Abstract
In 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.
Highlights
As the economy is growing, more passengers are choosing air travel as a preferred option
As the delay time is the comprehensive manifestation of flight operations, it is used as an input parameter for Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to cluster different delay time windows; 3) As per our knowledge, no research was carried out to fit the distribution of flight block time, flight air time, flight taxi-out time, and flight taxi-in time in literature and present models for determining the flight block time reliability
FLIGHT BLOCK TIME RELIABILITY MODEL AND RELIABILITY INDEX we present a methodology to set up the delay time window based on departure delay time and arrival delay time by using DBSCAN algorithm
Summary
As the economy is growing, more passengers are choosing air travel as a preferred option. Y. Tian et al.: Assessment of Flight Block Time Reliability Under Different Delay Time Windows: Case Study. According to [4], the airport taxiingout and taxiing-in are the critical phases in flight operation During these phases, the pilots have the least technical means to rely on and their workload is relatively higher than flight air time phase which increases the likelihood of the delays [5]. This article focuses on addressing the following questions: 1) How to build a reliability model for flight block time and set delay time windows which are consistent with flight operating characteristics?.
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