METRICS TO EVALUATE MULTI-STAKEHOLDER AIRPORT CONTROL CENTER DECISION MAKING PROCESSES – A CRITICAL DISCUSSION

Since the beginning of the century, airport management decision-making processes have been under scientific discussion. The introduction of Airport Collaborative Decision Making (A-CDM) has set an operational standard which is a about to be succeeded by Total Airport Management and Performance Based Airport Management. Within the design and validation of these concepts and the necessary tools multiple assessments of the decision-making processes have been made. Although being under research for almost 20 years, the right selection of metrics to evaluate the decision-making processes remains still a challenge. Reflecting the different stakeholder objectives and the intricate dependent working processes into metrics and performance indicators is complex and was in some cases not sensitive to the operational improvement. Summarizing the experiences of the past, this paper suggests a novel approach towards the evaluation of airport control centre decision-making processes. This approach assesses performance on bases of comprehensive indicators such as costs and decision time which are valid for all stakeholders. It allows the application of computational power to calculate reliable reference values as well as to identify optimization potentials. Moreover, this paper suggests to encounter objective metrics for human factors aspects as well as to consider additional communication and personality indicators. Last but not least recurrence analysis and cross-lagged panel designs are introduced to analyse effects over time and causal relationships between human factors and performance indicators. This novel approach to decision-making evaluation leads away from single performance indicator selection and assessment to a more comprehensive evaluation of the airport in connection with highly sophisticated communication pattern analysis

The new Dynamic Driving Simulator at DLR

The DLR Institute of Transportation Systems is conducting research in driver's behaviour and interaction with advanced and future driver assistant systems. It has recently built up a large motion based simulator to be able to simulate driving situations and new assistance functions with a very high degree of realism. This paper will describe in detail the requirements and design ideas of the new simulator and show some first impressions of the simulator in operation. The simulator is a motion based system with a high quality large field of view projection system and carries a full vehicle cabin. An innovative hexapod design with the hydraulic cylinders hinged at the upper rim of the projection system delivers a very large motion envelope within only six meters ceiling height. Another benefit of the novel design is that the rotation point is lying in a plane below the actuator hinges, which promises a big advantage for tilt coordination. A modular rear-projection system with nine channels equipped with high resolution DLP-projectors offers a field of view of 270°x40° and a total resolution of about 8500x1240 pixels. The use of a rear projection system guarantees an unobstructed projection even with a large cockpit. The simulator is driven by a real passenger car, a VW Golf. This increases the driver's impression of reality dramatically. All driver control inputs are available via the vehicles bus-systems plus special sensors. A high quality steering force simulation enhances the controllability of the simulator

TAMS Simulation Concept Document

This document describes the Simulation Concept for the third and fourth TAMS project iteration. The main step from iteration-2 to Iteration-3/-4 with respect to the simulation is that the simulation shall implement the planning results of the connected tactical tools (AMAN/DMAN/SMAN/TMAN). This requires a feedback loop to be closed from the tools to the simulation. The document describes the functional requirements and the interfaces between the simulation and the TAM-suite, so that the development and implementation of the software can proceed

Total Airport Simulation supporting research for future airport management concepts

This paper describes a simulation suite for total airport simulation. This suite is being developed at the German Aerospace Center (DLR) to support research activities in the area of total airport management (TAM). The simulation suite is designed to simulate all processes relevant to the pre-tactical planning processes being investigated in TAM research, including flying aircraft, ground movements, turnaround process, and passenger movements. The simulation suite is designed to be very flexible in that simulation modules can be added or replaced easily

EPISODE3 - Gaming Exercise on Collaborative Airport Planning - Experimental Plan

This document describes the work to be carried out conducting a gaming exercise to evaluate collaborative airport planning, which shall lead to a more efficient utilization of airport resources. The methodology employed is to simulate reference scenarios i.e. current operations without collaborative planning, then to simulate those scenarios with collaborative planning, allowing comparison between the reference and modified scenarios. Results from the gaming exercise obtained at the local airport level will be analyzed by a network analysis model to obtain data about the effects of local replanning on the network. This analysis will also provide data that can be used as constraints in the planning at airport level. This will however not be addressed by the exercise

Dealing with Adverse Weather Conditions by Enhanced Collaborative Decision Making in a TAM APOC

The paper will provide an insight into enhanced collaborative decision making being conducted in adverse weather conditions in a simulated Oslo Airport environment within the framework of Total Airport Management research as it is being conducted by Europe’s ambitious Single European Sky ATM Research program (SESAR2020) as project PJ.04. SESAR 2020 is operated in two defined program waves, wave 1 covering the years 2016-2019 and wave 2 following until 2022. The paper will focus on a set of two out of seven V2 level validation exercises that are conducted in wave 1 of PJ.04’s Solution 2 (PJ.04-02), addressing concepts for Collaborative Airport Performance Management. The key aim of PJ.04-02 is to develop procedures, mechanisms and tools to support stakeholder groups that are cooperatively conducting airport operations, providing enhanced multi-stakeholder decision support especially in adverse conditions, such as bad weather, strikes, or unforeseen events such as runway blockages. In the Oslo Airport environment extreme snowy winter conditions are a major reason for performance degradation of airport operations. An enhanced integration of stakeholder actions and collaborative operations planning is expected to provide performance benefits. The philosophy of Collaborative Decision Making advocated by SESAR is that of ‘consensus’ building amongst the different airport stakeholders through a common impact assessment and a structured solution finding process with a mutually agreed solution. The goal is to have shared situation awareness and a collaborative problem solving approach leading to better, earlier and therefore more stable solutions. Orchestrated by a moderator, the so-called APOC supervisor, the global impact assessment is supported by each stakeholder assessing the impact on their own operations, documented in an electronic Impact and corresponding Solution Message. The validation and assessment of the underlying conceptual approach to collaborative airport performance management in adverse conditions requests for an artificial airport environment. In contrast to a live environment the simulated reality allows for any necessary changes in weather situation, traffic patterns or support system composition. The target level for the validation experiments is E-OCVM V2, requiring the simulators to allow for an operational concept feasibility assessment while providing simulation of all airport processes under consideration. APOC stakeholders’ support systems and interconnected airline operation back offices need to be connected to the central simulation database, ideally by standardized interfaces. The objective assessment of benefits credited to specific operational improvements under consideration of the validation exercises PJ.04-02.V2.04 and PJ.04-02.V2.09 requires a stepwise approach in which the functionality and system complexity is consecutively enhanced. The baseline was represented by the results achieved by SESAR 1, providing an APOC and basic processes and support system functionality. The functionality of the V2.04 setup reflected the SESAR 2020 solution regarding advanced decision support, providing dynamic Total Airport Demand and Capacity Balancing alongside a guided enhanced collaborative decision making process and enhanced meteorological forecasts by weather alerts. The V2.09 solution setup provides enhanced information support by further enhancing the functionality by provision of sophisticated operational and performance dashboard information, taking into account probabilities for additional diverted traffic. Two exercise simulation runs were executed for each setup, subjecting the Oslo operators with different meteorological phenomena and resulting operational challenges. The PJ.04-02 validation objectives were broken down into exercise specific objectives, allowing for an impartial feasibility assessment based on objective metrics and qualitative human performance criteria. Preliminary exercise analysis results indicate a well-received conceptual approach, the stepwise functionality enhancement complying with benefit increase expectations

EPISODE3 - Gaming Exercise on Collaborative Airport Planning - Simulation Report

This document describes the work to be carried out conducting a gaming exercise to evaluate collaborative airport planning, which shall lead to a more efficient utilization of airport resources. The methodology employed is to simulate reference scenarios i.e. current operations without collaborative planning, then to simulate those scenarios with collaborative planning, allowing comparison between the reference and modified scenarios. Results from the gaming exercise obtained at the local airport level will be analyzed by a network analysis model to obtain data about the effects of local replanning on the network. This analysis will also provide data that can be used as constraints in the planning at airport level. This will however not be addressed by the exercise