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How we’re giving everyone, everywhere an address

How we’re giving everyone, everywhere an address

how were giving everyone

How we’re giving everyone, everywhere an address

We’ve gone behind the scenes to look at how we map the world, use imagery to capture the meaningful details around us.

And all the ways contributed content and AI make Google Maps. A more helpful tool from planning your trip to deciding where to go.

Today, we’ll dive into how we are working to make sure everyone in the world has access to an address using our free. Open-source digital address-making system called Plus Codes.

Plus Codes: Addresses for Everyone

Addresses help us find people and places, and they help people and things find us. An address is also necessary to secure official documents. And do things like open a bank account. However. Several billion people either don’t have an address at all or they have one that doesn’t accurately identify the location of their home or business. Plus Codes offer a simple but powerful solution. Already, Google Maps provides millions of directions each month to people looking up a place with a Plus Code and this volume is rapidly growing.

So what are Plus Codes? 

Plus Codes use latitude and longitude to produce a short, easy-to-share digital address that can represent any location on the planet. For example, the Plus Code “W2GJ+JQ, Johannesburg”. Represents the main entrance to the Google office in Johannesburg, South Africa. Put this code into Google Maps. Or Google Search and you’ll be brought right to our front door in Johannesburg.

The Plus Code address for Google’s Johannesburg office is W2GJ+JQ, Johannesburg

Helping people get on the map

A Plus Code can easily be used where no addresses, street names. Or even streets exist today.  Someone in an area without addresses no longer needs to give out complicated instructions to find a home or workplace like “drive to the community center. Turn left and look for the blue house with the red roof.”  Now, they can simply share a short Plus Code and it immediately works.

a) How were giving everyone, everywhere an address

Businesses and services that rely on navigating to peoples’ homes can simply enter the Plus Code into Google Maps. And get directions instantly. Emergency services and humanitarian groups can more easily find people who need aid, locate people for vaccine programs. And easily track health programs all with Plus Codes. 

Generating Plus Codes

In the absence of street names and accurate addresses. How are Plus Codes created? 

First, we divide the world along latitude and longitude lines to form a simple grid. The grid is labelled along the X and Y axis using a specific set of 20 alphanumeric characters  {2,3,4,5,6,7,8,9,C,F,G,H,J,M,P,Q,R,V,W,X}. You’ll never see a vowel or characters like “1”, “L” and “l” in a Plus Code as we want to avoid confusion over the characters when writing them down and prevent any accidental word formations. And by using a carefully selected set of alphanumeric characters. Plus Codes can be used by anyone no matter what language you speak.

b) How were giving everyone, everywhere an address

Each grid cell on the digital globe is then further divided, the X and Y-axes again labelled with the 20 characters above and the process repeated to build out a full Plus Code. In the case of the Google Johannesburg office this would result in a full Plus Code of “5G5CW2GJ+JQ”. 

Since a full Plus Code might not be easy to recall. You can conveniently drop the first four characters of the code if you know the area you are in,  just as we drop area codes on telephone numbers when already in the area. In this case. If I know I am in Johannesburg the Plus Code for the Google office can be shortened to “W2GJ+JQ, Johannesburg.”

c) How were giving everyone, everywhere an address

Depending on the number of characters included in the code after the ‘+’ sign, the code can be even more specific. For example a Plus Code with two characters after the ‘+’ sign represents an area of approximately 13m x 13m. About the size of a half a basketball court. Adding an additional character reduces this size to approximately 3m x 3m, providing an exact address for a sidewalk vendor who may not even have a storefront. 

And this might go without saying. 

how were giving everyone

Plus Codes in São Paulo, Brazil

Community addressing

Often taking years to set up and become useful. With Plus Codes. a village. town. city or even country can quickly and efficiently set up an addressing system. And unlike conventional addressing projects. This means that new services (both digital and non-digital) are more readily available to traditionally underserved communities that lack proper addresses.

d) How were giving everyone, everywhere an address

The power of Plus Code addresses

While there are other digital address-making solutions. Which can mean unnecessary costs, complications and longer term uncertainty for businesses and governments. These solutions also have challenges with universal recognition and adoption. As they are generally not open source or freely available.  

Here’s a taste of the positive impact we’ve seen Plus Codes deliver.

How we're giving everyone
  • NoneIn India, the NGO Addressing The Unaddressed has successfully used Plus Codes to provide addresses to hundreds of thousands of residents.

We recently introduced a refreshed Plus Codes icon to make it more recognizable. Visit maps.google.com/pluscodes

Earthtopomaps.com

xAn address is also necessary to secure official documents. And do things like open a bank account. However. Several billion people either don’t have an address at all or they have one that doesn’t accurately identify the location of their home or business. Plus Codes offer a simple but powerful solution.

yAn address is also necessary to secure official documents. And do things like open a bank account. However. Several billion people either don’t have an address at all or they have one that doesn’t accurately identify the location of their home or business. Plus Codes offer a simple but powerful solution.

zyAn address is also necessary to secure official documents. And do things like open a bank account. However. Several billion people either don’t have an address at all or they have one that doesn’t accurately identify the location of their home or business. Plus Codes offer a simple but powerful solution.

A smoother ride and a more detailed Map thanks to AI.

A) A smoother ride and a more detailed Map thanks to AI.

a smoother ride

B) A smoother ride and a more detailed Map thanks to AI.

AI is a critical part of what makes Google Maps so helpful. With it. We’re able to map roads over 10 times faster than we could five years ago. And we can bring maps filled with useful information to virtually every corner of the world. Today. We’re giving you a behind-the-scenes look at how AI makes two of the features we announced at I/O possible.

B) A smoother ride and a more detailed Map thanks to AI.

Teaching Maps to identify and forecast when people are hitting the brakes.

Let’s start with our routing update that helps you avoid situations that cause you to slam on the brakes. Such as confusing lane changes or freeway exits. We use AI. And navigation information to identify hard-braking events — moments that cause drivers to decelerate sharply and are known indicators of car crash likelihood. And then suggest alternate routes when available. We believe these updates have the potential to eliminate over 100 million hard-braking events in routes driven with Google Maps each year. But how exactly do we find when and where these moments are likely to occur?

That’s where AI comes in. To do this, we train our machine learning models on two sets of data.

The first set of information comes from phones using Google Maps. Mobile phone sensors can determine deceleration along a route. But this data is highly prone to false alarms because your phone can move independently of your car. This is what makes it hard for our systems to decipher you tossing your phone into the cupholder or accidentally dropping it on the floor from an actual hard-braking moment. To combat this. We also use information from routes driven with Google Maps when it’s projected on a car’s display, like Android Auto. This represents a relatively small subset of data, but it’s highly accurate because Maps is now tethered to a stable spot your car display. Training our models on both sets of data makes it possible to spot actual deceleration moments from fake ones, making detection across all trips more accurate.

C) A smoother ride and a more detailed Map thanks to AI

Understanding spots along a route that are likely to cause hard-braking is just one part of the equation. We’re also working to identify other contextual factors that lead to hard-braking events. Like construction or visibility conditions. For example. If there’s a sudden increase in hard-braking events along a route during a certain time of day when people are likely to be driving toward the glare of the sun. Our system could detect those events and offer alternate routes. These details inform future routing so we can suggest safer. Smoother routes.

Using AI to go beyond driving

When you’re walking or biking or taking public transit. AI is also there helping you move along safely and easily. Last August we launched detailed street maps which show accurate road widths. Along with details about where the sidewalks. Crosswalks and pedestrian islands are in an area so people can better understand its layout and how to navigate it. Today. We announced that detailed street maps will expand to 50 more cities by the end of 2021. While this sounds straightforward. A lot is going on under the hood especially with AI to make this possible! 

A before and after comparison of detailed streets maps built from satellite imagery

a smoother ride

E) A smoother ride and a more detailed Map thanks to AI.

Imagine that you’re taking a stroll down a typical San Francisco street. As you approach the intersection. You’ll notice that the crosswalk uses a “zebra” pattern — vertical stripes that show you where to walk. But if you were in another city. Say London. Then parallel dotted lines would define the crosswalks. To account for these differences. And accurately display them on the map. Our systems need to know what crosswalks look like — not just in one city but across the entire world. It gets even trickier since urban design can change at the country. State. And even city level.

  • A street level picture of crosswalks in San FranciscoCrosswalks in San Francisco

To expand globally and account for local differences. We needed to completely revamp our mapmaking process.

Traditionally. We’ve approached mapmaking like baking a cake one layer at a time. We trained machine learning models to identify and classify features one by one across our index of millions of Street View. Satellite and aerial images starting first with roads. Then addresses. Buildings and so on.

A smoother ride and a more detailed Map thanks to AI

But detailed street maps require significantly more granularity and precision than a normal map. To map these dense urban features correctly. We’ve updated our models to identify all objects in a scene at once. This requires a ton of AI smarts. The model has to understand not only what the objects are. But the relationships between them like where exactly a street ends. And a sidewalk begins. With these new full scene models. We’re able to detect and classify broad sets of features at a time without sacrificing accuracy. Allowing us to map a single city faster than ever before. 

A smoother ride 1
A smoother ride 1

Single-feature AI model that classifies buildings.

a smoother ride

Full-scene AI models that capture multiple categories of objects at once.

Once we have a model trained on a particular city.

We can then expand it to other cities with similar urban designs. For example. The sidewalks. Curbs. And traffic lights look similar in Atlanta and Ho Chi Minh City despite being over 9,000 miles away. And the same model works in Madrid as it does in Dallas. Something that may be hard to believe at first glance. With our new advanced machine learning techniques combined with our collection of high definition imagery. We’re on track to bring a level of detail to the map at scale like never before.

AI will continue to play an important role as we build the most helpful map for people around the globe. For more behind-the-scenes looks at the technology that powers Google Maps. Check out the rest of our Maps 101 blog series.

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Maps 101

Google Maps helps you navigate. Explore. And get things done every single day. In this series. We’ll take a look under the hood at how Google Maps. Uses technology to build helpful products from using flocks of sheep. And laser beams to gather high-definition imagery to predicting traffic jams that haven’t even happened yet.

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How ai is making information more useful

Earth Timelapse. Now available on phones and tablets. Includes a handy new “Maps Mode”. Toggle to let you navigate the map using Google Maps. The design of the new Timelapse interface leverages Material Design with simple. Clean lines. And clear focal areas. So you can easily navigate the immense dataset.

AI is a critical part of what makes Google Maps so helpful. With it. We’re able to map roads over 10 times faster than we could five years ago. Teaching Maps to identify and forecast when people are hitting the brakes. Such as confusing lane changes or freeway exits. And then suggest alternate routes when available. But how exactly do we find when and where these moments are likely to occur?. But this data is highly prone to false alarms because your phone can move independently of your car. We also use information from routes driven with Google Maps when it’s projected on a car’s display, like Android Auto. This represents a relatively small subset of data, but it’s highly accurate because Maps is now tethered to a stable spot your car display. For example. If there’s a sudden increase in hard-braking events along a route during a certain time of day when people are likely to be driving toward the glare of the sun.

AI is a critical part of what makes Google Maps so helpful. With it. We’re able to map roads over 10 times faster than we could five years ago. Teaching Maps to identify and forecast when people are hitting the brakes. Such as confusing lane changes or freeway exits. And then suggest alternate routes when available. But how exactly do we find when and where these moments are likely to occur?. But this data is highly prone to false alarms because your phone can move independently of your car. We also use information from routes driven with Google Maps when it’s projected on a car’s display, like Android Auto. This represents a relatively small subset of data, but it’s highly accurate because Maps is now tethered to a stable spot your car display. For example. If there’s a sudden increase in hard-braking events along a route during a certain time of day when people are likely to be driving toward the glare of the sun.

X) A smoother ride and a more detailed Map thanks to AI

Y) A smoother ride and a more detailed Map thanks to AI

Z) A smoother ride and a more detailed Map thanks to AI

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