Waymo open-sources data set for autonomous vehicle multimodal sensors

Waymo, the Alphabet subsidiary that hopes to someday pepper roads with self-driving taxis, today pulled back the curtains on a portion of the data used to train the algorithms underpinning its cars: The Waymo Open Dataset. Waymo principal scientist Dragomir Anguelov claims it's the largest multimodal sensor sample corpus for autonomous driving released to date. "[W]e are inviting the research community to join us with the [debut] of the Waymo Open Dataset, [which is composed] of high-resolution sensor data collected by Waymo self-driving vehicles," wrote Anguelov in a blog post published this morning. "Data is a critical ingredient for machine learning … [and] this rich and diverse set of real-world experiences has helped our engineers and researchers develop Waymo's self-driving technology and innovative models and algorithms." The Waymo Open Dataset contains data collected over the course of the millions of miles Waymo's cars have driven in Phoenix, Kirkland, Mountain View, and San Francisco, and it covers a wide variety of urban and suburban environments during day and night, dawn and dusk, and sunshine and rain.