Identification of Biomarkers to Predict Driver Take-over Control Quality
Condition: Healthy Subjects; Attention Deficit
MeSH terms: Attention Deficit Disorder with Hyperactivity
Study type: Interventional

Summary: 
      At level 3 conditionally automated, the vehicle ensures driving and the driver disengages
      from driving to perform another activity independent of driving (ex: read a book, play on his
      phone ....). However, drivers are expected to be available to take over control for the case
      of system failure or limitation. This take-over control must take place in a limited time,
      very short, of the order of a few seconds. To take-over control of the vehicle quickly and
      efficiently, the driver must be, at the time of take-over, vigilant, efficient, and attentive
      to the environment and focused on the take-over of manual driving. Predicting the driver's
      reengagement capabilities to ensure that the driver will be able to take-over control of the
      vehicle is crucial at level 3 of autonomous driving.

      The objective of ANTIDOTE is to determine physiological and behavioural parameters capable of
      predicting the take-over quality in level 3 conditionally automated vehicles in a simulated
      highway driving situation in healthy drivers or drivers with attention disorders.
    

Detailed description: 
      At level 3 conditionally automated, the vehicle ensures driving and the driver disengages
      from driving to perform non-related driving tasks (ex: read a book, play on his phone ....).
      However, drivers are expected to be available to take over control for the case of system
      failure or limitation. This take-over control must take place in a limited time, very short,
      of the order of a few seconds. To take-over control of the vehicle quickly and efficiently,
      the driver must be, at the time of take-over, vigilant, efficient, and attentive to the
      environment and focused on the take-over of manual driving. Predicting the driver's
      reengagement capabilities to ensure that the driver will be able to take-over control of the
      vehicle is crucial at level 3 of autonomous driving.

      In this context, the objective of ANTIDOTE is to determine physiological and behavioural
      parameters capable of predicting the take-over quality in level 3 conditionally automated
      vehicles in a simulated highway driving situation.

      This study will examine how engagement will impact take-over control quality in 6 non-driving
      related secondary tasks. A driving simulator study will be conducted and data from a total of
      32 healthy drivers and 16 drivers with attention disorders will be used to evaluate take-over
      quality.

      Electrophysiological (EEG, ECG, EDA, EMG, respiration) and behavioral data will be recorded
      before, during and after the take-over control.
    

Intervention name(s): Driving simulator sessions
Intervention type(s): Behavioral
Intervention description(s): The volunteers will be placed in a driving simulator that will simulate autonomous highway driving. This autonomous driving will be interrupted by take-over requests related to events that disrupt autonomous driving. During autonomous driving, the driver will have to disengage from driving by performing non-related driving tasks. During each non-related driving tasks, a take-over request will be sent. Electrophysiological (EEG, ECG, EDA, EMG, respiration) and behavioural data will be recorded before, during and after the take-over control.
Intervention model: Single Group Assignment
Intervention model description: Monocentric preliminary study including an experimental driving session in a driving simulator.
Masking: None (Open Label)
Primary purpose: Basic Science
Keywords: Automated driving; Conditional automation; Driver distraction; Driver take-over quality; Biomarkers