COgnitive assessment of Remote Drivers (CORD)

Purpose and goal:

In this project, the aim was to study the feasibility of employing the Brain-Computer Interface technology using the foundation of neuroscience and the analyzing power of artificial intelligence to evaluate the cognitive performance of remote drivers. The intention is to explore this new approach and realize the possibility of providing deeper insights on related cognitive features of a human operator, i.e. cognitive load, distraction, fatigue, alertness, or motion sickness.

Expected results and effects:

The result of this pre-study can contribute to increase the safety of autonomous mobility. A new approach was investigated to better understand why incidents and accidents occur due to human errors and how best to design new safety systems and HMI interfaces to mitigate safety-critical situations raised by human error. The obtained knowledge from this pre-study will establish a basis to see how a Neuro-AI based approach can be used in the context of semi-autonomous and remote driving and contribute to increased road safety.

Approach and implementation:

Having multi-disciplinary partners in this project, an extensive state-of-the-art literature review were conducted in the context of driver cognitive performance. Accordingly, different protocols for performing pre-tests were defined in order to perform a benchmark analysis in different driving environments. The outcome provided a better understanding of the usefulness of insights obtained from a Neuroscience-AI based approach compared to ones from the classical methods.