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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


Traffic Sensors

How dense is the traffic?


Foot Position Sensors

Is driver getting ready to apply brake?


Finger Position Sensors

Driver hands/mind busy?


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++


Pressure Sensors

  • Using force sensitive resistors we sense grip pressure on:

    • Steering Wheel

    • Shift Knob


Pressure Sensors

  • Two custom data acquisition boards can read 16 sensors.

  • Embedded microcontrollers perform analog to digital conversion.


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

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


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.


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