Our Aurora Voices series celebrates the people and teams whose unique experiences, backgrounds, and voices bring Aurora’s mission to life.
How does a self-driving vehicle learn to intuitively make in-the-moment decisions, such as making an unprotected left turn amidst oncoming traffic, merging onto a crowded freeway, or nudging to the left to give a cyclist some extra room as you pass by? To handle these everyday driving maneuvers, the Aurora Driver relies on a motion planning system that generates the series of decisions and actions a self-driving vehicle executes to safely get from point A to B.
As we march toward the commercial launch of Aurora Horizon, our autonomous trucking product, we are developing the Aurora Driver to safely navigate increasingly complex and critical situations that are necessary to operate autonomously on a defined route. Venkat, a leader on Aurora’s Motion Planning team, plays a key role in our progress toward delivering our feature complete Aurora Driver.
Read on to learn about how he helps the Aurora Driver learn to safely navigate the world around it, and how his approach to motion planning parallels his philosophy of life.
Tell us about your role at Aurora.
As a tech lead on the Motion Planning team, I oversee the Aurora Driver’s highway and surface street capabilities. There are two aspects to this role — continuously improving the autonomy architecture, and establishing efficient feedback loops around the on-road and offline testing, triage, and software