With the progress of automated driving technologies, self-driving cars are driving safely on highways and freeways in most circumstances. However, the lack of safe and smooth interactions with pedestrians becomes one of the significant obstacles preventing fully autonomous vehicles in city streets. Protections of vulnerable road users like pedestrians are of the highest priority in traffic safety, and crashes with pedestrians will significantly impact the trust and public attitudes towards the new mobility technology. Disruptive interactions with pedestrians may also lower both the riding experiences and driving efficiency in the pedestrian-rich road environments. It is vital to understand pedestrians and make motion planning based on the predictions of their behaviors.
Besides pedestrian detection and tracking, many research efforts have been put into recognizing pedestrians' behaviors and predicting their trajectories in the past few years. The achievements can predict potential crashes and make motion-planning decisions accordingly in a longer duration. This workshop will focus on the detection, recognition, and prediction of pedestrian behaviors for automated driving cars to interact with them smoothly. The goal is to build a platform for sharing state-of-the-art models, algorithms, and datasets in the field and identifying research needs and directions.
Short bio: Dr. Renran Tian is an assistant professor in the Department of Computer Information & Graphics Technology and the Transportation & Autonomous Systems Institute (TASI) at Indiana University-Purdue University Indianapolis (IUPUI). He received his Ph.D. degree from the School of Industrial Engineering at Purdue University –West Lafayette in 2013, and B.S. and M.S. in Mechanical
Engineering from Tsinghua University – Beijing, China in 2002 and 2005. His research interests include human-centered computing, cognitive ergonomic, computational behavior analysis, human-AI interaction, and autonomous driving. He serves as the co-chair for Technical Activities Committee on Human Factors in Intelligent Transportation Systems (HFITS), IEEE Intelligent Transportation Systems Society.
Short bio: Dr. Ding is a Tenure-Track Assistant Professor at the Department of Computer Science, Tulane University. He is an active researcher in the fields of face recognition, transfer learning, multi-view learning, and has published over 50 articles in the flagship conferences/journals and books. He serves as Associate Editor of IET Image Processing, and Journal of Electronic Imaging. He also serves many leading conferences/workshops in the vision and data mining fields, e.g., the Publicity Chair of AMFG2017, program co-chair of IEEE Big Data Workshop 2017, and workshop Chairs of AMFG 2021.He organizes four tutorials on multi-view learning in the FG 2017, CVPR 2018, IEEE BigData 2018, AAAI 2019 and IJCAI 2020. He also serves as senior program committee for AAAI 2019/2020, IJCAI 2021, and program committee for CVPR2018-2021, FG 2017-2019, and reviewers of many prestigious journals including IEEE TPAMI, TNNLS, TKDE, TIP, TMM.
Short bio: Dr. Yaobin Chen is a Chancellor’s Professor of electrical and computer engineering and the Founding Director of the Transportation and Autonomous Systems Institute (TASI) in the Purdue School of Engineering and Technology, IUPUI, Indianapolis, IN, U.S.A. He received his BS degree from Nanjing Institute of Technology, Nanjing, China in 1982, MS and Ph.D. degrees from Rensselaer Polytechnic Institute, Troy, New York, in 1986 and 1988 respectively, all in electrical engineering. From 1988 to 1990, Dr. Chen was a visiting assistant professor of electrical engineering at the George Washington University, Washington, DC. Since 1990, Dr. Chen has been with the Purdue School of Engineering and Technology, IUPUI, where he served as Associate Dean for Research from 2003 to 2005 and Chair of the Department of Electrical and Computer Engineering from 2005 to 2015. Dr. Chen’s areas of expertise include intelligent transportation systems, automated vehicles, EV and HEV, intelligent controls and robotics. He has published 190 technical papers in refereed journals and conference proceedings in his field of research. He is a co-inventor of 8 U.S. patents. He was a recipient of the National Science Foundation Research Initiation Award in 1991. He is a senior member of IEEE and a member of SAE.