Where to from here? Algorithmic, Legal, and Societal Challenges for Autonomous Driving

Where to from here? Algorithmic, Legal, and Societal Challenges for Autonomous Driving

The BROAD workshop

What are the new frontiers of autonomous driving: Are there open technical or non-technical issues that impede autonomous driving now or in the upcoming future? Can cognitive inspiration and machine learning (ML) help us here or do these approaches lead to new problems?

The workshop focuses on two major aspects of these questions. The first is the identification of major challenges across all aspects of autonomous driving (algorithmic, societal, law-related, standardization, etc.) that are supposed to or that could probably impede the development of autonomous driving (AD) or its introduction on the market. These could be technical issues (how many test miles need to be driven? is ML reliable? do we need explainable ML methods in general? how to select training data?). But these could also be non-technical questions like law-, insurance-related, or ethical questions.

The second aspect is the discussion of potential, cognitively-inspired and ML-based solutions. Here, we will focus on two approaches: pure ML, and bio-inspired approaches that try to mimic cognitive mechanisms observed in humans and/or animals in a reasonable amount of detail. Each approach has their own particular advantages and limitations. For example pure ML often requires large amounts of training data, yet is typically very brittle while bio-inspired approaches are by necessity based on incomplete theories, and we’re still missing convincing demonstrations in real applications.


Workshop format: half day.

The IV 2020 was postponed to October 20 - 23, 2020, the workshops to later days. Workshop BROAD will take place on Friday, November 6th. The link to the BROAD workshop session is: https://haw-hamburg.zoom.us/j/93586713678 (pass code 309322).

(All times given in Las Vegas local time!)

Time Topic
08:00-08:15 Welcome talk: “What Are This Year’s Challenges for AD?” (Tim Tiedemann, HAW Hamburg)
08:15-09:15 Keynote “Why the Safety of Autonomous Vehicles Must Be A Collaborative Affair” (Jack Weast, Intel, USA)
09:15-09:30 Coffee break (short)
09:30-10:00 “Can AI-Based Components Be Part of Dependable Systems?” (Bettina Buth, HAW Hamburg, Germany)
10:00-10:30 “Qualification Concepts for Machine Learning Algorithms in Automotive Perception” (Julia Nitsch, Ibeo, Germany)
10:30-10:45 Coffee break (short)
10:45-11:15 “Autonomous Driving in a Developing Country : A discussion” (Vijayasri Iyer, VIT Mumbai, India)
11:15-11:30 “Presentation of EU project BEYOND5” (Francois Brunier, Soitec Bernin, France)
11:30-11:35 “Presentation of ITS World Congress 2021” (Tim Tiedemann, HAW Hamburg, Germany)
11:35-11:45 “Presentation of other Projects?” (Tim Tiedemann, HAW Hamburg, Germany)
11:45-12:00 Final discussion

The program, slides, videos, and further material is available via Infovaya for registered participants.


The workshop will feature a keynote from a prominent representative from industry:

  • Jack Weast, Sr. Principal Engineer at Intel and VP Autonomous Vehicle Standards at Mobileye and Chair of IEEE’s new P2864 working group (a standard for safety considerations in automated vehicle decision-making).
    Title: Why the Safety of Autonomous Vehicles Must Be A Collaborative Affair
      Abstract: Thanks in large part to the work of the IEEE Intelligent Vehicles research community, momentum has culminated in an opportunity for industry to finally collaborate on the development of formal standards for AV safety that can be used to inform and guide regulators. The time is now to formalize this work and get our AVs off the test track and into the real world.
    For several years now, Intel and Mobileye have advocated for industry and regulatory consensus on AV safety. An effort that is now beginning to bear fruit. At the center of the conversation today – thanks to the collaborative work of researchers, engineers, practitioners and students from across academia, industry and government agencies -  is a forthcoming standard – IEEE 2846 – that will establish a formal rules-based mathematical model for automated vehicle decision-making that will be formally verifiable (with math), technology neutral (meaning anybody can apply it) and adjustable to allow for regional customization by local governments.
    This standard will be crafted by representatives from across the industry and is eagerly anticipated by regulators. The session will provide a global overview of all standards efforts, how they fit, and why the IEEE standard initiative fills a unique spot in that global landscape. It will take a deeper dive into the work of the standards committee, with an eye to encouraging healthy debate. It will  also provide an opportunity to peak around the corner and examine the next hurdles facing AVs, and why it is imperative for the industry to adopt a more open, transparent and collaborative approach to deliver on the AV promise. A shared promise to save lives.


There will be a mixture of invited talks, regular paper presentations, and discussion rounds.

Poster Session

Unfortunately, this year there will be no poster session.

CFP / Submission

Paper submission site is closed.

Authors of accepted workshop papers will have their paper published in the conference proceeding. At least one author needs to be registered for the workshop and the conference. Information on paper and submission is common with all symposium papers and is available at https://2020.ieee-iv.org/information-for-authors/


  • Tim Tiedemann:
    Affiliation: Department of Computer Science, Faculty TI, University of Applied Sciences Hamburg
    Email address: Tim.Tiedemann@haw-hamburg.de

  • Serge Thill:
    Affiliation: Interaction Lab, School of Informatics, University of Skövde, Sweden and Donders Institute for Brain, Cognition, and Behaviour, Radboud University, The Netherlands

  • Sean Anderson:
    Affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield


This workshop is supported by the European H2020 project Dreams4Cars, grant agreement number 731593.