학술논문

A type-2 fuzzy modelling framework for aircraft taxi-time prediction
Document Type
Conference
Source
2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) Intelligent Transportation Systems (ITSC), 2017 IEEE 20th International Conference on. :1-6 Oct, 2017
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Fuzzy sets
Fuzzy logic
Aircraft
Uncertainty
Airports
Atmospheric modeling
Error compensation
taxi
fuzzy
uncertainty
aircraft
airport operations
ground movement
Language
ISSN
2153-0017
Abstract
Knowing aircraft taxi-time precisely a-priori is increasingly important for any airport management system. This work presents a new approach for estimating and characterising the taxi-time of an aircraft based on historical information. The approach makes use of the interval type-2 fuzzy logic system, which provides more robustness and accuracy than the conventional type-1 fuzzy system. To compensate for erroneous modelling assumptions, the error distribution of the model is further analysed and an error compensation strategy is developed. Results, when tested on a real data set for Manchester Airport (U.K.), show improved taxi-time accuracy and generalisation capability over a wide range of modelling assumptions when compared with existing fuzzy systems and linear regression-based methods.