Earlier this month, we teamed up with Girl Scouts of Northeast Texas (GSNETX) to transport cookies for the annual Girl Scout Cookie Program with our Waymo Via truck fleet. Girl Scouts has long encouraged girls at every age and from all different backgrounds to explore science, technology, engineering, and math (STEM) fields through their girl-centric programming. And at Waymo, we need a diverse group of people to develop the Waymo Driver and deliver on our mission, so we look for opportunities to open these dialogues with younger generations who will forge the future of autonomous driving technology.
5 years as a Girl Scout in Dupage County, IL
“To me, [being a] girl meant inside voices, dolls, clothes I couldn’t get dirty, legs without bruises, being small. I felt limited. I wanted to be seen for things I was good at: how fast I could run, how high I could climb, how brave I was… Girl Scouts was the first time I felt like I was a part of a group of girls. I didn’t have to be anything I wasn’t in Girl Scouts. It was the first time I felt like being a girl was OK, maybe even great.”
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| Emily and her mom during her bridging ceremony |
3 years as a Girl Scout in San Jose, CA
“I was a Girl Scout for several years. Cookie sales was a formative experience for me. The act of selling is a skill I started to harness at an early age through Girl Scouts. That experience prepared me in my career and ultimately led me to my role of selling the experience of working at Waymo (as a recruiter).”
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| Maggie and her pup |
16 years as a Girl Scout and Girl Scout camp counselor in Colorado
“I think that some parts of the Girl Scout curriculum really helped with understanding STEM careers, and introducing STEM and engineering concepts. I became a mechanical engineer and that was influenced by many things, but the hands-on experiences that I got at the Girl Scout camps definitely gave me early experience with this. I also think that my leadership experience that I got in the Girl Scouts likely helped me to get a scholarship to college.”
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| Megan working in one of our hardware labs |
“What does being a Girl Scout mean to me? The answer can be found in the Girl Scout Promise. ‘On my honor, I will try to serve God and my country, to help people at all times, and to live by the Girl Scout Law.’ I literally use this pledge to think about how I should move about my life every single day. I also try to help those who reach out to me for career advice or networking. I do whatever it takes to make the time because that’s how you learn! I stay in touch with many women I’ve worked with throughout my career and am super proud to see them grow and be successful.”
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| Michelle’s daughter, Mary Charlotte, during her days as a Brownie |
7 years as a Girl Scout in Peninsula Bay Area
“I’d say there are a lot of similarities between our mission at Waymo and the Girl Scout Law. At Waymo, we’re teaching the Waymo Driver to be friendly and helpful, considerate and caring, to respect authorities, and use resources wisely, and to make the world (and our roads) a better place.”
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| Sandy showing off her Waymo spirit! |
Image caption and source: Girl Scouts of Northeast Texas cheer the new branding on a Waymo Via truck used to fulfill Girl Scout Cookie Program logistics (GSNETX staff photographer)
Editor’s Note: Last year, we opened up our fully autonomous ride-hailing service to all of our Waymo One riders, and Xavier is one of the people who relies on this service to get where he needs to go. He shared this video with us, and we gave him a call to learn more about how he likes the service and what it’s like to ride with Waymo, solo.
I’m Xavier, and I live in Chandler, Arizona. I’ve been riding with Waymo for around a year now and first heard about Waymo when I saw them driving around my neighborhood. I started wondering what they were and finally looked it up and saw on the website that you could sign up to ride in them.
I’d heard about autonomous cars before on a few tech podcasts I listen to, but I didn’t know the technology was fully there yet or that there was a possibility of riding in one until I signed up. It took about a week to get accepted, and I’ve been riding since.
What do you normally use the service for?
I don’t own a car myself, so my primary mode of transportation is Waymo, other ride-hailing services, or the bus.
I mainly use Waymo to get to and from work. I’m a restaurant manager at Wendy’s and don’t live too far away; it’s a short 10 minute ride usually. I also use it to visit my mother every once in a while.
Waymo generally is a nice ride, and you get a very consistent experience. The cars are always super clean and it feels futuristic, almost like you have a robot butler. You get in, press the button, and you’re on your way.
I compare it a lot to other ride-hailing services that aren’t automated. With those, you don’t know what you’re going to get. Sometimes the driver is having an off day, may speed, or not obey the traffic laws.
With Waymo, it picks the same route, goes the same speed, and feels more secure. I also like the fact that you get to specifically choose where it’s going to pick you up and drop you off.
Have your transportation habits changed at all through COVID-19?
I still feel comfortable using the service. I feel as comfortable as I do going to work, which I still have to get to somehow!
You’ve had the opportunity to ride a lot in our 100% fully autonomous cars with no human driver. Can you talk about what that’s like? Any major differences or similarities from the experience you’ve previously had with vehicle operators?
Every fully autonomous ride has been pleasant. For me personally, anytime I get in a car with a driver, Waymo or otherwise, I usually don’t play my music too loud or fully relax since I’m trying to consider the other person. But when I’m by myself, I’m more likely to change the temperature or adjust my seat and feel more at ease watching YouTube videos or listening to a podcast on my phone.
I also feel more comfortable changing the destination during the trip, like if I’m heading home from work and remember I need to stop by the store on the way home. It doesn’t feel like I’m inconveniencing anyone in fully autonomous rides.
That’s awesome to hear. Any feedback you have on the overall experience?
The only flaw I’ve noticed, but it’s not actually a flaw, is that sometimes Waymo is overly cautious. I can’t complain about that because it’s a good thing it’s cautious. Sometimes it will make decisions on the road, like routing, that don’t make sense to me all the time, but again, I understand it’s just being cautious.
In my head, all of these things are going to improve or already are.
What do you think the potential is for fully autonomous technology, both in times like these and in the future more broadly?
For me, I don’t have any doubt that autonomous cars are the way to go for the future, and if the world is just, it’s going to replace people driving cars. If it’s not necessary for humans to drive, why would we if it’s safer for computers to drive?
And, it’s going to have a good impact on the environment because if not everyone owns a car there’s going to be less cars out there because we’d all be sharing them.
Anything else you want to share about your experience?
I definitely recommend that people try it! It’s really fun and you feel like you’re part of the future.
“The Girl Scouts’ Cookie Program has helped girls and young women recognize and pursue their dreams for more than a century, and we’re honored to now be part of that legacy,” said Becky Bucich, chief people officer at Waymo. “We’re delivering today for tomorrow’s leaders, and we’re dedicated to inspiring the next diverse and inclusive generation of engineers, coders, programmers and STEM professionals.”
Waymo, which has been pioneering autonomous driving technology for more than a decade, announced it would begin testing its Class-8 trucks in Texas in January. The California-based company also operates a fully autonomous ride-hailing service in Metro Phoenix and has tested in more than 25 cities nationwide.
The collaboration between Girl Scouts of Northeast Texas (GSNETX) and Waymo aligns with the longstanding mission of Girl Scouts to prepare girls to thrive in the world, a vision set by Girl Scouts founder Juliette Gordon Low in 1912. In recent years, that has translated to a commitment to encourage girls to pursue careers in the fields of science, technology, engineering, and math (STEM). Girl Scouts of the USA, the national organization to which GSNETX is a council, has made building the STEM pipeline a priority across the country as our reliance on technology and science grows even more important.
“We are excited about our partnership with Waymo,” said Jennifer Bartkowski, chief executive officer for Girl Scouts of Northeast Texas. “Girls will experience a practical use for technology that is shaping our future, inspiring them to become the next generation of engineers, coders, and STEM professionals. At the same, the North Texas community will see cutting-edge technology that can improve the world’s access to mobility. It is a win-win as Girl Scouts continues to change the workforce pipeline for North Texas.”
As part of GSNETX’s virtual “Camp-In Camp Cookie,” which sets girls up for success during cookie season, Xinfeng Le, a product manager for Waymo’s trucking program, presented to the council’s young members about her work at Waymo while also giving girls an inside look at the variety of opportunities in a STEM career.
GSNETX is also joining the Waymo-led public education initiative, Let’s Talk Autonomous Driving, which supports public dialogue around and understanding of autonomous driving technology. GSNETX is Let’s Talk Autonomous Driving’s first STEM-focused education partner and joins a diverse group of national and state-based organizations that share the belief that autonomous driving could make roads safer and improve mobility and accessibility.
“We’re fortunate that Girl Scouts share our passion to cultivate a deeper understanding of the world around us, and we’re excited they have joined Let’s Talk Autonomous Driving as our first STEM-focused education partner,” said Bucich.
- “The safety and independence that a fully autonomous ride with a Waymo Driver provides to our clients is immeasurable. It means that our clients, no matter the level of their visual impairments, can travel just as independently as their sighted peers. They can travel in their own time and their own terms. This distinction between ‘self-driving’ and ‘autonomous’ properly conveys this freedom.” — Marc Ashton, CEO, Foundation for Blind Children
- “We’ve been a proud partner of the Waymo-led publication education initiative since 2017, and rebranding as Let’s Talk Autonomous Driving makes sense because it’s important consumers understand the difference between some car features like blind spot or lane departure warnings and fully autonomous vehicles. For seniors who have lost the ability to drive these convenience features may increase safety, but they don’t overcome the hurdles they face that are a barrier to their continued driving. Waymo gives seniors a safe mode of transportation and we fully support their rebrand.” – Tom Egan, CEO, Foundation for Senior Living
- “Getting motorists ready for autonomous driving technology will be critical to reaping the safety benefits that automation offers. GHSA is proud to be a part of Let’s Talk Autonomous Driving as they make this change to promote the use of accurate terminology.” – Jonathan Adkins, executive director of the Governors Highway Safety Association
- “MADD congratulates Waymo for their incredible work on autonomous technology and the promise their advancements hold for eliminating drunk and drugged driving. We look forward to continuing our partnership with Waymo’s Let’s Talk Autonomous Driving to educate the public about how emerging technologies can make our roads safer.” – Jason Frazier, Arizona State Executive Director for MADD
- “Technology is a key component to keeping teen drivers safe, and Waymo continues to be a leader and innovator in the field. We’re thrilled to support this new chapter of the campaign.” – Rick Birt, President & CEO, SADD
It is an exciting time to join the leader in fully autonomous technology. The release of Waymo’s Safety Methodologies and road safety performance data affirms Waymo’s leadership in autonomous vehicles and demonstrates a level of openness and transparency unparalleled in the industry.
I am honored by the opportunity to help this team go further and build a safer mobility future.
We want to give everyone who rides with the Waymo Driver a deeper understanding of the incredibly high standards to which we hold ourselves in the safety practices that govern our deployments. Today, we’re publishing two papers that explain the processes we use to drive fully autonomously on public roads and validate the safety of our operations.
The first, Waymo’s Safety Methodologies and Safety Readiness Determinations, includes details of our Safety Framework – the careful and multilayered approach to safety that has helped make it possible to deploy fully autonomous vehicles on public roads.
The second, Waymo’s Public Road Safety Performance Data, analyzes the miles we’ve driven on public roads in Arizona – one of 10 states we’ve driven in the U.S. since our founding – to provide data about our safe operations in practice.
This is the first time an autonomous technology company has released a framework describing the safety of its fully autonomous commercial operations. We believe this transparency and accountability is important for demonstrating the trustworthiness of our operations, and critical to deepen the dialogue around autonomous driving safety. We look forward to ongoing engagement with experts and academia to help ensure our work can continue to evolve and grow.
Waymo’s Safety Framework: Safety Methodologies and Safety Readiness Determinations
There is currently no universally accepted approach for evaluating the safety of autonomous vehicles – despite the efforts of policymakers, researchers and companies building fully autonomous technologies. Since we began our work in 2009, we have worked to develop a robust Safety Framework – with multiple complementary methodologies – that embeds safety in all aspects of our technological and product development. This framework draws on insights from the research and automotive communities, and is based on our extensive experience in building autonomous systems.
By publishing our framework, we aim to transparently share details about our approach; show how we evaluate our safety performance; demonstrate how we understand and measure our readiness for safe autonomous operations at scale; and invite perspectives from experts as we continue to expand our operations.
As our industry progresses, we encourage other autonomous driving companies to develop and publish guiding frameworks and principles that can demonstrate how autonomous systems are safely and responsibly deployed.
Our Safety Framework, available here, maps out our approach to safety in three fundamental layers:
We call our automated driving system (ADS) the Waymo Driver. A vehicle equipped with the Waymo Driver has four main subsystems, which form the ‘hardware layer’. This includes the vehicle itself; the systems used for steering and driving; the sensor suite built into the vehicle; and the computational platform used to run our software.
Our Safety Framework explains:
- How we verify and validate the performance of these components.
- How we select our base vehicles with safety performance in mind.
- Our use and testing of backup steering and control actuators.
- How we specify and measure the performance of vehicle sensors.
- The backup computers and power sources within our computational platform.
In combination, these steps have led to the development of a robust hardware stack that has been designed around the goal of ensuring safety in any scenario. You can read about the latest generation of our hardware here.
2. The ADS Behavioral Layer
There are three primary capabilities upon which we evaluate the performance of the Waymo Driver’s behavioral layer:
- Avoiding incidents with other vehicles or users of the roads.
- Successfully completing trips in fully autonomous mode.
- Adhering to applicable driving rules where the vehicle is operating.
We use a series of methodologies to evaluate these capabilities, including:
- Hazard analysis techniques to design for the robustness of the Waymo Driver from the beginning of the development process.
- Scenario-based testing, both in simulation and closed-course test environments, to verify the behavior and performance of the Waymo Driver.
- Simulated deployments to evaluate the aggregate performance of the Waymo Driver over a large number of miles and a wide variety of situations.
3. The Operations Layer
The first two parts of our Safety Framework lead to the development of safe, capable autonomous vehicles. The final part – operations – reflects the importance of the systems, approaches and culture we have been building around our technology to help ensure it is safe. Our Safety Framework sets out the inner workings of several important operations processes at Waymo:
- Fleet Operations includes a broad range of monitoring and support functions to help ensure the safe operation of the Waymo Driver and our vehicles. For example, while the Waymo Driver handles the entire driving task, our fleet response team can confirm what our ADS is seeing and provide additional information.
- Our Risk Management Program enables us to proactively identify and resolve potential safety issues that are triggered by ongoing technological change, categorizing and prioritizing potential risks so they can be mitigated.
- Finally, our Field Safety Program helps collect, assess and resolve potential safety concerns that occur during real-world operations. We draw from many sources, including employees, our riders, and the public.
Our governance structures are important tools that help us monitor and review safety-related decisions within our company. Our Safety Framework details this work, which includes the role of the Waymo Safety Board. This group works together to help resolve safety issues, approve new safety activities, and ensure our overall approach to safety continues to evolve and improve.
We use these methodologies to assess and continuously improve safety of the Waymo Driver. We also use them collectively to make our assessment about whether the Waymo Driver is ready to make the next step – as we did before opening fully autonomous operations for ride-hailing to the public in Phoenix earlier this month.
We establish rigorous performance criteria for our Driver in a particular operating environment, and drawing on all our safety methodologies to determine whether the Driver is ready to be tested or deployed in new conditions without creating any unreasonable risks to safety.
As we broaden the availability of Waymo services and vehicle platforms enabled by the Waymo Driver, we want to be sure that the communities in which we operate understand the safety approach we take so they can be confident in the safety of our products.
In addition to the Safety Framework, today we are sharing a white paper on Waymo’s Public Road Safety Performance Data. There is not yet a globally or nationally recognized framework to assess the relative safety of autonomous vehicles – so we are taking this opportunity to share safety-relevant data with our peers, our stakeholders, and our communities.
The paper includes results from 6.1 million miles of automated driving with a trained vehicle operator in Arizona in 2019. It also includes an additional 65,000 miles of fully autonomous operations – operating at Level 4 autonomy, with no human driver behind the wheel and no remote operators – from 2019 and the first nine months of 2020.
This data represents over 500 years of driving for the average licensed U.S. driver – a valuable amount of driving on public roads that provides a unique glimpse into the real-world performance of Waymo’s autonomous vehicles. The data covers two types of events:
- Every event in which a Waymo vehicle experienced any form of collison or contact while operating on public roads
- Every instance in which a Waymo vehicle operator disengaged automated driving and took control of the vehicle, where it was determined in simulation that contact would have occurred had they not done this
In addition to sharing data, the paper describes the simulation processes Waymo uses to understand how events would likely have played out in situations with on-board vehicle operators where they chose to disengage the Waymo Driver. These simulations use models of human behavior, and help us better understand how our vehicles and other road users interact.
The paper is available at www.waymo.com/safety. Like our Safety Framework, it is intended to inform our riders, our stakeholders, our peers, and the communities in which we drive about the safety of the Waymo Driver and our progress.
We hope that our transparency will lead to greater openness within our industry and a more meaningful conversation on autonomous driving performance and safety. Ultimately, we believe this will build trust and understanding in responsibly developed autonomous technology as they are deployed in fully autonomous operations to move people and goods safely and efficiently.
We invite academics, industry experts, other interested stakeholders, and members of the community to share their feedback with our team at safety-report-feedback@waymo.com.
Autonomous trucking is poised to improve road safety and offer greater efficiency across the logistics industry. As we configure the Waymo Driver to operate Class 8 trucks and unlock these benefits, we’re pleased to share that Waymo has entered a broad, global, strategic partnership with Daimler Trucks, the global market leader in large commercial vehicles.
Martin Daum, Chairman of the Board of Management of Daimler Truck AG and Member of the Board of Management of Daimler AG: “As leader of our industry, Daimler Trucks is the pioneer of automated trucking. In recent years, we have achieved significant progress on our global roadmap to bringing series-produced highly automated trucks to the road. With our strategic partnership with Waymo as the leader in autonomous driving, we are taking another important step towards that goal. This partnership complements Daimler Trucks’ dual strategy approach, of working with two strong partners to deliver autonomous L4 solutions that are seamlessly integrated with our best-in class trucks, to our customers.”
Roger Nielsen, Member of the Board of Management of Daimler Truck AG, President and CEO of Daimler Trucks North America: “The combination of increased road freight volumes and the need and vision of fleet operators for highly automated trucks, is what fuels our relentless pursuit of innovation. We are pushing engineering solutions that strive above all to increase safety and help our customers improve business efficiencies. Based on our collaboration with Waymo, we will be in the unique position to be able to provide our fleet customers with a choice among the best solutions for their individual requirements.”
For more information, you can read the joint press release here.
In 2017, after nearly a decade of developing self-driving technology for passenger cars, we launched our trucking and local delivery program now known as Waymo Via. Since then, our autonomous Class 8 trucks have been tested in a wide variety of cities and environments in California, Georgia, Arizona, New Mexico and Texas. Utilizing the same core technology stack across all of our vehicles allows us to bring fully driverless trucks to the market safely and quickly.
The same way that software and hardware components power our phones and tablets, the Waymo Driver is the foundation for all our vehicles, whether it’s one of our cars navigating the busy streets of San Francisco, a van delivering packages to a local neighborhood, or an 18-wheeler truck driving down the highway. Using the same core technology and infrastructure allows each vehicle platform to benefit from 20 million self-driven miles on public roads and over 15 billion miles in simulation. Now, our trucking efforts help further advance the Waymo Driver by unlocking more freeway driving capabilities for our entire fleet.
Navigating complexities of truck driving
Even if you’ve never been behind the wheel of a truck before, many of us have driven on the roads alongside them and can imagine the difficulties of this job. Driving an 80,000lb semi-truck at 65mph, merging into fast-moving traffic, dealing with blind spots, trying to keep the truck and trailer in line with only about 8 inches on either side to spare, constantly checking your mirrors to keep an eye on the trailer and everyone else on the road — these are just a handful of challenges truck drivers must grapple with.
Not only is truck driving a tough job, but serious crashes can also occur. More than one in three long-haul truck drivers have experienced a serious crash during their career. The trucking industry values safety deeply and is constantly seeking innovations to improve statistics like these. By bringing self-driving technology to trucking, we can make every mile traveled safer.
In order to identify the main challenges of truck driving — from construction zones, to potentially larger blind spots, to trailer movements that can vary with different types of loads, to slower acceleration and braking — we utilize not only our experience building self-driving technology, but also the wealth of knowledge gained from professional truck drivers. As part of our testing program, Waymo partners with test drivers who are trucking industry veterans with more than 20 years of invaluable expertise to help inform our approach.
Jon Rainwater, an experienced truck driver who provides instruction to the test drivers for Waymo Via, says: “By working with the engineering teams and sharing all about truck behavior and the rules of the road, I’m helping the Waymo Driver see and learn what I have. It’s my job to impart the lessons I’ve learned the hard way, so that the Waymo Driver is the safest it can be. That is the largest impact I can have—knowing that society will benefit from my lived experience for years and years to come.”
Designed for scale and engineered to tackle diverse driving environments
When designing a new platform, we work closely with our OEM partners to ensure we can integrate our Waymo Driver seamlessly into their vehicles and manufacture them easily. We begin this process by using our most recent self-driving system, comprised of radar, lidar, cameras, and compute and adapt it to the new vehicle, optimizing it for the various platform requirements, such as the variation in potential blind spots.
Each generation of our hardware suite is informed by more than a decade’s worth of our experience and millions of miles of on-road testing. This experience provides us an understanding of the edge cases that self-driving technology needs to handle to take people and things safely from A to B.
Compared to passenger vehicles, trucks spend a lot more time on freeways, which are higher-speed environments. They also have a lot more mass, are slower to accelerate and brake than passenger cars, requiring a distance of nearly two football fields to come to a stop, and they have trailers that can move independently from the tractor. Therefore, when configuring the self-driving system for our trucks, we take into account that our trucks require more time and space to maneuver and can have different blind spots than cars. To accommodate for these differences, we increased the number of sensors we apply to the trucks. The most noticeable difference is that our trucks feature two perception domes versus the single iconic perception dome on our passenger cars. The dual perception domes on our trucks help increase rear visibility by reducing blind spots caused by the trailer.
Another thing we have learned from our over 20 million miles of on-road testing is the importance of redundancies in safety. Unlike with passenger cars, which already come equipped with multiple levels of redundancy, you can’t order or easily build a truck with all of the safety features necessary for self-driving, such as redundant braking and steering. The trucking industry isn’t as far down this path yet, but we’re using everything we’ve learned to work closely with our OEM partners and suppliers to equip our trucks with the same level of safety and redundancy.
Advancing the Waymo Driver’s capabilities across platforms
Machine learning plays a significant role in addressing some of the key freeway driving requirements needed in perception, prediction, and planning. We use the same core algorithms across all types of vehicles, but we’re fine-tuning them for trucks and freeway driving specifically. Although our passenger cars have been driving on freeway segments for quite a while now, having vehicles that spend nearly all their time on the highway, allows us to learn more about this environment and better prepare for its challenges.
Even routine maneuvers such as lane changing can be challenging for an 18-wheeler truck driving at freeway speed. Turns become wider and can take unique shapes due to the trailer movements. The Waymo Driver can see objects at great distances, which allows it to respond to objects earlier and maneuver more smoothly.
We encounter several situations driving on freeways that we do not frequently see on surface streets, including navigating metering lights when getting onto a ramp and moving over a lane when another vehicle stops on the shoulder to give them room. Dealing with construction zones and median crossovers that direct traffic to the “wrong” side of the road can also be more challenging on a freeway. Training the Waymo Driver to navigate a variety of these scenarios allows us to unlock additional freeway driving capabilities not only for our trucks but for the entire fleet.
Ensuring reliability through testing
Freeway driving requires exceptionally high reliability from every part of the self-driving system. The Waymo Driver and its applicable platforms go through rigorous testing and validation processes that we’ve developed to ensure the safety and reliability of our system. This includes base vehicle and hardware level reliability and durability testing, as well as validating our software through simulation, evaluation techniques, structured testing and public road operations with trained drivers.
For example, simulation allows us to rigorously test and prepare our system to handle many trucking-specific challenges. In a simulated environment, we can recreate any scene — experienced or new — including other drivers’ behavior.
As we continue to develop the hardware and software components of the Waymo Driver to power trucks, our technical progress will carry over into all other vehicle platforms, including passenger cars. At Waymo, we’re fortunate to have some of the greatest minds working on honing this technology and we’re looking for more people to join our growing team and help us make roads safer for everyone. Learn more at waymo.com/joinus.
Over time, as we improved the capability of our Waymo Driver, we increased the scope and quantity of our operations, with 5-10% of our rides in 2020 being fully driverless for our exclusive group of early riders under NDA. We’ve been gathering key learnings from these riders on how to optimize our driverless service experience and continuously improve it (in their words, it’s a magical experience). We also began to offer more people access to our public Waymo One service, with a vehicle operator monitoring the ride.
Beginning today, October 8, we’re excited to open up our fully driverless offering to Waymo One riders. Members of the public service can now take friends and family along on their rides and share their experience with the world. We’ll start with those who are already a part of Waymo One and, over the next several weeks, welcome more people directly into the service through our app (available on Google Play and the App Store). In the near term, 100% of our rides will be fully driverless. We expect our new fully driverless service to be very popular, and we’re thankful to our riders for their patience as we ramp up availability to serve demand. Later this year, after we’ve finished adding in-vehicle barriers between the front row and the rear passenger cabin for in-vehicle hygiene and safety, we’ll also be re-introducing rides with a trained vehicle operator, which will add capacity and allow us to serve a larger geographical area.
We’ve achieved this milestone with the thought and care that our riders expect from us. We’ve enhanced our health and safety policies and procedures throughout our fully-owned fleet, sought the feedback of our team, partners, riders, as well as federal, local, and state authorities, all while continuing to advance the Waymo Driver’s capabilities.
To our entire community: thank you for being a part of this important journey. And to all the Waymonauts who’ve worked so hard getting us here: thanks for your dedication to our mission. Together, we’re building a safe and more accessible future with every autonomous mile we drive.
Check out more on how we’re safely resuming our rider services at waymo.com/coronavirus.
For any emerging technology to be trusted, it helps to first be understood. In the past, people could see how their cars worked, looking under the hood and tinkering with them with the help of a user manual. In 2020, vehicles have so much technology that they’ve become difficult for the general public to comprehend. We want to change that. With this blog series, we’ll unpack the different parts of our technology stack to explain the fundamentals of self-driving technology. How does the Waymo Driver perceive the world? How does it learn to understand its surroundings? How can it predict the intentions of other drivers and pedestrians? And how does it keep our riders safe? We’re starting with one of the foundational questions: how does a self-driving car know where it is?
While wrestling with maps and folding them up may bring nostalgic memories for some, the maps we create for the Waymo Driver are orders of magnitude more complex. The information our vehicles care about is quite different from someone trying to find their way to a restaurant. For example, it’s far more important for the Waymo Driver to know the speed limit than the name of the road. We’ve built an incredibly detailed set of mapping technologies that help our cars navigate places even where GPS struggles, like tunnels or between skyscrapers.
Maps are like memory for the Waymo Driver that complements what it’s actually seeing on the road. In this video, the Waymo Driver knows it’s a one way street, but detects another vehicle driving the wrong direction which allows it to quickly adjust its speed and trajectory. Building custom maps for the Waymo Driver
To create a map for a new location, our team starts by manually driving our sensor equipped vehicles down each street, so our custom lidar can paint a 3D picture of the new environment. This data is then processed to form a map that provides meaningful context for the Waymo Driver, such as speed limits and where lane lines and traffic signals are located. Then finally, before a map gets shared with the rest of the self-driving fleet, we test and verify it so it’s ready to be deployed.
Just like a human driver who has driven the same road hundreds of times mostly needs to focus only on the parts of the environment that change, such as other vehicles or pedestrians, the Waymo Driver knows permanent features of the road from our highly-detailed maps and then uses its onboard systems to accurately perceive the world around it, focusing more on moving objects. Of course, our streets are also evolving, so if a vehicle comes across a road closure or a construction zone that is not reflected in a map, our robust perception system can recognize that and make adjustments in real-time.
Over 25 cities across the USA: What we learn through mapping new locations
While the process of creating our custom maps is similar for all geographies, every place is, in many ways, unique. Traffic laws differ from city to city, so we work closely with local officials and traffic engineers to become experts at local driving rules to convey that information to our vehicles.
A Safety Zone in San Francisco (Image credit: Google Maps)For example, in San Francisco there are special areas called Safety Zones where buses and streetcars drop off and pick up passengers. If there is a bus stopped near a Safety Zone and it is not otherwise signed, it’s illegal for a car to drive more than 10 mph past the bus. We’re encoding Safety Zones into our map as a base layer, which helps ensure we are abiding by local laws.
There are many factors we look at when mapping new cities: the width of lanes, bicycle lanes, reversible lanes (think of the Golden Gate Bridge adjustable lanes that can change their direction with the traffic flow), and more. Some nuances are even more subtle. For example, many stores have roller shutter doors and curb cuts that make them almost look like driveways. Knowing which of them are actual driveways helps the Waymo Driver understand whether other cars could be emerging from these areas.
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A store in Los Angeles that looks similar to a driveway (Image credit: Google Maps) |
A crack or a lane separator? Our maps can tell the exact lane width of this street in SF |
The situations we encounter mapping a new area also help improve other parts of our self-driving system. When our mapping vehicles come across a rare or complex situation, we can use this experience to help create our map and also train our perception and behavior prediction models. For example, in Los Angeles’ Fashion District, hundreds of mannequins stand outside the stores and could be mistaken for pedestrians who want to cross the street. Capturing this early means we can better prepare the Waymo Driver to handle unusual, real-world situations. Similarly, observing different traffic behavior patterns helps us evaluate and train our behavior prediction system.
Keeping our maps up to date
Our streets are ever-changing, especially in big cities like San Francisco and Los Angeles, where there’s always construction going on somewhere. Our system can detect when a road has changed by cross-referencing the real-time sensor data with its on-board map. If a change in the roadway is detected, our vehicle can identify it, reroute itself, and automatically share this information with our operations center and the rest of the fleet in real time.
We can also identify more permanent changes to the driving environment, such as a new crosswalk, an extra vehicle lane squeezed into a wide road, or a new travel restriction, and quickly and efficiently update our maps so that our fleet has the most accurate information about the world around it at all times.
We’ve automated most of that process to ensure it’s efficient and scalable. Every time our cars detect changes on the road, they automatically upload the data, which gets shared with the rest of the fleet after, in some cases, being additionally checked by our mapping team.
As city landscapes now face new challenges brought by the COVID-19 pandemic and continue to adapt to our new lifestyles with shared spaces and slow streets, we have also proactively gone out to map and capture these changes.
We’ve been building highly-detailed maps since we started driving more than a decade ago and, combined with our state-of-the-art onboard autonomy system, they’ve been instrumental to helping us get people and things where they are going safely. In the next blog posts we will take a closer look at the other parts of our self-driving technology stack, explain how they enable the Waymo Driver to safely cope with challenges on the road, and share interesting insights from behind the scenes. Stay tuned!
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