Creating an Immersive Map for Self-Driving Cars

with Wei Luo, David Rumsey (@davidrumseymaps), and Hanne Tidnam (@omnivorousread)

In this episode, Wei Luo, founding COO of DeepMap -- who build HD maps for autonomous vehicles -- and David Rumsey, founder of the David Rumsey Map Collection (one of the largest paper private map collections in the world, now at Stanford University, and the largest digital online private collection in the world, at 80,000 + maps) talk with a16z's Hanne Tidnam about how maps -- and mapmaking tools -- are changing in the age of autonomous vehicles.

New ways of mapping the world have always led to profound changes. In the Renaissance -- another golden age of mapmaking -- mapmakers used tools such as sextants to measure distance to the stars and compasses to navigate the world around them. Cartography is undergoing yet another major paradigm shift as it now evolves into HD mapping. So what kinds of data and information do maps now need to contain in order to allow cars (and other autonomous robots of all kinds) to navigate the world around them, down to only a few centimeters of accuracy? How will the nature of maps fundamentally change when they are made by self-driving cars, for self-driving cars, in the era of HD mapping?

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