Conflict Detection and Resolution System for Manned / Unmanned Aerial Vehicles Cooperation in a Confined Airspace

  • 賴 亞咸

Student thesis: Doctoral Thesis


In this dissertation a new conflict detection and resolution (CD&R) system is designed to meet the special specifications of manned and unmanned aircraft rescue and surveillance cooperation in a disaster site The high dynamic flight trajectory needed to navigate through disaster sites causes traditional CD&R systems unsuitable The proposed system adopts additional parameters to assist in trajectory predications under high dynamic maneuvers The proposed CD&R system design can be split into hardware/software and algorithms A Quasi ADS-B hardware is designed to communicate the necessary data between each aircraft A front-mounted display is designed to aid pilots to avoid possible conflict visually and audibly The algorithm of the proposed CD&R system is further split into 3 stages: flight prediction conflict detection and conflict resolution By implanting additional parameters and auxiliary mechanisms into flight predictions the Short Term Sector (STS) path prediction system is designed for manned aircraft and Short Term Parameter Guided (STPG) path prediction system is designed for unmanned aircraft Long-Term Parameter Guided (LTPG) path prediction is designed for preflight avoidance planning 4D Gaussian distributions are generated based on the STS and STPG models to construct the conflict detection probability grid This grid is further used by the confined Theta* pathfinding algorithm with the aid of Grid Size Factor (GSF) to generate a resolution pathway for the pilot to follow to ensure a conflict-free trajectory With these designs both hardware and algorithm a new CD&R system suitable for cooperation between manned and unmanned aircraft in a confined airspace is shown Theoretical formulations and system implementation are presented with simulations and real flight tests The proposed Quasi ADS-B technique for CD&R is strongly verified in a complete solution
Date of Award2018 Feb 12
Original languageEnglish
SupervisorChin-E. Lin (Supervisor)

Cite this