Ideation

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OpenLABEL Concept Project

PROJECT NUMBER
P2019-09
PROJECT TYPE
Concept Project
PROJECT LEADER
Mr. Nicola Croce, Deepen AI
DOMAIN
Simulation
PROJECT LEADER
Mr. Nicola Croce, Deepen AI
IDEATION WORKSHOP
PROPOSAL WORKSHOP
PROJECT START
Apr 2020
PUBLIC REVIEW
none
PROJECT END
Q3 2020
RELEASE
none


Contact

ASAM Technical Support

support(at)asam.net

Main Goal of the Project

Following up on multiple discussions within our OpenX development activities, we have identified the need for further standardization in the AD workflow.

 

Motivation

From working with different customers, a significant fragmentation emerged in the way each individual organization categorizes and describes the objects populating the driving environment. Such categorizations and descriptions are the fundamental building block of any Autonomous Driving System’s (ADS) perception stack, since it is through them that an ADS come to a primal understanding of the status of around itself, including the entities present and some aspects of their behavior. Many vital driving decisions are based on this understanding.


The lack of a common Labeling Standard in the industry is the root cause of several different issues:

  • Hampered Vehicle2Vehicle Interaction: the different descriptions/understandings of surroundings may cause casualties in complex situations involving two or more different ADSs
  • Precluded sharing: It results highly difficult if not impossible to share data across organizations adopting different Labeling taxonomies and specifications
  • Lowered Annotation quality: Each individual labeling task requires ad-hoc training and even custom software features development to be completed, that translates into a higher probability of errors and thus a threat to safety
  • Deprecation of old labels: Long-term operation of ADS development imply changes in quantity and richness of labels to be produced, considering the evolution of the driving scenes, new sensors, and scenarios. As a consequence, a flexible descriptive language is required to absorb future extensions/modifications of labels and guarantee back-compatibility.

 

In sum, the absence of a labeling Standard such as OpenLABEL is ultimately a significant safety threat for all road users surrounding any kind of vehicle which is being operated in autonomous or semi- autonomous (SAE Level >=2) mode. OpenLABEL objective is to increase overall operational safety by providing a language that allows for the encoding of a common baseline understanding of the driving environment for any ADS.

 

Project Contents

The OpenLABEL Concept Project will come up with a concept on how a future labeling Standard could look like. This concept will include topics on labeling methodology, labeling structure, File Format. The OpenLABEL Concept project will be closly coupled with tne upcoming ontology project, as the object descriptions will be delivered by the ontology project. on the other hand the OpenLABEL Project will deliver requirements to the ontology project.
Next to the Object labeling the OpenLABEL project will also cover the scenario labeling, in this case the coupling will be with the ontology project and the upcoming OpenSCENARIO project.

 

In the end the concept paper will cover:

  • labeling methodology
  • labeling structure (including relations)
  • fileformat and structure definitions
  • scenario labeling
    • labels derived from object labels
    • abstract labeling of scenarios


Participating Companies

  • Advanced Data Controls Corp.
  • Akkodis Germany Consulting GmbH (AKKA)
  • Ansys, Inc.
  • Automotive Data of China (Tianjin) Co., Ltd
  • Connected Places Catapult
  • Deepen AI
  • Deutsches Zentrum für Luft- und Raumfahrt e.V. DLR
  • dSPACE GmbH
  • iASYS Technology Solutions Pvt. Ltd.
  • LiangDao GmbH
  • Peak Solution GmbH
  • RA Consulting GmbH
  • Siemens Digital Industries Software
  • Vicomtech
  • WMG University of Warwick
  • EFS - Elektronische Fahrwerksysteme GmbH
  • understand.ai

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Contact

ASAM Technical Support

support(at)asam.net

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