Just a decade ago, the field of Autonomous Vehicles (AVs) was relatively esoteric, with only a few research teams around the world focused on it. Fast forward to today: tens of thousands of engineers and scientists around the globe work in this area; AV-related topics dominate the tech press; and there is strong consensus that AVs will profoundly change people's lives and reshape our cities. However what is still unclear is exactly how quickly this transformation will take place. At Lyft, the core belief is that deploying AVs as part of hybrid "Transportation as a Service" (TaaS) networks is the safest and most effective way towards large scale and impact. The "Level 5 Engineering Center" was created in mid 2017 to drive this transformation for the company. In this talk, I will explain how an existing large scale rideshare service is a major asset to use to speed up development and deployment of autonomous vehicles, at large scale, within the service. Specifically, the data and insights that are gathered from the existing service can fuel advances in HD mapping, autonomy, and more broadly any part of the stack that relies on machine learning. I'll also give an update on the current status of Lyft Level 5.
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