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For many AI-systems, there is a high demand for good computer vision datasets. There are only a few datasets on the market today which are free and open. The purpose of the VAMLAV project – Validation of Mapping and Localization for Autonomous Vehicles – is to create a new dataset which is free and open to stakeholders, and also contains HD maps that include changes in the environment.


The project aims to give the possibility for other partners to contribute to the dataset at the Rural Road test track at AstaZero.

VAMLAV will develop a HD map of the Rural Road at AstaZero, by using the existing measurement infrastructure specifically installed at the test track for measuring positions and by designing and installing anchor points. VAMLAV will also collect data from the specific sensors for the dataset.

The dataset that will be created in the project is mainly supposed to be used in VAMLAV for validating and testing map generation technologies and localization/positioning systems.

This new dataset will include changes in the testing environment, a corresponding HD map and effects of repeated driving around the same test track. By making the dataset open, multiple other research areas are enabled and this creates the possibility for crowdsourcing with VAMLAV’s dataset.

Project team

AstaZero is responsible for project management and AI Sweden for distributing the dataset and helping to spread knowledge about the dataset to its partners within academy, public sector and industry. RISE will contribute with expertise on within reference systems, GNSS as well as knowledge in estimation and calculation of measurement uncertainties. Zeunity will contribute in validating maps, data collection, localization and provide input on anchor points. 


Project partners: Lindholmen Science Park, AstaZero AB, RISE, Zenuity. This project is funded by Vinnova ´s FFI Program

Project period: 20191001 - 20210930


Project Manager

Ebba Josefson Lindqvist

Project Manager

Adam Eriksson