra’s Algorithm, an algorithm is proposed to safely move aircraft from the terminal to the runway. Applying constraints to the algorithm creates a program that can dynamically update the taxiway system schedule in near real-time while maintaining a safe environment. The objective of this thesis is to solve the taxiway-scheduling problem by proposing an algorithm for optimizing the path traversed by aircraft on the taxiway. The algorithm only handles departing aircraft to simplify the model. The origin and destination of each aircraft on the taxiway are static. The algorithm calculates the shortest path using nodes and weighted links. As more aircraft are added to the model, the algorithm can dynamically recalculate the schedule to ensure no safety constraints are violated. The model is created in Python 3 and utilizes the extensive library freely available. Inspiration for the taxiway system was taken from O’Hare International Airport in Chicago and the model uses a small part of the taxiway system. The algorithm consists of numerous smaller functions that can be altered and tested separately from the entire program, making debugging and testing easier as the model does not have to be run for every test. Compared to previous research in the field of taxiway-schedule optimization, this model proposes a new approach by using Python instead of commercial software packages. The algorithm takes inspiration from Dijkstra’s Algorithm to find the shortest path and then relies on several sub-functions with constraints to ensure safe aircraft taxiway traversal. The model uses a First-Come, First-Serve strategy that relies of delays to optimize the schedule and ensure aircraft safety.