In automated vehicles (AVs), ensuring a comfortable user experience is essential for the broad acceptance and uptake of AVs. In higher levels of AVs (SAE Level 4+), drivers become passengers or riders, as the automation system takes over the control from the driver. Freed from driving responsibilities, users can engage in non-driving-related activities (NDRAs). However, without the ability to anticipate or predict the vehicle’s movements generated by the automation system, users may experience discomfort, such as motion sickness. One potential solution is to implement human-like driving styles that mimic users’ manual driving styles and habits, therefore offering a more familiar, natural, and predictable experience to the user. This is expected to enhance user comfort.
However, it remains unclear whether users indeed prefer these familiar or natural driving styles, given the diversity of personalities and road environments. Even worse, there is no commonly agreed definition or evaluation method for comfort! In this case, how can we measure comfort and make sure the designed driving style is “comfortable”?
Therefore, my PhD project aims to address these challenges by focusing on the following objectives:
- Investigating users’ subjective evaluations of different driving styles (human-like vs. robotic) in terms of naturalness and comfort, considering individual personality traits and external road environments.
- Establishing connections between subjective evaluations and objective vehicle metrics, such as velocity, acceleration, and distance to roadside objects.
- Conceptualising user comfort in automated driving by identifying and characterising the factors that influence user comfort.
By pursuing these goals, my research aims to provide valuable insights into optimising user comfort in automated vehicles and the development of comfortable driving styles catering to individual preferences.
Peng, C., Merat, N., Romano, R., Hajiseyedjavadi, F., Paschalidis, E., Wei, C., Radhakrishnan, V., Solernou, A., Forster, D., & Boer, E. (2022). Drivers’ Evaluation of Different Automated Driving Styles: Is It both Comfortable and Natural? Human Factors. https://doi.org/10.1177/00187208221113448
Peng, C., Hajiseyedjavadi, F., & Merat, N. (2022). A comparison of two methodologies for subjective evaluation of comfort in automated vehicles. 12th International Conference on Methods and Techniques in Behavioral Research and 6th Seminar on Behavioral Methods, May, 192–199. https://doi.org/10.6084/m9.figshare.20066849.v1
Peng, C., Horn, S., Madigan, R., Marberger, C., Lee, J., Krems, J., Beggiato, M., Romano, R., Wei, C., Wooldridge, E., Happee, R., Hagenzieker, M., & Merat, N. (submitted). Conceptualising user comfort in automated driving: Findings from an expert group workshop. https://doi.org/10.13140/RG.2.2.14206.87369
Conference Talk & Poster
Peng, C., Horn, S., Madigan, R., Marberger, C., Lee, J., Krems, J., Beggiato, M., Romano, R., Wei, C., Wooldridge, E., Happee, R., Hagenzieker, M., & Merat, N. Conceptualising user comfort in automated driving: Findings from an expert group workshop. 7th International Conference on Traffic and Transport Psychology. Gothenburg, Sweeden.
Peng, C., Horn, S., Madigan, R., Marberger, C., Lee, J., Krems, J., Beggiato, M., Romano, R., Wei, C., Wooldridge, E., Happee, R., Hagenzieker, M., & Merat, N. Conceptualising user comfort in automated driving: Findings from an expert group workshop. Human Factors and Ergonomics Society Europe Chapter 2023 Annual Conference. Liverpool, England.
Figalová, N., Jokhio, S., Nasser, M., Mbelekani, N. Y., Zang, C., Yang, Y., Peng, C., Liu, YC., & Berge, S. H. (2021). Methodological Framework for Modelling and Empirical Approaches (Deliverable D1. 1 in the H2020 MSCA ITN project SHAPE-IT). https://repository.tudelft.nl/islandora/object/uuid:5a424d04-5ee1-4c33-95f3-947f40d61287
Merat, N., Yang, Y., Lee, Y. M., Berge, S. H., Figalová, N., Jokhio, S., Peng, C., Mbelekani, N. Y., & Nasser, M. (2021). An Overview of Interfaces for Automated Vehicles (inside/outside)(Deliverable D2. 1 in the H2020 MSCA ITN project SHAPE-IT). https://repository.tudelft.nl/islandora/object/uuid:8f78a3df-1f60-4746-bf0b-e8d5b4922217
Workshop co-organiser. 2023 IEEE ITSC 2nd workshop on Are You Happy with AV ? User Experience (UX) in AV-Human Interaction. 2023
Accessibility co-chair. 13th International ACM Conference on Automotive User Interfaces (AutoUI). 2021.
Workshop co-organiser. 2021 IEEE Intelligent Vehicles Symposium (IV21) Workshop on Trust Calibration. 2021
Workshop co-organiser. 2021 IEEE Intelligent Transportation Systems (ITSC) Workshop on Communication between AVs – HTPs. 2021
My host university is the University of Leeds, UK. Here I work at the Human Factors & Safety group, at the Institute for Transport Studies.
My supervisors are Prof Natasha Merat (Leeds), Prof Marjan Hagenzieker (TU Delft), and Dr Chongfeng Wei (Queen’s University Belfast).
Who am I?
My name is Chen Peng, and I am the ESR 5 in the SHAPE-IT project. Currently, I also work as a Research Fellow at the Institute for Transport Studies, University of Leeds, where I am working on the HiDrive project.
My primary research interests revolve around human-like driving styles and user comfort in automated vehicles. Additionally, I am intrigued by topics such as human-machine interfaces (HMI), ageing, and inclusiveness in transportation.
I received my Master of Science degree (with distinction; see dissertation) in Human-Technology Interaction from Eindhoven University of Technology (TU/e) in the Netherlands, and my Bachelor of Engineering degree from the University of Electronic Science and Technology of China (UESTC).