In-Vehicle Interface Adaptation to Environment-Induced Cognitive Workload
Author:
Affiliation:
1. German Research Center for Artificial Intelligence, Germany
2. German Research Center for Artificial Intelligence, Germany and Saarland Informatics Campus, Germany
Funder
Bundesministerium für Bildung und Forschung
Publisher
ACM
Reference18 articles.
1. Driving simulators to evaluate road geometric design effects on driver behaviour: A systematic review;Bobermin Mariane Paula;Accident Analysis & Prevention,2021
2. Behavioral Entropy as a Measure of Driving Performance
3. Brad Cain. 2007. A review of the mental workload literature. (2007). https://apps.dtic.mil/sti/citations/ADA474193 Brad Cain. 2007. A review of the mental workload literature. (2007). https://apps.dtic.mil/sti/citations/ADA474193
4. Rebecca L Charles and Jim Nixon. 2019. Measuring mental workload using physiological measures: A systematic review. Applied ergonomics 74(2019) 221–232. https://doi.org/10.1016/j.apergo.2018.08.028 Rebecca L Charles and Jim Nixon. 2019. Measuring mental workload using physiological measures: A systematic review. Applied ergonomics 74(2019) 221–232. https://doi.org/10.1016/j.apergo.2018.08.028
5. Driving task analysis as a tool in traffic safety research and practice
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1. Towards Adaptive User-centered Neuro-symbolic Learning for Multimodal Interaction with Autonomous Systems;INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION;2023-10-09
2. A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload Monitoring;Sensors;2023-02-16
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