Dr. Yongqi Dong
Institute Institute of Highway Engineering,
RWTH Aachen University
Date & Time Date: 13 Sep. 2024 Time: 15:00-16:00 Venue Zoom ID: 898 654 4121 Passcode: 123456
The transition to fully Automated Vehicles (AVs) and their deployment on the road will be gradual, leading to a phase of mixed-traffic conditions where AVs at various levels coexist with human-driven vehicles (HDVs). This transition poses unprecedented hurdles, requiring a deeper understanding of the emerging challenges for AVs in sensing and perceiving road environments, as well as in the novel interactions between AVs and HDVs. Furthermore, the social compliance of AVs needs to be considered as well. This study addresses the emerging challenges associated with AVs in mixed-traffic environments. The main objective is to enhance the capabilities of AVs enabling them with a wider Operational Design Domain (ODD) and thus facilitate the implementation of safe, efficient, and socially compliant automated driving in mixed traffic. Referring to the modular design of AV systems, three key perspectives, i.e., sensing and perception, anomaly detection, as well as planning and control, are tackled. To be specific, two hybrid spatial-temporal deep learning models and one self-supervised pretraining method for sensing, a semi-supervised learning approach for abnormal driving detection, together with a model-based social-aware planning and control algorithm will be introduced.
Yongqi Dong is currently a Junior Research Group Leader (AI & Automated Mobility) at RWTH Aachen University. From January 2020 to May 2024, he was a PhD researcher supervised by Dr. Haneen Farah and Prof. Bart van Arem [dissertation to be released soon]. His PhD research was funded by the Dutch Research Council (NWO). From May 2023 to October 2023, Yongqi did a research visit at UC Berkeley, supervised by Prof. Masayoshi Tomizuka. Yongqi obtained his Master’s degree in Control Science and Engineering from Tsinghua University and his Bachelor’s degree in Telecommunication Engineering from Beijing Jiaotong University. He had also spent time at Singapore-MIT Alliance for Research and Technology (SMART) as a research intern.
With a broad interdisciplinary background, Yongqi’s ultimate goal is to employ Artificial Intelligence (AI) and multi-disciplinary research as tools to shape a better world. To achieve this, he has focused on the transportation domain and explored various aspects of shared and automated mobility. His works have been published in top-tier transportation conferences and journals, such as the IEEE Transactions on ITS and Transportation Research Part C. He also serves as an active reviewer for these top conferences and journals.
Yongqi has obtained several competitive research grants (e.g., IEEE ITSS New Initiatives Proposal Funding), scholarships (e.g., Chinese Government Award for Outstanding Self-financed Students Abroad), and travel fellowships (e.g., 2023 Fellowships for Young Researchers, Promoting Diversity and Leadership in ITS). He took the initiative to organize and coordinate three international workshops and established the interdisciplinary research community of "Automated Mobility in Mixed Traffic".
来源：智能交通学域
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