Adaptation of the Cognitive Avionic Tool Set (CATS) into Automotive Human Machine Interface Design Process

Paper #:
  • 2011-01-0594

  • 2011-04-12
Pala, S., Schnell, T., Becklinger, N., Giannotti, C. et al., "Adaptation of the Cognitive Avionic Tool Set (CATS) into Automotive Human Machine Interface Design Process," SAE Technical Paper 2011-01-0594, 2011,
DENSO International America, Inc. and the University of Iowa-Operator Performance Laboratory (OPL) have developed a series of new Multi-Modal Interface for Drivers (MMID) in order to improve driver safety, comfort, convenience and connectivity. Three MMID concepts were developed: GUI 1, GUI 2 and GUI 1-HUD. All three of the MMIDs used a new Reconfigurable Haptic Joystick (RHJ) on the steering wheel and new concept HMI Dual Touch Function Switches (DTFS) device. The DTFS use capacitive and mechanic sensing located on the back of the steering wheel as input operation devices. Inputs from the new controls were combined with a large TFT LCD display in the instrument cluster, a Head Up Display (HUD) and Sound as output devices. The new MMID system was installed in a Lexus LS-430. The climate control panel and radio panels of the LS-430 were used as a baseline condition to which the new designs were compared. DENSO and OPL have also developed a new metrology for the quantitative evaluation of the MMID. The Driver Workload Function (DWF) model was created to quantitatively measure the performance of HMI design. DWF is a predictive model developed by adapting the Cognitive Avionic Tool Set (CATS) for a series of driving tasks. Five tasks were completed for each MMID concept and the LS-430 baseline: change radio volume, change temperature, change fan speed, change fan mode, and change radio to a preset station. A modified Bedford scale was used to obtain subjective workload measurements after each task, and the NASA-TLX scale was used to obtain subjective workload scores for each GUI. Physiological and performance measures were regressed against the Bedford workload scores to create the DWF. Physiological measurements used to create the DWF include eye tracking data, Electroencephalogram (EEG) and Electrocardiogram (ECG). A single performance measure, time to complete task, was also included.
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