A risk assessment method for mid-air collisions in urban air mobility operations

Date published

2024-12-31

Free to read from

2024-09-20

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Department

Type

Article

ISSN

2379-8858

Format

Citation

Su Y, Xu Y. (2024) A risk assessment method for mid-air collisions in urban air mobility operations. IEEE Transactions on Intelligent Vehicles, Available online 15 July 2024

Abstract

This paper proposes a method to systematically assess the risk of mid-air collisions in Urban Air Mobility (UAM) operations, considering unique flight characteristics, mission requirements, and the evolving airspace dynamics. The method encompasses three pivotal phases: the encounter leading to collision, the loss of control post-collision, and the resulting harm to third parties on the ground or in the air. Instead of focusing solely on the collision risk, this method quantifies potential harms, introducing the metric of “fatalities per flight hour” akin to conventional aviation. Three main barriers, strategic mitigation, tactical mitigation, and collision avoidance, are modelled to calculate the probability of mid-air collisions. The gas model evaluates the probability of strategic mitigation failure, while an encounter timeline concept determines the probability of tactical mitigation failure. This paper concludes with Monte Carlo simulations validating the proposed model and a real-world case study demonstrating its applicability for regulators, operators, and stakeholders in ensuring the safety and efficiency of future UAM operations.

Description

Software Description

Software Language

Github

Keywords

40 Engineering, 4001 Aerospace Engineering, 4002 Automotive engineering, 4007 Control engineering, mechatronics and robotics, 4603 Computer vision and multimedia computation, Urban Air Mobility (UAM), Mid-Air Collision, Risk Assessment, Monte Carlo Simulation

DOI

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Attribution 4.0 International

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Funder/s

This work was partially funded by the SESAR JU under grant agreement No 101017702, as part of the European Union’s Horizon 2020 research and innovation programme: AMU-LED (Air Mobility Urban - Large Experimental Demonstrations