Project number:
Title of the project:
Human-Centric Driving Interface
Grant scheme:
Project type:
European Projects
Project duration (start):
Project duration (end):
Principal investigator:
Martin Klaučo

Road vehicles are known to be the most hazardous of all mobility means causing major societal challenges for the EU. Almost 90% of

road accidents are caused by driver behaviour which literally means an improvement in road safety directly depends on a good

understanding of driver behaviour and its interaction with the surrounding environment. One of the very first elements that drivers

are interacting with and are affected by is the Machine Interface. Historically the vehicle HMI was optimized for “heavy machinery”

operation purposes and unfortunately did not receive sufficient attention for passenger vehicles. This project will take the HMI as its

core focus by taking the human in the centre. This project will establish a methodology to develop holistic and multi-agent models

including, driver behavior, HMI functionality, vehicle system interface, and functionality as well as operating environments and traffic

conditions. This project benefits from a multi-disciplinary approach toward investigating, evaluating, and building a scalable Human-

Centric Machine Interface (HCMI). The HCMI allows a typical group of population (all genders, age groups, and representatives of

different mental/physical capabilities) to be equally considered. Provided with a holistic and multi-sided approach, driver distractions

will passively be reduced by the new HMI framework and will preventively and pro-actively be mitigated by exploiting vehicle system

levels to increase the safety of all road users. The studies in this project will not only rely on the theoretics, computer-based

simulations, and mock-ups but rather will employ advanced technologies such as AR, VR, physical vehicle, and traffic simulators as

well as building functional prototypes on a real scale. The introduced paradigm for data collection through biosignals will enable

further employment of on-edge technologies such as artificial intelligence, cognitive- and neuroscience to improve traffic safety in a

predictive manner.


Responsibility for content: doc. Ing. MSc. Martin Klaučo, PhD.
Last update: 18.10.2021 20:22
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