24th IEEE International Conference on Intelligent Transportation - ITSC2021
8 AM——12 AM, EST UTC -4.
September 19, 2021
Indianapolis, IN, United States
Social and Interactive Behavior Modelling in Intelligent Transportation Systems
（Code: g7823）
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1-Abstract (Scope and Topics):
With the development of intelligent transportation systems, many novel methods and algorithms have been developed for interactive behaviors modelling in highly dynamic scenarios. The complicated, critical and interactive conditions in the highway and urban scenarios bring a higher demand on precisely formulating, modelling and understanding behaviors of heterogeneous traffic participants. Meanwhile, new evaluation metrics for risky environments are required for a safer and more efficient intelligent transportation system. There have been lots of approaches proposed for interactive behavior modelling. The explorations cover a broad range of techniques and efforts from different aspects, such as graph-based representation (e.g., graph neural network) to reinforcement learning (e.g., STL), and to adaptation of learning methods (transferable driver behavior learning). Meanwhile, the progress also includes the development in benchmark dataset (e.g., INTERACTION Dataset) and simulated environments (e.g., highway-envs). Different methods have their particular advantages and characteristics, which are applied in diverse domains and scenarios. This workshop focuses on the discussion of above aspects, including contributions of methodology (graph learning, model adaptation, reinforcement learning, etc.) and development of infrastructures (simulated environment and benchmark).
Researchers in related areas from both, academia or industry are invited to submit full papers to be presented in the format of spotlight presentation and poster presentation.
The topics of interest within the scope of this workshop include, but not limited to, the following:
Novel methods in multi-agent tracking and prediction in intelligent transportation systems;
Novel algorithms for multi-agent reinforcement learning;
Transferable driver behavior modelling;
The development and evaluation of simulation environments for multi-agent interactive behavior modelling;
Interpretability and generalizability of behavior modeling algorithms;
Novel testing and validation methods in highly interactive and dynamic scenarios;
Risky behavior modelling and analysis;
The development of GNN, GAN, VAE in the prediction of motion and behavior;
The influence of human factors in intelligent transportation systems;
The application and deployment of novel algorithms on the intelligent vehicle platform;
Systematic survey or review for social and interactive behavior modelling.
2-Schedule:
The conference time is EDT (Eastern Daylight Saving time), UTC -4.
8:00--8:10 Welcome and Opening
8:10--8:35 Prof. Chen Lv
8:35--9:00 Prof. Jing Zhao: Two-dimensional vehicular movement modelling at intersections based on optimal control
9:00--9:25 Prof. Jinxiang Wang: Trajectory planning and path tracking on large curvature roads considering driver’s steering characteristics
9:25--9:50 Bolin Zhou: Scenario based testing and scenario validation methods
9:50--10:00 Coffee break
10:00--10:25 Dr. Wenshuo Wang: Spatiotemporal learning of multivehicle interaction patterns with nonparametric Bayesian statistics
10:25--10:50 Prof. Victor Knoop: Back to the basics and beyond: the value of small data
10:50--11:15 Prof. Meng Wang: Maneuver coordination of connected automated vehicles at freeway merges
11:15--11:40 Dr. Xiaoxiang Na: Measurement, Assessment and Modelling of Heavy Goods Vehicle Energy Consumption
Chen Lv, Assistant Professor, Nanyang Technological University
Chen Lv is currently an Assistant Professor at School of Mechanical and Aerospace Engineering, and the Cluster Director in Future Mobility Solutions at ERI@N, Nanyang Technology University, Singapore. He received the Ph.D. degree at the Department of Automotive Engineering, Tsinghua University, China in 2016. He was a joint PhD researcher at EECS Dept., University of California, Berkeley, USA during 2014-2015, and worked as a Research Fellow at Advanced Vehicle Engineering Center, Cranfield University, UK during 2016-2018. His research focuses on advanced vehicles and human-machine systems, where he has contributed over 100 papers and obtained 12 granted patents.
Meng Wang, Assistant Professor, Delft University of Technology
Meng Wang is currently an Assistant Professor and Co-Director of the Electric and Automated Transport Research Lab of TU Delft. He is an Associate Editor of IEEE Transactions on Intelligent Transportation Systems, IET Intelligent Transport Systems, and Transportmetrica B. He is Program Chair of IEEE Forum on Integrated and Sustainable Transportation Systems 2020. He serves as a member of IEEE ITSS Technical Committee on Cooperative Driving and TRB Subcommittee on Traffic Flow Modelling for Connected and Automated Vehicles.
Bolin Zhou, Project Lead for ASAM OpenSCENARIO 1.x Project
Bolin Zhou, senior manager at China Automotive Technology and Research Center Co., Ltd, graduated from Columbia University. Currently he works as the secretary for ISO TC22/SC33 WG9 for “Test scenarios of Automated Driving Systems” and as the project lead of ASAM OpenSCENARIO 1.x project. Research area including scenario based testing and automated simulation functional testing for ADS.
Jing Zhao, Associate Professor, University of Shanghai for Science and Technology
Dr. Jing Zhao is currently an Associate professor and the Chair of the Department of Traffic Engineering at University of Shanghai for Science and Technology. He is a member of the expert group for the Transportation Bureau of the Ministry of Public Security of the People's Republic of China. He is also the co-chair of the public transportation design committee of the world transport convention (WTC). His expertise mainly focuses on traffic control and management, traffic flow model, and transit system. He is the first author of more than 40 papers in SCI/SSCI indexed journals. He hosted 3 research projects of the National Natural Science Foundation. As a major designer, he participated in several road engineering projects with over 4-billion-yuan investment.
Victor Knoop, Associate Professor, Delft University of Technology
Dr. Victor Knoop is associate professor at the Department of Transport & Planning. His main research interest lies in traffic dynamics. His research focuses on how driver movements create effects at the level of a traffic stream. Moreover, he increases the scale of traffic description to an even higher level, analysing effects of multiple roads combined into a single zone.
Wenshuo Wang, Postdoctoral Researcher, University of California at Berkeley
Wenshuo Wang received his Ph.D. degree in Mechanical Engineering from Beijing Institute of Technology in 2018. He is now working as a Postdoctoral Researcher at UC Berkeley. Before joint UC Berkeley, he worked as a Postdoc at Carnegie Mellon University (2018-2019). During his Ph.D. program, he also worked as a research scholar at UC Berkeley (2015-2017) and the University of Michigan, Ann Arbor (2017-2018). His research focuses on Bayesian nonparametric learning, reinforcement learning on multi-agent interaction behavior modeling and prediction at human-levels for autonomous vehicles, and intelligent transportation systems in common-but-challenging situations.
Jun Ni, Associate Research Professor, Beijing Institute of Technology
Jun Ni received the Ph.D. degree from Beijing Institute of Technology (BIT), Beijing, China, in 2019. He is currently an Associate Professor with BIT. He was a Visiting Scholar in the Vehicle Dynamics Control Lab, University of California, Berkeley, CA, USA. His current research interests include vehicle dynamics control and autonomous vehicle control. Dr. Ni was elected to the Young Elite Scientists Sponsorship Program by CAST of China. He was the recipient of the National Award of Science and Technology for Youth in 2013.
Jinxiang Wang, Associate Professor, Southeast University
Jinxiang Wang received the B.S. degree in mechanical engineering and automation and the Ph.D. degree in vehicle engineering from Southeast University, Nanjing, China, in 2002 and 2010, respectively. From 2014 to 2015, he was a Visiting Research Scholar with the Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, OH, USA. He is currently an Associate Professor with the School of Mechanical Engineering, Southeast University, Nanjing. His research interests include vehicle dynamics and control, assisted-driving system, and control on autonomous vehicles.
Xiaoxiang Na, Senior Research Associate, University of Cambridge
Xiaoxiang Na is currently a Senior Research Associate with the Centre for Sustainable Road Freight (SRF) at Cambridge University Engineering Department. His research focuses on the development of a system of methods for measuring, modelling, analysing and understanding energy consumption of road freight vehicles. He received his BSc and MSc degrees in Automotive Engineering from the College of Automotive Engineering, Jilin University, China in 2007 and 2009, respectively. Xiaoxiang Na joined the Driver-Vehicle Dynamics Group as a PhD student at Cambridge University Engineering Department, where he obtained his PhD in Nov 2014. Xiaoxiang Na joined the Centre for SRF in April 2014.
Zirui Li (Corresponding organizer) Ph.D. Candidate at Beijing Institute of Technology (E-mail: 3120195255@bit.edu.cn)
Zirui Li received the B.S. degree from the Beijing Institute of Technology (BIT), Beijing, China, in 2019, where he is currently pursuing the Ph.D. degree in mechanical engineering. His research interests include intelligent vehicles, driver behaviour modelling and transfer learning.
Jiachen Li, Ph.D. Candidate at UC Berkeley (E-mail:jiachen_li@berkeley.edu)
Jiachen Li is a Ph.D. Candidate at UC Berkeley. His research interests include machine learning, computer vision, optimization approaches and their applications to relational reasoning, behavior prediction, decision making and planning for autonomous vehicles and mobile robots, especially in multi-agent settings. He served as a co-organizer of the workshop on behavior prediction and decision making in 2019 IEEE Intelligent Vehicles Symposium and 2020 IEEE Intelligent Vehicles Symposium. He also serves as a reviewer for multiple top conferences and journals in the fields of machine learning, autonomous driving and robotics.
Chao Lu, Lecturer at Beijing Institute of Technology (E-mail: chaolu@bit.edu.cn)
Chao Lu received the B.S. degree in transport engineering from the Beijing Institute of Technology (BIT), Beijing, China, in 2009, and the Ph.D. degree in transport studies from the University of Leeds, Leeds, U.K., in 2015. In 2017, he was a Visiting Researcher with the Advanced Vehicle Engineering Centre, Cranfield University, Cranfield, U.K. He is currently a Lecturer with the School of Mechanical Engineering, BIT. His research interests include intelligent transportation and vehicular systems, driver behaviour modelling, reinforcement learning, and transfer learning and its applications.
Jianwei Gong, Professor at Beijing Institute of Technology (E-mail: gongjianwei@bit.edu.cn)
Jianwei Gong received the B.S. degree from the National University of Défense Technology, Changsha, China, in 1992, and the Ph.D. degree from Beijing Institute of Technology, Beijing, China, in 2002. Between 2011 and 2012, he was a Visiting Scientist with the Robotic Mobility Group, Massachusetts Institute of Technology, Cambridge, MA, USA. He is currently a Professor and the Director of the Intelligent Vehicle Research Centre, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China. His research interests include intelligent vehicle environment perception and understanding, decision making, path/motion planning, and control. He served as a co-organizer of the workshop in 2018 IEEE Intelligent Vehicles Symposium.
Bart Van Arem，Professor at Delft University of Technology (E-mail:b.vanarem@tudelft.nl)
Bart van Arem was appointed full professor Transport Modelling at Delft University of Technology in 2009. He was head of the department Transport & Planning from 2010 till 2017. Since 2011 he has served as director of the TU Delft Transport Institute. From 2003-2012 he was part-time full professor at the University of Twente. From 1991-2009, he worked at TNO. Bart van Arem has an MSc (1986) and PhD (1990) degree in Applied Mathematics at the University of Twente, the Netherlands.
If papers are submitted to workshop sessions, they must go through the same review process as regular and special session papers (submission deadline: March 31, 2021).
Please introduce the respective code (g7823) when submitting your paper.
Submitted papers shall not exceed six pages (two additional pages allowed with a fee) as a PDF file in IEEE two column format. All presented papers will be published by the IEEE and the conference proceedings will be submitted to the IEEE Xplore digital library, as long they follow the same review process of IEEE ITSC 2021, so that each paper will undergo a peer-reviewing process by at least two members of the International Program Committee.
Paper submission site: http://its.papercept.net/conferences/scripts/start.pl
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