Gaia-X 4 moveID
Automated Driving
Automated Driving
Operational Design Domain (ODD) classifier
Cities and municipalities want to offer automated passenger and freight transport. To achieve this, municipal decision-makers need a simple and well-structured classification of whether and how automated vehicles can be used and which infrastructural measures are required additionally. With the ODD classifier, we provide a solution for this.
What functions do the ODD and ODD classifier perform?
An Operational Design Domain (ODD) defines the specific conditions under which an autonomous vehicle can operate safely and effectively. Among these are geographical restrictions, weather conditions, road types and traffic densities.
An ODD classifier is a tool or system that compares the current surrounding environment and conditions with the defined ODD of an autonomous vehicle to determine if the vehicle can operate safely in the given situation.
The ODD classifier collects data on the surroundings (e.g. via sensors or maps) and compares them to the parameters of the ODD. If the conditions of the surrounding are within the defined limits of the ODD, the autonomous vehicle can be approved. If not, the vehicle will either not be used or will be transitioned to a safe mode until it reaches a suitable ODD. This means that in a city it is possible to precisely determine in which areas autonomous vehicles can drive and in which they cannot. This increases the safety and efficiency of autonomous driving.
Information deficits regarding automated driving in urban areas
Often, municipalities and cities do not have enough knowledge on automated vehicles to make decisions. It is unclear if automated driving is possible in desired target areas and which costs need to be budgeted to introduce it. This applies in particular to infrastructural measures, i.e. to modify roads and install additional C-ITS hardware along the road. The term C-ITS (Cooperative Intelligent Transport Systems) describes the exchange of digital radio messages on traffic events by vehicles, traffic lights, sign gantries and roadworks in order to increase road safety and improve traffic flow.
A tool for urban authorities to ensure safe automated driving
The ODD classifier is a tool for urban decision-makers that supports decisions and assessments for automated driving. The tool shows if automated driving is possible in the desired operating areas and where challenges are to be expected.
The ODD classifier uses the Federated Catalogue provided by Gaia-X 4 ROMS to check the individual criteria of the ODD. It identifies data sources that can provide the required data for a specific geographic area. Each ODD criterion for each relevant road segment is checked and converted into a simple statement ("fulfilled"/"not fulfilled").
The ODD classifier's benefit for transport stakeholders
Decision-makers in cities and municipalities are provided with a simple tool about the possibilities of automated driving in their city or municipality. Challenging geographical locations are highlighted and it shows which ODD criteria are not met, for example traffic lights without C-ITS equipment or unavailable road markings. This makes it easier to estimate the necessary costs for the introduction of automated driving services.
Providers of automated vehicles can use the tool to visualize the possible deployments of their vehicles.
Providers of C-ITS or infrastructure solutions can show which of their solutions lead to improvements in the areas of use.
Mobility providers can estimate how flexibly their vehicle fleet can be used in the respective city or municipality.
Gaia-X 4 Future Mobility family of projects and Gaia-X ecosystem
The ODD classifier combines various activities of the Gaia-X 4 Future Mobility family of projects: The use of vehicle fleets from Gaia-X 4 ROMS is connected to the ODD-OD matching from Gaia-X 4 AMS. The integration of various data sources from different areas (e.g. static data from maps, semi-dynamic data such as roadworks, dynamic data from weather forecasts) allows the connection to other services.
