{"665468":{"#nid":"665468","#data":{"type":"event","title":"ISyE Seminar - Linda Boyle","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EA framework for modeling human-vehicle interactions with increasingly autonomous systems\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EModeling human-vehicle interactions requires an understanding of the human behavior. The model development needs to capture human\u0026rsquo;s interaction with other people, the environment, and their surroundings.\u0026nbsp; 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).\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBio:\u003C\/p\u003E\r\n\r\n\u003Cp\u003ELinda Ng Boyle is Professor in Industrial \u0026amp; Systems Engineering at the University of Washington, Seattle. She has a joint appointment in Civil \u0026amp; Environmental Engineering. She has degrees from the University of Buffalo (BS) and University of Washington (MS, PhD).\u0026nbsp; She is a member of the National Academies Board of Human System Integration and co-author of the textbook, \u0026ldquo;Designing for People: An Introduction to Human Factors Engineering\u0026rdquo;.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EModeling human-vehicle interactions requires an understanding of the human behavior. The model development needs to capture human\u0026rsquo;s interaction with other people, the environment, and their surroundings.\u0026nbsp; 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).\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":" A framework for modeling human-vehicle interactions with increasingly autonomous systems"}],"uid":"36374","created_gmt":"2023-02-06 12:59:57","changed_gmt":"2023-02-06 12:59:57","author":"mwelch39","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-02-17T11:30:00-05:00","event_time_end":"2023-02-17T12:30:00-05:00","event_time_end_last":"2023-02-17T12:30:00-05:00","gmt_time_start":"2023-02-17 16:30:00","gmt_time_end":"2023-02-17 17:30:00","gmt_time_end_last":"2023-02-17 17:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}