An Objective Handling Qualities Assessment Framework of Electric Vertical Takeoff and Landing

Assessing handling qualities is crucial for ensuring the safety and operational efficiency of aircraft control characteristics. The growing interest in Urban Air Mobility (UAM) has increased the focus on electric Vertical Takeoff and Landing (eVTOL) aircraft; however, a comprehensive assessment of eVTOL handling qualities remains a challenge. This paper proposed a handling qualities framework to assess eVTOL handling qualities, integrating pilot compensation, task performance, and qualitative comments. An experiment was conducted, where eye-tracking data and subjective ratings from 16 participants as they performed various Mission Task Elements (MTEs) in an eVTOL simulator were analyzed. The relationship between pilot compensation and task workload was investigated based on eye metrics. Data mining results revealed that pilots’ eye movement patterns and workload perception change when performing Mission Task Elements (MTEs) that involve aircraft deficiencies. Additionally, pupil size, pupil diameter, iris diameter, interpupillary distance, iris-to-pupil ratio, and gaze entropy are found to be correlated with both handling qualities and task workload. Furthermore, a handling qualities and pilot workload recognition model is developed based on Long-Short Term Memory (LSTM), which is subsequently trained and evaluated with experimental data, achieving an accuracy of 97%. A case study was conducted to validate the effectiveness of the proposed framework. Overall, the proposed framework addresses the limitations of the existing Handling Qualities Rating Method (HQRM), offering a more comprehensive approach to handling qualities assessment.

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Publication Details

Journal
Aerospace
Published
2024-12-11
DOI
https://doi.org/10.3390/aerospace11121020
Citations
3
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
1.93

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article

An Objective Handling Qualities Assessment Framework of Electric Vertical Takeoff and Landing

Michael Zintl, Sharina Kimura, Florian Holzapfel, Yuhan Li et al.
3 citations
Aerospace
Human-Automation Interaction and Safety
1.93
article

An Objective Handling Qualities Assessment Framework of Electric Vertical Takeoff and Landing

Michael Zintl, Sharina Kimura, Florian Holzapfel, Yuhan Li, Shuguang Zhang, Yibing Wu
article en
3 citations

Abstract

Assessing handling qualities is crucial for ensuring the safety and operational efficiency of aircraft control characteristics. The growing interest in Urban Air Mobility (UAM) has increased the focus on electric Vertical Takeoff and Landing (eVTOL) aircraft; however, a comprehensive assessment of eVTOL handling qualities remains a challenge. This paper proposed a handling qualities framework to assess eVTOL handling qualities, integrating pilot compensation, task performance, and qualitative comments. An experiment was conducted, where eye-tracking data and subjective ratings from 16 participants as they performed various Mission Task Elements (MTEs) in an eVTOL simulator were analyzed. The relationship between pilot compensation and task workload was investigated based on eye metrics. Data mining results revealed that pilots’ eye movement patterns and workload perception change when performing Mission Task Elements (MTEs) that involve aircraft deficiencies. Additionally, pupil size, pupil diameter, iris diameter, interpupillary distance, iris-to-pupil ratio, and gaze entropy are found to be correlated with both handling qualities and task workload. Furthermore, a handling qualities and pilot workload recognition model is developed based on Long-Short Term Memory (LSTM), which is subsequently trained and evaluated with experimental data, achieving an accuracy of 97%. A case study was conducted to validate the effectiveness of the proposed framework. Overall, the proposed framework addresses the limitations of the existing Handling Qualities Rating Method (HQRM), offering a more comprehensive approach to handling qualities assessment.

AerospaceVol. 11(12)
Technical University of Munich (DE), Beihang University (CN)
National Natural Science Foundation of China, China Scholarship Council
Sustainable cities and communities
Openalex Percentile: Top 13%
Human-Automation Interaction and Safety
1.93
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