Please use this identifier to cite or link to this item: https://doi.org/10.1109/ACCESS.2020.2963986
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dc.titleAssessment of flight block time reliability under different delay time windows: A case study
dc.contributor.authorTian, Y.
dc.contributor.authorWang, Q.
dc.contributor.authorLi, H.
dc.contributor.authorVanga, R.
dc.date.accessioned2021-08-24T02:39:34Z
dc.date.available2021-08-24T02:39:34Z
dc.date.issued2020
dc.identifier.citationTian, Y., Wang, Q., Li, H., Vanga, R. (2020). Assessment of flight block time reliability under different delay time windows: A case study. IEEE Access 8 : 9565-9577. ScholarBank@NUS Repository. https://doi.org/10.1109/ACCESS.2020.2963986
dc.identifier.issn2169-3536
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/198974
dc.description.abstractIn transportation field, reliability is the probability of reaching the destination from the starting point within the expected time. While the concept of reliability, including travel time reliability model and its evaluation indicators have been extensively studied in ground transportation, they are relatively very scarce in air transportation. Flight block time reliability not only exert a strong influence on passenger behavior but also greatly affect aerodromes, airlines and air traffic management, thus affecting the entire air transportation. This paper proposes a methodology for evaluating the flight block time under different delay time windows. We applied the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method to set windows which reflects different delays. We proposed a probabilistic model of flight block time based on a series system. A case study is performed to compare flight block time, flight air time, flight taxi-in time, and flight taxi-out time at different time reliability metrics with different delays. In particular, we found the best fit for each flight time segment of three delay time windows among nine well-known distribution functions to calculate the flight block time reliability indexes. Based on our analysis, we find that the reliability of delay time window 3 from 22:20- 23:00 to be relatively less compared to the other delay time windows. The results from the reliability estimation demonstrate that the model is efficient in estimating the reliability of flight block time in different delay time windows. @ 2013 IEEE.
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.sourceScopus OA2020
dc.subjectDBSCAN
dc.subjectflight block time reliability
dc.subjectflight delay
dc.subjectFlight operations
dc.subjectflight time distribution
dc.typeArticle
dc.contributor.departmentINDUSTRIAL SYSTEMS ENGINEERING AND MANAGEMENT
dc.description.doi10.1109/ACCESS.2020.2963986
dc.description.sourcetitleIEEE Access
dc.description.volume8
dc.description.page9565-9577
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