Aptiv, the previously known Delphi Automotive and a worldwide car parts supplier, recently announced the complete release of their autonomous car dataset, nuScenes. This new dataset will help self-driving developers increase safety standards for their cars.
Aptiv is one of the first companies to share such a large, comprehensive dataset with the public. Aptiv says it's solving for a gap in the AV industry, which has limited open source data available for research purposes. Open source means its free for developers to use as needed.
Datasets are used to training machine learning models across different AI fields. They are used by engineers and developers of autonomous vehicles to train autonomous driving systems. However, training machine learning models requires vast amounts of "training data", which is the reason Aptiv made available its nuScenes dataset to developers.
For autonomous driving, these datasets might contain videos of street scenes captured from self-driving vehicle's real-world environment, such as a busy urban intersections filled with pedestrians. The training data is used to "train" machine learning algorithms, so software can better detect each person as well as predicting their intended trajectory, allowing a self-driving car to safely navigate.
"At Aptiv, we believe that we make progress as an industry by sharing—especially when it comes to safety," said Karl Iagnemma, president of Aptiv Autonomous Mobility. "Our team thought carefully about the components of our data that we could open to the public in order to enable safer, smarter systems across the entire autonomous vehicle space."
Read more here