Motional and SiaSearch sign partnership to make nuScenes more accessible

Auto Tech Outlook | Monday, October 12, 2020

SiaSearch, a Berlin-based automated driving data handling platform, partnered with Motional, a global leader in driverless technology, to provide enhanced access to its nuScenes dataset for the self-driving research community. The partnership will enable nuScenes users to access, explore, and understand the data in an unprecedented way.

SiaSearch is a first of its kind platform that automatically extracts granular metadata from raw multimodal automated driving sensor data. It then makes the data fully searchable and accessible for evaluation through its GUI and API. With a catalog of over 50 different driving events and attributes, users can now ask any questions they have about the raw data and get answers within seconds thanks to the proprietary, lighting fast, Sia Interval Query Engine.

nuScenes is an industry-leading dataset that teaches autonomous vehicles how to safely engage with ever-changing road environments. It’s a highly sophisticated and diverse dataset, comprising a full sensor suite with data from two distinct cities: Boston and Singapore, and manual annotations for 23 object classes. Finding edge cases and interesting interactions within a large scale dataset, such as nuScenes, is like finding a needle in a haystack. By making nuScenes available through SiaSearch, the dataset is even more powerful, as it becomes fully accessible and the process of selecting the relevant driving sequences is streamlined.

SiaSearch automatically tags nuScenes with driving maneuvers, interactions with other traffic agents, and infrastructural and environmental attributes. With the tagging, researchers can use nuScenes to find any driving scenario they need within seconds! This allows researchers to focus on their job’s essence, training models, instead of spending precious time on manually reviewing the dataset.

SiaSeach and Motional are proud to support cutting-edge research to further the development of smarter and safer self-driving vehicles.

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