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1 Market-based DEMAND MANAGEMENT strategies Giovanni Andreatta, University of Padova Lorenzo Brunetta, Milan Polytechnic Un. Guglielmo Guastalla, Eurocontrol.

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Presentation on theme: "1 Market-based DEMAND MANAGEMENT strategies Giovanni Andreatta, University of Padova Lorenzo Brunetta, Milan Polytechnic Un. Guglielmo Guastalla, Eurocontrol."— Presentation transcript:

1 1 Market-based DEMAND MANAGEMENT strategies Giovanni Andreatta, University of Padova Lorenzo Brunetta, Milan Polytechnic Un. Guglielmo Guastalla, Eurocontrol Amedeo Odoni, MIT Other Universities …

2 2 Current focus on ATM: researchers + policymakers Constraint: –Maintain exceptionally high safety Aim: –Enhance system capacity Purpose: –Reduce Air Traffic congestion This is a loosing battle

3 3 Congestion happens when demand is higher than capacity

4 4 Idea Work not only on capacity issues but also on demand issues

5 5 Demand management Currently: only administrative measures: slot limitations and allocation guidelines (risk of re- regulation) To be investigated: Economic measures: –Congestion tolls –Peak period pricing –Slot auctions –Slot trading –…

6 6 Local Demand Management Local Airport Authorities manage demand through measures that combine: –Slot limitation –Slot coordination –Access pricing schemes Such measures are often mutually inconsistent and contradictory

7 7 Conclusion The EU should provide clearly-articulated policies and guidelines To achieve this result, research on market-based Demand Management strategies is needed

8 8 Example: Pricing of Air Traffic Routes Congestion may be lowered by redistributing flows of traffic: In time (scheduling) In space (rerouting) Do not impose rerouting. Use pricing instead.

9 9 Rerouting by pricing Different actors have different perspective: (System) (individual) ATM authorities Airlines Collaborative approach is needed

10 10 System perspective: Optimization problem System objective: reduce overall congestion Decision variables: Sectors prices Constraint: Total amount collected equal to a target value (sum of various ATM + ATC costs) Classical Optimization or Genetic Algorithms

11 11 Airlines perspective Flight cost for airlines = Direct flight costs + Fees + Delays

12 12 Collaborative process Scheduling + Routing Prices (+ Delay estimation) Airlines choices


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