Human Interaction with Automated Vehicles

Members of the AIDL have been working on various research projects related to automated vehicles, check out some of our projects in this area below!

Last Updated: June, 2024

Dynamic Alert Design Based on Driver’s Cognitive State for Take-over Request in Automated Vehicles

Duration: Jan 2023- Jun 2024

The thesis investigates the impact of dynamic alert designs based on drivers' cognitive states on takeover requests (TOR) in automated vehicles. Using an immersive driving simulator in the Autonomous Vehicle Research and Intelligence Lab (AVRIL), the study examines whether varying alert intensities—tailored to states of concentration or distraction—can improve driver performance and situational awareness. Participants navigate highway scenarios using Adaptive Cruise Control and Autopilot, with some engaging in secondary tasks to simulate distraction. Results indicate that dynamic alerts, which adjust intensity based on driver condition, enhance reaction times and perceived urgency without increasing annoyance, suggesting a potential for improved safety in automated driving systems.

Fault and Security Testing for Vehicle Systems: Attacks on the Human Operator

Duration: Feb. 2022- Present

This project examines vulnerabilities related to security attacks that unexpectedly force human operators to take over vehicle control under high cognitive loads. This project aims to analyze these risks, explore human resilience in such scenarios, develop interventions to mitigate vulnerabilities, and assess their effectiveness in enhancing driver safety.

Sponsors and Partners :

  • NSERC
  • Sebastian Fischmeister
  • Transport Canada

Exploration of the relationship between driving experience, driving style, and in-vehicle voice assistant characters

Duration: Jan 2021-Oct. 2022

This project investigates the impact of contextual factors on in-vehicle voice interfaces, such as whether the aggressiveness or the gender of voice assistants, prior experience, age, and driving history affect user attitudes like trust and perceived usefulness.

Related Publications:

He, F., & Burns, C. M. (2022, September). A battle of voices: A study of the relationship between driving experience, driving style, and in-vehicle voice assistant character. In Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 236-242).

A High-Fidelity VR Simulation Study on Autonomous Vehicles External Warnings on Pedestrian Safe Crossing

Duration: March 2019- Dec 2020

To improve pedestrian communication, external displays on autonomous vehicles (AVs) have been explored primarily through research methods that assess crossing intentions rather than actual behaviors. Our study utilized a high-fidelity virtual reality scenario to examine real crossing actions, revealing that although warning patterns increase perceptual vigilance, they do not necessarily lead to safer crossing behaviors, indicating that intentions may not effectively predict actual crossing practices.

Related Publication:

He, F. (2021). A High-Fidelity VR Simulation Study: Do External Warnings Really Improve Pedestrian Safe Crossing Behavior? (Master's thesis, University of Waterloo).

Experiences with Autonomous Vehicles (Master's Thesis)

Duration: Jan 2016 - May 2017

In this project, I investigated how Tesla drivers perceive and use the Autopilot and Summon systems. Data was collected from over hundred Tesla drivers and key issues with automated driving were identified.

Related Publications:

  1. Dikmen, M., & Burns, C. M. (2016, October). Autonomous driving in the real world: Experiences with tesla autopilot and summon. In Proceedings of the 8th international conference on automotive user interfaces and interactive vehicular applications (pp. 225-228).
  2. Dikmen, M., & Burns, C. (2017, October). Trust in autonomous vehicles: The case of tesla autopilot and summon. In 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 1093-1098). IEEE.

Sponsors and Partners:

  • NSERC 

Human Interaction with Automated Vehicles

This is a multi-year project funded by an NSERC CREATE and other sources of funding.  We are looking at issues of trust with automated vehicles.  How well do drivers of current automated vehicles trust their (imperfect) automation?  When automated vehicles are more ubiquitous, how will other road users interact with these vehicles?  To what degree should an automated vehicle communicate its intent?

Related Publications:

  1. Dikmen*, M., Burns, C.M. (2017). Trust in autonomous vehicles: The case of Tesla Autopilot and Summon. 2017 IEEE International Conference on Systems, Man and Cybernetics. 1093-1098. 10.1109/SMC.2017.8122757
  2. Dikmen*, M., and Burns, C.M. (2016). Autonomous driving in the real world: Experiences with Tesla Autopilot and Summon.  8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 225-228.
  3. Li*, Y., Hu, R., Burns, C.M. (2016). Representing stages and levels of automation on the decision ladder: The case of automated financial trading. Proceedings the 2016 Annual meeting of the Human Factors and Ergonomics Society. 328-333.