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个人简介
Dr. Ching-Yao Chan is a Research Engineer with California PATH, which he joined in 1994. He has served as the Program Leader for the Transportation Safety Research Area at California PATH (Partners for Advanced Transportation Technology) since 2009. He is also serving as the Associate Director of Berkeley Deep Drive, https://deepdrive.berkeley.edu/.
Dr. Chan has 3 decades of research experience in a broad range of automotive and transportation systems. After receiving his Ph.D. degree in Mechanical Engineering from UC Berkeley in 1988, he worked in the private sector before joining PATH in 1994. His research spans from the development of driver-assistance and automated driving systems, sensing and wireless communication technologies, and highway network safety assessment.
Within the Berkeley Deep Drive Consortium (bdd.berkeley.edu), Dr. Chan is managing the infrastructure vehicle and data project, and leading research in several topics on pedestrian intent and pedestrian-vehicle interaction, sensor fusion for driving policy adaptation, and supervisory control in automated driving systems.
Prior to joining PATH, Dr. Chan worked in the field of vehicular passive safety systems. While being involved in the research, and development of crash sensing technologies, he also gained first-hand knowledge on general passive restraint systems, as he worked with automotive tier-one supplies and automotive OEMs. During 1990-1994, he worked as an expert witness on accident reconstruction and participated in numerous cases of vehicle crashes, through which he gained insights on the interaction of drivers, vehicle characteristics, roadway environment, and their impacts on driving risks.
Due to his nationally recognized expertise in crash sensing and vehicular safety, Dr. Chan was invited by Society of Automotive Engineers (SAE) to provide lectures to more than 500 automotive professionals in an SAE seminar series. He has given lectures to various organizations. He collaborated with SAE to publish a book and a video tutorial, and he was the recipient of the 1998 SAE Forest R. MacFarland Award for his outstanding contributions to engineering education.
Dr. Chan has 3 decades of research experience in a broad range of automotive and transportation systems. After receiving his Ph.D. degree in Mechanical Engineering from UC Berkeley in 1988, he worked in the private sector before joining PATH in 1994. His research spans from the development of driver-assistance and automated driving systems, sensing and wireless communication technologies, and highway network safety assessment.
Within the Berkeley Deep Drive Consortium (bdd.berkeley.edu), Dr. Chan is managing the infrastructure vehicle and data project, and leading research in several topics on pedestrian intent and pedestrian-vehicle interaction, sensor fusion for driving policy adaptation, and supervisory control in automated driving systems.
Prior to joining PATH, Dr. Chan worked in the field of vehicular passive safety systems. While being involved in the research, and development of crash sensing technologies, he also gained first-hand knowledge on general passive restraint systems, as he worked with automotive tier-one supplies and automotive OEMs. During 1990-1994, he worked as an expert witness on accident reconstruction and participated in numerous cases of vehicle crashes, through which he gained insights on the interaction of drivers, vehicle characteristics, roadway environment, and their impacts on driving risks.
Due to his nationally recognized expertise in crash sensing and vehicular safety, Dr. Chan was invited by Society of Automotive Engineers (SAE) to provide lectures to more than 500 automotive professionals in an SAE seminar series. He has given lectures to various organizations. He collaborated with SAE to publish a book and a video tutorial, and he was the recipient of the 1998 SAE Forest R. MacFarland Award for his outstanding contributions to engineering education.
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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMSno. 99 (2024): 1-14
IEEE Transactions on Multimedia (2023): 1954-1963
CoRR (2023)
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2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)pp.445-446, (2023)
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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2022)
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