An integrated software platform for airport queues prediction with application to resources management. (March 2018)

• Record Type: Journal Article
• Authors: Chiti, Francesco; Fantacci, Romano; Rizzo, Andrea
• Is Part Of: Journal of air transport management. Volume 67(2018)
• Page Start: 11
• Page End: 18
• Publication Date: 2018-03
• Subjects: Airports management -- Waiting time -- Security checkpoint management -- Semi-Markovian queueing model; Airlines -- Management -- Periodicals; Aeronautics, Commercial -- Management -- Periodicals; 387.7068
• DOI: 10.1016/j.jairtraman.2017.11.003
• Languages: English
• ISSNs: 0969-6997

Abstract

Abstract: Currently, one of the main issue for both Airport Operators and Passengers is to provide a quick access to the Airport facilities and to prevent congestion during peak periods. Towards this end, this paper proposes an integrated service software platform, that aims at enhancing both the airport management efficiency and the travel experience. Through the use of an analytical approach based on the queueing theory, the proposed platform is able to carefully forecast the waiting time at the security desks as well the required the number of active Security Control Counters, in order to improve the overall efficiency. The accuracy of the obtained analytical predictions has been validated by comparisons with real data obtained from a measuring campaign carried out in an airport environment. Based on the obtained results, the proposed platform can be considered as a practical support to achieve an efficient resource airport management and to improve the passengers Quality of Experience. Highlights: This paper proposes an integrated and flexible service platform suitable for airport operations management; in designing the software architecture, a modular approach has been adopted, with a focus on on the security checkpoint operations. A specific module has been characterized, named QCM, whose procedures are based on the G/M/c queueing analytical model. The accuracy of the proposed approach has been validated by a statistical analysis of data collected in the Pisa airport. The effectiveness of the proposed estimation approach is shown, by comparing the analytical predictions with data measured in the Pisa airport.