Copyright: ThalesSource : Thales

Challenge

AI x Dynamic Pricing

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Challenge Overview

Description du challenge

In Aerospace, governments, airports, airlines, pilots, crews and passengers rely on Thales to make flight safer, easier and more efficient. We do this by designing, delivering and supporting the systems that keep our skies running.

With challenges facing the air traffic management sector, and the continuous increase of air traffic, the importance of Air Navigation Service Providers improving air control capacity, efficiency and safety are paramount.

There are many new commercial entrants demanding access to airspace – commercial space launch, long-endurance / high altitude airships, UAS, Air Taxis, Supersonic transport, etc.  This is in addition to existing civil aviation (largely scheduled airlines) and public users (defense, security, etc).  These new entrants will have a large proportion of ad-hoc operations vs scheduled operations which will reduce predictability of airspace use demand AND reduce capacity.

We expect as demand increases, the problem of balancing demand with the available capacity will become problematic AND determining priorities among many different commercial interests will be a difficult problem.  

Copyright: 945_7039.NEF
Copyright: 945_7039.NEF
Copyright: Thales
Copyright: Thales

Wanted

We are looking for an AI-based solution to address this problem. We are thinking of:

  • An economics-based system for capacity allocation, similar to congestion pricing on roads
  • A dynamic pricing system which predicts demand based on historical and other data and proposes an economic fee model to help spread the demand and allocate the available capacity

Projects you could be working on

This challenge is global in scope and does not focus on a specific project.