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Chrysler 300M Research Platform. Cooperative Effort. Current Social Issue. CC++ 300M Driver Study Apply lab experience in Media and Human Interface technologies Build vehicle platform to develop and test driver behavior Develop information workload manager.

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CC++ 300M Driver Study

Apply lab experience in Media and Human Interface technologies

Build vehicle platform to develop and test driver behavior

Develop information workload manager

OEM/Supplier/University Collaboration - DaimlerChrysler/Motorola/M.I.T.

Vehicle Thinks!

Controls Flow of Information

(warnings, phone, etc…)

Identify Vehicle Motion

(stop, turn, accel)

Location Aware

(speed, position, …)

Monitor In-vehicle Situation

(mood, cognitive load)

Develop Tangible Interfaces

(transfer info to human)

Identify Driver Behavior and Stress Level


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Traffic Sensors

How dense is the traffic?


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Foot Position Sensors

Is driver getting ready to apply brake?


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Finger Position Sensors

Driver hands/mind busy?


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Finger Position Sensors

Driver hands/mind busy?



Student faculty presentations 300m work effort
Student Faculty Presentations300M Work Effort

Carson Reynolds - Stress Sensings

Ashish Kapoor - Eye/Head Tracking

Joe Pompei – Audio Spotlight and Algorithm

Taly Sharon - Driving Coach

James Kemp – I/O Data Concentrator/Controller

Betty Lou McClanahan - Emotion

John Hansman - Driver-to-vehicle Interface


Perceptual sensors

Perceptual Sensors

Carson Reynolds & Ashish Kapoor

MIT Media Laboratory

CC++


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Pressure Sensors

  • Using force sensitive resistors we sense grip pressure on:

    • Steering Wheel

    • Shift Knob


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Pressure Sensors

  • Two custom data acquisition boards can read 16 sensors.

  • Embedded microcontrollers perform analog to digital conversion.


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Hypothesis: People apply distinctive pressure patterns to the mouse when encountering stressful situations.

Results: using pattern recognition, 88% accuracy distinguishing stressful situations from control.


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Pressure Sensors the mouse when encountering stressful situations.

  • Using pressure sensors we’ll be able to detect the position of driver’s hands.

  • Pressure patterns will help us understand driver cognitive load.