TOPIC : Optimised ATM Network Services: TBO
|Publication date:||15 December 2016|
|Types of action:||SESAR-RIA Research and Innovation action|
|DeadlineModel: Opening date:||single-stage 15 December 2016||Deadline:||11 May 2017 17:00:00|
|Time Zone : (Brussels time)|
Topic DescriptionSpecific Challenge:
The sharing and management of trajectory information provides consistent information which allows the use of each flight’s agreed trajectory as a unique, common reference for decision-making. In a trajectory-based environment, the starting point for a flight’s agreed trajectory is the Extended Flight Plan (EFPL) that has been accepted by the NM and distributed to all concerned Air Navigation Service Providers (ANSP). The agreed trajectory is the trajectory that the Airspace User (AU) agrees to fly and the ANSP agrees to facilitate, and it is used as the basis of the tactical prediction of traffic demand. However, in Trajectory-Based Operations (TBO) constraints on the flight trajectory are not systematically applied unless it is necessary to do so to fulfil an Air Traffic Management (ATM) function (i.e. separation, arrival sequencing, etc.). For this reason, the agreed trajectory is not a 4D contract that the AU is expected to adhere to within specific tolerances, and when a deviation larger than a pre-defined value is detected the agreement will be automatically updated. Moreover, due to the dynamic nature of the ATM system, the ANSP may be unable to facilitate the trajectory as agreed; in such cases a Collaborative Decision Making (CDM) revision process will be triggered. The uncertainty over how the agreed trajectory will be executed is translated into an uncertainty on the prediction of the volume and complexity of traffic demand that is used as the basis for DCB.
With reference to the SJU Annual Work Programme 2016, this topic covers Section 3.5.4, sub Work area 1.2 topic b).
The exploratory research challenge is to explore how the two types of uncertainties associated with the agreed trajectory (AU-originated uncertainty and ATM-originated uncertainty) affect the quality of the prediction of traffic demand, and how their impact on the quality of the predictions and on the effectiveness of DCB processes may be mitigated.Scope:
This is an applications-oriented research topic. Consortia applying for this topic shall formulate a new operational improvement in their proposal, explain the rationale for their expectation that it will provide benefits, and develop how the project would perform an initial validation of their proposed concept. It is expected that the validation techniques include any of the validation techniques that are commonly used for concepts at low Technology Readiness Levels (TRL), including expert groups, and model based validations. Innovative validation approaches may also be proposed.
The research may propose new prediction models and metrics for better understanding current and predicted traffic patterns. For example, projects may develop methods for the continuous and automatic monitoring of post-operations data in order to identify where the quality of the prediction of demand is affected by divergence between the trajectories that were actually flown from the trajectories that were agreed, and possibly identify patterns that allow the anticipation of where new divergences may happen in the future and derive correction factors that will allow an improvement in the quality of the predictions.
Projects may also propose new methods for using trajectory data for evaluating the complexity of a particular flight-list in order to improve the prediction of controller workload, and explore new concepts for Short Term Air Traffic Control Flow Management Measures (STAM) for fine-tuning the agreed trajectories in order to limit complexity or in order to bound specific uncertainties with the objective of improving the quality of the prediction. Projects may also develop innovative TBO processes for modifying already agreed trajectories in order to solve a demand and capacity imbalance, or consider how TBO processes can support innovative dynamic sectorisation concepts.Expected Impact:
The research will contribute to the improvement of the effectiveness of DCB processes in a trajectory-based environment. This will have a positive impact on the safety and cost-efficiency of the ATM system.
Topic conditions and documents
Please read carefully all provisions below before the preparation of your application.
- List of countries and applicable rules for funding: described in part A of the General Annexes of the General Work Programme.
Note also that a number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon 2020 projects. See the information in the Online Manual.
- Eligibility and admissibility conditions: described in part B and C of the General Annexes of the General Work Programme and in the SJU Annual Work Programme.
Proposal page limits and layout: Please refer to Part B of the SJU proposal template in the electronic submission system.
3.1 Evaluation criteria and procedure, scoring and threshold: described in the SJU Annual Work Programme.
3.2 Submission and evaluation process: Guide to the submission and evaluation process
- Indicative timetable for evaluation and grant agreement:
Information on the outcome of single-stage evaluation: maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
- Provisions, proposal templates and evaluation forms for the type(s) of action(s) under this topic:
Research and Innovation Action:
Specific provisions and funding rates
Standard evaluation form
SJU Model Grant Agreement
6. Additional provisions:
Horizon 2020 budget flexibility
Technology readiness levels (TRL) – where a topic description refers to TRL, these definitions apply.
7. Open access must be granted to all scientific publications resulting from Horizon 2020 actions, and proposals must refer to measures envisaged. Where relevant, proposals should also provide information on how the participants will manage the research data generated and/or collected during the project, such as details on what types of data the project will generate, whether and how this data will be exploited or made accessible for verification and re-use, and how it will be curated and preserved.
This topic participates per default in the open access to research data pilot which aims to improve and maximise access to and re-use of research data generated by projects:
- The pilot applies to the data needed to validate the results presented in scientific publications. Additionally, projects can choose to make other data available for open access and need to describe their approach in a Data Management Plan (to be provided within six months after the project start).
- Note that the evaluation phase proposals will not be evaluated more favourably because they are part of the Pilot, and will not be penalised for opting out of the Pilot.
- Projects can at any stage opt-out of the pilot.
The legal requirements for projects participating in this pilot are in the article 29.3 of the Model Grant Agreement.
Further information on the Open Research Data Pilot is made available in the H2020 Online Manual.
9. SJU additional documents
No submission system is open for this topic.
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