Enables a Safer, Smarter Autonomous Driving Industry
Motional a global leader in driverless technology, today announces an expansion to nuScenes, the industry-leading dataset that teaches autonomous vehicles how to safely engage with ever-changing road environments. nuScenes now includes nuScenes-lidarseg and nuImages.
nuScenes: a background
nuScenes, created in March 2019, was the first publicly available dataset of its kind, and pioneered an industry-wide culture of safety-focused data-sharing and collaboration. It launched as a collection of 1,000 urban “street-scenes” in Boston and Singapore. The scenes, composed of millions of photos and data-points collected from the vehicles’ full sensor suites, were then meticulously hand-annotated, and used to inform and advance machine learning models to build the safest possible self-driving vehicles.
The nuScenes expansion
Today, the nuScenes dataset becomes even more robust:
- nuScenes-lidarseg, is the application of lidar segmentation to the original 1,000 Singapore and Boston driving scenes, making it the largest publicly available dataset of its kind. Lidar segmentation provides a significantly more detailed picture of a vehicle’s surroundings than the original nuScenes’ bounding boxes, and adds an astonishing 1.4B annotated lidar points. It’s a significant step forward for the industry; it allows researchers to study and quantify novel challenges such as lidar point cloud segmentation and foreground extraction.
- nuImages is a brand new dataset. It comprises nearly 100,000 annotated images, carefully selected to generate a wide range of unpredictable, challenging driving conditions. nuImages was created in response to user demand, and will help self-driving vehicles safely navigate unusual scenarios – like jaywalkers, large intersections, and challenging weather conditions.
The nuScenes expansion is a demonstration of Motional’s commitment to making driverless vehicles a safe and reliable reality.
A culture of information sharing
Since release, over 8,000 researchers have used nuScenes, with over 250 scientific papers published using the data. Furthermore, nuScenes gave rise to a thriving culture of information-sharing in the autonomous vehicle industry. In the year-and-a-half since launch, more than ten new datasets have been made publicly available across the industry, helping to build safer, more educated autonomous vehicles.
“Safety transcends competition,” said Karl Iagnemma, President and CEO, Motional. “The belief that passenger safety must take priority over any competitive advantage is at the heart of nuScenes. We’ve been delighted to see so many peers follow suit and release their own datasets, all for the betterment of the industry.”
Motional has a long history at the forefront of safety. In 2019, the company was part of the team that released the Safety First for Automated Driving white paper, an organized framework for the development, testing and validation of safe automated passenger vehicles. The white paper has been widely regarded as the new standard in safety guidelines. Motional also operates the world’s most-established public robotaxi fleet (Las Vegas; 2018 – present). That fleet has provided over 100,000 rides, with 98% of riders rating their experience five-out-of-five stars.
nuScenes is free of charge for academic use, and licensing is available for commercial purposes. Annotations for nuScenes were provided by Scale AI.
For information on nuScenes, visit nuScenes.org
Motional is a driverless technology company making self-driving vehicles a safe, reliable, and accessible reality.
The Motional team was behind some of the industry’s largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world’s first robotaxi pilot, and operation of the world’s most-established public robotaxi fleet.
Motional is a joint venture between Hyundai Motor Group, one of the world’s largest vehicle manufacturers offering smart mobility solutions, and Aptiv, a global technology leader in advanced safety, electrification, and vehicle connectivity.