Research

Lead Researcher(s)

Shan Bao
Associate Professor of Industrial and Manufacturing Systems Engineering, College of Engineering and Computer Science, the University of Michigan-Dearborn, Associate Research Scientist, Human Factors, University of Michigan Transportation Research Institute and Intermittent Lecturer in Industrial and Operations Engineering, College of Engineering

Shaobing Xu

Aditi Misra

Project Team

Huizhong Guo

Project Abstract

For the vulnerable road user (VRU) community and individuals, effective communication between AVs and VRUs is a focus of this project, which is crucial to VRUs developing trust as they interact with AVs. The research team recognizes the lack of guidelines to govern external and internal communication designs for AVs through our involvement in previous and ongoing work related to VRUs. To support the effort of improving mobility and safety for all Americans by providing guidelines to automated vehicle (AV) technology and product designs, the research team is proposing this study to address this issue. This project will collect user needs data and assess the information display efficiency and system suitability of accommodations to address common needs by using the principles of user-centered design to ensure that the prototypes have been developed to maximize the use of AVs by VRUs.
Two research questions will be addressed in this project: RQ1-What information and display design requirements are needed to promote efficient communication and interactions between AVs and VRUs?- Human-Machine Interface Design Requirement; and RQ2-What options are available to display information to VRUs?- Human-Machine Interface Design Solutions.

Project Outcome

1. A set of user needs matrix for user interface designs related to AV-VRU communications.
2. User interface design recommendations and potential technology solutions.
3. Community outreach and interview conduction.
4. User interface prototype design and pilot-testing.
5. A final report including detailed description of study methodology, data collection, data analysis and results. At least one peer-reviewed conference/journal article will be generated.