The OpenLABEL Standard Development Project will develop a standard based on the concept paper of the OpenLABEL Concept. This standard will include topics on labeling methodology, labeling structure, file format. The OpenLABEL standard project will be closely coupled with the ontology project, as the object descriptions will be delivered by the ontology project. The OpenLABEL Standard will be developed using the OpenXOntology Core Domain model. The OpenLABEL Standard will be accompanied by a user guide.
The OpenLABEL Standard Development Project will develop a standard based on the concept paper of the OpenLABEL Concept. This standard will include object labeling topics on labeling methodology, labeling structure and file format. The OpenLABEL standard project will be closely coupled with the ontology project, as the object descriptions will be delivered by the ontology project. The OpenLABEL Standard will be developed using the OpenXOntology Core Domain model. The OpenLABEL Standard will be accompanied by a user guide.
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.
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 standard and the user guide will cover:
This is a proposal for the development of OpenLABEL, a new standard regarding the Labeling, for Machine Learning models training and validation, of raw data generated by vehicles equipped with sensors with the capacity to enable any SAE level of autonomy >= 2. In addition to the labeling of Datasets for machine learning the OpenLABEL Standard will also provide scenario labelling methodology
This is a proposal for the development of OpenLABEL, a new standard regarding the Labeling, for Machine Learning models training and validation, of raw data generated by vehicles equipped with sensors with the capacity to enable any SAE level of autonomy >= 2. In addition to the labeling of Datasets for machine learning the OpenLABEL Standard will also provide scenario labeling methodology
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 Vehicle2X Interaction*: the different descriptions/understandings of surroundings may cause casualties in complex situations involving two or more different ADS's OpenLABEL could support filling the existing V2X standards like ITS G5.
* *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
* *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.
