1. Airspace Concept Evaluation System- State of Development
ACES
Airspace Concept
Evaluation System-
State of Development
Gano B. Chatterji
28 January 2010

2. With Arrival Merging and Separation
ACES Development Guided by Research Needs
Oceanic In-Trail Procedures
Traffic Flow Management
Multi-Sector Planner
Dynamic Airspace Configuration
Integrated Weather Information
Separation Assurance
With Arrival Merging and Separation
Super Density Operations
Trajectory Prediction Synthesis & Uncertainty
CDAs & Tailored Arrivals
Metroplex Operations
Merging and Spacing
Closely Spaced Parallel Runways
Arrivals/Departures Management 2
Enhanced Surface Operations 2

3. Main Points
ACES development driven by research needs; Ideas from research being folded into ACES.
Validation based on data and not just software; emphasis on plotting, visualization, analysis with large datasets.
Results produced by ACES are reasonable.
ACES is faster and more stable.
ACES has higher fidelity models (surface, terminal area trajectory, separation-assurance). 3

4. Outline ACES Development: Research Examples Using ACES:
Separation-Assurance
Traffic Flow Management
Dynamic Airspace Configuration
Weather Data Handling
Trajectory Generators
Weight Estimation
ACES Analyst and Viewer
User Support Helpdesk
Research Examples Using ACES:
Surface Operations
Dynamic Airspace Configuration and Traffic Flow Management Integration
System-Wide Study

5. Separation-Assurance - New Capabilities
Original Trajectory
Final Trajectory
Weather Polygon
Predicted
Actual
Weather:
Weather polygons used for defining weather avoidance areas.
Trajectory Prediction Uncertainties:
Can perturb the predicted trajectories to understand the effects of uncertainty.
Multiple Centers:
Can operate independent Separation Assurance agents in multiple geographic areas to study coordination issues.

6. Traffic Flow Management Support
Objective:
Flexible structure
Disable TFM for open-loop simulations.
Enable/disable TFM in airport, TRACON, center domains.
Support for alternative algorithms
Distributed TFM
Centralized TFM
Linear-Programming based Optimal TFM
Causality and delay attribution
Who caused it and where was it realized.
Approach:
Support services for demand and capacity prediction.
Improved plug-in architecture.
Messaging interface.
Simple GUI based configuration prior to simulation.

7. Dynamic Airspace Configuration Support
Objective:
Implement Dynamic Airspace Configuration algorithms in ACES.
Support for capacity (including workload) metrics.
Approach:
Data interface for ACES traffic and geometry outputs in Enhanced Traffic Management System (ETMS) format.
Communications service for data exchange with DAC algorithms running on other computers.
ACES modified to read back subsector data (sector building blocks).

8. Weather Service Provider Support
Objective:
Support for dynamic convective weather products.
Support for forecast weather products.
Support for grid-based and contour-based weather data.
Approach:
Unified service interface for querying weather data.
Error models for weather forecast from nowcast data when forecast data are unavailable.
Time-shift error
Position error
Severity and coverage error

9. Trajectory Generators
Objective:
Airport to airport trajectory generation.
Surface
Terminal area
Enroute
Choice of trajectory generators.
Approach:
Swappable trajectory generator interface.
Kinematic trajectory generator uses BADA performance tables.
Kinetic trajectory generator uses BADA aircraft performance data and atmosphere data.
Key Finding:
New trajectory generators being tested.
Performance data updated based on BADA 3.7.
Will improve ACES runtime performance.

10. Take-Off Weight Estimation
Objective:
Determine takeoff weight for planned flight using aircraft performance model, and reserve and maneuvering fuel requirement.
Approach:
Iterative procedure to determine fuel and payload.
A closed-form solution based on constant altitude cruise, and climb and descent fuel increment factors.
Key Finding:
Payload-range curves compare well with aircraft manufacturer published data.
Computationally efficient.

11. ACES Analyst Tool Enhancements
ACES Grid Creator
Generation of sector grid maps from ETMS sector files.
ACES Disambiguation Tool
Bug fixes and compatibility enhancements for use with the ACES Grid Creator.
ACES Analyst
Flight data set from ETMS data.
Multiple data converters to support scenario generation.
Analyst reports.
ACES Report Generator
Enhances to generate .csv file versions of the ACES National Metrics.
ACES Viewer
Replaces the current ACES VST during runtime.
ACES-SA Web Application
Viewing and analyzing conflict resolution.
SurfTools
Airport surface design tool (STLE) – STLE is part of ACES.
TASSE
ACES runtime configuration management system and surface and terminal area airspace design tool.

12. ACES Viewer Flexible tool for visualization
Airport, airspace and weather
Trajectories
Conflict scenarios
Trial-plan trajectories
As flown trajectories

13. User Support Helpdesk Purpose of the ACES Helpdesk :
A single point of contact for answering ACES questions.
Helpdesk Queries:
Users send queries to
Each query assigned a unique tracking number.
Communication via , using the tracking number, until query resolved.
Common queries during the first two months:
Locating ACES documentation.
ACES setup questions.

14. Research Examples

15. Safe and Efficient Surface Operations (SESO)
Objective:
Improve airport surface capacity and efficiency.
SESO concepts:
Trajectory based surface operations.
Optimized taxi scheduling.
ACES Modeling Capabilities:
Node-link based airport representation.
Time based taxi routes.
Integrated airport/TRACON simulation environment.

16. Separation Assurance Objective: Approach: Key Finding:
Maintain required separation between aircraft.
Meter aircraft at points in space.
Avoid weather hazards.
Approach:
Solve all problems in an integrated fashion for coordination and efficiency.
Key Finding:
Can resolve over 99% of all conflicts for 2X traffic with weather.

17. Dynamic Airspace Configuration
Objective:
Create sectors such that traffic is at or below capacity.
Approach:
Use Genetic Algorithm to select Voronoi polygon generating points.
Iterative partitioning.
Maximize transit-time and minimize boundary crossings.
Key Finding:
Capacity thresholds are not exceeded by traffic.
Delays are reduced.
New
Current
Num. of sectors 14 19
Num. of overloaded sectors 1
Num. of boundary crossings
2,471
2,851

18. Dynamic Airspace Units
Objective:
Capacity re-allocation by changing sector boundary.
Approach:
Exchanges ‘slices’ between sectors to address over-utilization.
Merges under-utilized sectors.
Key Finding:
Minor adjustments rather than a complete boundary change.
ZOB66A workload higher
ZOB66B and ZOB66C units are assigned to sector ZOB67 (left).

19. Dynamic Airspace Configuration and Traffic Flow Management Integration
Objective:
Study interaction between airspace configuration and traffic flow management.
Approach:
Integration using data and ACES simulations.
Key Finding:
TFM delay can be determined as a function of number of sectors.
Sectors can be designed to reduce delays due to mismatch between demand and capacity.

20. System-Wide Weather Effect Study
Objective:
Establish weather affected baseline data for common scenario days.
Determine yearly weather delays for current day operations.
Assess the ability of Separation-Assurance, Traffic Flow Management and Dynamic Airspace Configuration to reduce delay in the presence of weather.
Approach:
17 days of traffic, wind, weather, AAR/ADR, FAA data from 2006 collected.
Traffic volume: low and high
Weather: light, moderate and severe
Average arrival delay with 2006, 2018 and 2025 assumed traffic and capacities computed.

21. Common Scenario Generation
Current Day (2006)
Cluster Analysis
NAS Data Gathering
Database Generation
NAS state data
NAS weather data
NAS wind data
Airport Capacity and State
VAMS
ASPM
JPDO-SMAD + ASPM + VAMS
Airport Taxi Times
Expanded ACES Airport database
Most frequently used terminal area configurations
Runway modeled airports (FAA Metro 7 airports)
Added aircraft types
Terminal Area Transit Times
Data Gathering
Updated ACES transit times
Sector Enhancements for use with ACES
2006 and 2007 Sector models
Correction of “Gaps and Overlaps” laterally and vertically
Alignment of sector boundaries
Oceanic coverage
Demand Generation (TAF 2008)
1.0x, 1.1x (NGIP (2018)), 1.2x (NextGen (2025)), 1.5x, 2.0x, 2.5x, and 3.0x.
Unconstrained version of demand
Constrained (time shifted) version of demand
NGIP (2018) configuration
NextGen (2025) configuration

22. Parting Thoughts
ACES development driven by research needs; Ideas from research being folded into ACES.
Validation based on data and not just software; emphasis on plotting, visualization, analysis with large datasets.
Results produced by ACES are reasonable.
ACES is faster and more stable.
ACES has higher fidelity models (surface, terminal area trajectory, separation assurance).