2022

A9-Dataset: Multi-Sensor Infrastructure-Based Dataset for Mobility Research

Creß, Christian, Zimmer, Walter, Strand, Leah et al.

Understand

Data-intensive machine learning based techniques increasingly play a prominent role in the development of future mobility solutions - from driver assistance and automation functions in vehicles, to real-time traffic management systems realized through dedicated infrastructure.

The availability of high quality real-world data is often an important prerequisite for the development and reliable deployment of such systems in large scale.
Towards this endeavour, we present the A9-Dataset based on roadside sensor infrastructure from the 3 km long Providentia++ test field near Munich in Germany.
The dataset includes anonymized and precision-timestamped multi-modal sensor and object data in high resolution, covering a variety of traffic situations.

Built on

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