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BMW to Demonstrate Car That Can Find a Spot and Park Itself in a Garage

We’ve all been there: you’re in a rush to find a spot in a parking lot—say, to catch a movie that is about to start—and you discover that not only are there no open spots nearby, but there is a crush of cars with drivers all waiting to snatch any opening that appears. Now BMW is promising to put an end to this kind of parking lot frustration with a car that finds a spot and parks itself autonomously. You can run to the movie theater and the car will even lock itself.

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Jaguar Plans a (Partially) Transparent Car

Jaguar Land Rover is developing a system to allow a driver to see right through pillars and posts. By thus eliminating blind spots, it could be among the first augmented-reality techniques to go beyond entertaining people and actually save their lives.

Cameras pointing outside the car feed imagery to screens embedded in the posts and pillars, providing what the company calls a 360-degree view. By coupling these screens with images from a projector that casts images onto the windshield, the system can incorporate various driving aides. One example is a “ghost car” that appears in front of the car, so that the driver can follow it. The company argues that this is a much more intuitive way of providing navigation advice than the current method, in which a robotic voice intones, “left turn in five seconds,” or whatever.

Screens are activated only when they have important visual information to convey. Notice that the back pillars of the car become transparent only when the driver turns his head or signals that he’s about to make a turn:

The embedded screens make only parts of the car’s body disappear, unlike a more ambitious program developed by Susumu Tachi and his colleagues at Japan's Keio University. They describe their idea in a recent issue of IEEE Spectrum; the effect is to make doors, roofs, back seats—and even the people sitting there—seem to fall away. The Tachi system uses projectors and mirrors to throw images onto surfaces bearing retroreflective screens that can reflect even oblique rays of light right back along the path they came in on. The Jaguar Land Rover system has the countervailing advantage of requiring neither screens nor mirrors.

Jaguar Land Rover says in its press release that the system will reach its full potential when it can be linked to information beamed in from the road, traffic signs, and other infrastructure, so drivers will have it at their fingertips just when they need it. 

For Self-driving Cars, Another Maker of Maps to Steer By

Google’s competitor in the race to map the world in preparation for self-driving cars is already HERE. That was not a typo. HERE is the maps division of Nokia, the company best known as a maker of cellular handsets (although it unceremoniously hung up on its phone business just over a year ago). Google has focused its engineers’ tremendous technical acumen on mapping every detail of 3200 kilometers (2000 miles) of roads surrounding its Mountain View, Calif., headquarters. But HERE has been taking a different route, so to speak. Over the past year or so, Nokia unit has used its fleet of robocars to map 2 million kilometers (1.2 million miles) in 30 countries on every continent but Antarctica.

In an bid to publicize its ongoing mapping plan for self-driving cars, two of the people leading its self-driving car effort gave reporters at Wired a first-hand look at HERE’s mission-control-like headquarters, a ride in one of the autonomous vehicles in its fleet, and even dropped by Wired’s offices to provide further details. Lucky them. Here’s what we can all take away from what the HERE engineers revealed.

To build its digital maps, HERE starts with satellite and aerial imagery and incorporates so-called “probe data” collected by trucking companies and other fleet operators whose vehicles contain GPS devices. This rich data source—which comprises about 100 billion data points per month—allows engineers at HERE’s Berkeley, Calif., control center to populate the maps upon which its fleet relies with up-to-the-second traffic information. But the probe data is still not as important to the operation as the details provided by HERE’s own fleet—nearly 200 cars equipped with GPS, cameras, and lidar.

Its fleet uses a lidar system that “spins around, shooting out 32 laser beams and analyzing the light that bounces back,” John Ristevski, HERE’s head of reality capture, told Wired. Talk about detailed? Ristevski told Wired that:

[The lidar] collects 700,000 points per second... An inertial sensor tracks the pitch, roll, and yaw of the car so that the lidar data can be corrected for the position of the car and used to create a 3-D model of the roads it has traveled. The lidar instrument’s range tops out about 10-15 stories above the street. At street level, its resolution is just a few centimeters.

Another issue for autonomous vehicles that HERE is addressing is how to, in near real time, deliver updates about things such as accidents and the congestion that occurs when hundreds of cars spill out of a stadium parking lot at the end of a sporting event. Just as important is relaying information about, say, a pothole or a downed tree that would allow a self-driving car to take precautions in a way that wouldn’t scare the daylights out of the “driver.” Peter Skillman, Nokia HERE’s lead designer, told Wired that,

“Sensors on future autonomous cars could feed information over cellular data networks to HERE’s map in the cloud, but…it could take several seconds for a car in San Francisco to beam its data to a data center in, say, North Carolina, and get a response. Getting response times down to tens of milliseconds—fast enough for a car to switch lanes to avoid some debris in the road spotted by another car ahead of it—will require applications that live inside the LTE networks and can be accessed locally.”

That, says Skillman, will be necessary to get humans to trust that a car suddenly swerving out of its lane hasn’t suddenly shut down or gone rogue. Well, that and an onboard digital map that gives them a preview of what the car is about to do and a sense of why the robocar makes certain choices.

Teenage Boffin's Research Could Help Self-driving Cars Avoid Crashes

The winners of the 15th Annual Siemens Competition in Math, Science & Technology  were announced yesterday. The individual winner was Peter Tian, a senior at The Wellington School in Columbus, Ohio. Tian was awarded a US $100,000 college scholarship for his mathematical research on pattern avoidance multidimensional matrices. The advance, say the competition’s judges and other observers, will help improve the performance of self-driving cars and drones by making them better at obstacle avoidance.

Tian was one of 2263 students who submitted projects for consideration. His project, Extremal Functions of Forbidden Multidimensional Matrices, advances the theoretical understanding of pattern avoidance, which may let computers consistently identify the shortest rectilinear path around obstacles in space.

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Euro Robotaxis Will Park and Charge, All by Themselves

A European research consortium is finishing up a project to build a car that can drop you off at a train station, find an empty spot and park there, then pick you up later.

The project is called V-Charge because its cars will charge themselves, too. And, though it would fully automate just the beginning and the end of a trip and would work only at low speeds, the impact could be big if such cars reach the market soon.

And they will, asserts Paul Furgale, of ETH Zurich, the scientific director of the project. He spoke on Thursday at the REWORK Future Cities summit in London, according to Engineering and Technology magazine, which is based there. Three universities besides his own are involved: Oxford University, the Università degli Studi di Parma, and the Technische Universität Braunschweig. So are two companies: Volkswagen AG and Robert Bosch GmbH.

The cars will respond to commands sent through a smartphone app, and they will steer themselves, even in closed spaces that don’t have access to GPS signals, by using what are described as low-cost, “near-market” sensors. That would seem to include compact LIDAR units, which suppliers like Vimeo and Ibeo hope to sell for less than US $300 by 2016.

Right now, though, the researchers are testing Volkswagen Polos equipped with eight cameras of different kinds and 12 ultrasonic sensors. 

Even though the cars will proceed at a crawl, they’ll need all the eyes and brains they can get to stay out of trouble. 

“Pedestrians behave quite unpredictably in areas where cars are driving slowly,” Furgale said. “There are many objects around, and the car needs to be able to figure out whether these objects are static or moving and in what directions are they moving.” 

UK Shifts its Self-Driving Car Research Into a Higher Gear

British efforts aimed at developing self-driving cars are likely to speed up with the announcement of the four UK locations where driverless cars will be tested. The tests, which begin in January, will last as long as 36 months. The government announced £9 million (US $14 million) in funding for the work—on top of the £10m that was committed to the project in July. The funds will support three consortia (one of which will conduct its tests in two places in the same region).

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Car Camera Network Could Produce Virtual Maps of Pedestrians

A growing fleet of smart cars may add their street camera views to those of the surveillance camera networks already covering many major cities. That could open the door for a new technology that enables different video cameras to “talk” with one another and track the same individual person across many different camera views—possibly giving rise to Google Earth style maps that can display pedestrian and vehicle traffic.

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Robotic Taxis Could Slash Fares in Austin, Texas

When driverless taxis are at our beck and call, a lot of people will give up the chore of driving and parking, streets will be less crowded, and commuting times will drop, say proponents of automated automobiles.

It makes sense, but does it compute? Many computer models have attempted to answer that question; now a particularly detailed one for Austin, Texas, suggests that robocabs could indeed save commuters a lot of hassle and money.

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Self-driving Cars: Saving Lives AND Energy

If you follow this blog, you’re definitely aware that the main benefit of self-driving cars is their unwavering vigilance. Someday soon, autonomous vehicle developers hope, you’ll be able to hop in your car, tell it where to go, and turn your attention elsewhere. So will end the tens of thousands of avoidable deaths that occur each year because humans get behind the wheel when they’re drunk or sleepy, decide to text and drive, or otherwise lose focus.

But a Rocky Mountain Institute (RMI) article highlights another important way that robocars will benefit us that we’ve previously mentioned. The environmental impact of driving, says RMI, will be radically altered. Once we reach a critical mass of self-driving cars on the world’s roads, these vehicles will be able to move through highway networks like schools of fish, communicating with each other so they can travel together at close distances without concern for collisions or even traffic jams.

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Cars That Think

IEEE Spectrum’s blog about the sensors, software, and systems that are making cars smarter, more entertaining, and ultimately, autonomous.
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