Self-Driving Cars: Getting there

Autonomous vehicles are disrupting traditional business models within one of the world’s largest industries and it’s happening much sooner than anyone expected. What are the forces behind the push for self-driving cars? Is the necessary road infrastructure in place, or do we still need to build it? What happens if an autonomous vehicle needs to make life-or-death decisions? In this section we explore the possibilities – and the risks – involved when humans hand over control to robo-chauffeurs.

Four years. That was the answer given by Jensen Huang, CEO of Nvidia, early last year when he was asked how long it would take for artifcial intelligence to enable fully automated cars. Then a funny thing happened. Suddenly, self-driving vehicles began to crop up on public roads all over the place. At the Barcelona Motor Show in May, Audi unveiled the 2018 Audi A8, which it claimed as the world’s first production car to offer Level 3 autonomy. Level 3 means the driver doesn’t need to supervise things at all, so long as the car stays within certain guidelines. In Audi’s case that means never driving faster than 60 kph (37 mph). Audi billed this feature as the AI Traffic Jam Pilot.

In the US, Las Vegas became the first city in America to have a self-driving shuttle operating in real-time traffic. However, on its first day of service the shuttle collided with a truck. The driverless bus couldn’t back off when the truck was reversing into an alley so, technically at least, the human driver caused the crash, not the shuttle. In September, General Motors showcased the third generation of its autonomous Chevrolet Bolt, which it has developed with recently acquired Cruise Automation, headquartered in San Francisco. Kyle Vogt, the CEO of Cruise automation, called it the “first production model self-driving car in the world.”

The time of the self-driving vehicle has come much faster than anyone expected. For Jensen Huang and Nvidia it means big bets are paying out even sooner than they’d hoped The company has invested heavily in research involving machine learning, which Huang says is the “bottom-up approach to artificial intelligence” – and probably the most promising technology today. Machine learning requires the processing of huge amounts of data, and as it turns out, the company’s commutative graphics processing units (GPUs) can do the job both faster and using less energy than the traditional central processing units (CPUs) found at the heart of most mainframe, desktop, and laptop computers today.

The commutative power of GPUs has increased as computer images have become more complex and, in 2007, Nvidia pioneered a new generation of GPU/CPU chips that now power many energy-efficient data centers in government laboratories, universities, and enterprises.

It was almost by accident that the company became a big player in the nascent autonomous car sector, but it now plans to release the Nvidia Drive PX2 platform next year, describing it as the first “AI brain” capable of full autonomy.

Nvidia’s approach is so revolutionary that other chipmakers are scrambling to catch up. Intel and AMD, two of the largest manufacturers of computer chips, have teamed up to pool their resources in order to head off Nvidia by developing a GPU/CPU combo of their own. In addition, Intel made the biggest acquisition of its lifetime early in 2017 when it paid $15.3bn for Mobileye, an Israeli-based specialist in sensors, mapping technology, and camera-based devices for advanced driver-assistance systems (ADAS). This is just one example of many that hint at the impending disruption autonomous vehicles will bring to the automotive and related industries. As for when self-driving cars will hit the mainstream, opinions still vary. But Tesla, Ford, Audi, General Motors, and Nissan are among those that believe cars operating without humans will be on the road within the next five years.

This visionary or perhaps doom-laden scenario, depending on your view, is driving the whole supply chain to frantically figure out where to position themselves. Delphi, a UK supplier of proprietary automobile components and integrated systems and modules, acquired NuTonomy, a developer of autonomous driving (AD) software solutions for $450m in November 2017. Delphi, which will soon change its name to Aptiv, has announced it intends to build a self-driving system it can sell to all the big auto makers. ADAS requires immense computing resources to provide higher levels of predictability and autonomy.

Typical components are: radar, lidar (similar to radar but using laser light), camera, ultrasonic, vehicle-to-everything (V2X) wireless sensors (allowing see-through and 360° non- Interview with Janina Loh line of sight sensing), 3D HD maps, and precise positioning using the Global Navigation Satellite System (GNSS). V2X communications should improve driving comfort and has the potential to save lives by reducing accidents caused by human error. More than 1.3 million people die on the roads every year. Automated driving, supported by safe and dynamic driving algorithms, could change this by delivering Vision Zero, an EU project with a target of reducing the number of traffic fatalities to zero.

Challenges ahead for self-driving cars

Automated driving calls for extremely complex systems. Service-oriented, end-to-end vehicle control architectures require an holistic approach embracing cloud services and the delivery of software updates over the air. Safety, and system architectures need to be developed in tandem if they are to rely on one another. Reliability, safety and availability in particular depend on the real-time analysis of trafc situations, road conditions, weather, and other variables. Increasingly, carmakers are addressing concerns about “carjacking” where hackers gain control of vehicles via wireless transmission to cause new kinds of problems, from vandalism, by intentionally crashing a vehicle, to holding passengers for ransom.

Car hacking is a hot topic. It’s not new for researchers to hack cars and they have demonstrated previously how to hijack a car remotely, how to disable a car’s crucial functions such as airbags, and even how to steal cars. The latest car hacking trick doesn’t require any extraordinary skills to accomplish.

Ranking Autonomy Levels

The Society of Automotive Engineers (SAE) definitions of vehicle automation (Image Credit: © SAE International and J3016).

How autonomous is autonomous?

No Automation. The full-time performance of all aspects of the dynamic driving task, even when enhanced by warning or intervention systems, is left to the human driver. 

A research team from the University of Washington demonstrated in 2016 how anyone could print stickers at home, put them on road signs and trick autonomous cars into misreading the signs and potentially causing serious accidents.

The European Union Agency for Network and Information Security (ENSIA) published a guide in December 2016, Cyber Security and Resilience of Smart Cars, which contains good practices and recommendations for all players. It includes advice on how manufacturers can:

• Improve cybersecurity in smart cars
• Improve information sharing between industry actors
• Improve exchanges with security researchers and third parties

Another challenge relates to vehicle-tovehicle (V2V) communication for which a dedicated short-range communications (DSRC) standard is proposed, based on the IEEE 802.11p standard working in the 5.9GHz ITS spectrum. In addition, communication with networks and pedestrians will also be needed for everything to function seamlessly; something that is hardly guaranteed given today’s patchy GSM and LTE coverage. For this reason, many observers think acceptance of autonomous vehicles will depend on the rollout of 5G networks, which is not expected until 2020 at the earliest. Regulation for legal aspects is needed, preferably sooner rather than later. Who is liable in the case where technology fails? Germany was the first to add relevant paragraphs to its traffic laws in early 2017. In most other countries the regulators still need to come to grips with the situation.

GM paves the way towards car2car communications

California has licensed 27 companies such as Lyft, Tesla, Uber, and Waymo to test driverless vehicles on public roads. San Diego will be the site of a frst-of-its-kind feld trial of cellular-connected car technology for autonomous vehicles to be conducted by the Smart Cities Council global lead partners Qualcomm and AT&T, plus associate partner Ford. General Motors has become the frst carmaker to make vehicle-to-vehicle (V2V) communications standard in a consumer car. The 2017 Cadillac CTS now comes with dedicated short-range communications that allow it to talk to sibling CTS cars. Meanwhile, the auto industry is stepping on the gas. During September 2016 in Germany, Audi, BMW, Daimler, Ericsson, Huawei, Intel, Nokia, and Qualcomm came together to form the 5G Automotive Association (5GAA). In March 2017, 5GAA announced it had signed a memorandum of understanding with the European Automotive Telecom Alliance (EATA). The stated aim of this partnership is to “foster cooperation in the field of connected and autonomous driving solutions as well as standardization, spectrum and related use cases.

Private and public field tests begin

The first German public test field began in November 2015 on the A9 highway between Munich and Nuremberg with a total length of 160 km. In February 2017, the first cross-border test field was set up between Merzig in Germany and Metz in France. It was recently extended to Luxemburg.

In March 2017, 29 European countries signed a Letter of Intent to intensify cooperation on testing of automated road transport in cross-border test sites. An additional test field was added in September 2017 connecting Rotterdam and Eindhoven in the Netherlands, Antwerp in Belgium, Porto and Evora in Portugal, Vigo and Merida in Spain, Tromsø in Norway, and Oulu in Finland.

Another initiative, called the Nordic Way, is a pilot project that seeks to enable cars to share safety-hazard alerts through cellular networks on a road corridor through Finland, Norway, Sweden, and Denmark. Agriculture is another hot candidate for self-driving vehicles. It is expected that a fully automatic tractor will be available in 2018. Austrian vendor Lindner demonstrated the necessary technology during Agritechnica in Hannover in November 2017.

According to the McKinsey report Smart Moves Required – The Road Towards Artificial Intelligence in Mobility, robo-taxis could represent the future. These self-driving taxis could disrupt the auto industry. But it doesn’t end there. For some services the road may be abandoned completely. A fully auto-piloted airtaxi service based on Chinese-made E-Hang 184 aircraft has been flying passengers on selected routes within Dubai since October 2017.

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