Self-driving technology presents a rare opportunity to improve the quality of life in many of our communities. Avoidable collisions, single-occupant commuters, and vehicle emissions are choking cities, while infrastructure strains under rapid urban growth. Autonomous vehicles are expected to redefine transportation and unlock a myriad of societal, environmental, and economic benefits. You can apply your data analysis skills in this competition to advance the state of self-driving technology. [Lyft](https://level5.lyft.com/), whose mission is to improve people’s lives with the world’s best transportation, is investing in the future of self-driving vehicles. Level 5, their self-driving division, is working on a fleet of autonomous vehicles, and currently has a team of 450+ across Palo Alto, London, and Munich working to build a leading self-driving system ([they’re hiring!](https://level5.lyft.com/#joinourteam)). Their goal is to democratize access to self-driving technology for hundreds of millions of Lyft passengers. From a technical standpoint, however, the bar to unlock technical research and development on higher-level autonomy functions like perception, prediction, and planning is extremely high. This implies technical R&D on self-driving cars has traditionally been inaccessible to the broader research community. This dataset aims to democratize access to such data, and foster innovation in higher-level autonomy functions for everyone, everywhere. By conducting a competition, we hope to encourage the research community to focus on hard problems in this space—namely, 3D object detection over semantic maps. In this competition, you will build and optimize algorithms based on a large-scale dataset. This dataset features the raw sensor camera inputs as perceived by a fleet of multiple, high-end, autonomous vehicles in a restricted geographic area. If successful, you’ll make a significant contribution towards stimulating further development in autonomous vehicles and empowering communities around the world.