You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Enhancing Trust in AI for Remote Digital Towers: From Gap Analysis to Integration

Authors:

Sara Kebir , Alexandre Veyrie , Nicola Cavagnetto , Mobyen Uddin Ahmed, Shaibal Barua, Mir Riyanul Islam, Pietro Aricò , Christophe Hurter

Research group:

Artificial Intelligence and Intelligent Systems

Publication Type:

Conference/Workshop Paper

Venue:

SESAR Innovation Days (SIDs)

Abstract

Remote Digital Towers (RDTs) use multimodal feeds and AI to support air traffic controllers. While AI offers vigilance and consistency, trust remains essential to preserve human authority in safety-critical operations. This paper presents: (1) a review of human–AI collaboration in RDTs, (2) a gap analysis of trust, task allocation, and human–machine interface (HMI) design, and (3) integration strategies including explainable AI, adaptive workload management, and progressive trust-building. We propose initial Key Performance Indicators (KPIs) linking psychological trust constructs to operational outcomes. Our contribution clarifies how to deploy AI in RDTs without com- promising safety, transparency, or human agency.

Bibtex

@inproceedings{Kebir7298,
author = {Sara Kebir and Alexandre Veyrie and Nicola Cavagnetto and Mobyen Uddin Ahmed and Shaibal Barua and Mir Riyanul Islam and Pietro Aric{\`o} and Christophe Hurter},
title = {Enhancing Trust in AI for Remote Digital Towers: From Gap Analysis to Integration},
month = {January},
year = {2026},
booktitle = {SESAR Innovation Days (SIDs) },
url = {http://www.es.mdu.se/publications/7298-}
}