Monitoring driver’s mental workload for user adaptive aid
User adaptive machines use sensor technology and computer algorithms to infer the user’s internal state and make decisions based on this information. Future cars could use this technology to intervene if the capacity of the driver to drive safely is degraded, even before performance starts to break down. The main challenge for such a support system is that it needs to interpret individual data automatically and immediately, while the individual is influenced by the same system. My thesis aims at this challenge, focussing on mental workload. In chapter three it is argued that a reliable system probably needs multiple types of measures to infer the user’s internal state, such as driving performance, physiology, and subjective experiences. The main result from chapter four is that users may use support actions of an adaptive system as a warning signal, and thereby not use the system as intended by the designers. In chapter five the potential was explored to use automatic music selection to influence mental workload was, but a direct link between mental effort and music type was not confirmed. Individual data analyses from brainwaves were the topic of chapter six, resulting in highly accurate workload classifications. This inspired the development of a performance and brain-based cruise control described in chapter seven. The adaptive performance of this system led to the conclusion that future research should focus on decreasing the context and time dependency of workload monitors for user adaptive systems.
PhD Ceremony Chris Dijksterhuis: June 5
Last modified: | 12 November 2019 12.23 p.m. |
More news
-
01 May 2024
Behavioral Scientist Carsten de Dreu Appointed as Professor at the University of Groningen
The University of Groningen is pleased to announce the appointment of renowned social and behavioral scientist Carsten de Dreu as research professor at the UG.
-
09 April 2024
Kirsten van den Bosch: 'Connecting students with the work field really is achievable in every programme'
Dr Kirsten van den Bosch en her team won the Best Practice Award 2024 with their initiative to connect students with organizations to solve real problems within Academic Learning Communities.
-
03 April 2024
Research: much stress among Groningers due to gas extraction issues, including among the elderly
The gas extraction issue still has its effect on people in Groningen. Questionnaire research shows that people who had multiple instances of damage to their homes have increasingly poor health. In addition, interviews with elderly people show a...