Abstract
The recent advances in automated vehicle technologies are expected to contribute to driving safety by reducing human error. Especially, in level 3 automated vehicles, the driver’s role is emphasized because of the control mode transition between automated and manual driving. When the control mode changes from automated to manual mode, it is important that the driver is ready to regain control of the vehicle. To confirm that the driver safely takes over control of the vehicle, a driver status monitoring (DSM) is needed to observe the driver’s behaviour. In this context, we have designed a sensor selection framework to choose the most appropriate sensors for DSM considering practical issues such as market constraints and system complexity. The proposed framework is validated with practical settings of the driver’s workload, motion primitives and sensors. The results show the trade-off relationship between accuracy and cost.
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