On the Utilisation of Fuzzy Rule-Based Systems for Taxi Time Estimations at Airports

The primary objective of this paper is to introduce Fuzzy Rule-Based Systems (FRBSs) as a relatively new technology into airport transportation research, with a special emphasis on ground movement operations. Hence, a Mamdani FRBS with the capability to learn from data has been adopted for taxi time estimations at Zurich Airport (ZRH). Linear regression is currently the dominating technique for such an estimation task due to its established nature, proven mathematical characteristics and straightforward explanatory ability. In this study, we demonstrate that FRBSs, although having a more complex structure, can offer more accurate estimations due to their proven properties as nonlinear universal approximators. Furthermore, such improvements in accuracy do not come at the cost of the model’s interpretability. FRBSs can offer more explanations of the underlying behavior in different regions. Preliminary results on data for ZRH suggest that FRBSs are a valuable alternative to already...

• Type: Journal
• Year: 2011
• Where: ATMOS
• Authors: Jun Chen, Stefan Ravizza, Jason A. D. Atkin, Paul Stewart
• Keywords: ATMOS 2011, Optimization, Regression Methods, Time Estimations, Zurich Airport