Could someone please direct me to a benchmarked dataset for  the subject of driver attention/distraction detection using machine learning, I've surveyed a few papers and they seem to collect their own data, which I was not able to acquire, the data signals used usually include the following, in both attention and distraction scenarios:

      - Speed [m/s].

      - Time to collision [s].

      - Time to lane crossing [s].

      - Steering angle [deg].

      - Lateral position [m].

      - Position of the accelerator pedal [%].

      - Position of the brake pedal [%].

      - Heading angle: angle between the longitudinal axis of the vehicle and the tangent on the centerline of the street.

      - Lateral deviation: deviation of the center of the car from the middle of the traffic lane.

      - Head rotation: rotation around the vertical axis of the car, measured using the head tracking system installed in the car console.

Thanks.

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