ROGER: An On-Line Flight Efficiency Monitoring System using ADS-B Data
|Title:||ROGER: An On-Line Flight Efficiency Monitoring System using ADS-B Data||Authors:||Wang, Shen
|Permanent link:||http://hdl.handle.net/10197/9465||Date:||28-Jun-2018||Abstract:||Flight efficiency indicators reported monthly in the European area by the Performance Review Unit (PRU) help the air traffic management (ATM) community determine if excessive distances are being flown (compared with the ideal lengths of flight routes). Recent research, however, provides more indicators that comprehensively capture flight efficiencies in terms of other factors including fuel consumption, time adherence, and route charges. The efficacy of all of these indicators, however, is diminished as they are currently only available almost a month after flights take place. This is not sufficiently timely to use these indicators for the allevi- ation of unpredictable hotspots (i.e. sectors with congested air traffic), which often leads to unexpected ground delays. This paper proposes a methodology to calculate general flight efficiency indicators on-line in near real-time using nearest point search. A prototype system called ROGER (compRe- hensive On-line fliGht Efficiency monitoRing) is implemented using Apache Kafka and Spark. ROGER can digest large- scale heterogeneous datasets (i.e. mainly ADS-B data, the next generation aircraft surveillance technology) to compute indi- cators every 5 seconds. Our experiments on realistic datasets demonstrate that the proposed on-line indicator calculation method can achieve high accuracy compared with existing off-line approaches, and that ROGER can achieve desirable system performance in throughput and latency. A use case is also described showing how ROGER can assist in alleviating hotspots more effectively.||Funding Details:||Enterprise Ireland
European Commission Horizon 2020
|Type of material:||Conference Publication||Publisher:||IEEE||Other versions:||http://mdmconferences.org/mdm2018/index.html||Language:||en||Status of Item:||Not peer reviewed||Conference Details:||IEEE MDM 2018 - 19th IEEE International Conference on Mobile Data Management, Aalborg, Denmark, 26-28 June 2018|
|Appears in Collections:||Computer Science Research Collection|
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