A framework for modeling human-vehicle interactions with increasingly autonomous systems
Modeling human-vehicle interactions requires an understanding of the human behavior. The model development needs to capture human’s interaction with other people, the environment, and their surroundings. A challenge in model development is the ability to accurately predict human behavior, particularly in complex environments that include other human road users, such as pedestrians and bicyclists. In this presentation, a framework is provided to better quantify and predict interactive human-vehicle decision-making, which can then be used to better inform the algorithms for advanced driver assistance systems (ADAS).
Linda Ng Boyle is Professor in Industrial & Systems Engineering at the University of Washington, Seattle. She has a joint appointment in Civil & Environmental Engineering. She has degrees from the University of Buffalo (BS) and University of Washington (MS, PhD). She is a member of the National Academies Board of Human System Integration and co-author of the textbook, “Designing for People: An Introduction to Human Factors Engineering”.