Adapting Automated People Mover Capacity on Airports to Real-Time Demand Via Model-Based Predictive Control
Adapting Automated People Mover Capacity on Airports to Real-Time Demand via Model-Based Predictive Control M.P. van Doorne1, G. Lodewijks2, W.W.A. Beelaerts van Blokland3 1 Airbiz Aviation Strategies Ltd., 92 Albert Embankment, SE1 7TY, London, United Kingdom 2 University of New South Wales, School of Aviation, NSW 2052, Sydney, Australia 3Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands Abstract The Automated People Mover (APM) is an important asset for many airports to transport passengers inside or between terminal and satellite buildings An APM system normally runs on fixed schedules throughout the day, which means that the capacity of the APM is pre-determined and not depending on the actual demand. This at times can cause either an overcapacity, which leads to a waste of resources, or an under capacity, which results in passengers waiting at the station. Especially the latter factor is problematic, as it reduced passenger experience and can negatively affect the transfer process between airport facilities. In order to better match the offered APM capacity with the demand, it is proposed in this paper to use sensor-based predictive control system, which adapts the APM system capacity to real-time demand. By means of sensor data, passenger numbers are determined before they walk onto the stations platforms, and subsequently the APM system capacity is adjusted to the measured demand. In principle there are two methods to change the APM system capacity, i.e.: 1) by changing the APM capacity (i.e. more cars per train) or 2) by changing the frequency.
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