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In March 2020, we launched the Waymo Open Dataset Challenges, inviting researchers to build and test their machine learning models using Waymo’s diverse self-driving dataset. We received over 100 submissions from around the world and invited the winners to present their work at our virtual Workshop on Scalability in Autonomous Driving at CVPR 2020. Today, we are excited to introduce some of the winners and their learnings.
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One of the key qualities of a good driver is being able to anticipate and predict what others on the road might do. For example, what is the probability of another car merging into our lane or the cyclist in front of us making a left turn? The ability to accurately predict the intentions of other road users allows the Waymo Driver to make the safest possible decisions.
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COVID-19 has had a significant impact on the world, affecting people’s lives and forcing many businesses to suspend their operations. At Waymo, we're actively monitoring the situation, taking steps to support our local communities, and contributing to COVID-19 response efforts. While Waymo has temporarily suspended its on-the-road operations as we put the health and safety of our riders, partners, and employees first, we are still driving our technology forward with our work in simulation.
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In early 2009, when Waymo was first founded as the “Google Self-Driving Car Project,” Google founders Sergey Brin and Larry Page challenged our first engineers to drive autonomously without human intervention or disengagements along ten challenging 100-mile routes in our home state of California. By December 2009, the team had completed their first route, and nine months later in mid 2010, we had wrapped up the last.
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To help safely navigate the complexities of the road, our self-driving technology needs to see and identify what’s around it. To perceive its surroundings, the Waymo Driver relies on our powerful custom sensor suite of lidar, cameras, and radars, while neural nets empower the “brain” of our self-driving system to understand the sensor data and respond to a wide range of scenarios.
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Designing a driver for autonomous vehicles is one of the things we do best here at Waymo, but few people are familiar with what that entails and how it differs from designing the car itself. Whereas a traditional car is one platform usually designed for one purpose, we’ve designed our recently unveiled fifth-generation Waymo Driver to apply to multiple vehicle platforms and power a variety of different use cases, from moving people with Waymo One to transporting goods with Waymo Via.
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ThumbnailLast August, we invited the research community to join us in accelerating self-driving technology with the release of one of the largest multi-sensor self-driving datasets available today. Even as COVID-19 continues to develop, we are committed to fostering an environment of innovation and learning - one that can continue to grow and thrive in our temporarily virtual world. That is why today, we are launching the next phase of our program: expanding the Waymo Open Dataset by an additional 800 segments and inviting researchers to participate in Waymo’s Open Dataset Challenges.
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At Waymo, we’re building the World's Most Experienced Driver - our combination of hardware, software, and compute that powers vehicles to safely get people and things where they’re going.
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At Waymo, we use machine learning to detect and classify different types of objects and road features. The powerful neural nets that make up our perception system learn to recognize objects and their corresponding behaviors from labeled examples of everything our Waymo Driver encounters, from joggers and cyclists, to traffic light colors and temporary road signs, or even trees and shrubs. Over the past decade we have built up an enormous collection of objects captured by our powerful custom-designed hardware.
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Halloween is a fun and exciting night. People dress up as robots, fairies, or their favorite superhero. Parents and children travel from house to house, creating a great sense of community. However, behind all of this fun is a scary reality: Halloween is one of the deadliest days of the year for pedestrians in the US. 
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My father-in-law was responsible for teaching all of his kids to drive. During the winter, he would ask, “How do we drive on the ice?” And everyone responded in unison, “We don’t!”
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Data is a critical ingredient for machine learning. Our vehicles have collected over 10 million autonomous miles in 25 cities; 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.

Today, we are inviting the research community to join us with the release of the Waymo Open Dataset, a high-quality multimodal sensor dataset for autonomous driving.
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Waymo’s self-driving vehicles employ neural networks to perform many driving tasks, from detecting objects and predicting how others will behave, to planning a car’s next moves. Training an individual neural net has traditionally required weeks of fine-tuning and experimentation, as well as enormous amounts of computational power. Now, Waymo, in a research collaboration with DeepMind, has taken inspiration from Darwin’s insights into evolution to make this training more effective and efficient.
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We were founded a decade ago on a mission to make our roads safer. Since then, we’ve been focused on building the world’s most experienced driver. Safely sharing the road is an important part of driving, and the Waymo driver tirelessly scans for objects around the vehicle — including pedestrians, cyclists, vehicles, road workers, animals, and obstructions — and then predicts their future movements based on information such as speed, trajectory, and road context.
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This week our CTO Dmitri Dolgov sat down with MIT Technology Review’s Editor-in-Chief Gideon Lichfield at EmTech Digital. This year’s forum brought together experts from around the world to discuss advancements in AI in a variety of fields, from healthcare and public safety, to transportation and urban design.
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At Waymo, machine learning plays a key role in nearly every part of our self-driving system. It helps our cars see their surroundings, make sense of the world, predict how others will behave, and decide their next best move.
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At Waymo, we are focused on building the world’s most experienced driver. And just like any good driver, our vehicle needs to perceive and understand the world around it by recognizing surrounding objects and predicting what they might do next, before deciding how to drive safely while obeying the traffic rules.
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This morning, we took the stage at Google I/O, Google’s annual developer conference, to share details on how Waymo is using artificial intelligence (AI) to make fully self-driving cars a reality. If you’re familiar with our work, you know that AI and machine learning (ML) have played a critical role in moving us closer to our goal of bringing self-driving technology to everyone, everywhere.
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To bring Waymo’s technology to life, we leaned on the unique format of 360 video.
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Over the past nine years, we’ve put our vehicles through the world’s longest and toughest ongoing driving test.
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