Markov chain-based flight operations risk analysis

Wang, Wei; Zhang, Tianwei; Wang, Lin

doi:10.1109/fskd.2017.8393157

Cited by 4 publications

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Subsequently, they proposed a new algorithm based on the rough set theory and a particle swarm multi-objective optimization algorithm [24] to analyze the flight safety risk. Some scholars divided the safety incident subspace according to the value of each parameter in the QAR and then constructed the state transition function of risk based on the Markov model [25]. Liu et al [26] studied the risk assessment model of a safety incident and defined the risk as the probability of occurrence and the severity of the incident.…”

Section: Flight Safety Analysismentioning

confidence: 99%

An Unsupervised Learning Approach for Analyzing Unsafe Pilot Operations Based on Flight Data

Qian

Chen

et al. 2022

Applied Sciences

View full text Add to dashboard Cite

Flight safety is a hot topic in the aviation industry. Statistics show that safety incidents during landing are closely related to the flare phase because this critical period requires extensive pilot operations. Many airlines require that pilots should avoid performing any forward stick inputs during the flare. However, our statistical results from about 86,504 flights show that this unsafe pilot operation occasionally happens. Although several case studies were conducted previously, systematic research, especially based on a large volume of flight data, is still missing. This paper aims to fill this gap and provide more insights into the issue of pilots’ unsafe stick operations during the flare phase. Specifically, our work is based on the Quick Access Recorder (QAR) data, which consist of multivariate time-series data from various flight parameters. The raw data were carefully preprocessed, then key features were extracted based on flight expert experience, and a K-means clustering algorithm was utilized to divide the unsafe pilot operations into four categories. Based on the clustering results, we conducted an in-depth analysis to uncover the reasons for different types of unsafe pilot stick operations. In addition, extensive experiments were conducted to further investigate how these unsafe operations are correlated with different factors, including airlines, airports, and pilots. To the best of our knowledge, this is the first systematic study analyzing pilots’ unsafe forward stick operations based on a large volume of flight data. The findings can be used by airlines to design more targeted pilot training programs in the future.

show abstract

Section: Flight Safety Analysismentioning

confidence: 99%