This study tackles the gate allocation problem (GAP) at the airport terminal, considering the current covid-19 pandemic restrictions. The GAP has been extensively studied by the research community in the last decades, as it represents a critical factor that determines an airport's capacity. Currently, the airport passenger terminal operations have been redesigned to be aligned and respect the covid-19 regulation worldwide. This provides operators with new challenges on how to handle the passengers inside the terminal. The purpose of this study is to come up with an efficient gate allocator that considers potential issues derived by the current pandemic, i.e., avoid overcrowded areas. A sim-opt approach has been developed where an evolutionary algorithm (EA) is used in combination with a dynamic passenger flow simulation model to find a feasible solution. The EA aims to find a (sub)optimal solution for the GAP, while the simulation model evaluates its efficiency and feasibility in a real-life scenario. To evaluate the potential of the Opt-Sim approach, it has been applied to a real airport case study.
This study examines the effect of seat assignment strategies on the transfer time of connecting passengers at a hub airport. Passenger seat allocation significantly influences disembarkation times, which can increase the risk of missed connections, particularly in tight transfer situations. We propose a novel seat assignment strategy that allocates seats to nonpaying passengers after check-in, prioritising those with tight connections. This approach diverges from traditional methods focused on airline turnaround efficiency, instead optimizing for passenger transfer times and reducing missed connections. Our simulation, based on real-world data from Paris-Charles de Gaulle airport, demonstrates that this passenger-centric model decreases missed connections by 12%, enhances service levels, reduces airline compensation costs, and improves airport operations. The model accounts for variables such as seat occupancy,luggage, and passenger type (e.g., business, leisure) and is tested under various scenarios, including air traffic delays.
MULTIFILE
Amsterdam Airport Schiphol has faced capacity constraints, particularly during peak periods. At the security screening checkpoint, this is due to the growing number of passengers and a shortage of security staff. To improve operating performance, there is a need to integrate newer technologies that improve passing times. This research presents a discrete event simulation (DES) model for the inclusion of a shoe scanner at the security screening checkpoint at Amsterdam Airport Schiphol. Simulation is a frequently used method to assess the influence of process changes, which, however, has not been applied for the inclusion of shoe scanners in airport security screenings yet. The simulation model can be used to assess the implementation and potential benefits of an optical shoe scanner, which is expected to lead to significant improvements in passenger throughput and a decrease in the time a passenger spends during the security screening, which could lead to improved passenger satisfaction. By leveraging DES as a tool for analysis, this study provides valuable insights for airport authorities and stakeholders aiming to optimize security screening operations and enhance passenger satisfaction.
More and more aged people are joining the traffic, either using a passenger car or through a special low speed two-seater for in-city use. For elderly people, self-management in staying mobile is an essential part of their quality of life. However, with increased involvement of elderly in traffic, the risk of serious accidents increases, especially in cities. Fortunately, a rapid development of innovative technology is shown in vehicle design, with focus on advanced driver support, herewith referred to as ‘ambient intelligence’. This holds a promise to improve the safety situation, under the condition that adaption to the elderly driver’s need is accounted for. And that is not a straightforward issue, since ‘no size fits all’. With increasing age, we see an increased variety in driving skills with emphasis on cognitive, perceptual and physical limitations. In addition, people may suffer from diseases with a neurological background or other (cardiopulmonary disease, obesity or diabetes). The partners in this project have expressed the need to survey the feasibility of ‘ambient intelligence’ technology for low-speed vehicles also addressing E-Health functions to bring people safely home or involve medical help in case of health-critical situations. The MAX Mobiel make their vehicle available for that, and will help to guard the elder customer demand. The HAN Automotive Research team carries out the research, in cooperation with the HAN professorship on E-Health. Hence, both the automotive technology part of the HAN University of Applied Sciences as well as expertise from the Health oriented part of the HAN are included, being essential to successfully extend the relevant technologies to a fully integrated elderly driver support system, in the future. Noldus Information Technology is involved on the basis of their knowledge in human monitoring (drive lab) and data synchronization. The St. Maartenskliniek (Nijmegen) brings in their experience with people being restricted in physical or neurological sense.
