Inhoudsopgave:
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\u003cp\u003e\u003ci\u003eHuman-Machine Interaction for Automated Vehicles: Driver Status Monitoring and the Takeover Process\u003c/i\u003e explains how to design an intelligent human-machine interface by characterizing driver behavior before and during the takeover process. Multiple solutions are presented to accommodate different sensing technologies, driving environments and driving styles. Depending on the availability and location of the camera, the recognition of driving and non-driving tasks can be based on eye gaze, head movement, hand gesture or a combination. Technical solutions to recognize drivers various behaviors in adaptive automated driving are described with associated implications to the driving quality.\u003c/p\u003e \u003cp\u003eFinally, cutting-edge insights to improve the human-machine-interface design for safety and driving efficiency are also provided, based on the use of this sensing capability to measure driversâ cognition capability.\u003c/p\u003e\u003cul\u003e \u003cli\u003eCovers everything needed to design an effective driver monitoring system, including sensors, areas to monitor, computing devices, and data analysis algorithms\u003c/li\u003e \u003cli\u003eExplores aspects of driver behavior that should be considered when designing an intelligent HMI\u003c/li\u003e \u003cli\u003eExamines the L3 take-over process in detail\u003c/li\u003e\u003c/ul\u003e |
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