In the development of highly automated driving, strong focus is laid on the takeover and the improvement of takeover quality. Some research has shown that the complexity of a traffic situation has an influence on the takeover. However, different approaches towards complexity in driving exist and the topic has so far not been addressed sufficiently. In this study, a differentiation between subjective- and objective complexity is drawn. Their impact on eye movement patterns is evaluated and compared to the resulting takeover quality. Results of a driving simulator study show that objective and subjective complexity have an influence on several eye movement patterns. These eye movement patterns serve as an indicator of the resulting takeover quality. Furthermore, traces of the eye movement patterns are compared to predicted traces of the cognitive model for the takeover task. It can be shown that the cognitive model predicts visual traces in different traffic situations well. In order to support individual drivers during a takeover, it is thus important to consider complexity measurements in the development of cognitive assistance systems. Based on information about the environment and the cognitive model for the takeover task, a cognitive assistance system can be developed. In addition to that, eye tracking information further improves cognitive assistance systems.
How Are Eye Tracking Patterns in Takeover Situations Related to Complexity, Takeover Quality and Cognitive Model Predictions?
Lect.Notes Mobility
International Forum on Advanced Microsystems for Automotive Applications ; 2020 ; Berlin, Germany May 26, 2020 - May 27, 2020
11.12.2020
16 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Highly Automated Driving (HAD) , Takeover , Objective complexity , Subjective complexity , Cognitive assistance , Takeover quality , Cognitive modelling , ACT-R , Eye tracking Engineering , Automotive Engineering , Robotics and Automation , Cyber-physical systems, IoT , Transportation Technology and Traffic Engineering
Online Contents | 2008