Transdisciplinary design approach based on driver's workload monitoring

Driving is a high-demanding task, related to human capacity, required performance and events occurring in the external environment. Mental workload depends on numerous factors: task difficulty, task complexity, level of traffic, additional activities required by the driving action or imposed by the driver, the contextual conditions, as well as the individual response to stress. The study of driver's workload is crucial in guiding future car design, in order to improve the user experience, comfort as well as driving performance and safety. Indeed, if task demands are too high in relation to the user's capabilities, errors may occur and may become critical for safety. The present paper defines a transdisciplinary approach based on monitoring the driver's workload during driving tasks in order to map the perceived user experience, and finally understand the interaction between the driver and the car systems. The approach is based on three layers: the human conditions to detect, the vital parameters to be monitored, and the adopted monitoring technologies. The paper proposes: a protocol to monitor the driver's workload during both real and simulated tasks, a technological set-up including physiological and performance data collection, and a proper data elaboration strategy. The key findings are: the selection of the most relevant subjective and objective parameters to measure the driver's mental workload, the definition of a preliminary technological set-up for monitoring the workload during simulated driving, and the evaluation of the effects of task complexity and of a secondary task on driver's performance. The research paved the way to further studies about how to miniaturize and embed sensors inside the car for a less intrusive application during real driving. Results can also be used to assess the interaction with car devices and to compare different design alternatives