1. Modeling and Measuring Cognitive Load to Reduce Driver Distraction in Smart Cars Tanvi Jahagirdar April 21, 2015 Committee: Ashraf Gaffar, Chair Arbi Ghazarian Robert Gray

3. What causes driver distraction ? Listening to music, Talking, Interactive Speech System Ears off the Road

4. Research how frequently drivers engage in certain distracting activities, how long and under what conditions they usually engage in them, drivers’ subjective assessments of the degree of distraction imposed by particular devices and their perceived ability to cope with these distractions, risk associated with distracted driving tasks whether and how training and practice can minimize driver distraction.

5. How to measure driver distraction? Measures e.g., SSS (Stanford Sleepiness Scale), KSS (Karolinska Sleepiness Scale) Driver biological measures e.g., EEG (Electroencephalogram), ECG (Electrocardiogram) Driver physical measures e.g., PERCLOS (proportion/percentage of time in a minute that the eye is 80% closed), Gaze direction Driving performance measures/ Engineering based e.g., steering wheel angle, yaw angle, reaction times etc. Hybrid measures

6. Technology Evolution

7. Why speech recognition is bad?

8. DISTRACTION DRIVING RELATEDNON-DRIVING RELATED EXTERNALINTERNALEXTERNALINTERNAL Checking Car Information, Switching Lights, Indication, GPS Road Signs, Traffic Lights, Pedestrian Crossing Media player, Wireless, Kids or Pets on board, Eating, Grooming Commercials, Unlawful Pedestrians States:- 1.Stable State1.Stable State 2.Dynamic State2.Dynamic State 3.Emergency State3.Emergency State

9. Human – Car Interaction (HCaI) HCaI is subjected to different constraints that generally do not apply to HCI. Every task has precedence in car and driver has to share his attention between activities. Input and output devices demanding high attention is not feasible. Two-handed operations are unacceptable. Driving situations greatly affect the interaction.

10. Multi-modal Interaction More Modes Better Interaction Human – Human Interaction is Multi-Modal: o Verbal o Para-Verbal o Non-Verbal o Lip Reading o Context o History o … “Attaining Perfection in Speech Recognition” is not the answer. We DO need Multi-Modal Interaction.

11. However is it safe?

12. Experiment For this study, we tested an abstract layout of icons of varying sizes, orientation and number of icons while driving, to effectively identify driver distraction and time taken to perform the distractive task. Our Hypothesis – Large & Simple icons  Minimal Driver Distraction

13. Screen Holder

14. Abstract UI for testing

15. Results

17. Conclusion Thus, the most complex task using our prototype should take 2 seconds per screen x 4 screens = maximum 8 seconds. The change in screen sizes or orientation did not affect the driver. There was also no significant change in using 6 +/- 2 number of icons with an average of less than 2 second response time per command and even less than a second with more experience.

18. Future Work This above work was conducted only on a limited small number of participants. More test cases and more participants would show more accurate results. Evaluate our borderlines by testing non-minimalist design of 24 icons compared to the minimalist design of 6+/- 2, Also in this work, the order of icons was serialized. Research should be done on randomizing the placement of icons, a comparison between novice and expert drivers in using the In-Vehicle Interactive System. Future research can also be done on 5 times vs. 20 times the UI was tested, to study the effect of learning mode and the effect of experience. There is also a need to check the difference between the 3 driving states as mentioned in the model. Future researchers can change the position of the screen by placing it at the bottom or angling it more to the driver.

19. Thank you & Drive Safe

20. Questions?