journal article·2026-02-28Open access

Early Detection of Flying Obstacles Using Optical Flow to Assist the Pilot in Avoiding Mid-Air Collisions

Daniel Vera-Yanez, António Pereira, Nuno Rodrigues, José Pascual Molina, Arturo S. García, Antonio Fernández-Caballero

Applied Sciences· Volume 16· Issue 5

Abstract

The seemingly endless expanse of the sky might suggest that it could support a large volume of aerial traffic with minimal risk of collisions. However, mid-air collisions do occur and are a significant concern for aviation safety. Pilots are trained in scanning the sky for other aircraft and maneuvering to avoid such accidents, which is known as the basic see-and-avoid principle. While this method has proven effective, it is not infallible because human vision has limitations, and pilot performance can be affected by fatigue or distraction. Despite progress in electronic conspicuity (EC) systems, which effectively increases the visibility of aircraft to other airspace users, their utility as collision avoidance systems remains limited. This is because they are recommended but not mandatory in uncontrolled airspace, where most mid-air accidents occur, so other aircraft may not mount a compatible device or have it inactive. In addition, their use carries some risks, such as causing pilots to over-focus on them. In response to these concerns, this paper presents evidence on the utility of using an optical flow-based obstacle detection system that can complement the pilot and electronic visibility in collision avoidance, but that, unlike pilots, neither gets tired like the pilot does nor depends on whether other aircraft have mounted devices, such as EC devices. The current investigation demonstrates that the proposed optical flow-based obstacle detection system meets or exceeds the critical minimum time required for pilots to detect and react to flying obstacles (12.5 s) using a mid-air collision simulator in various test environments.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Air Traffic Management and Optimization · Human-Automation Interaction and Safety · Aerospace and Aviation Technology

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, 02071 Albacete, Spain

Computer Science and Communications Research Centre, School of Technology and Management, Polytechnic Institute of Leiria, 2411-901 Leiria, Portugal

Institute of New Technologies—Leiria Office, INOV INESC InovaÇÃO, 2411-901 Leiria, Portugal

Departamento de Sistemas Informáticos, Universidad de Castilla-La Mancha, 02071 Albacete, Spain

Funding

Junta de Comunidades de Castilla-La Mancha · Universidad de Castilla-La Mancha · European Regional Development Fund “ERDF A way of making Europe” · FCT – Fundação para a Ciência e a Tecnologia

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