ITB 2017 Berlin Can we handle airport s future security challenges?

Transcription

1 ITB 2017 Berlin Can we handle airport s future security challenges? Bismarckstr Aachen, Germany Tel.: +49 (0) Fax.: +49 (0) mail@airport-consultants.com Internet: Olaf Junker, Managing Partner, Head of Software Development

2 Zahl der internationalen Passagiere in der EU (in Tausend) Intra EU Europa ohne EU Nordamerika Asien & Australien Afrika Mittel und Südamerika Airport Research Center - Fields of Expertise Market Analysis & Forecast Masterplanning & Architecture Capacity Planning & Simulation Software Product Development 2

3 CAST Airport Simulation CAST Airport Simulation Terminal Vehicle Aircraft Ground Handling Development partners Integration of landside and airside Dynamic linking of all processes and components Allocation and communication 3

4 Airport security Airport Security is required to assure a safe flight, avoid attacks and disturbances caused by passengers and/or staff Security measurements are based on juridical and law enforcement decisions, executed by either federal police and/or a service provider Security measurements change quickly, based on experience (e.g. regular security fail body scanner) Security requires close cooperation between all participating stakeholders Security takes time, effort and money, so reduce all of them. Security: Airport View 4

5 The passenger s view Most people understand the additional requirements, still although important, security at airports is annoying to the passengers. Passenger is forced through the airport, without possibility to change the primary facilities, increasing feeling of helplessness and passivity Basic human rights are violated, every time Security takes time and patience in an uncomfortable environment, so reduce waiting times (can do), and make waiting more comfortable (not our job). Security: Passenger s view 5

6 Airport Security vs. Passenger s Service Level Airport Security and Passenger s Service level appear to be contradictory an infinite number of controls is too expensive, and extensive waiting times will make person not fly anymore so what to do? The complex security process cannot be avoided, so use the buffers available, make a better prediction of what will happen. optimize security and waiting area layout optimize passenger flows optimize staff management investigate different options without expensive realtime tests, and pick the best. 6

7 Simulation: Investigations in a virtual environment Build a virtual model to investigate the real situation The model behaves like reality and allows investigations by parameter (KPI) variations A simulation model requires Security control layout (DXF Plans) Facilities: Transaction times, staffing rules Passenger Behaviour Passenger arrival profiles Desired Level of Service A simulation returns Waiting times Queue lengths Staffing 7

8 Detail: Staff allocation Currently, rough estimation and experience is the basis for staff planning at airports works sometimes, sometimes not. Based on the passenger arrival at the control, the simulation can allocate the staff efficiently, and the facilities work more efficiently. The Facility Requirement mode returns the opening times of the security control, given is a Maximum Waiting time or Queue Length. Obviously, the allocation algorithm needs a valid passenger arrival profile next sheet! 8

9 Detail: Estimating Passenger Arrival Profiles How to get the exact arrival profile in advance? The arrival behaviour of passengers is based on the actual flight schedule, which is known in advance Problem: The passenger numbers of the flights are unknown (missing data). Data Mining: Estimate the number of passengers based on historical data Extract rules and try to find historical patterns, and apply them to actual flight schedule, or other data sets, to apply the unknown values. 9

10 Executing the simulation, extracting the results When input data and rule sets are complete, the simulation can execute and returns Waiting Times and Queue Lengths the optimal staffing so the desired waiting time is not exceeded For comparison and optimization purposes, compare real data and prognosis data. Short-term effects (strike, fog, congestion) are not covered by long-term simulation, so At any time, based on the most actual data, a prediction for the rest of the day should be available. Waiting Times Staffing / Open Controls Prognosis vs. Reality 10

11 From planning to operations Planning: Simulation Input is usually prepared long-term, and executed days or weeks before Operational: The simulation is executed in short term, based on most actual data (flight schedule in real time with actual delays) With continuously updated real time data available, the simulation can be executed in short intervals (5-15 min) and always returns the best prognosis available. So, simulation turns from a planning tool into an operational tool, to be executed anywhere, any time, and from every different stakeholder s point of view. When real-time data is not available or shall be overruled (due to some reason staff reduction), the simulation can still be executed manually in short term. 11

12 State of the art, and the future Simulation tool usage have become mandatory as the complexity of interconnected airport layers cannot be managed manually anymore. Airports turn from reactive into pro-active because they know the short-term future Simulation becomes an operational prognosis tool, to be executed anywhere, any time, and from every different stakeholder s point of view. Several German and international airports use CAST real-time data prognosis simulation and staffing optimization and save a lot of money (no details here), while the passenger s service level is kept still, there are limits we re actually pushing successfully. 12