Workshop on Autonomous Vehicles Across Scales

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Progress in autonomous vehicle (AV) technologies is indisputable, as evidenced by growing industrial and even commercial deployments. The time is ripe for the research community to reflect on the road ahead — including upcoming challenges and opportunities. Despite the real-world deployments, there remains no satisfactory answer to the questions of how safe is `safe enough,’ how to assure safety at scale, the extent to which AV technology will provide societal value (e.g., congestion relief, emissions reduction, increased mobility access), nor to the role of digital and physical infrastructure in complementing AV technology. These questions require not only consideration of the ego vehicle, but also the traffic system and the transportation network as a whole.

While robotics research has focused on the ego vehicle challenges, such as advancing perception, localization, and planning, parallel lines of research in the control, operations research, and transportation communities examine questions beyond the ego vehicle, such as system-level control, operations, and broader implications of AV technologies. These emerging efforts revolve around the challenges, impact, and applications of AVs, spanning the traffic level (e.g., utilizing AVs as Lagrangian actuators for optimizing traffic flow), network level (e.g., integrating AVs as robo-taxis in dynamic mobility-on-demand systems), and even the regional level (e.g., shaping AV-related policymaking).

In this workshop, we encourage discussion and collaboration across the three ‘scales’ of AV research: (1) ego vehicle, (2) traffic, and (3) network. Up to this point, such scales have primarily been investigated by disparate research communities. But ultimately, they will affect people’s lives in the same transportation system. Hence, this workshop seeks to bring together these perspectives and researchers, with the aim of providing space for lively discussion and debate on how to best move forward for a holistic design of future AV-enabled mobility systems.

Discussion Topics

  • Ego-vehicle scale: What fundamental technical challenges remain for autonomous driving? How safe is safe enough, and how can we know if we have achieved the appropriate level of safety? Potential sub-topics include planning, perception, localization, mapping, behavior prediction, human factors, and safety assurances for AVs.
  • Traffic scale: What value can AVs provide to the traffic flow, beyond their immediate passengers? What is the role of infrastructure in complementing AV technology? What are the fundamental similarities and differences in leveraging vehicles for traffic control versus traditional means, such as traffic signal control, ramp metering, variable speed limit control, or congestion pricing? Potential sub-topics include optimizing AVs for system-level objectives(ex: traffic smoothing and eco-driving), mixed autonomy traffic, cooperative sensing or control, long-term traffic simulation and calibration, large-scale multi-agent traffic optimization, value of sensor information, and infrastructure readiness.
  • Network scale: What are the implications of AV technology on travel demand, energy demand, mobility access, land use, and parking? What is the role of algorithmic research in supporting changes to policy and operations at the transportation network scale? Potential sub-topics include network optimization, transit integration, and land use optimization (e.g., parking) in light of AVs.
  • Scale overlaps: Potential sub-topics include co-design techniques that involve two or more scales of autonomous vehicle research.
  • Benchmarks: What benchmark environments will help the community better measure the progress of autonomous vehicle research at different scales?


The workshop will be held in-person as a full day workshop on July 15 in Delft, Netherlands.

A link to live stream of the workshop will be provided closer to the date. The recording will be made available through Youtube after the workshop.

Time (CET, GMT+1) Event
8.45 am - 9:00 am Introductory Remarks
9:00 am - 9:30 am Invited Talk 1: Marco Pavone (NVIDIA)
9:30 am - 10:00 am Invited Talk 2: Samitha Samaranayake (Cornell University)
10:00 am - 10:30 am Coffee Break and Poster Session
10:30 am - 11:00 am Invited Talk 3: Negar Mehr (UC Berkeley)
11:00 am - 11:10 am Spotlight Talk 1 (Scale 1)
11:10 am - 11:20 am Spotlight Talk 2 (Scale 2)
11:20 am - 11:30 am Spotlight Talk 3 (Scale 3)
11:30 am - 12:30 pm Panel Discussion 1: Marco Pavone, Samitha Samaranayake, Negar Mehr
12:30 pm - 2:00 pm Lunch Break
2:00 pm - 2:30 pm Invited Talk 4: John Subosits (Toyota Research Institute)
2:30 pm - 3:00 pm Invited Talk 5: Stephen Zoepf (U.S. Department of Tranportation)
3:00 pm - 3:30 pm Invited Talk 6: Cathy Wu (MIT)
3:30 pm - 4:00 pm Coffee Break and Poster Session
4:00 pm - 4:45 pm Panel Discussion 2: John Subosits, Stephen Zoepf, Cathy Wu
4:45 pm - 5:00 pm Best Paper Award & Conclusion Remarks


Speaker Bio

Marco Pavone is Director of Autonomous Vehicle Research at NVIDIA and an Associate Professor of Aeronautics and Astronautics at Stanford University, where he directs the Autonomous Systems Laboratory and the Center for Automotive Research. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems.

Samitha Samaranayake is an Associate Professor at Cornell University in the School of Civil and Environmental Engineering and a Graduate Field Faculty in the School of Operations Research and Information Engineering, the Center for Applied Math, and the Systems Engineering Program. His primary research interest is in mathematical modeling and algorithm design for large-scale transportation network problems, and his current focus is on problems at the intersection of public transit and ride-sharing.

John Subosits is the manager of the Performance-Centric Machine Learning (PCML) team within the Human Interactive Driving (HID) division at Toyota Research Institute (TRI). His research focuses on the creation of driver models that drive and adapt as well as the best human racing drivers. He holds a bachelor’s degree in mechanical and aerospace engineering from Princeton University and master’s and Ph.D. degrees in mechanical engineering from Stanford University. Trajectory planning for autonomous vehicles at their performance limits was the focus of his doctoral work.

Cathy Wu is an Assistant Professor at MIT in the Laboratory for Information & Decision Systems, the Department of Civil & Environmental Engineering, and the Institute for Data, Systems, and Society. She is interested in developing principled computational tools to enable reliable decision-making in sociotechnical systems, and focuses on the intersection of machine learning, control, and mobility.

Negar Mehr is an assistant professor in the Mechanical Engineering Department at the University of California at Berkeley. Her research focus to develop control algorithms that allow autonomous systems to safely and intelligently interact with each other and with humans. She was a Postdoctoral Scholar in the Department of Aeronautics and Astronautics at Stanford from 2019 to 2020. Negar received her PhD in Mechanical engineering at UC Berkeley in 2019 and received her bachelor’s degree in Mechanical Engineering at Sharif University of Technology in 2013.

Stephen Zoepf is the Acting Director of the Highly Automated Systems Safety Center of Excellence (HASS COE) and Chief Analyst for the Office of the Assistant Secretary for Research and Technology at the U.S. Department of Transportation. He holds a Ph.D., M.Sc. and B.Sc. from MIT and has two decades of experience in transportation and mobility. Stephen held previous roles leading Research at Lacuna Technologies, leading the Center for Automotive Research at Stanford, and as an engineer and product manager at BMW and Ford. He was an ENI Energy Initiative Fellow, a Martin Energy Fellow, and a recipient of the Barry McNutt award from the Transportation Research Board and the Infinite Mile award from MIT. His research has been covered in numerous popular press articles, initiated a Congressional probe, and has been lampooned in The Onion.