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Simulation-Based Evaluation of Collision Avoidance System for Medium and Large UAVs

  • Xingye Cheng
  • , Xuejun Zhang*
  • , Yue Xiao
  • , Bingjie Yang
  • , Chenglong Li
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In order to integrate unmanned aerial vehicle (UAV) into the national airspace system safely, one of the keys is to realize UAV detect and avoid (DAA). Validating the effectiveness of DAA systems through rigorous simulation is crucial to ensure their reliability and compliance with aviation safety requirements. In this study, leveraging manned aircraft trajectory data obtained from RadarBox, Monte Carlo simulations are conducted to generate potential UAV flight paths for DAA evaluation. Subsequently, the birth-death process is employed to obtain the initial air risks associated with UAV flights. To evaluate the effectiveness of the DAA system, the same methodological framework is utilized to assess the mitigated risks after DAA system implementation. Based on simulations using manned aircraft data over the Chengdu region, the risk is successfully reduced from 1.65111×10-6per flight hour to 6.12871×10-8per flight hour, ensuring that UAV operations can meet the safety standards.

Original languageEnglish
Title of host publicationProceedings of the 2nd Aerospace Frontiers Conference, AFC 2025 - Volume II
PublisherSpringer Science and Business Media Deutschland GmbH
Pages477-487
Number of pages11
ISBN (Print)9789819530069
DOIs
StatePublished - 2026
Event2nd Aerospace Frontiers Conference, AFC 2025 - Beijing, China
Duration: 11 Apr 202514 Apr 2025

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

Conference2nd Aerospace Frontiers Conference, AFC 2025
Country/TerritoryChina
CityBeijing
Period11/04/2514/04/25

Keywords

  • air risk
  • detect and avoid
  • manned aircraft
  • system evaluation
  • unmanned aerial vehicle

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