Abstract
The use of in-vehicle information systems has increased in the past years. These systems assist the user but can as well cause additional cognitive load. The study presented in this paper was carried out to enable workload estimation in order to adapt information and entertainment systems so that an optimal driver performance and user experience is ensured. For this purpose smartphone sensor ...
Abstract
The use of in-vehicle information systems has increased in the past years. These systems assist the user but can as well cause additional cognitive load. The study presented in this paper was carried out to enable workload estimation in order to adapt information and entertainment systems so that an optimal driver performance and user experience is ensured. For this purpose smartphone sensor data, situational factors and basic user characteristics are taken into account. The study revealed that the driving situation, the gender of the user and the frequency of driving significantly influence the user’s workload. Using only this information and smartphone sensor data the current workload of the driver can be estimated with 86% accuracy.
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