VAMLAV Dataset
The VAMLAV dataset is a large autonomous driving (AD) dataset, created by Zenseact with support from Astazero and RISE. It was collected over a 2-year period in the rural road at Astazero test track under controlled conditions and different weather conditions. The Rural Road is approximately 5.7 km long. Half is designed for 70 km/h and half for 90 km/h.
In short
Content
The dataset consists of 7-day drives in different weather conditions and variable minute lengths. The data collection has been conducted using several vehicles with an identical sensor layout driven around the rural road test track in Astazero.
Camera images: jpeg
Lidar Point clouds: npy
OXTS GNSS: hdf5
Vehicle data/consumer-grade sensors: hdf5
Author
The author of the data is Zenseact as a partner in the VAMLAV project. Special thanks to Gabriel Garcia Jaime, Peter Jason, Lina Sjöstrand, Per Lofter, Adam Eriksson (Asta Zero), Carl-Henrik Hanquist (RISE) Erik Lindvall (RISE), Adam Larsson (AI Sweden) and Andreas Olsson (AI Sweden) and for the help during data collection and extraction.
Data Type
The dataset is a controlled environment in a closed test track with limited traffic. Each drive contains a specific hazard-related scenario, e.g., reductions of lanes, yellow lane markers, road work traffic signs. The data was collected during the day under varying weather conditions. More specifications around sensor setup, drive files setup are similar to those in Zenseact Open Dataset. The cars are equipped with a high-resolution camera, 3x LiDARs, a high-precision GNSS/IMU sensor and other consumer-grade sensors.
Camera images: jpg
Lidar Point clouds: npy
OXTS GNSS: hdf5
Vehicle data/consumer-grade sensors: hdf5
Anonymization
The dataset is anonymized. Faces and vehicle license plates are anonymized using the BrighterAI tools for GDPR compliance and the intent to preserve every identity on roads with blurred faces and license plates.
Annotations
None
Size
2 TB
Access
The dataset is available for all AI Sweden partners.
Terms and Conditions
To use this dataset, you must comply with the VAMLAV Terms and Conditions available below
Access
The dataset is available for all AI Sweden partners. Contact Beatrice Comoli for further instructions on how to access the data. If you are interested in becoming a partner of AI Sweden, getting access to the partner benefits, including the Data Factory and datasets, or in sharing a dataset or a model, please feel free to reach out.
