Advanced TFM Congestion Management Performance Analysis and Research Results
Abstract
This document describes the results of Fiscal Year 2009 (FY09) research on advanced congestion prediction and automated en route congestion resolution. An improved model for aggregate traffic demand prediction uncertainty was completed. Three different models for estimating the impact of weather on sector capacity were compared, and a hybrid solution is proposed. A new technique for developing rerouting options was developed for application to near-term, semi-automated congestion management tools. An existing sequential decision-tree approach for tactical, probabilistic congestion management was converted to a continual approach that can be realistically applied to real-time decision support. Finally, two methods for improving the performance of automation-developed congestion resolution maneuvers were studied: a partial-optimization approach that can consider multiple congestion resolution goals, and an approach for adapting to poor forecasts by explicitly planning deferred resolution maneuvers.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2009
- Accession Number
- AD1108352
Entities
People
- Anthony J. Masalonis
- Christine P. Taylor
- Claude K. Jackson
- Craig R. Wanke
- Lixia Song
- Norma J. Taber
- Stephen M. Zobell
Organizations
- MITRE Corporation