HADRIAN · Project

Adaptive Dashboard Tech That Makes Self-Driving Handoffs 85% Safer

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Imagine you're in a semi-self-driving car and the system suddenly needs you to take the wheel. Right now, that handoff is clunky and dangerous — like someone tossing you a ball without warning. HADRIAN built smart dashboard interfaces that watch the driver's state (are you alert? distracted? tired?) and adjust how and when they ask you to take control. They tested this across 19 real studies with actual drivers in simulators and on roads, covering everything from passenger cars to freight trucks.

By the numbers

85%

targeted improvement in safety of automated driving level transitions vs. traditional HMI

95%

targeted acceptability rate among drivers

human participant studies conducted across diverse demographics

consortium partners across 9 countries

industry partners in the consortium

The business problem

What needed solving

Self-driving cars still need human drivers to take over in critical moments, but current dashboard warning systems treat every driver the same — whether alert or drowsy, experienced or nervous. This one-size-fits-all approach leads to dangerous, poorly timed handoffs that erode trust in autonomous technology and create liability risks for manufacturers.

The solution

What was built

The consortium built working demonstrators including adaptive human-machine interface prototypes (WP3) and sensory instrumentation systems for real-time driver monitoring (WP2). These were validated through 19 human participant studies in both driving simulators and field demonstrations across light vehicles, passenger vehicles, and freight trucks. The project also produced OEM guidelines for integrating safe driver-vehicle handoff systems.

Audience

Who needs this

Automotive OEMs developing Level 2-4 autonomous vehiclesTier 1 suppliers building driver monitoring systems and cockpit electronicsCommercial truck and bus manufacturers adding autonomous featuresFleet management companies deploying semi-autonomous vehicle fleetsAutomotive safety testing and certification bodies

Business applications

Who can put this to work

Automotive OEM

enterprise

Target: Car manufacturers developing Level 2-4 autonomous vehicles

If you are a car manufacturer struggling with safe driver-to-vehicle handoffs in your autonomous models — this project developed adaptive human-machine interfaces that adjust warnings and authority transfers based on real-time driver monitoring. Their testing across 19 participant studies showed the system targets 85% safer transitions compared to traditional static dashboards, with 95% driver acceptability.

Commercial Vehicle & Fleet Management

enterprise

Target: Truck and bus manufacturers or fleet operators integrating autonomous driving features

If you are a fleet operator or commercial vehicle maker worried about driver fatigue during long-haul autonomous stretches — HADRIAN built and demonstrated fluid interfaces for L, M, and N class vehicles (light vehicles through freight trucks). The system includes real-time driver status models and sensor fusion that detects when a truck driver needs graduated alerts before taking back control.

Automotive HMI & Sensor Suppliers

mid-size

Target: Tier 1/Tier 2 suppliers developing driver monitoring systems or cockpit electronics

If you are a Tier 1 supplier building driver monitoring cameras or cockpit display systems and need validated algorithms for when and how to intervene — HADRIAN produced decision logic algorithms and sensor fusion methods tested across 19 studies covering diverse driver demographics. Their guidelines and effectiveness metrics are designed for direct integration into OEM supply chains.

Frequently asked

Quick answers

What would it cost to license or integrate this technology?

The project did not publish licensing fees or per-unit costs. HADRIAN was a Research and Innovation Action coordinated by Virtual Vehicle Research GmbH (Austria). Commercial terms would need to be negotiated directly with the consortium partners who hold the relevant IP.

Is this ready for industrial-scale deployment in production vehicles?

Not yet at full production scale. The consortium built demonstrators and ran 19 human participant studies in driving simulators and field demonstrations across light, passenger, and freight vehicle classes. The outputs are validated algorithms, sensor fusion methods, and OEM guidelines — integration into series production would require further engineering.

Who owns the intellectual property and how can I access it?

IP is distributed across the 17-partner consortium spanning 9 countries. The coordinator Virtual Vehicle Research GmbH (AT) would be the first point of contact. As an EU-funded RIA project, certain results may be subject to open access requirements, but core algorithms and sensor designs likely remain with the developing partners.

Does this comply with European automotive safety regulations?

HADRIAN was specifically designed within the European future mobility vision and addresses automated driving level transitions. The project produced guidelines and recommendations for OEMs worldwide on human-systems integration. However, formal homologation or type approval for specific vehicle models would still be needed.

How long would integration into our vehicle platform take?

The project ran from December 2019 to May 2023 to develop and validate the technology. Based on available project data, the outputs include decision logic algorithms, driver status models, and integration guidelines. Adapting these to a specific vehicle platform would depend on your existing HMI architecture and sensor setup.

Can this work with our existing driver monitoring cameras and cockpit displays?

HADRIAN developed sensor and information fusion methods designed to work with real-time driver status inputs. The deliverables include sensory instrumentation evaluated in realistic contexts. Integration with specific existing hardware would need to be assessed, but the modular approach (sensor fusion + decision logic + display) suggests adaptability.

Consortium

Who built it

The 17-partner consortium across 9 countries (AT, DE, EL, ES, FR, NL, SI, TR, UK) brings a solid mix of 7 universities for research depth and 5 industry partners (29% industry ratio) for real-world grounding. The coordinator, Virtual Vehicle Research GmbH in Austria, is an SME specializing in vehicle research — meaning they bridge academic innovation and commercial automotive needs. With 3 SMEs and 5 research organizations rounding out the team, the consortium covers the full chain from driver behavior science to vehicle integration. The presence of partners from major European automotive markets (Germany, France, Spain, Netherlands) strengthens the path to OEM adoption.

VIRTUAL VEHICLE RESEARCH GMBHCoordinator · AT
VDI/VDE INNOVATION + TECHNIK GMBHparticipant · DE
NERVTECH, RAZISKAVE IN RAZVOJ DOOparticipant · SI
RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHENparticipant · DE
ETHNICON METSOVION POLYTECHNIONparticipant · EL
FUNDACION TECNALIA RESEARCH & INNOVATIONparticipant · ES
COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVESparticipant · FR
UNIVERSIDAD DE GRANADAparticipant · ES
PARIS-LODRON-UNIVERSITAT SALZBURGparticipant · AT
AVL LIST GMBHparticipant · AT
AUTOBAHNEN- UND SCHNELLSTRASSEN-FINANZIERUNGS- AKTIENGESELLSCHAFTparticipant · AT
IESTA - INSTITUT FUR INNOVATIVE ENERGIE -STOFFAUSTAUSCHSYSTEMEparticipant · AT
FORD OTOMOTIV SANAYI ANONIM SIRKETIparticipant · TR
BUNDESANSTALT FUER STRASSEN-UND VERKEHRSWESENparticipant · DE
UNIVERSITY OF SURREYparticipant · UK
TECHNISCHE UNIVERSITEIT DELFTparticipant · NL
UNIVERZA V LJUBLJANIparticipant · SI

How to reach the team

Virtual Vehicle Research GmbH (Austria) — contact via project website or university/research networks in Graz

Order a report on this consortium See VIRTUAL VEHICLE RESEARCH GMBH profile →

Next steps

Talk to the team behind this work.

Want an introduction to the HADRIAN team to discuss licensing their adaptive HMI algorithms or driver monitoring methods for your vehicles? SciTransfer can arrange a direct meeting with the right consortium partners.

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