2 min read

This week, the team at Lyft released a subset of their autonomous driving data, the Level 5 Dataset, and will be sponsoring a research competition. The Level 5 Dataset includes over 55,000 human-labelled 3D annotated frames, a drivable surface map, as well as an HD spatial semantic map for contextualizing the data.

The team has been perfecting their hardware and autonomy stack for the last two years. As the sensor hardware needs to be built and properly calibrated, there is also the need for a localization stack and an HD semantic map must be created. Only then it is possible to unlock higher-level functionality like 3D perception, prediction, and planning.

The dataset allows a broad cross-section of researchers in contributing to downstream research in self-driving technology. 

The team is iterating on the third generation of Lyft’s self-driving car and has already patented a new sensor array and a proprietary ultra-high dynamic range (100+DB) camera.


Since HD mapping is crucial to autonomous vehicles, the teams in Munich and Palo Alto have been working towards building high-quality lidar-based geometric maps and high-definition semantic maps that are used by the autonomy stack.

The team is also working towards building high quality and cost-effective geometric maps that would use only a camera phone for capturing the source data. 

Lyft’s autonomous platform team has been deploying partner vehicles on the Lyft network. Along with their partner Aptiv, the team has successfully provided over 50,000 self-driving rides to Lyft passengers in Las Vegas, which becomes the largest paid commercial self-driving service in operation. Waymo vehicles are also now available on the Lyft network in Arizona that expands the opportunity for our passengers to experience self-driving rides.

To advance self-driving vehicles, the team will also be launching a competition for individuals for training algorithms on the dataset. The dataset makes it possible for researchers to work on problems such as prediction of agents over time, scene depth estimation from cameras with lidar as ground truth and many more.

The blog post reads, “We have segmented this dataset into training, validation, and testing sets — we will release the validation and testing sets once the competition opens.”

It further reads, “There will be $25,000 in prizes, and we’ll be flying the top researchers to the NeurIPS Conference in December, as well as allowing the winners to interview with our team. Stay tuned for specific details of the competition!”

To know more about this news, check out the Medium post.

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