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Bolt is an Estonian mobility company that offers ride-hailing, scooter and e-bike rentals, car-sharing, and food delivery services in over 50 countries and 850 cities. In partnership with the Autonomous Driving Lab of the University of Tartu, the company developed self-driving technology for a Level 4 autonomous car.
Technical/scientific Challenge:
Autonomous cars acquire up to 357 GB/hour of data during test drives. Autonomous car engineers needed a system to store and easily access those test logs.
Solution:
Acquired test logs are copied to HPC storage, into appropriately guarded directory. Regularly cron job processes those log files into metadata stored in MongoDB database. Processing is distributed over cluster and happens in parallel. Longest logs can take up to 24 hours to process, so processing them sequentially would be very time-consuming. On top of MongoDB sits custom-made application that allows filtering of test sessions and browsing them using Webviz visualization tool. Visualization tool accesses the raw sensor data from HPC storage.
Business impact:
People's needs for different means of transport are on the rise, which is why self-driving cars are a very good alternative to current modes of transport. HPC solutions offer the company an indispensable opportunity to develop the maps, car camera, radar, lidar and sensor analysis needed for self-driving vehicles, as well as the ability to detect the surrounding situation and make decisions. Quick results, in turn, improve the company's competitiveness.
Benefits:
Custom database application and visualization tool enables easy analysis of the logs.
Thanks to distributed processing in the cluster the metadata about the drives usually shows up already next morning.
Thanks to custom database application and visualization tool, the team members can easily analyse the logs and share their findings with each other.
Thanks to petabytes of storage at the HPC centre, the company can keep all the data they need.