The project

Design and implementation of an Air Traffic Control safety console for information analysis and integration of operational and safety performance data.

The scope

The objective of this project was to develop a safety method that considers systemic and dynamic aspects of safety as part of an integrated safety management system. Risks emerge gradually from the interaction of stakeholders, but unfortunately nobody has the full picture to understand them. A technology is required to capture the ‘risk patterns’ that emerge from this interaction between stakeholders. To achieve a total optimisation of the system, the safety concept must address the trade-offs between safety and productivity. Because a lot of existing safety knowledge is captured in bow ties and barrier analysis, the safety concept must properly interface with bow ties together with risk patterns and data mining techniques.

Our solution

The Corballis Safety Management System and Pattern Matching System were configured to support air traffic controller decision-making and operational risk management. An ATM dashboard has been developed integrating aspects of complexity, safety and operations in air traffic control.

The ATM information solution consists of the following functions:

  • An ATM SMS dashboard which is a meaningful context for embedding a complexity metric along with operational and safety related data that the controllers need to do their job in monitoring traffic on the radar and in team coordination
  • A safety console that updates information about hazards and occurrences
  • The system supports the management of safety objectives including performance indicators
  • It receives feedback in terms of imminent hazards and safety barriers
  • Integration of information from different sources to serve both operational and safety requirements
  • A new safety method for relating complexity to hazards and risks
  • Monitoring of KPIs and responsibilities in applying barriers to hazards
  • Provision of data for applying data science approaches to identify risk patterns
  • Identification of daily hazards in a ATM dashboard
  • Evaluation of changes over time in leadership, safety programs and procedures
  • Implements a complexity metric that integrates a multiplicity of factors such as:
    • airspace capacity
    • traffic flows
    • separation procedures
    • pilot requests for new demands
    • weather restrictions
    • airport restrictions

The outcome

This project demonstrated how data science principles and use of risk intelligence can be applied to the design of an integrated safety information system. Our innovative approach to data collection techniques allowed the ATC operators to seamlessly integrate safety data (incidents/hazards/barriers) with operational information (weather, flight data, controller rosters) to calculate the complexity metric that defines thresholds of controller performance on day to day operations.

Technology stack

  • Corballis ATM Safety Management System
  • Corballis Pattern Matching System
  • Corballis KPI Monitoring System