mlsanityData to 14 Oct 2026

Quantification of Actual Road User Behavior on the Basis of Given Traffic Rules

arXiv 2202.09269 ↗First posted 7 Feb 2022cs.RO cs.LGcited by 2

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Abstract (arXiv)

Driving on roads is restricted by various traffic rules, aiming to ensure safety for all traffic participants. However, human road users usually do not adhere to these rules strictly, resulting in varying degrees of rule conformity. Such deviations from given rules are key components of today's road traffic. In autonomous driving, robotic agents can disturb traffic flow, when rule deviations are not taken into account. In this paper, we present an approach to derive the distribution of degrees of rule conformity from human driving data. We demonstrate our method with the Waymo Open Motion dataset and Safety Distance and Speed Limit rules.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 13 of its 27 references that are in the map. First posted on arXiv 7 Feb 2022.

Builds on

13 of 27 references.

References · 13

  1. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
  2. 2016End to End Learning for Self-Driving Carscited by 1,009
  3. 2019INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Mapscited by 231
  4. 2019Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systemscited by 205
  5. 2019The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersectionscited by 137
  6. 2021TPCN: Temporal Point Cloud Networks for Motion Forecastingcited by 94
  7. 2019Liability, Ethics, and Culture-Aware Behavior Specification using Rulebookscited by 43
  8. 2021Description of Corner Cases in Automated Driving: Goals and Challengescited by 35
  9. 2021Learning from Demonstrations using Signal Temporal Logiccited by 17
  10. 2021The Reasonable Crowd: Towards evidence-based and interpretable models of driving behaviorcited by 12
  11. 2022Ad-datasets: a meta-collection of data sets for autonomous drivingcited by 11
  12. 2021Safety of the Intended Driving Behavior Using Rulebookscited by 9
1 more
  1. 2021How To Not Drive: Learning Driving Constraints from Demonstrationcited by 2

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Cited by year

Citing papers per year: 2024: 2.

2 papers.

  1. 2024AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Drivingcited by 14
  2. 2024Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptionscited by 4