Design space for driver-based automotive user interfaces
Proceedings of the 1st International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Heart on the road: HRV analysis for monitoring a driver's affective state
Proceedings of the 1st International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Eulerian video magnification for revealing subtle changes in the world
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Generating route instructions with varying levels of detail
Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Defining workload in the context of driver state detection and HMI evaluation
Proceedings of the 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
"FaceLight": potentials and drawbacks of thermal imaging to infer driver stress
Proceedings of the 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Exploring user expectations for context and road video sharing while calling and driving
Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
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Driving a car is becoming increasingly complex. Many new features (e.g., for communication or entertainment) that can be used in addition to the primary task of driving a car increase the driver's workload. Assessing the driver's workload, however, is still a challenging task. A variety of means are explored which rather focus on experimental conditions than on real world scenarios (e.g., questionnaires). We focus on physiological data that may be assessed in an non-obtrusive way in the future and is therefore applicable in the real world. Hence, we conducted a real world driving experiment with 10 participants measuring a variety of physiological data as well as a post-hoc video rating session. We use this data to analyze the differences in the workload in terms of road type as well as especially important parts of the route such as exits and on-ramps. Furthermore, we investigate the correlation between the objective assessed and subjective measured data.