MINI already has plans to produce its first battery electric MINI at its main plant in Oxford starting in 2019. Shortly thereafter, Chinese production should begin. BMW Group already has a foothold in mainland China with its highly successful BMW Brilliance Automotive (BBA) joint venture with Chinese partner Brilliance. BBA already has two automotive production plants and a battery factory in Shenyang. This battery factory is the first ever to be operated by a premium automobile manufacturer in China.

Using this blueprint for success, the electrification of MINI in China could be a big deal for the brand. Last year MINI delivered about 35,000 units to China. With new electric models coming soon, MINI hopes to increase this number significantly over the next few years. To give some perspective, BMW delivered 560,000 vehicles in China last year.

BMW points out that despite expanding the brand in China, production has not decreased at the company’s German plants. In the last decade, German production has increased nearly 25 percent to 1.15 million cars per year. Despite nearly half of BMW production taking place at plants outside of Germany. I’m sure this should calm the folks over in Oxford for MINI. Don’t worry, the company isn’t planning to phase out U.K. production, instead to add to the overall volume within the Chinese factories.

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Hytch connects drivers with riders who are going to the same destination, just like regular carpooling. But it also tracks the route and pays both driver and passengers for making the trip together. The goal is to get more people to carpool, and in turn, reduce traffic congestion. Hytch claims that if six percent of road users switched to carpooling, it would eliminate 1,500 daily trips into Nashville. Depending on traffic speeds, that could be equivalent to adding an extra lane to the interstates that pass through the city, according to Hytch.

But Nissan has its own motivation for backing the app. It believes Hytch will allow for closer studying of consumer habits, and that this information could become a competitive advantage as automakers move into mobility services.

Carpooling, car sharing, and ride sharing may decrease the need for people to own cars, but automakers also view these services as an opportunity. Companies like BMW, Daimler, and General Motors already operate their own car-sharing services. Ford operates the Chariot shuttle service in multiple cities, as well as a bike-sharing service called GoBike in San Francisco. These services represent potential new sources of revenue for automakers.

All of these services provide the convenience of not having to drive oneself from Point A to Point B, but when it comes to reducing traffic congestion, they may not all be equal. Ride-sharing services like Uber and Lyft encourage people to ride by themselves (although Uber and Lyft both offer carpooling options), which doesn’t really reduce the number of vehicles on the road. By putting multiple people in one car, services like Hytch and Ford’s Chariot are the most likely to reduce traffic.

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The application potential of intelligent data analysis methods for monitoring and optimizing test data, ECUs and test benches in the automotive industry is regarded as extraordinary high. For example, a modern engine control unit has more than 50,000 setting parameters that are decisive for fuel consumption, wear and tear and the overall performance of the engine. Deep learning technologies, or more precisely the use of neural networks in the control unit, enable the latter to “learn” independently how to optimally adjust the input variables. The use of such networks in the time series analysis of engine test data also opens up new approaches to predictive engine health monitoring, thus improving the prediction of wear and maintenance cases. Such methods are to be researched and developed in the new research laboratory.

At the same time, FLaP, as the new lab is called, will also work on new visualization options for the diverse measurement data from the neural networks. The aim is to create a toolbox of AI tools that can be used intuitively and appropriately by automotive engineers.

“In addition to the promising possibilities for use on existing hardware in production vehicles, FLaP also investigates novel applications for self-learning neural networks,” says Prof. Dr. Andreas Dengel, Head of the Smart Data & Knowledge Services Research Unit at DFKI. “The aim is both to gain fundamental knowledge in the long term and to develop concrete solutions to current problems in the short term.”

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Uber’s proposed system used a light bar and motorized seat, but the system patented by Sivak and Schoettle just involves some eyewear. Lights fitted to the glasses flash in the wearer’s peripheral vision, which is supposed to help reconcile what a person is seeing with the movement of the vehicle. A patent covers both wearable and vehicle-based versions of the system, according to the University of Michigan.

Both the Uber and the University of Michigan systems rely on lights to keep autonomous-car passengers from vomiting, but Uber’s version works in concert with a special seat that can both move and blow air over specific parts of the body. The University of Michigan system offers the option of portability, which could make it easier to commercialize.

Being granted a patent doesn’t make a technology commercially viable, but the University of Michigan does plan to shop its system around to automakers and suppliers. Researchers believe motion-sickness deterrents will be more important in self-driving cars because everyone will be a passenger. About half of adults get motion sick while reading a book in a car, according to the university.

But even if a solution is found, people may not want to ride in self-driving cars if there is a high chance of getting carsick. Having to put on special glasses to avoid losing your breakfast on the morning commute doesn’t sound like the most glamorous kind of future.

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MBUX is Mercedes’ attempt to bring the long horizontal dashboard-screen setup previously seen on the S-Class and E-Class to smaller models. What Mercedes calls the “widescreen cockpit” replaces the traditional center-stack touchscreen and instrument cluster with two side-by-side screens that run about half the length of the dashboard.

Three configurations of screens will be offered: two 7.0-inch screens, two 10.25-inch screens, and a version with one screen of each size. What the screens display is reconfigurable, but the default setting puts a traditional speedometer and tachometer in front of the driver.

Where Mercedes previously relied heavily on a somewhat confusing touchpad controller, MBUX offers more options. In addition to a touchpad, the driver can simply tap the screens (not an option on most recent Mercedes systems), use touchpads on the steering wheel, or use voice control.  Mercedes says the voice-control system can recognize natural speech patterns, and it enables another of MBUX’s key new features.

As if Amazon Alexa and Google Assistant didn’t have enough people shouting at inanimate objects, Mercedes now has a digital assistant of its own. By saying “Hey Mercedes,” the driver can access features like weather information, or just adjust the climate control. The ability to recognize natural speech means he or she just has to say “I’m cold,” rather than specifying a temperature.

Mercedes says the system attunes itself to a specific user’s voice, allowing it to more easily understand non-native speakers. The software can also “learn new buzzwords or changing use of language with time,” according to Mercedes, meaning your car will soon pick up the latest slang. Crucially, the system will respond without an Internet connection.

MBUX debuts on the next Mercedes A-Class hatchback later this year. That model won’t be sold in the United States, but MBUX will be available here on a new four-door variant that will replace the current CLA-Class.

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At a discussion event at CES, VW and Nvidia gave an idea of how AI will change the automotive industry. “Autonomous driving and networked mobility are not possible without AI and deep learning,” said VW brand manager Herbert Diess. Nvidia’s founder and CEO Jensen Huang explained exactly where he imagined the use of AI in the car. “In a few years’ time, every new vehicle will be equipped with AI assistants for speech, gesture and face recognition or augmented reality,” Huang predicted.

A possible feature of the VW electric minibus I. D. Buzz, which is planned for 2020, could be the capabilities of an intelligent co-pilot who will process sensor data from both the car’s interior and its surroundings for comfort and assistance systems. These systems can be optimized throughout the vehicle’s entire lifecycle by means of software updates and can acquire new capabilities in the course of further developments in autonomous driving. Thanks to’ Deep Learning’, the car of the future can learn to accurately assess situations as well as analyze the behavior of other road users and will be able to make the right decisions, VWs Diess explained.

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The Chinese government is blocking foreign companies from mapping its roads in great detail, according to a Financial Times report. The restrictions, which reportedly do not apply to Chinese firms, are being instituted in the name of national security. China is concerned about spying.

China has restricted the recording of geographic information for more than a decade because it believes giving other countries access to that information constitutes a security risk. Geographic surveys can’t be performed without permission from the government, and many digital cameras don’t record GPS coordinates for geotagging, as they do in other countries, according to Fortune.

The restrictions on mapping mean foreign companies looking to sell or operate self-driving cars in China may have to partner with local firms to gain access to all of that precious map data. This wouldn’t be too different from the situation foreign automakers currently face in China.

Foreign automakers that want to build cars in China have to partner with a local automaker. This arrangement has led to concerns over the theft of intellectual property, although many companies have complied in order to gain access to a large enough share of the world’s biggest new-car market. A notable exception has been Tesla, although it appears the company may be moving closer to a deal to manufacture cars in China on its terms.

Chinese firms like Baidu and TuSimple are already working on autonomous driving. Their ability to map roads in their home country unrestricted may give them an advantage there, something the Chinese government probably wouldn’t mind. It’s already tried to boost the domestic electric-car industry by inflating demand through generous purchase incentives, so why not do the same with self-driving cars?

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The Blue Oval will reportedly test selling cars directly to Chinese customers through Alibaba’s online retail arm Tmall as well as a brick-and-mortar “Automotive Vending Machine” store concept. This would mark Ford’s first major foray into direct sales, a system that is currently used by Tesla and is gaining attention from other automakers.

Representatives of Ford and Alibaba, including Ford chairman Bill Ford Jr. and CEO Jim Hackett, are expected to sign a letter of intent in Hangzhou on Thursday outlining these programs, according to Reuters. Ford confirmed that it will make an announcement in Hangzhou Thursday, but did not provide details. The partnership could mark an escalation in Ford’s efforts to increase sales in China. The company recently announced a deal with local firm Zotye Auto to build electric cars there.

While cars could be sold online, customers may take delivery at conventional Ford dealerships, who would also handle maintenance, the report said. But Alibaba’s Tmall is also testing something called the “Automotive Vending Machine,” a retail store based around a multi-story garage that would actually resemble a giant vending machine. Customers would browse available cars supplied directly by Ford on their phones to buy or test drive. Alibaba envisions customers putting 10 percent of the purchase price down, and paying the balance in monthly installments through its Alipay service.

Both models could bypass traditional franchised dealerships, something Tesla is already doing. The Silicon Valley automaker has sold cars directly to customers from the start, angering franchised dealers who view direct sales as a threat to their business. In the U.S., Tesla has fought a state-by-state battle against dealer-franchise laws, which still bar it from selling cars directly to customers in some states.

A major legacy automaker like Ford embracing the concept could be a big boost for direct sales. But it’s unclear if Ford would actually import direct sales to the U.S., and risk alienating its network of dealers. Anyone who has bought a car knows that current franchised dealerships are far from perfect, but the system is well entrenched

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Yandex released a new video of its two Toyota Prius V development mules driving around in snowy conditions. Winter weather is challenging for self-driving cars not only because of reduced traction but because snow can obscure the lane markings autonomous vehicles rely on as a visual cue to orient themselves. Winter capability is particularly important for Yandex, which hopes to develop an autonomous ride-sharing service in Russia, a country known for harsh winters.

The conditions Yandex’s self-driving cars negotiate in this video aren’t exactly extreme; at times there isn’t even any snow on the roads. The cars perform basic functions like avoiding other vehicles and pedestrians and making smooth stops. With so many companies testing self-driving cars, it’s more a demonstration of minimal competence than of technological boundaries being pushed.

For self-driving cars to replace human drivers, it goes without saying that they will have to function in all kinds of weather. With most U.S. autonomous-car testing taking place in and around Silicon Valley, winter weather is not something most cars will encounter on a daily basis. But companies are accounting for that.

Ford and General Motors test self-driving cars year round in Michigan and Ford has already conducted dedicated snow testing. Waymo will bring some of its autonomous Chrysler Pacifica Hybrid minivans to Michigan this winter for testing as well. To improve the technology, autonomous cars dashing through the snow will have to become a more common sight.

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In the paper, Yin Zhou and Oncel Tuzel propose a software program called “VoxelNet” to help computers detect three-dimensional objects. That’s relevant to autonomous cars because pedestrians, cyclists, and other potential obstacles tend to be three-dimensional.

The software could potentially boost the effectiveness of sensors used in self-driving cars to identify obstacles. Most companies developing autonomous vehicles use a combination of cameras, radar, and lidar (which works like radar, but with light), to create a complete picture of the environment. Each type of sensor has its own weakness, which is why all three are needed.

But the software described in the Apple researchers’ paper has shown the ability to spot pedestrians and cyclists with lidar alone, at least in computer simulations.  The system hasn’t been tested on an actual car in the real world yet.

Apple recently received approved to test self-driving cars on public roads in California, and its Lexus RX development mules have been spotted a few times over the past few months. But the company’s specific goals remain unclear. CEO Tim Cook has called autonomous driving the “mother of all AI projects,” but has hinted that Apple will develop autonomous-driving systems only, rather than complete cars.

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