Support Cognitive Abilities for Predictive Processing through Driver Monitoring

Purpose and goal:

Our project will analyze and evaluate effective differences in cognitive factors in the interaction between different traffic situations, different drivers (age & gender), and information from the driver monitoring system and different ways of interaction with the ADAS. The goal is to identify the key cognitive prediction factors for interaction with ADAS and propose the further development of driver monitoring and driver support functions to create a higher traffic safety by designing more individually adaptable driver support systems, and help them overcome their weaknesses.

Expected results and effects: Current driving experimental simulations of driver monitoring systems and ADAS will be used

to determine the cognitive predictive limitations that need to be supported to increase more reliable interaction with ADAS and increase road safety. Traffic situations, time frames, driver characteristics (e.g., age, gender, mood, driving style), reaction time and crash avoidance are variables to be used. The result is to propose further development of driver monitoring and driver support functions to design more individually adaptable driver support systems.

Approach and implementation:

The Operative Design Domain will be used and defines the specific operating conditions, environments, and scenarios in which a particular vehicle or automated driving system is designed to function safely. The user study will also investigate the gender differences in the acceptance and effectiveness of driver monitoring and ADAS. We will determine how to deal with these differences and investigate how they affect the safety levels of the driver support systems to improve the acceptance and effectiveness levels of the provided driving support systems in a gender-adjusted way.