Skip to main content
TRIMIS

Human Factors of Automated Driving

PROJECTS
Funding
European
European Union
Duration
-
Status
Complete with results
Geo-spatial type
Other
Total project cost
€3 864 201
EU Contribution
€3 864 201
Project website
Project Acronym
HF AUTO
STRIA Roadmaps
Connected and automated transport (CAT)
Transport mode
Road icon
Transport sectors
Passenger transport

Overview

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.

Objectives

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

Methodology

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

Funding

Parent Programmes
Funding Source
funded by a Marie Curie Initial Training Network (ITN).

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.
 

Partners

Lead Organisation
EU Contribution
€0
Partner Organisations
EU Contribution
€0

Technologies

Contribute! Submit your project

Do you wish to submit a project or a programme? Head over to the Contribute page, login and follow the process!

Submit