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Human Factors of Automated Driving


Human Factors of Automated Driving

Link to CORDIS:
Background & policy context: 

HFAuto generates knowledge on Human Factors of automated driving towards safer road transportation. HFauto bridges the gap between engineers and psychologists through a multidisciplinary research and training programme. We combine engineering domains such as simulator hardware, traffic flow theory, control theory, and mathematical driver modelling with psychological domains such as human action and perception, cognitive modelling, vigilance, distraction, psychophysiology, and mode/situation awareness, to optimally address the interdisciplinary domain of human factors.


To generate knowledge on Human Factors of automated driving towards safer road transportation.


HFauto will train 13 Early Stage Researchers and 1 Experienced Researcher. The researchers are clustered in five synergistic work packages, conducting research on:
1. Human behaviour during highly automated driving
2. Human-machine interface of the future highly automated vehicle
3. Driver-state monitor for highly automated driving
4. Predicting real-world effects of highly automated driving
5. Legal and market perspective of highly automated driving

Institution Type:
Type of funding:
Funding Source(s): 
funded by a Marie Curie Initial Training Network (ITN).
Key Results: 

The expected results are 
(1) a comprehensive understanding of human capabilities and side effects of automated driving, both in monotonous and transient situations, 
(2) a HMI that optimally interacts with the driver of a highly automated car, for situations of different criticality, 
(3) an ‘ecological’ driver monitor that estimates the operator’s vigilance level and hazard awareness, 
(4) realistic traffic flow models that predict the effects of HAD on safety and efficiency,
(5) a roadmap for market introduction of highly automated driving, and 
(6) trained researchers having the multidisciplinary and generalizable knowledge, skills, and vision required to address human factors challenges of automated driving.


• Delft University of Technology
Full Partner (Coordinator), Netherlands
• Chalmers University of Technology
Full Partner, Sweden
Full Partner, France
• Technische Universität München
Full Partner, Germany
• University of Southampton
Full Partner,  United Kingdom
• University of Twente
Full Partner, Netherlands
Full Partner, Sweden
• BMW Group
Associated Partner
• Continental AG
Associated Partner
• Jaguar
Associated Partner
Associated Partner
• TNO‎
Associated Partner
• Toyota Motor Europe
Associated Partner
• Volvo Cars Cooperation
Associated Partner
• Volvo Group Trucks Technology
Associated Partner

Delft University of Technology
Mekelweg 2
Contact country: