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Jonas Lundberg

Researcher at Linköping University

Publications -  80
Citations -  1358

Jonas Lundberg is an academic researcher from Linköping University. The author has contributed to research in topics: Newspaper & Resilience (network). The author has an hindex of 18, co-authored 72 publications receiving 1181 citations.

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Journal ArticleDOI

UTM City—Visualization of Unmanned Aerial Vehicles

TL;DR: A digital platform for unmanned traffic management, UTM City, is presented for research on visualization, simulation, and management of autonomous urban vehicle traffic and the need for visualization in future scenarios to ensure safe, free, and efficient air spaces is explored.
Journal ArticleDOI

A method to identify investigative blind spots (MIBS): Addressing blunt-end factors of ultra-safe organizations’ investigation-work-as-done

TL;DR: In this paper , the authors present a method to identify and address investigative blind spots (MIBS), which are issues that are systematically not addressed in investigative work and emerge due to work pressures when using methods, or due to gaps in methods.
Proceedings ArticleDOI

NIRS-based Cognitive Assessment of Safety-Critical Air Traffic Operations

TL;DR: In this paper, NIRS was used to assess the cognitive processes of operators performing complex, safety-critical Air Traffic Control (ATC) tasks, and the haemodynamic response in the Prefrontal Cortex (PFC) was obtained from an event-based analysis of the NIRs recordings.
Book ChapterDOI

Classification of Safety-Relevant Activities by Using Visual Scan Pattern in Airport Control Operations

TL;DR: A first baseline from a conventional tower is created using a verbal coding method and eye tracking data for classifying periods of visual activities by the related control task to identify characteristics in the visual scan patterns using the out-the-window view.
Journal ArticleDOI

Extraction of CD&R Work Phases from Eye-Tracking and Simulator Logs: A Topic Modelling Approach

TL;DR: In this article , the authors investigated a novel approach based on topic modeling to learn controllers' work patterns from temporal event sequences obtained by merging eye movement data with data from simulation logs, which indicated that there was a correspondence between the phases captured by the proposed method and the Conflict Life Cycle (CLC) reference model, derived from post-simulation interviews with the ATCOs.