Workshop Topics

With the advancement of vehicle automation and vehicle-to-everything (V2X) communications, the concept of cooperative driving has been attracting increasing attention from both academia and industry. Connected and automated vehicles are able to coordinate with each other or infrastructures to benefit the transportation system in terms of safety, mobility, resilience, and/or environmental sustainability.

However, the market penetration rate of such vehicles is expected to evolve gradually. There will certainly be a transition period where only a portion of the vehicles traveling in the traffic environment are connected and/or automated, while others are still conventional vehicles. How to perform cooperative driving maneuvers in mixed traffic environments to allow the coordinations among all these vehicle types remains an open research question.

This workshop focuses on sharing the state-of-the-art design, modeling, algorithms, simulation, and field implementation of cooperative driving in mixed traffic, and identifies challenges as well as research needs, aiming to encourage cross-disciplinary cooperation.

Invited Speaker: Sergei S. Avedisov

Research Scientist, Toyota Motor North America R&D, InfoTech Labs, USA

Biography: Dr. Avedisov is currently a Research Scientist at InfoTech Labs, Toyota Motor North America R&D. He received his M.Sc. and Ph.D. in Mechanical Engineering from the University of Michigan, Ann Arbor, USA, in 2016 and 2019 respectively. His current research interests are cooperative perception and cooperative maneuvering of connected vehicles, 5G communication technology, and applications of vehicle connectivity to ADAS.

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Invited Speaker: Erdem Bıyık

Ph.D. Candidate, Stanford University, USA

Biography: Mr. Bıyık is a Ph.D. candidate in the Electrical Engineering department at Stanford. He has received his B.Sc. degree from Bilkent University, Turkey, in 2017; and M.Sc. degree from Stanford University in 2019. He is interested in enabling robots to learn from various forms of human feedback and designing altruistic robot policies to improve the efficiency of multi-agent systems both in cooperative and competitive settings. Specifically, he works on developing learning algorithms for robots that actively query the humans and on training the robot policies that influence the humans to get more cooperative, which in turn improves the payoff for all agents.

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Invited Speaker: Yan Chang

Tech Lead and Senior Software Engineer, Lyft Level 5, USA

Biography: Dr. Chang is a tech lead and senior software engineer at Level 5, Lyft’s self-driving division (Level 5 is being acquired by Woven Planet, a subsidiary of Toyota Motor Corporation). She received M.S. and Ph.D. degrees from University of Michigan, Ann Arbor. Her research is mainly focused in the development and optimization of automotive systems, the application of machine learning, and the decision making and motion planning of autonomous vehicles.

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Invited Speaker: Gabor Orosz

Associate Professor, University of Michigan, USA

Biography: Dr. Orosz is currently an Associate Professor in Mechanical Engineering at the University of Michigan, USA. He received his Ph.D. in Engineering Mathematics from the University of Bristol, UK, in 2006. Before that, he received MSc in Engineering Physics from Budapest University of Technology and Economics, Hungary, in 2002. His current research interests are Nonlinear dynamics and control, time delay systems, reinforcement learning, connected and automated vehicles, traffic flow, biological networks.

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Invited Speaker: Zhanbo Sun

Professor and Associate Dean, Southwest Jiaotong University, China

Biography: Dr. Sun is currently a Professor and Associate Dean in the School of Transportation and Logistics at Southwest Jiaotong University, China. He received his Ph.D. in Transportation Engineering from Rensselaer Polytechnic Institute, USA, in 2014. Before that, he received his B.S. in Civil Engineering from Tsinghua University, China, in 2009. His current research interests are Collaborative Decision working for mixed Traffic with connected Automated Vehicles and Human Operated Vehicles.

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Lightning Talk Speaker: Yougang Bian

Assistant Professor, Hunan University, China

Biography: Dr. Bian received the B.E. and Ph.D degrees from Tsinghua University in 2014 and 2019, respectively. From 2017 to 2018, he was a Visiting Student with the Department of Electrical and Computer Engineering, University of California at Riverside. His research focuses on cooperative control and distributed control with their applications to connected and automated vehicles.

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Lightning Talk Speaker: Behdad Chalaki

Ph.D. Student, University of Delaware, USA

Biography: Mr. Chalaki is a research assistant at the Information and Decision Science Laboratory at the University of Delaware. His research interests are in network optimization, optimal control, and machine learning, with an emphasis on transportation networks. In particular, he is motivated by problems related to improving traffic efficiency and safety in smart cities using optimization techniques.

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Lightning Talk Speaker: Xishun "Heeson" Liao

Ph.D. Candidate, University of California, Riverside, USA

Biography: Mr. Liao is currently a Ph.D. student in Electrical and Computer Engineering at University of California, Riverside. He received the master degree in Mechanical Engineering at University of Maryland, College Park, and the B.E. degree in Mechanical Engineering and Automation at Beijing University of Posts and Telecommunications. His research focuses on decision making, driver behavior and connected and automated vehicle technology.

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Lightning Talk Speaker: Xinpeng Wang

Ph.D. Candidate, University of Michigan, USA

Biography: Mr. Wang received his B.S. degree in automation from Tsinghua University, Beijing, China in 2017. He is currently pursuing the Ph.D. degree in Mechanical Engineering at the University of Michigan, Ann Arbor. His research interests include human driving behavior modeling, and the control and evaluation of highly automated vehicles.

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Lightning Talk Speaker: Yanbing Wang

Ph.D. Student, Vanderbilt University, USA

Biography: Ms. Wang is currently a Ph.D. student at Vanderbilt University. During Spring 2021, she was a Research Intern at Toyota InfoTech Labs. She received B.S. in Civil Engineering from University of Illinois at Urbana-Champaign. Her research focuses on state estimation, nonlinear system identification and control with applications on adaptive cruise control design.

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Lightning Talk Speaker: Ziran Wang

Research Scientist, Toyota Motor North America R&D, InfoTech Labs, USA

Biography: Dr. Wang is currently a Research Scientist at InfoTech Labs, Toyota Motor North America R&D. He received his Ph.D. in Mechanical Engineering from the University of California, Riverside, USA, in 2019. His current research interests are cooperative automated driving, driver behavior modeling with machine learning, and digital twin of intelligent vehicles.

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Contributed Speaker: Fumiaki Sato

Professor, Department of Information Science, Toho University, Japan

Biography: Dr. Sato is currently a Professor at the Department of Information Science, Toho University, Japan. He received his M.E. and D.E. from Tohoku University in 1986 and 1992, respectively. His current research interests are mobile computing, vehicular ad-hoc networks, and traffic estimation by image recognition using deep learning and its application.

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Contributed Speaker: Haoran Wang

Ph.D. Candidate, College of Transportation Engineering, Tongji University, China

Biography: Mr. Wang received the bachelor’s degree from Tongji University in 2017. He is currently a Ph.D. candidate with the College of Transportation Engineering, Tongji University. He is a researcher on vehicle engineering, majoring in vehicle control and cooperative automation.

Contributed Speaker: Yong Wang

Master Student, College of Computer Science, Chongqing University, China

Biography: Mr. Wang is currently studying at the College of Computer Science, Chongqing University. In 2019, he received a bachelor's degree in computer science and technology from the College of Computer Science, Chongqing University. His current research interests are car network and intelligent networked vehicle test.

Contributed Speaker: Yiming Zhang

Ph.D. Student, College of Transportation Engineering, Tongji University, China

Biography: Mr. Zhang received the B.S. degree from Shenzhen University, Shenzhen, in 2016 and M.S. degree in traffic engineering from Tongji University, Shanghai, in 2019. He is currently pursuing the Ph.D. degree in traffic engineering at Tongji University, Shanghai. His research interests include connected vehicles, Intelligent Transportation Systems, cooperative driving.

Workshop Agenda

The workshop will be held in two seperate sessions across two days.

Session 1:
Jul. 11 (Sunday) 10am-1pm Japan Standard Time (JST)
Jul. 11 (Sunday) 3-6am Central European Summer Time (CEST)
Jul. 10 (Saturday) 6-9pm Pacific Time (PDT)

10:00-10:30am JST
Zhanbo Sun, Southwest Jiaotong University
Cooperative Ramp Merging for Mixed Traffic with Connected Automated Vehicles and Human-Operated Vehicles

10:30-11:00am JST
Haoran Wang, Tongji University
Make Space to Change Lane: A Cooperative Adaptive Cruise Control Lane Change Controller 

11:00-11:10am JST
Behdad Chalaki, University of Delaware
Optimal Control of Connected and Automated Vehicles at Multiple Adjacent Intersections

11:10-11:20am JST
Xishun Liao, University of California, Riverside
A Game Theory Based Ramp Merging Strategy for Connected and Automated Vehicles in the Mixed Traffic

11:20-11:30am JST
Yougang Bian, Hunan University
Stabilizing Mixed Traffic Flow via Connected and Automated Vehicles

11:30am-noon JST
Yong Wang, Chongqing University
Research on Optimization and Evaluation Method of the Car Following Model based on SUMO Application Test Scenario 

noon-12:30pm JST
Yiming Zhang, Tongji University
An Adaptive Cooperative Adaptive Cruise Control against Varying Vehicle Loads

12:30-1pm JST
Sergei S. Avedisov, Toyota Motor North America
Assessing Awareness of Connected Vehicles in Mixed Traffic Environments through Perceived Safety




Session 2:
Jul. 12 (Monday) 10am-1pm Japan Standard Time (JST)
Jul. 12 (Monday) 3-6am Central European Summer Time (CEST)
Jul. 11 (Sunday) 6-9pm Pacific Time (PDT)

10:00-10:30am JST
Fumiaki Sato, Toho University
Predicting Motorcycle Riding Behavior using Vehicle Density Variation

10:30-11:00am JST
Gabor Orosz, University of Michigan
Connectivity Assisted Automated Driving among Human-Driven Vehicles 

11:00-11:10am JST
Xinpeng Wang, University of Michigan
Accelerated Evaluation of Highly Automated Vehicles at the Pedestrian Crossing Scenario

11:10-11:20am JST
Yanbing Wang, Vanderbilt University
Interstate-24 MOTIONS: Enabling Smart Mobility with High-fidelity Trajectory Extractions

11:20-11:30am JST
Ziran Wang, Toyota Motor North America
Digital Twin-Assisted Cooperative Driving at Unsignalized Intersections

11:30am-noon JST
Erdem Bıyık, Stanford University
Learning how to Route Autonomous Vehicles on Shared Roads

noon-12:30pm JST
Yan Chang, Lyft Level 5
Data-Driven Planning




Workshop Organizers

Ziran Wang, Research Scientist
Toyota Motor North America R&D - InfoTech Labs, USA
Guoyuan Wu, Associate Research Engineer
University of California, Riverside, USA
Shuo Feng, Post-Doctoral Researcher
University of Michigan, USA
Zhaojian Li, Assistant Professor
Michigan State University, USA
Jia Hu, Professor
Tongji University, China
Meng Wang, Assistant Professor
TU Delft, Netherlands