Citation

Malygin I, Borodina O, Komashinsky V. Transp. Res. Proc. 2020; 50: 422-429.

Copyright

(Copyright © 2020, Elsevier Publications)

DOI

10.1016/j.trpro.2020.10.050

PMID

unavailable

Abstract

The decision-making model for controlling overland traffic at major airports serves as a prototype for high-traffic spaces with a complex structure. Traffic monitoring and control at major airports is facilitated by the Surface Movement Guidance and Control System (SMGCS). The use of the SMGCS poses several challenges, mainly because it is rather difficult to predict situations where human performance is involved. This paper provides statistics for airport accidents caused by overland traffic safety violations. We highlight the factors related to the overland vehicle drivers' traffic safety violations and list the airport environment factors that may endanger drivers. We also provide a rationale for a cognitive approach to dynamic situation analysis, aimed at predicting driver violations and based on cognitive analysis within the Decision Support System (DSS) algorithm. We design a functional DSS model that can be used to control overland traffic safety at major airports, and elaborate on the sources of data for the predictive algorithm.

Language: en

Keywords

cognitive data analysis; cognitive maps; controlled traffic region; decision support system; driver; hazard factors; operator; overland traffic; risk factors; traffic controller; traffic safety