Fast Aircraft Turnaround Enabled by Reliable Passenger Boarding

Michael Schultz
2018 Aerospace (Basel)  
Future 4D aircraft trajectories demand comprehensive consideration of environmental, economic, and operational constraints, as well as reliable prediction of all aircraft-related processes. Mutual interdependencies between airports result in system-wide, far-reaching effects in the air traffic network (reactionary delays). To comply with airline/airport challenges over the day of operations, a change to an air-to-air perspective is necessary, with a specific focus on the aircraft ground
more » ... raft ground operations as major driver for airline punctuality. Aircraft ground trajectories primarily consists of handling processes at the stand (deboarding, catering, fueling, cleaning, boarding, unloading, loading), which are defined as the aircraft turnaround. Turnaround processes are mainly controlled by ground handling, airport, or airline staff, except the aircraft boarding, which is driven by passengers' experience and willingness/ability to follow the proposed boarding procedures. This paper provides an overview of the research done in the field of aircraft boarding and introduces a reliable, calibrated, and stochastic aircraft boarding model. The stochastic boarding model is implemented in a simulation environment to evaluate specific boarding scenarios using different boarding strategies and innovative technologies. Furthermore, the potential of a connected aircraft cabin as sensor network is emphasized, which could provide information on the current and future status of the boarding process. Aerospace 2018, 5, 8 2 of 18 times. Typical standard deviations for airborne flights are 30 s at 20 min before arrival [8], but could increase to 15 min when the aircraft is still on the ground [9]. As Figure 1 demonstrates, the average time variability (measured as standard deviation) is higher in the flight phase (5.3 min) than in the taxi-out (3.8 min) and taxi-in (2.0 min) phase but significantly lower than the variability of both departure (16.6 min) and arrival (18.6 min) [10] . If the aircraft is departing the airport, changes with regards to the arrival time are comparatively small [11] . Thus, the arrival punctuality is clearly driven by the departure punctuality. Punctual air traffic operations depend on the performance of all parties involved (airlines, airport, network management, air navigation service provider). To achieve a target value of punctuality, airlines implement time buffers to compensate for deviations at the operational level. In 2016 only 80.5% of the flights were punctual (delay shorter than 15 min)-a decreasing trend since 2013, when there was 84% punctuality [10]. Aerospace 2018, 5, 8 2 of 18 departure times. Typical standard deviations for airborne flights are 30 s at 20 min before arrival [8], but could increase to 15 min when the aircraft is still on the ground [9]. As Figure 1 demonstrates, the average time variability (measured as standard deviation) is higher in the flight phase (5.3 min) than in the taxi-out (3.8 min) and taxi-in (2.0 min) phase but significantly lower than the variability of both departure (16.6 min) and arrival (18.6 min) [10] . If the aircraft is departing the airport, changes with regards to the arrival time are comparatively small [11] . Thus, the arrival punctuality is clearly driven by the departure punctuality. Punctual air traffic operations depend on the performance of all parties involved (airlines, airport, network management, air navigation service provider). To achieve a target value of punctuality, airlines implement time buffers to compensate for deviations at the operational level. In 2016 only 80.5% of the flights were punctual (delay shorter than 15 min)-a decreasing trend since 2013, when there was 84% punctuality [10] .
doi:10.3390/aerospace5010008 fatcat:5r77lctfbrfjxo7idq5n467ghe