Coordinated tactical air traffic and airspace management

Abstract

Air traffic management and airspace management reduce air traffic congestion to maintain safety. Managing traffic induces costs on airspace users and managing airspace causes additional work for air traffic controllers. This paper proposes and simulates algorithms for tactically reducing airspace congestion with coordinated air traffic and airspace management. A modified version of the Projective Cone Scheduling algorithm performs tactical air traffic management. An algorithm based on approximate dynamic programming accomplishes tactical airspace management. Three types of coordination between these air traffic and airspace management algorithms are investigated. Monte Carlo simulations of a simple problem instance involving severe congestion indicate that increased coordination between air traffic and airspace management can lead to lower costs with no increase in algorithm computation time.

Bi-Criteria Diverse Plan Selection via Beam Search Approximation

“…A planner can be used for diverse planning if it can generate a diverse set of satisficing plans of a certain cardinality k, and several approaches were proposed to solve this problem. An early line of work (Coman and Munoz-Avila 2011;Nguyen et al 2012;Roberts, Howe, and Ray 2014;Bloem 2015) has utilized a greedy strategy, similar to what was proposed in Hebrard et al (2005), in the context of diverse planning. This strategy involves a process of generating a candidate plan, adding this plan to a solution set, and providing feedback to the planner so that it tries to find new plans that are distant from the current solution set.…”

“…More broadly, many real-world scenarios can benefit from having a diverse set of plans. In dynamic and complex environments, a diverse set of plans enhances system robustness by offering alternative courses of action and increases the chance that one of the plans is acceptable to the user (Bloem 2015).…”