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

Yuhan Li,

Shuguang Zhang, Yibing Wu

и другие.

Aerospace, Год журнала: 2024, Номер 11(12), С. 1020 - 1020

Опубликована: Дек. 11, 2024

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

Язык: Английский

A New Era in Human Factors Engineering: A Survey of the Applications and Prospects of Large Multimodal Models DOI
Fan Li, Han Su, Ching‐Hung Lee

и другие.

International Journal of Human-Computer Interaction, Год журнала: 2025, Номер unknown, С. 1 - 14

Опубликована: Янв. 19, 2025

Язык: Английский

Процитировано

1
User Need Prediction Based on a Small Amount of User-Generated Content—A Case Study of the Xiaomi SU7 DOI Creative Commons
Lingling Liu, Biao Ma

World Electric Vehicle Journal, Год журнала: 2024, Номер 15(12), С. 584 - 584

Опубликована: Дек. 19, 2024

(1) Background: In the current competitive market environment, accurately forecasting user needs is crucial for business success. By analyzing user-generated content (UGC) on social network platforms, enterprises can mine potential and discern shifts in these needs, thereby enabling more efficient precise product design that aligns with needs. For newly launched products a limited presence market, scarcity of UGC poses challenge to businesses seeking predict from small datasets. (2) Methods: To address this challenge, paper proposes model using correlation analysis (CA) linear regression (LR) combined multidimensional gray prediction (a CA-LR-GM (1, N) model) help use sample data Using Xiaomi SU7 as case study, demonstrates vehicle refines outcomes through an optimization informed by principle optimal key feature distribution. (3) Results: The findings validate feasibility proposed theoretical framework, offering technical solution identification need trends. (4) Conclusions: This research puts forward strategic recommendations regarding their products.

Язык: Английский

Процитировано

3
Understanding emotional values of bionic features for educational service robots: A cross-age examination using multi-modal data DOI
N. Y. Wang,

Zengrui Li,

Di Shi

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102956 - 102956

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

1
An Objective Handling Qualities Assessment Framework of Electric Vertical Takeoff and Landing DOI Creative Commons

Yuhan Li,

Shuguang Zhang, Yibing Wu

и другие.

Aerospace, Год журнала: 2024, Номер 11(12), С. 1020 - 1020

Опубликована: Дек. 11, 2024

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

Язык: Английский

Процитировано

0