Dataset Information

Universal patterns in passenger flight departure delays.

ABSTRACT: Departure delays are a major cause of economic loss and inefficiency in the growing industry of passenger flights. A departure delay of a current flight is inevitably affected by the late arrival of the flight immediately preceding it with the same aircraft. We seek to understand the mechanisms of such propagated delays, and to obtain universal metrics by which to evaluate an airline's operational effectiveness in delay alleviation. Here we use big data collected by the American Bureau of Transportation Statistics to design models of flight delays. Offering two dynamic models of delay propagation, we divided all carriers into two groups exhibiting a shifted power law or an exponentially truncated shifted power law delay distribution, revealing two universal delay propagation classes. Three model parameters, extracted directly from dual data mining, help characterize each airline's operational efficiency in delay mitigation. Therefore, our modeling framework provides the crucially lacking evaluation indicators for airlines, potentially contributing to the mitigation of future departure delays.

SUBMITTER: Wang Y

PROVIDER: S-EPMC7181864 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Universal patterns in passenger flight departure delays.

Wang Yanjun Y Cao Yakun Y Zhu Chenping C Wu Fan F Hu Minghua M Duong Vu V Watkins Michael M Barzel Baruch B Stanley H Eugene HE

Scientific reports 20200423 1

Departure delays are a major cause of economic loss and inefficiency in the growing industry of passenger flights. A departure delay of a current flight is inevitably affected by the late arrival of the flight immediately preceding it with the same aircraft. We seek to understand the mechanisms of such propagated delays, and to obtain universal metrics by which to evaluate an airline's operational effectiveness in delay alleviation. Here we use big data collected by the American Bureau of Transp ...[more]

PMID: 32327671

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Project description:BACKGROUND:The development of satellite tracking technology enables the gathering of huge amounts of accurate data on animal movements over measured time intervals, to reveal essential information about species' patterns of spatial use. This information is especially important in optimizing the design of conservation and management strategies for endangered species. In this study, we analysed the main drivers of daily patterns in the flight activity of the threatened Bearded Vulture Gypaetus barbatus. We studied 19 Bearded Vultures tagged with solar-powered GPS transmitters from 2006 to 2016 in the Pyrenees (Spain). We assessed the relative influence of external factors (season and daylight time) and internal factors (sex, breeding season and territorial status) on their daily activity behaviour by computing mean hourly distance travelled, maximum displacement and cumulative distance travelled per hour. RESULTS:Our findings showed a clear difference in all the estimators between territorial and non-territorial (floating) members of the population, showing that non-territorial individuals spent much longer in flight and travelled larger distances per day. We detected an important influence of daylight time and season on the daily rhythms of Bearded Vultures; flight activity increased during the last three quarters of daylight and was greatest in the spring. Breeding period and sex had also an effect on the maximum displacement and cumulative distance travelled. Individuals flew more during the breeding period and females tended to exhibit greater cumulative and maximum distances per hour than males regardless of breeding season. CONCLUSIONS:Pyrenean Bearded Vultures flight daily activity was strongly influenced by daylight time, season, and territorial status, while individual sex and breeding season showed a milder effect on the birds' movement behaviour. This study gives a novel insight into how external factors act as main drivers of the daily flight activity pattern of a long-lived avian scavenger.

Dataset Information

Universal patterns in passenger flight departure delays.

Publications

Universal patterns in passenger flight departure delays.

Similar Datasets

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