Quantifying collision potential in airport surface movement

Waldron, Timothy J.; Ford, Alexander C; Borener, Sherry

doi:10.1109/icnsurv.2013.6548655

Cited by 2 publications

(2 citation statements)

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“…V is the midpoint of RZ, corresponding to half the camera pixel width of 720 braking reaction times [40], the reaction time t varies among pilots, and in this paper, t is taken as the maximum value of 2 s. The distance 𝜑 1 travelled by the aircraft during the reaction time is:…”

Section: Methods Of Delineating the Wingtip Safety Protection Zonementioning

confidence: 99%

“…In addition to the original wingtip clearance σ , the distance travelled by the pilot at the current speed in a uniform linear motion during the reaction time and the distance between the application of the brakes to the full stop is also considered in the calculation. According to NASA research on pilot braking reaction times [40], the reaction time t varies among pilots, and in this paper, t is taken as the maximum value of 2 s. The distance φ 1 travelled by the aircraft during the reaction time is:

\begin{equation}{\varphi _1} = vt\end{equation}

where v is the taxiing speed of the aircraft without braking, and t is the reaction time.…”

Section: Methodsmentioning

confidence: 99%

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Research on conflict detection model for taxi‐in process on the apron based on aircraft wingtip keypoint detection

Zhang

Zhu

et al. 2022

IET Intelligent Trans Sys

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Apron safety is critical to aviation operations and aprons are prone to wingtip scraping accidents. However, few studies have been conducted on wingtip conflicts. In this paper, a class of aircraft conflict detection models based on wingtip keypoint detection is devised to solve the problem of wingtip scraping that may occur during the aircraft taxi‐in process on the apron. Firstly, a concise camera calibration technique is designed for the conversion between the pixel coordinate and the airport actual coordinate, which allows for the acquisition of high accuracy activity posture within the apron. Secondly, the static and dynamic safety protection zone delineation methods for wingtip conflict detection are given, taking the apron standard operating procedures and aircraft kinematic model into consideration. Then, the corresponding conflict detection models and algorithms are designed for the possible scraping between the vehicle and aircraft wingtips and between the aircraft and aircraft wingtips during the aircraft taxi‐in process on the apron. Finally, HRNet is selected to detect the keypoint of the wingtip by comparison, and the corresponding models and algorithm validation are carried out based on the apron physical sandbox. The verification results indicate that the models have strong accuracy and real‐time performance.

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Section: Methods Of Delineating the Wingtip Safety Protection Zonementioning

confidence: 99%

\begin{equation}{\varphi _1} = vt\end{equation}

where v is the taxiing speed of the aircraft without braking, and t is the reaction time.…”

Section: Methodsmentioning

confidence: 99%

Research on conflict detection model for taxi‐in process on the apron based on aircraft wingtip keypoint detection

Zhang

Zhu

et al. 2022

IET Intelligent Trans Sys

View full text Add to dashboard Cite

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Airline Safety Improvement Through Experience with Near‐Misses: A Cautionary Tale

2015

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In recent years, the U.S. commercial airline industry has achieved unprecedented levels of safety, with the statistical risk associated with U.S. commercial aviation falling to 0.003 fatalities per 100 million passengers. But decades of research on organizational learning show that success often breeds complacency and failure inspires improvement. With accidents as rare events, can the airline industry continue safety advancements? This question is complicated by the complex system in which the industry operates where chance combinations of multiple factors contribute to what are largely probabilistic (rather than deterministic) outcomes. Thus, some apparent successes are realized because of good fortune rather than good processes, and this research intends to bring attention to these events, the near-misses. The processes that create these near-misses could pose a threat if multiple contributing factors combine in adverse ways without the intervention of good fortune. Yet, near-misses (if recognized as such) can, theoretically, offer a mechanism for continuing safety improvements, above and beyond learning gleaned from observable failure. We test whether or not this learning is apparent in the airline industry. Using data from 1990 to 2007, fixed effects Poisson regressions show that airlines learn from accidents (their own and others), and from one category of near-misses-those where the possible dangers are salient. Unfortunately, airlines do not improve following near-miss incidents when the focal event has no clear warnings of significant danger. Therefore, while airlines need to and can learn from certain near-misses, we conclude with recommendations for improving airline learning from all near-misses.

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Quantifying collision potential in airport surface movement

Cited by 2 publications

References 0 publications

Research on conflict detection model for taxi‐in process on the apron based on aircraft wingtip keypoint detection

Research on conflict detection model for taxi‐in process on the apron based on aircraft wingtip keypoint detection

Airline Safety Improvement Through Experience with Near‐Misses: A Cautionary Tale

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