The accident trends show the pilots do mistakes which can be divided into several groups where every year the percentage distribution of the accidents reaches similar values. The most accidents happen during landing and sometimes it is connected with engine failure. Some accidents happen after a chain of bad decisions which were made by the pilot. This article describes two approaches intended for accident rate mitigation. The first is a software tool which evaluates pilot's performance during the flight with respect of the airplane type which was used for the flight. The second tool replays certain phase of a flight with requirement imposed on the pilot to recognize beginning of potentially dangerous situations.The flight evaluation is performed based on the data recorded during the flight. The minimal set of recorded data is prescribed for the evaluation algorithm. The software performs evaluation against the flight envelope of the used airplane, against the terrain and surrounding traffic, and the airspaces surrounding the airplane. Before of these evaluations, an actual status of the airplane is determined with regards to the actual data and its history. The status of the airplane means e.g. taxiing, take off, climb, cruise, etc. This information is used in the evaluation algorithm to choose the right evaluation methods. Finally, a report about the violations of flight rules is generated with timestamps that allows simple localization of the identified moment. This software can be used for either data acquired during the flight tests on a simulator or on the data recorded during real flights. The second software tool is intended to preview situations which were identified as often repeating in the accidents reports. The selected accident type was identified and a description introducing the tested pilot into the situation and its background was prepared. Set of these descriptions is presented to thepilot and he gets familiar with the situations. Then the pilot undertakes a test where we watches simulated phase of a flight and he is supposed to determine moment where he identifies potentially dangerous situation. Based on the evaluation which compares tested pilot inputs with a time marks inserted in the scenario the algorithm evaluates pilot's ability to determine potentially dangerous situation. The aim is to show the pilot moments preceding the accident to help him to identify this situation in real life. The second aim to make the testing easier and allow for computer aided evaluation which makes the life of flight instructor easier. Finally, the pilots are allowed to control the scenarios tested by the second tool and their performance is evaluated with help of the first tool. The article shows examples of reports from the first tool and results of evaluation from the second tool.
[1]
Erik Blasch,et al.
Level 5 (User Refinement) issues supporting Information Fusion Management
,
2006,
2006 9th International Conference on Information Fusion.
[2]
E. P. Blasch.
Learning attributes for situational awareness in the landing of an autonomous airplane
,
1997,
16th DASC. AIAA/IEEE Digital Avionics Systems Conference. Reflections to the Future. Proceedings.
[3]
E. Thöndel.
DESIGN AND OPTIMISATION OF A MOTION CUEING ALGORITHM FOR A TRUCK SIMULATOR
,
2012
.
[4]
J. Leuchter,et al.
Investigation and measurement of aircraft communication system immunity
,
2012,
2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC).
[5]
Eloi Bosse,et al.
High-Level Information Fusion Management and System Design
,
2012
.
[6]
Evzen Thoendel.
Design and Optimal Control of a Linear Electromechanical Actuator for Motion Platforms with Six Degrees of Freedom
,
2011
.