The Missing Self-Driving Puzzle Piece? Hyper Local Maps

In addition to using sensors and artificial intelligence, autonomous vehicles need know their environment and how it changes.

Thanks to advances in sensor and artificial intelligence, autonomous vehicles are almost as smart as competent human drivers. But while a person instinctively knows how to quickly deal with, say, a road or lane closure due to construction, autonomous vehicles could easily become confused and take too long to deal with the situation as traffic backs up.

This is why we're seeing advances in mapping software, as well as acquisitions and partnerships that focus on the need for hyper-local, constantly updated maps. Part of the motivation for Intel buying sensor-maker Mobileye for $15 billion was to gain access to the company's Road Management Experience, which crowd-sources images from cameras in millions of cars to create highly accurate and constantly updated maps.

Similarly, German automotive supplier Bosch partnered with mapping giant TomTom to develop a platform that captures billions of reflections created by a car's radar signals bouncing off roadside objects. Called Radar Road Signature, "it uses radar sensors to always measure objects so you get a kind of fingerprint of the road," Gerhard Steiger, president of the automotive supplier's Chassis Systems Control Division, told me in an interview last week.

Veröffentlichung:
03. August 2017

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