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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Cano, M. Sanchez-Escalonilla, P. Dorado, M.M. |
| Copyright Year | 2007 |
| Description | Author affiliation: Isdefe, Madrid (Cano, M.; Sanchez-Escalonilla, P.) |
| Abstract | The SESAR operational concept is based on the move away from tactical to strategic management of flights. The predictive capabilities of the European ATM network will be improved with the objective of taking more strategic actions prior to departure. This process will be supported by 4D trajectory information, managed on a shared network. In this paper, we present a methodology to analyze and react to the expected traffic flows that will take advantage of this more predictive ATM network. The method consists of dynamically adapting the configuration of the sectors to the future situations by predicting not only the traffic flows but also the complexity of those flows. Currently, the traffic volume that can be managed into the sector is determined by the declared capacity or maximum number of incoming aircraft per hour. However, with the same number of incoming aircraft, the complexity of the traffic can vary over time with a significant impact to the controller's workload. Low traffic complexity can lead to situations of low cost efficiency, or other situations could lead to a degraded safety level because of an increase in the number of ATC interventions, traffic in evolution or weather conditions. The measurement of traffic complexity would allow a more efficient use of human resources by balancing workload among the operative sectors, an increase in the flexibility of the capacity management by adapting the sector boundaries to the expected situation, more efficient decisionmaking support to protect controller from overloads, and, possibly, an overall capacity gain by allowing to break free from conservative figures based on the number of aircraft per sector. These expected improvements have pushed Aena, Spain's Air Navigation Service Provider, to develop a new tool called eTLM (Enhanced Traffic Load Monitoring) to measure and react to the traffic complexity. eTLM is based on the continuous complexity that takes into consideration up-to-date data rather than historical demand. Every sector's complexity is measured in terms of the controller's workload from the present time through the next few hours by means of continuous Fast-Time Simulations of planned traffic. eTLM uses this information to dynamically adjust sector configurations to the real traffic situation. The best sectorisation is determined based on a predefined set of possible combinations, avoiding workloads higher than the maximum acceptable safety level, minimizing the number of open sectors and balancing workloads between the operative sectors. This methodology, together with the associated operational concept was validated at Aena. Several fast-time and real-time simulations were looped in order to analyze the applicability and benefits of this concept in the Spanish airspace. The first assessment was carried out by applying the current operational practices. The second step was the validation of a future operational environment with new technical enablers such as MTCD and CPDLC. This paper will detail the consolidated results, conclusions and further steps of all the validation exercise. Safety, acceptability, efficiency and capacity were the main areas that were taken into account in the validation strategy. |
| File Size | 462436 |
| File Format | |
| ISBN | 9781424411078 |
| DOI | 10.1109/DASC.2007.4391890 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-10-21 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Air traffic control Telecommunication traffic Safety Traffic control Aerospace control Aircraft navigation Information management Communication system traffic control Costs Degradation |
| Content Type | Text |
| Resource Type | Article |
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