Research is important for To70 for several reasons. First and foremost it allows To70 to stay up-to-date with the latest developments and actively shape those developments. Also, the increased understanding of these developments improves To70 consultancy services and competitiveness. Some of the research projects are carried out in collaboration with universities and clients.
Air Traffic Controller support during Continuous Descent Operations
To70 and Delft University of Technology collaborate in a four year research project to develop a controller support tool for CDA operations.
A time-space diagram is the basis of the tool, which is commonly used to solve transportation related problems. Application as an air traffic controller support tool is new. The time-space diagram provides the controller with task relevant information derived from air- or ground-based trajectory predictors and supports the controller in planning his actions for a conflict free and efficient operation.
This research is supported in part by a grant from the Netherlands Organisation for Scientific Research (NWO), under the Casimir programme.
Solution space complexity as controller workload metric
To70, Delft University of Technology and Air Traffic Control the Netherlands, are developing a new controller workload metric based on the concept of “solution space”. The solution space is defined as the subset of all possible vector commands that can be issued by a controller. High correlations between several properties of the solution space and the self-reported task difficulty have been found, supporting the hypothesis that operator workload is primarily caused by the difficulty of the task to be conducted.
To70 is working on implementation of this metric in fast time simulation to improve controller workload estimations of concepts evaluated in desktop studies.
Airport Simulation Model for optimal runway location from a network perspective
To70 and the Delft University of Technology have constructed a detailed network model to evaluate hub performance and robustness to degraded weather conditions. The model is used to quantify the network performance in terms of flight delays and NOC-costs for different alternative runway layouts, thereby allowing for long term developments to be evaluated. Whereas models to evaluate environmental impact and safety implications are widely available, models evaluating hub performance based on weather conditions are not. This model is an innovative approach to quantify the impact of different runway configurations on operational performance from an airline perspective.
Context‐Aware Adaptive Automation for Air Traffic Control
Despite the benefits and huge advances in (aviation) automation over the last decades, the current automated tools are in many cases unaware of the ‘bigger picture’. That is, they are not yet able to understand the intentions of users or the intricacies of the environment it is operating in. When the level of automation support in future air traffic control increases, the automated systems will need more awareness about the dynamic context in which they operate.
To70 and Delft University of Technology collaborate in a four year research project to provide fundamental insight into, and practical experience with, the difficult challenge of adaptive automation and level of automation transitioning in a human-centred air traffic control work environment. An innovative element in this research project is the development of autonomous, environmentally-driven adaptive automation, where the appropriate level of automation will be determined by the functional demands of the operational context. The goals are: (1) to discover the metrics that constitute an operational context, and (2) to develop a rule base for level switching and human-machine interface adaptation.
The focus will be on a subset of the air traffic controller’s operational context, namely ‘spacing and merging’ tasks. In order to capture the constraints imposed by the surrounding traffic, the ‘Solution Space’ methodology, developed by Delft University of Technology, will be used and extended to the full three dimensions. Attempts will be made to identify parameters in the solution space that correlate with the complexity of a traffic situation, and investigate and experimentally test how these parameters can be employed to determine the context and the rules to switch between the levels of automation.