Google tries to win map war again
Autonomous vehicles need more precise details, so many companies are fighting a battle of car-tography
On any given day, there could be a half dozen autonomous cars mapping the same street corner in Silicon Valley. These cars from different companies are all doing the same thing: building highdefinition street maps, which may eventually serve as a navigation guide for driverless vehicles.
Autonomous cars require powerful sensors to see and advanced software to think. They especially need up-tothe-minute maps of every conceivable roadway to move. Whoever owns the most detailed and expansive version of these maps will own an asset that could be worth billions.
Which is how you get an all-out mapping war, with dozens of contenders entering into a dizzying array of alliances and burning tens of millions of dollars in pursuit of a huge payoff that could be years away. Google emerged years ago as the winner in consumer digital maps, blanketing the globe with its street-mapping cars and with software expertise that couldn’t be matched by navigation companies, automakers and even Apple. Nobody wants to let Google win again.
The companies working on maps for autonomous vehicles are taking two approaches. One tries to create complete maps that will let the driverless cars navigate all on their own; another creates maps piece-by-piece, using sensors in today’s vehicles that will allow cars to gradually automate more and more parts of driving.
Alphabet, Google’s parent, is trying both approaches. A
team inside Google is working on a 3-D mapping project that it may license to automakers, according to four people familiar with its plans. This service is different than the maps that Waymo, another Alphabet unit, is creating for its autonomous vehicles.
Google’s project is focused on driver-assistance systems that enable cars to automate features and help them see what’s ahead or around a corner. Google released an early version in December, called Vehicle Mapping Service, that incorporates sensor data from cars into their maps.
For now, Google is offering it to carmakers that use Android Automotive, the company’s embedded operating system. Google has named three partners, but other automakers are reluctant to hand over their dashboards. So the Mountain View company is looking to expand the features on the mapping service and find other ways to distribute it, these people said.
At the same time, Waymo and other rivals — including General Motors, Uber and Ford — are all sending their own fleets to create detailed maps for driverless cars. There are also smaller startups hawking gadgets or software to build these maps for automakers that find themselves farther behind. Still other suppliers are working on mapping services for conventional cars with limited robotic features, such as adaptive cruise control or night vision.
These maps are far more demanding than older digital ones, prompting huge investments across Detroit, the Bay Area and China.
“An autonomous vehicle wants that to be as precise, accurate and up-to-date as possible,” said Bryan Salesky, who leads Argo AI, a yearold startup backed by a $1 billion investment by Ford. The “off-the-shelf solution doesn’t quite exist.”
Making a driverless map, like making a driverless car, is a laborious task. Fleets of autonomous test cars, loaded with expensive lidar sensors and cameras, go out into the world with human backup drivers and capture their surroundings. Plotting the results helps train the next fleet, which will still have safety drivers at the wheel—and, in some cases, scores of additional humans sitting behind computer monitors to catalog all the footage.
It’s an expensive ordeal with a payoff that’s years, if not decades, away. “Even if you could drive your own vehicles around and hit every road in the world, how do you update?” asked Dan Galves, a spokesman for Mobileye. “You’d have to send these vehicles around again.”
Unlike conventional digital maps, self-driving maps require almostconstant updates. The slightest variation on the road — a construction zone that pops up overnight, or a bit of debris — could stop a driverless car in its tracks.
“It’s the freak thing that happens that’s going to make autonomous not work,” said McNally, the analyst.
Mobileye argues that it’s more efficient and cost-effective to let the cars we’re driving today see what’s ahead. In January, the Intel Corp. unit announced a “lowbandwidth” mapping effort, with its frontfacing camera and chip sensor that it plans to place in 2 million cars this year. The idea is to get cars to view such things as lane markers, traffic signals and road boundaries, letting them automate some driving.
Mobileye says this will take less computing horsepower than building a comprehensive HD map of the roads would; Mobileye’s Galves said the company will pair its sensor data with the maps from navigational companies and, over time, create a map that a fully driverless car could use.
That’s also the tactic of Google’s longtime mapping foes: Here and TomTom. These two European companies have positioned themselves as the primary alternatives to Google Maps, selling the dashboard screen maps to automakers. Yet these “static” maps see only broad street shapes and capture snapshots in time. Now both companies are working on replacement products: “dynamic” maps that represent lanes, curbs and everything else on the road. The hope is that car manufacturers will stick with old-guard mapmakers as vehicles move from somewhat intelligent to fully automated.
Tesla is the car company most eagerly embracing the incremental march toward autonomous driving with its driver-assistance software, Autopilot. Tesla relies on cameras and sensors on its vehicles but has eschewed lidar. The company hasn’t disclosed what mapping service it’s using, and a company representative declined to comment. Tesla had a nasty public split with Mobileye two years ago.
But Tesla has leaned on at least one other company, Mapbox, to help assemble its maps. Tesla paid $5 million to Mapbox for a two-year licensing deal in December 2015, according to a regulatory filing. Mapbox has mostly sold its location data to apps such as Pinterest and Snapchat. Fresh off a $164 million financing round, the startup has started to inch into automotive maps. Through its software installed on phones, Mapbox said it plots some 220 million miles of road data globally a day, providing an updated snapshot of basic features like street lanes.
“We have more sensors on the road today than the entire connected car space will have by 2020,” said CEO Eric Gundersen. Its pitch to carmakers is to use that location data as a base layer for future maps — pairing it with camera systems, such as Mobileye’s, or their own sensor data. And like other companies targeting automakers, Mapbox is happy to play neutral and work with anyone. “We don’t know who is going to win,” Gundersen said.
It’s not just that no one knows who will come out on top. The mapping industry doesn’t even know which strategy is best. Every self-driving map looks different because each one depends on the sensor system of the vehicle that creates it. And there isn’t a standard sensor package, said Spark Capital’s Nabeel Hyatt, an early investor in Cruise Automation, the autonomous-driving company bought by General Motors in 2016 for $581 million.
As a result, a slew of mapping companies are taking different stabs at the problem, each gobbling up venture capital and competing for lucrative contracts. Some of them disparage Mobileye’s approach, which relies on a seamless transition from semiautonomous driving (what’s called Level 2 and 3) to driving without human assistance (Level 4 or 5). “It’s very hard to climb the ladder from 2 to 3 and then to 4,” said Wei Luo, chief operating officer of DeepMap. “There’s a very intense gap.” The best HD maps, Luo argues, are built with only driverless functions in mind. The startup said it’s working with Ford, Honda Motor Co. and China’s SAIC Motor Corp. (Mobileye is also working with SAIC, and Waymo is in talks with Honda.)
Waymo is in this camp, too. The effort formerly known as the Google self-driving car project started on maps in 2009, with Waymo’s Andrew Chatham and one other engineer doing the “super tedious” work of crafting them from scratch — shipping cars packed with sensors to capture a city’s surroundings, then coding those 3-D images into a digital landscape. Chatham said cars may rely on perceptions systems alone to drive on the highway but would be helpless in other traffic conditions. Imagine pulling up to a busy, double-left-lane intersection you’ve never seen before. Now imagine a self-driving car trying to do that.
Another potential force in this market is Uber. It is also working on maps for its driverless program, using test vehicles in a similar way to Waymo. Lisa Weitekamp, an Uber manager, said the company is exploring ways to place map-generating sensors inside the millions of human-driven vehicles in its service. The maps those cars already use — the “static” navigation software in the app that takes in popular routes and driving decisions — helps inform Uber’s driverless maps, Weitekamp added.
“It gives us a leg up,” she said.
The slightest variation on the road — a construction zone that pops up overnight, or a bit of debris — could stop a driverless car in its tracks.