CHPR CENTER FOR HUMAN PERFORMANCE RESEARCH BV

Their core work

CHPR is a Dutch private research firm specialising in human performance and human factors within safety-critical, automated environments — primarily civil aviation and air traffic management (ATM). They study how human operators perceive, trust, and work alongside automated systems, bringing cognitive and behavioural science into technically complex domains. In practice this means running experiments with eye-tracking equipment to measure operator attention and workload, and evaluating whether machine-learning-based ATM tools are sufficiently transparent for controllers to rely on them. Their H2020 participation covered two distinct aviation challenges: integrating unmanned aircraft (RPAS/drones) into managed airspace, and optimising how human controllers and AI systems learn from each other during conflict detection and resolution.

What they specialise in

How they've shifted over time

CHPR's earliest H2020 work (TERRA, 2017–2020) addressed the human performance dimension of a structural airspace challenge: how to safely integrate drones into ATM without overwhelming controllers. No detailed keyword data survived for that project, suggesting a broad human factors scope. By 2020–2022, the MAHALO project reveals a sharper, more technically defined focus: machine learning interpretability, conflict detection and resolution, eye tracking, and the conformance of AI behaviour to human expectations. The trajectory is from general human-performance-in-aviation toward a specialised niche — the cognitive and behavioural science of human oversight of learning automation.

CHPR is moving toward the explainable-AI and human-automation teaming space, where demand is growing as aviation regulators and operators grapple with certifying AI-assisted decision tools — making them a natural partner for any consortium that needs empirical human factors evidence to support AI deployment in regulated environments.

How they like to work

CHPR has participated in both projects as a partner, never as coordinator, which is consistent with a boutique specialist that contributes a defined, bounded capability — human performance experiments and assessment — rather than managing large multi-partner initiatives. With approximately 4–5 partners per project across 5 countries, they operate in focused, technically tight consortia rather than broad umbrella partnerships. For a consortium builder, CHPR is most valuable as the human factors "plug-in" that larger engineering or technology-focused teams lack internally.

CHPR has worked with 9 unique partners across 5 countries over two projects, indicating a compact but genuinely international European network concentrated in the SESAR aviation research ecosystem. Their partnerships are almost certainly with aviation authorities, ATM technology developers, and academic human factors groups active in Single European Sky research.

What sets them apart

CHPR occupies a specific intersection that few organisations cover: cognitive and behavioural science applied to AI-driven ATM tools, backed by empirical methods like eye tracking. Most ATM research consortia are dominated by engineering firms, technology vendors, or aviation authorities — CHPR brings the human performance measurement capability that these groups cannot credibly provide themselves. For any project that must demonstrate human-centred design or validate that an automated system is actually usable by real operators under realistic conditions, CHPR fills a gap that is otherwise hard to source.

Highlights from their portfolio

• MAHALO
  Their largest and most technically detailed project (EUR 199,275), covering machine learning, explainability, eye tracking, and conflict detection in ATM — the clearest evidence of CHPR's current specialisation and a strong portfolio reference for AI-in-aviation consortia.
• TERRA
  An early SESAR-funded project on RPAS integration in ATM that established CHPR's credentials in the drone-airspace domain before the topic became mainstream in EU research.