Call for Workshop Papers

This workshop will be held at the 33rd IEEE Intelligent Vehicles Symposium (IV), on June 5th, 2022, in Aachen, Germany. We call for contribution of novel, unpublished ideas and will invite presentation of accepted peer-reviewed papers. Please find details on submission, scope and topics below and check this page regularly for updates.

Scope and Topics

Research on Automated Vehicles enabled safe prototypes, driving in public traffic. However, safety comes at the price of overly conservative inconvenient behavior, e.g. in unprotected left turns or merging scenarios. Reasons can include prediction errors in vehicle interactions or lack of probabilistic considerations in motion planning. While it must be ensured that safe and possibly uncomfortable reactions to worst-case behaviors of others remain feasible, the intended reaction should be comfortable.

Approaches providing sufficient and comfortable actions require sophisticated behavior prediction for other traffic participants. Predictions with maneuver options for other vehicles are needed, which cannot be evaluated against one single “right prediction”. Options may depend on destinations, driving styles and even emotions. Novel methods, not limited to machine learning or common evaluation schemes, are needed.

Similarly, motion planning in highly interactive scenarios lacks one single “ground truth”. In public traffic, a good plan should lead to stereotypical behavior, predictable by other road users. It’s realization requires research on the combination of planning and prediction and its evaluation and benchmarking.

The organizers support research with the published INTERACTION dataset https://interaction-dataset.com/ of trajectory data from highly interactive traffic scenarios on high-definition maps but all contributions within the scope of the workshop are welcome, with or without use of the dataset.

Topics of Interest

The topics of interest of the workshop include, but are not limited to:

  • Cooperative and comprehensible motion planning
  • Probabilistic decision making and motion planning (including MDPs, POMDPs, MMDPs)
  • Probabilistic behavior prediction (with help of semantic high-definition maps)
  • Evaluation and benchmarking for probabilistic prediction
  • Evaluation and benchmarking for comprehensible motion planning

Contributions

Papers should not exceed 6 pages and fulfill the requirements stated in the IEEE IV 2022 Guidelines. Each paper will undergo a peer-reviewing process by three independent reviewers. Contributions will be reviewed according to relevance, originality, novelty, technical soundness and quality of presentation.

Authors are encouraged to submit original work, not previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journals, conferences or workshops. For publication, at least one author needs to be registered for the workshop and the conference and present their work.

Please check the conference webpage for the details of submission guidelines - see https://iv2022.com/program/workshops

Submissions are welcome via papercept. Please use our workshop code wh622 for your submission. Submission deadline is March 15th, 2022. See https://iv2022.com/program/workshops for details on the workshop paper submission and https://iv2022.com/program/your-contribution for a template.

Please get in touch with the organizers in case you have any further questions.

Agenda

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Organizers

  • Sascha Hornauer, MINES ParisTech. Email: sascha.hornauer@mines-paristech.fr
  • Maximilian Naumann, Bosch Center for Artificial Intelligence (BCAI)
  • Eike Rehder, Mercedes-Benz AG
  • Jiachen Li, Stanford University
  • Wei Zhan, University of California at Berkeley
  • Martin Lauer, Karlsruhe Institute of Technology (KIT)
  • Masayoshi Tomizuka, University of California at Berkeley
  • Arnaud de La Fortelle, MINES ParisTech
  • Christoph Stiller, Karlsruhe Institute of Technology (KIT)

Past Editions

At IV2021, the organizers hosted a previous edition of this workshop: https://kit-mrt.github.io/iv2021-workshop/.