Athens in Greece is the city selected to host the 2004 Olympic Games. Many simulations and analyses have been performed in order to properly approach the logistics problems arising from such an event. In this paper we address one of these problems. More precisely, we present a model for analyzing the terminal of AIA (Athens International Airport) under three different scenarios: (i) a historic scenario, based on a typical “busy day”, (ii) a foreseeable scenario with AIA becoming a hub and increasing its traffic volume, and (iii) a traffic intense scenario, as expected during the 2004 Olympic Games. The airport simulation is performed through the OPAL platform. While the airside analysis does not evidence any major cause of congestion, the landside, evaluated through an enhanced version of the Simple Landside Aggregate Model (SLAM), shows possible situations of congestion with a consequent degradation in the level of service provided. The use of SLAM allows signaling out the bottlenecks and the corresponding possible causes. A simple modification in the airport policies is sufficient to significantly improve the overall performance.
Evaluating Terminal Management Performances Using SLAM: The Case Of Athens International Airport
ANDREATTA, GIOVANNI;BRUNETTA, LORENZO;RIGHI, LUCA
2007
Abstract
Athens in Greece is the city selected to host the 2004 Olympic Games. Many simulations and analyses have been performed in order to properly approach the logistics problems arising from such an event. In this paper we address one of these problems. More precisely, we present a model for analyzing the terminal of AIA (Athens International Airport) under three different scenarios: (i) a historic scenario, based on a typical “busy day”, (ii) a foreseeable scenario with AIA becoming a hub and increasing its traffic volume, and (iii) a traffic intense scenario, as expected during the 2004 Olympic Games. The airport simulation is performed through the OPAL platform. While the airside analysis does not evidence any major cause of congestion, the landside, evaluated through an enhanced version of the Simple Landside Aggregate Model (SLAM), shows possible situations of congestion with a consequent degradation in the level of service provided. The use of SLAM allows signaling out the bottlenecks and the corresponding possible causes. A simple modification in the airport policies is sufficient to significantly improve the overall performance.
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