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ASAM OpenLABEL V1.0.0

PROJECT NUMBER
P_2020_12
PROJECT TYPE
New Standard Development
DOMAIN
Simulation
PROPOSAL WORKSHOP
ENROLL BY
Dec 04, 2020
PROJECT START
Dec 2020
PUBLIC REVIEW
Sep 2021
PROJECT END
Nov 2021
RELEASE
Nov 2021


Enroll in the Project: 

(Enroll by: Dec 04, 2020)

 

 

Please note: 

  • ASAM membership is required to
    take part.
  • We recommend a committment of 
    25 person-days per company.
  • To enroll please fill in the form below
    or contact
    nicco.dillmann(at)asam.net
     

 

Project Contents

The ASAM OpenLABEL Concept work group has developed a concept for a future standard for labeling objects and scenarios (ASAM OpenLABEL Concept Paper). It coveres the following aspects: labeling methodology, labeling structure and file format

 

The concept was developed in close collaboration with the project group ASAM OpenXOntology. While ASAM OpenXOntology defines WHAT is to be labelled, ASAM OpenLABEL will describe HOW it shall be labelled.  

 

 

Motivation for ASAM OpenLABEL

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.



Participating Companies

  • Annotell AB
  • Dataloop
  • Five
  • LiangDao GmbH
  • Peak Solution GmbH
  • Tata Consultancy Services Pvt. Ltd
  • understandAI GmbH
  • Vicomtech

BACK TO OVERVIEW



Enroll in the Project: 

(Enroll by: Dec 04, 2020)

 

 

Please note: 

  • ASAM membership is required to
    take part.
  • We recommend a committment of 
    25 person-days per company.
  • To enroll please fill in the form below
    or contact
    nicco.dillmann(at)asam.net
     

 

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