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{ "item_title" : "Human-Machine Interaction for Automated Vehicles", "item_author" : [" Yifan Zhao", "Chen LV", "Lichao Yang "], "item_description" : "Human-Machine Interaction for Automated Vehicles: Driver Status Monitoring and the Takeover Process 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. Finally, 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 drivers' cognition capability.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/0/44/318/997/0443189978_b.jpg", "price_data" : { "retail_price" : "220.00", "online_price" : "220.00", "our_price" : "220.00", "club_price" : "220.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Human-Machine Interaction for Automated Vehicles|Yifan Zhao

Human-Machine Interaction for Automated Vehicles : Driver Status Monitoring and the Takeover Process

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Overview

Human-Machine Interaction for Automated Vehicles: Driver Status Monitoring and the Takeover Process 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.

Finally, 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 drivers' cognition capability.

This item is Non-Returnable

Details

  • ISBN-13: 9780443189975
  • ISBN-10: 0443189978
  • Publisher: Academic Press
  • Publish Date: May 2023
  • Dimensions: 9.01 x 5.91 x 0.51 inches
  • Shipping Weight: 0.8 pounds
  • Page Count: 260

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