Where to from here? Algorithmic, Legal, and Societal Challenges for Autonomous Driving
IEEE IV 2019 BROAD workshop 2019
- URL: https://autonomesysteme.informatik.haw-hamburg.de/page/ieee-iv-2019-broad-ws/
- Event Date: 2019-06-09 ~ 2019-06-09
- Submission Date: 2019-02-07
- Location: Paris, France
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 is structured in two sessions to focus on two major aspects of these questions. The first session will identify major challenges across all aspects of autonomous driving (algorithmic, societal, 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? how to select training data?). But these could also be non-technical questions like law-, insurance-related, or ethical questions. Therefore, two different keynotes will be given: one OEM (Mercedes-Benz USA: Dr. Christoph Schroeder, Vice President Autonomous Driving N.A.) and one legal scientist (Prof. Stender-Vorwachs, Leibniz University, Germany).
In the second session, cognitively-inspired and ML-based solutions will be presented. 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.
*CFP*
The workshop explicitly focusses on broad, general issues (such as general properties of different paradigms currently in use (in particular biological or cognitively inspired ones that go beyond reducing cognition to classification problems), and comparisons thereof), including societal and ethical ones. We solicit papers that are in the spirit of this broad nature of the workshop.
Workshop papers have to be submitted in the same process as the symposium papers.
Workshop paper submission: February 7th, 2019 (the submission code is BROAD)
Notification of workshop paper acceptance: March 29, 2019
Final Workshop paper submission: April 22, 2019
IV 2019: June 9 - 12, 2019 (workshop: June 9th)
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 http://iv2019.org/information-for-authors/
The paper submission site is: https://its.papercept.net/conferences/scripts/start.pl
The submission code for this workshop is “BROAD”.
The workshop is structured in two sessions to focus on two major aspects of these questions. The first session will identify major challenges across all aspects of autonomous driving (algorithmic, societal, 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? how to select training data?). But these could also be non-technical questions like law-, insurance-related, or ethical questions. Therefore, two different keynotes will be given: one OEM (Mercedes-Benz USA: Dr. Christoph Schroeder, Vice President Autonomous Driving N.A.) and one legal scientist (Prof. Stender-Vorwachs, Leibniz University, Germany).
In the second session, cognitively-inspired and ML-based solutions will be presented. 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.
*CFP*
The workshop explicitly focusses on broad, general issues (such as general properties of different paradigms currently in use (in particular biological or cognitively inspired ones that go beyond reducing cognition to classification problems), and comparisons thereof), including societal and ethical ones. We solicit papers that are in the spirit of this broad nature of the workshop.
Workshop papers have to be submitted in the same process as the symposium papers.
Workshop paper submission: February 7th, 2019 (the submission code is BROAD)
Notification of workshop paper acceptance: March 29, 2019
Final Workshop paper submission: April 22, 2019
IV 2019: June 9 - 12, 2019 (workshop: June 9th)
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 http://iv2019.org/information-for-authors/
The paper submission site is: https://its.papercept.net/conferences/scripts/start.pl
The submission code for this workshop is “BROAD”.
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