A Naturalistic Bicycling Study in the Ann Arbor Area

Principal Investigator(s):

Shan Bao, Associate Research Scientist – The University of Michigan Transportation Research Institute
Associate Professor of Industrial and Manufacturing Systems Engineering – University of Michigan-Dearborn
Fred Feng, Assistant Professor in Industrial and Manufacturing Systems Engineering – The University of Michigan-Dearborn

Project Abstract:
In the past few years much progress have been made in the self-driving technologies and related issues (e.g., legislation and regulation) by a variety of entities from automotive and tech industries, academic institutions, and government and organizations. However, there are still great challenges to be solved. One of the critical challenges is that the self-driving cars need to share the existing infrastructure with other non-motorized road users such as bicyclists and pedestrians. Given the complexity of the real-world road environment and the presumably high variability of the behaviors of the non-motorized road users, how the self-driving cars should be designed, tested, and tuned to share the road with bicyclists and pedestrians in a safe and efficient manner is a complicated and yet crucial question. One way to potentially help answer this question is to collect naturalistic data of people riding bicycles in their everyday trips on real-world roadways, and use the collected quantitative data to create guidelines, supports, and test scenarios to develop the artificial intelligence algorithms for self-driving cars in their ability to effectively interact with bicyclists in real-world environment. The final report for this project will not be publicly available.

Institution(s): University of Michigan Transportation Research Institute
University of Michigan – Dearborn

Award Year: 2017

Research Thrust(s): Enabling Technology, Human Factors, Infrastructure Design & Management, Policy & Planning

Project Form(s):