ESR7 – Assessing AV Transparency

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What is my automated vehicle doing?

Automation in our daily lives has been an unstoppable trend in many aspects. It could highly improve the efficiency of repetitive work and minimize errors. However, when it comes to safety, we should consider more sides. During the first few encounters with automated vehicles, drivers often asked, “What is my automated vehicle doing?”. This asymmetry in information could easily lead to serious accidents while driving. Hence, ESR 7 aims to develop a systematic evaluation method to estimate the transparency of the automation system, or how easy is the automation system to be understood, and use it to achieve a transparent human-machine interface (HMI), and safer ride in automation.

Who am I?

Yuan-Cheng Liu finished his Bachelor’s and Master’s degree in Mechanical Engineering, National Taiwan University. His research experiences include battery management system, automated mobile robot and driver behavior modeling.

Email :

My affiliation

Yuan-Cheng is now a PhD student in Technical university of Munich, and an employee of the Chair of Ergonomics, Mechanical Engineering.


Prof. Klaus Bengler (Technical University of Munich) /


Prof. Martin Baumann (Ulm University) /


As automated vehicles become more common, it’s important to ensure that they can communicate with humans effectively. One key aspect is transparency, or the ability of the vehicle to convey its capabilities and intentions to its passengers clearly and understandably. Human-machine interfaces (HMIs) are widely adopted in automated vehicles as a way to use and provide passengers with the information needed. However, researchers have argued that the necessary information is often not correctly transmitted to users from automated vehicles (AVs), which could result in serious accidents [1]. Hence, a transparent HMI could not only support an unerring understanding of the automation system but also help reduce stress and improve the acceptance of automated vehicles.

Aims and objectives

In this research, we try to answer the question, “How well does the AV convey its capabilities and intent to interact with humans?”, by defining the transparency of the AV HMI, and the systematic method to measure it. In the end, we aim to apply the proposed method during the HMI design process to make the process more efficient and the HMI more transparent. Here is the summary of the objectives :

  • Define transparency of in-vehicle AV HMI.
  • Develop and validate the method for assessing AV transparency.
  • Application of the method to improve the HMI design process.

My publications

Journal and Conference Papers

  • Liu, Y. C., Figalová, N., Baumann, M., & Bengler, K. (2023). Human-Machine Interface Evaluation Using EEG in Driving Simulator. 2022 IEEE Intelligent Vehicle Symposium (IV). (accepted)
  • Liu, Y. C., Figalová, N., & Bengler, K. (2022). Transparency Assessment on Level 2 Automated Vehicle HMIs. Information13(10), 489.

Posters and Talks

  • Liu, Y. C., Figalová, N., Pichen, J., Baumann, M. & Bengler, K. (2022). What Is the Automated Vehicle Doing Now? Poster session presented at 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022), New York, United States.
  • Liu, Y. C., & Bengler, K. (2022). Automated Vehicle Transparency in Driving Simulator Study. The special session presentation at the 7th International Conference on Traffic and Transport Psychology (ICTTP 7), Gothenburg, Sweden.

References and links

  1. Banks, V.A.; Plant, K.L.; Stanton, N.A. Driver error or designer error: Using the Perceptual Cycle Model to explore the circumstances surrounding the fatal Tesla crash on 7th May 2016. Saf. Sci. 2018, 108, 278–285