IMHOTEP: Integrated Multimodal Airport Operations For Efficient Passenger Flow Management
1 January 2020 - 31 August 2022
With IMHOTEP, the Amsterdam University of Applied Sciences (AUAS) has developed an operational concept and set of data analysis methods, predictive models and decision support tools. This allows information sharing, common situational awareness and real-time collaborative decision-making between airports and ground transport stakeholders.
Airport as a multimodal connection platform
The airport of the future is expected to become a multimodal connection platform, allowing travellers to reach their destination through the most efficient and sustainable combination of modes. It will also allow the airport and its surrounding region to make better use of their resources. The IMHOTEP project increased transparency in terms of airport transport systems information. This enhanced decision-makers’ ability to realize potential improvements, resulting in a four-hour (or less) door-to-door travel time in Europe.
A four-step methodological approach
The specific approach of IMHOTEP involved:
- Proposing an operational concept that increased an airport’s collaborative decision-making to ground transport stakeholders, including local transport authorities, traffic agencies, transport operators and mobility service providers.
- Developing new data collection, analysis and fusion methods to provide a comprehensive view of the door-to-door passenger trajectory. This involved the coherent integration of different types of high resolution passenger movement data collected from personal mobile devices and digital sensors.
- Developing predictive models and decision support tools to anticipate the evolution of airport passenger flows within the day of operations, and assess the operational impact on both airport processes and the ground transport system. The ultimate goal here was to enable real-time collaborative decision-making between airports, ground transport stakeholders and passenger information services.
- Validating the proposed concept and newly-developed methods and tools through a set of case studies. These case studies were conducted in direct collaboration with airports, local transport authorities and transport operators. They covered two airports with heterogeneous characteristics and serve different markets – Palma de Mallorca Airport and London City Airport.
The researchers developed computer models of the airports’ terminal buildings to simulate passenger trajectories once they enter the building. They then performed analysis to identify particular KPIs of interest for the project partners. They also used a simulation-optimization methodology that the group of Dr. Mujica Mota have been developing in recent years.
Education
In terms of education, this research can serve as a case study for reducing variability and sharing information to improve the performance of systems. A variety of deliverables were also produced at international conferences (such as the Winter Simulation Conference, Sesar Innovation Days, MULTILOG or EUROSIM) and in reports to the European Commission.
Funding and partners
This project was funded by Horizon (H2020) and SESAR. The project involved a consortium of partners: Nommon Solutions And Technologies Sl (Spain), Ingeniería De Sistemas Para La Defensa De España S.A.-S.M.E. M.P. (Spain), Aimsun S.L. (Spain), Aena S.M.E. S.A. (Spain), Empresa Municipal De Transports Urbans De Palma De Mallorca S.A. (Spain), Amsterdam University Of Applied Sciences (The Netherlands), Cranfield University (The United Kingdom), London City Airport Limited (The United Kingdom), Technische Universitat Dresden (Germany).
Some of these partners were scientific collaborators, while the airports provided information and data for the simulations. An advisory board composed mainly of experts from IGAMT also participated.
Contact
For more information, please contact Miguel Mujica Mota.
Airport and Airspace Capacity line of research
This project was conducted within the Airport and Airspace Capacity line of research. Airport and Airspace Capacity research uses computer modelling, mathematical programming, algorithmic development and even a combination of all three to understand and improve systems at an airport or across an entire network.