My Master’s Thesis Overview.

 

Self driving cars. Are we nearly there?

  • Automation technology is becoming better

  • Manufacturers have already started to incorporate self driving capabilities at some level

  • At this stage we’re moving towards full automation but we are at conditional automation (Level 3) (SAE International, 2018)

SAE
 
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The curse of semi-automation

  • The curse of semi-automation Level 3 autonomous vehicles should support transitions that are smooth and safe

  • This necessitates the use of highly salient warnings for transitions between manual and autonomous modes

  • These warnings should work for everyone and work for every situation

  • The driver will essentially have to take-over control of the vehicle when required.

 

Emotions & Automation

  • Affect(emotion in our case) can influence information processing, especially if the emotion induces high arousal (Brave & Nass, 2003).

  • There is a lot of evidence that anger can degrade driving performance (Jallais et al., 2014; Jeon, Walker, & Gable, 2014; Jeon, Yim, & Walker, 2011)

  • Driver abilities such as perception, decision making, focus and attention can be affected by emotion and affect driver performance (Eyben et al., 2010).

Angry drivers + takeover in self-driving cars = dangerous driving?

Angry drivers + takeover in self-driving cars = dangerous driving?

 

Auditory Alert Design

  • Participants exposed to a total of 9 auditory alerts

  • Loudness will be maintained at 70dbA

  • Larger frequency can make an auditory warning sound more urgent (Edworthy et al., 1991)

  • Faster repetitions of an auditory warnings can make it sound more urgent (E. J. Hellier, Edworthy, & Dennis, 1993).

Research Objectives

  • Measure the effects of anger on takeover performance and safety in semi-autonomous vehicles.

  • Measure the effects of warning urgency on takeover performance in semi-autonomous vehicles.

 
takeover
Visual takeover warning

Visual takeover warning

Auditory alerts

Auditory alerts

The Tobii Pro 2 eye tracker was used to measure eye gaze.

The Tobii Pro 2 eye tracker was used to measure eye gaze.

Methodology

  • Scenario Participants had emotion induced before drive (Control Group had no emotion induced)

  • 3 Lane Highway simulated drive in semi autonomous vehicle

  • Participants faced transitions of control (takeover) while in the vehicle where they were required to switch lanes to avoid obstacles .

  • Participants took over control after hearing an auditory alarm(takeover request) sent 7 seconds (lead time) before their vehicle would crash into an obstacle.

The Nervteh driving simulator running Oktal’s SCANeR studio was used to run experiments.

The Nervteh driving simulator running Oktal’s SCANeR studio was used to run experiments.

 

Example of a driver taking over control from the self-driving car

Measures

  • Reaction time to the takeover warnings

  • How often a driver looks at the rearview mirrors before turning

  • Driving behavior such as lane-keeping, speeding, steering wheel angle, braking, etc.

Since the study is still ongoing, results and publications will be shared shortly after completion this May,2020.

For further information, please contact me. :)

References

  1. Brave, S., & Nass, C. (2003). Emotion in human-computer interaction. The human-computer interaction handbook: fundamentals, evolving technologies emerging applications, 81-96.

  2. Eyben, F., Wöllmer, M., Poitschke, T., Schuller, B., Blaschke, C., Färber, B., & Nguyen-Thien, N. (2010). Emotion on the Road—Necessity, Acceptance, and Feasibility of Affective Computing in the Car. Advances in Human-Computer Interaction, 2010, 1-17. doi:10.1155/2010/263593

  3. Edworthy, J., Loxley, S., & Dennis, I. (1991). Improving auditory warning design: Relationship between warning sound parameters and perceived urgency. Human factors, 33(2), 205-231.

  4. Hellier, E. J., Edworthy, J., & Dennis, I. A. N. (1993). Improving auditory warning design: Quantifying and predicting the effects of different warning parameters on perceived urgency. Human factors, 35(4), 693-706.

  5. Jallais, C., Gabaude, C., & Paire-Ficout, L. (2014). When emotions disturb the localization of road elements: Effects of anger and sadness. J Transportation research part F: traffic psychology, 23, 125-132.

  6. Jeon, M., Walker, B. N., & Gable, T. M. (2014). Anger Effects on Driver Situation Awareness and Driving Performance. 23(1), 71-89. doi:10.1162/pres_a_00169

  7. Jeon, M., Yim, J.-B., & Walker, B. N. (2011, 2011). An angry driver is not the same as a fearful driver.

  8. SAE International. (2018). Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. In: SAE International.