AII aims to infer the most likely future intent based on current aircraft motion states, therefore, it has become an essential method to enhance air traffic situational awareness [1]. Generally, aircraft motion states consist of aircraft IDs, latitude/longitude/altitude coordinates, ground speeds, accelerations and heading angles, which could be directly gained from the surveillance infrastructures like Radars and Automatic Dependent Surveillance-Broadcast (ADS-B) systems. Given current aircraft motion states, one important issue in gaining future air traffic situation prediction is to infer aircraft intent. This is significant because AII plays a fundamental role in conflict detection and avoidance, which hence determines the operational safety of air transportation system.
Genetic algorithm and support vector machine based aircraft intent inference algorithm in terminal area
2012-10-01
1223279 byte
Conference paper
Electronic Resource
English
IEEE | 2012
|Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering
DOAJ | 2015
|Predicting Aircraft Intent in the Terminal Area
AIAA | 2012
|Predicting Aircraft Intent in the Terminal Area
British Library Conference Proceedings | 2012
|Intent inference for free flight aircraft
AIAA | 2000
|