Observations & Opportunities: Self-Driving Vehicles—Challenges Abound

Remember when you used the rearview mirror to back into a parking space? Some of us still do but many vehicles now include, or provide as an option, automated parking driving aids. In practice, it conveniently works with another system that avoids backing over unsuspecting pedestrians or hitting inanimate objects (the increasingly common AI-based automated braking systems).

This is just one example of what basic driver-assistance systems can do now. Yes, some consumers are still skeptical of fully AVs (autonomous vehicles)/ADS/ADAS (advanced driver assistance systems). They question their practicality but also like the idea of being able to do other things to pass the time while stalled in traffic congestion. The many heavyweight companies developing AVs are counting on the latter. The expected decrease in traffic accidents and minimized congestion are benefits that insurance companies and governments applaud.

To counter the increasingly common dashboard infotainment systems, and all the mobile devices including laptops for consuming media and information brought onboard, and seemingly ubiquitous smartphones, that dangerously distract drivers now, AVs that could safely transport distracted occupants should become more popular and better for all concerned.

Perhaps the practical limits of AV system implementation are “driver” and passenger sensory overload plus the thought of simply not being in control. Also, significant AV system costs and technology maturity are concerns. Even when AV systems become commonplace, the cost of the components alone will be substantial. As Tesla Inc. indicated recently, the cost differential between assisted driving and full AV capabilities is several thousand dollars. What all of these various systems use is dependent, to varying degrees, upon affordable and reliable artificial intelligence (AI) implementation with associated sensors and actuators. [Also see earlier blogs on AI & Virtual Reality—Let The Games (and Work) Begin and AI & Autonomous Vehicles—Awesome Implications]

Some AV Reality Checks

At this point in time, it would be difficult to find an automobile manufacturer that is not actively working on integrating sophisticated autonomous vehicle operation in some, or all, of its vehicles. At the same time, these manufacturers are increasingly focusing on electric vehicles (EVs) or hybrid gasoline-electric vehicles. In a decade, internal-combustion engine vehicles will be disappearing.

Since many “technology” companies regard the automobile industry as lacking in computer, microelectronics and software expertise, the established computer hardware and software companies are either developing AV systems independently or in joint ventures with familiar automotive companies. Alphabet’s Google, Apple, Intel, Microsoft, and others are very active with massive ongoing investments. Recently, NVIDIA Corp. has been releasing AI chips specifically for AV applications with impressive early evaluations. Realistically, not all will be successfully adopted but differing AV systems will eventually enter mass production.

General Motors Co. recently acquired the LIDAR technology company Strobe, Inc. As part of the deal, Strobe’s engineering talent joins GM’s Cruise Automation team to define and develop next-generation LIDAR solutions for self-driving vehicles. GM thinks its AV team is complete now.

Lidar (also called LIDAR, LiDAR, and LADAR) originally was a surveying technology that measured distance by illuminating a target with a pulsed laser light and measuring the reflected pulses with a sensor. Differences in laser return times and wavelengths made digital 3D-representations of the target.

LIDAR is said to create higher-resolution images that provide more accurate views of the world than cameras or radar alone. As self-driving technology continues to evolve, LIDAR’s accuracy may play a critical role in its deployment.

“The successful deployment of self-driving vehicles will be highly dependent on the availability of LIDAR sensors,” said Julie Schoenfeld, Founder and CEO, Strobe, Inc.

GM is planning to test its vehicles in “fully autonomous mode” in New York state in early 2018, according to New York Governor Andrew Cuomo. However, the planned testing by GM and its self-driving unit, Cruise Automation, will initially be a Level 4 autonomous vehicle.

A level 3 car still needs a steering wheel and a driver who can take over if the car encounters a problem, while level 4 promises driverless features in dedicated lanes. A level 5 vehicle is capable of navigating roads without any driver input and in its purest form would have no steering wheel or brake pedal.

General Motors’ Cruise Automation LIDAR on a Chevrolet Bolt EV (electric vehicle)

 

Caveats

The many AV systems use very sophisticated sensors to evaluate the immediate surroundings that vehicle owners, or automobile mechanics, may not fully understand. Looking at AV going forward, the mainstream vacuum-dependent deposition and etching/cleaning processes will likely need refinements and evolution. Unlike a PC or smartphone problem where failure may be annoying, if a driverless vehicle goes awry because of a microprocessor or sensor component manufacturing defect, the consequences can be tragic and very expensive.

Those using the ICs, MEMS and other micro devices for AI and AV have at least two options to minimize liability, build in considerable redundancy or use fail-safe components and systems. With IC manufacturing, although each device on a wafer may be very similar, they are not absolutely identical. That means that the patterning lithography must be nearly perfect and each layer of material deposited must be incredibly uniform. What was acceptable yesterday may not be good enough going forward.

AI, in the most basic terms, suggests that its (dedicated) computer is cognizant of the specified environment (using sensors) and performs tasks within its defined decision-making capabilities (using actuators). In a vehicle, AV control is tied into an already extremely complex electrical/electronic system with its own central computer and with dedicated embedded computers within specific components—a complex network.

“Artificial intelligence (AI, also machine intelligence, MI) is apparently intelligent behavior by machines, rather than the natural intelligence (NI) of humans and other animals. In computer science AI research is defined as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving” per Wikipedia.

“Intelligent agents are often described schematically as an abstract functional system similar to a computer program. For this reason, intelligent agents are sometimes called abstract intelligent agents (AIA) to distinguish them from their real world implementations as computer systems, biological systems, or organizations.”

Simple reflex agent, Utkarshraj Atmaram, Wikipedia

 

A Broader Perspective of AI and AV

Microelectronics technology is invading many products and usually are interconnected via the Internet. If one looks at a self-driving car, i.e., will the passengers be viewing live TV?

Recently, Gartner, Inc., the Stamford, CT technology research company, highlighted the top strategic technology trends that will impact most organizations in 2018. Creating systems that learn, adapt and potentially act autonomously will be a major battleground for technology vendors through at least 2020. The ability to use AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience will drive the payoff for digital initiatives through 2025.

“Currently, the use of autonomous vehicles in controlled settings (for example, in farming and mining) is a rapidly growing area of intelligent things. We are likely to see examples of autonomous vehicles on limited, well-defined and controlled roadways by 2022, but general use of autonomous cars will likely require a person in the driver’s seat in case the technology should unexpectedly fail,” said David Cearley, vice president and Gartner Fellow in his Top 10 Strategic Technology Trends for 2018 presentation. “For at least the next five years, we expect that semiautonomous scenarios requiring a driver will dominate. During this time, manufacturers will test the technology more rigorously, and the nontechnology issues such as regulations, legal issues and cultural acceptance will be addressed.”

“AI techniques are evolving rapidly and organizations will need to invest significantly in skills, processes and tools to successfully exploit these techniques and build AI-enhanced systems,” added Mr. Cearley. “Investment areas can include data preparation, integration, algorithm and training methodology selection, and model creation. Multiple constituencies including data scientists, developers and business process owners will need to work together.”

The first three strategic technology trends explore how artificial intelligence (AI) and machine learning are seeping into virtually everything and represent a major battleground for technology providers over the next five years. The next four trends focus on blending the digital and physical worlds to create an immersive, digitally enhanced environment. The last three refer to exploiting connections between an expanding set of people and businesses, as well as devices, content and services to deliver digital business outcomes.

Cearley adds, “Intelligent things are physical things that go beyond the execution of rigid programming models to exploit AI to deliver advanced behaviors and interact more naturally with their surroundings and with people. AI is driving advances for new intelligent things (such as autonomous vehicles, robots and drones) and delivering enhanced capability to many existing things (such as Internet of Things [IoT] connected consumer and industrial systems).”

Next time: Examining widespread ADS/ADAS (advanced driver assistance systems) efforts worldwide continues.

Observations & Opportunities: AI & Autonomous Vehicles—Awesome Implications

Simply put, the business and technology implications for autonomous vehicles, or Automated Driving Systems (ADSs) per the U.S. Department of Transportation (DoT), for those making or using vacuum equipment and related materials, are enormous. These vehicles will require powerful and reliable ICs plus sophisticated MEMS sensors and actuators—all made with vacuum-centric technology to varying degrees.

Will ADSs be widely accepted and their use be on a massive scale? No one seems to know when it will happen on a large scale but some huge global companies are betting that it will be soon. The driving public may be skeptical of Autonomous Vehicles (AVs) at the moment but that was true with personal computers and smartphones too. Before the iPhone just a little over a decade ago, how many of us would have thought that today’s reliance on smartphones, laptops and other mobile devices would be so pervasive, even for TV experiences, on the smaller screens?

Many huge manufacturing and high-tech firms using contract manufacturers to build their products are involved that are not part the automobile industry itself. Insurance companies would really like ADS as would cities where gridlock traffic and accidents are a constant problem as are driver distractions. Adding some control to vehicles could help reduce accidents and traffic jams.

With President Trump proclaiming that massive infrastructure investment is needed, as have several previous presidents, it might actually happen this time. If roads are going to be rebuilt for the 21st Century, then we need smarter roads, bridges, etc. —computational devices, sensors, actuators, precise positioning information, and other technologies to make ADS vehicles safe and reliable. ADSs absolutely rely upon Artificial Intelligence (AI) and that is computational intensive. The value of electrical/electronics content in new vehicles now exceeds the mechanical component costs.

Autonomous Vehicles Defined
So what exactly is an autonomous vehicle or ADS?

“An autonomous car (also known as a driverless car, auto, self-driving car, robotic car) and Unmanned Ground Vehicle is a vehicle that is capable of sensing its environment and navigating without human input. Many such systems are evolving, but as of 2017 no cars permitted on public roads were fully autonomous. They all require a human at the wheel who must be ready to take control at any time.” per Wikipedia [https://en.wikipedia.org/wiki/Autonomous_car]. Intel Corp. uses automotive Advanced Driver Assistance Systems (ADAS) terminology.

Caption: Courtesy of Intel Corporation

 

Why ADS/ADAS?
With so many distracted drivers making your commute or everyday driving trips hazardous, perhaps ADSs does offer some compelling advantages worth consideration.

The U.S. DoT recently issued their “Automated Driving Systems (ADSs)” report. In it, Secretary Elaine L. Chao says, “Today, our country is on the verge of one of the most exciting and important innovations in transportation history— the development of Automated Driving Systems (ADSs), commonly referred to as automated or self-driving vehicles.

“The future of this new technology is so full of promise. It’s a future where vehicles increasingly help drivers avoid crashes. It’s a future where the time spent commuting is dramatically reduced, and where millions more—including the elderly and people with disabilities–gain access to the freedom of the open road. And, especially important, it’s a future where highway fatalities and injuries are significantly reduced.

“Since the Department of Transportation was established in 1966, there have been more than 2.2 million motor- vehicle-related fatalities in the United States. In addition, after decades of decline, motor vehicle fatalities spiked by more than 7.2 percent in 2015, the largest single-year increase since 1966. The major factor in 94 percent of all fatal crashes is human error. So ADSs have the potential to significantly reduce highway fatalities by addressing the root cause of these tragic crashes.”

A report from AAA reveals that the majority of U.S. drivers seek autonomous technologies in their next vehicle, but they continue to fear the fully self-driving car, so far. Despite the prospect that autonomous vehicles will be safer, more efficient and more convenient than their human-driven counterparts, three-quarters of U.S. drivers report feeling afraid to ride in a self-driving car, and only 10 percent report that they’d actually feel safer sharing the roads with driverless vehicles. As automakers press forward in the development of autonomous vehicles, AAA urges the gradual, safe introduction of these technologies to ensure that American drivers are informed, prepared and comfortable with this shift in mobility. [http://newsroom.aaa.com/2017/03/americans-feel-unsafe-sharing-road-fully-self-driving-cars/]

From a practical perspective, it will take a while to improve infrastructure that can accommodate ADSs and for the inevitable tweaking of the many ADS systems.

Tech Giants Pushing ADS Technology

For those exploring ADS technology’s opportunities, consider SAE International’s efforts to date. It is a global association of more than 128,000 engineers and related technical experts in the aerospace, automotive and commercial-vehicle industries [https://www.sae.org/misc/pdfs/automated_driving.pdf]. It’s worth reading their description of then levels of Driving Automation to better understand the challenges involved. Although it certainly addresses vehicles, it also has aerospace implications. Military drones today, and some missiles, use AI to perform their assigned tasks. Decades ago, fully automated aircraft with automated air traffic control (ATC) was demonstrated.

A few weeks ago, Brian Krzanich, the chief executive officer of Intel Corp., announced the fact that Waymo and Intel were collaborating on self-driving car technology.

Autonomous Driving will End Human Driving Errors and Lead to Safer Roads for Everyone.
Per Mr. Krzanich, “One of the big promises of artificial intelligence (AI) is our driverless future. Nearly 1.3 million people die in road crashes worldwide every year – an average 3,287 deaths a day1. Nearly 90 percent of those collisions are caused by human error. Self-driving technology can help prevent these errors by giving autonomous vehicles the capacity to learn from the collective experience of millions of cars – avoiding the mistakes of others and creating a safer driving environment.

“Given the pace at which autonomous driving is coming to life, I fully expect my children’s children will never have to drive a car. That’s an astounding thought: Something almost 90 percent of Americans do every day will end within a generation. With so much life-saving potential, it’s a rapid transformation that Intel is excited to be at the forefront of along with other industry leaders like Waymo.

“Waymo’s newest vehicles, the self-driving Chrysler Pacifica hybrid minivans, feature Intel-based technologies for sensor processing, general compute and connectivity, enabling real-time decisions for full autonomy in city conditions. As Waymo’s self-driving technology becomes smarter and more capable, its high-performance hardware and software will require even more powerful and efficient compute. By working closely with Waymo, Intel can offer Waymo’s fleet of vehicles the advanced processing power required for level 4 and 5 autonomy.

“With 3 million miles of real-world driving, Waymo cars with Intel technology inside have already processed more self-driving car miles than any other autonomous fleet on U.S. roads. Intel’s collaboration with Waymo ensures Intel will continue its leading role in helping realize the promise of autonomous driving and a safer, collision-free future,” added Krzanich

Consumer Adoption of ADS Driving & On-Demand Car Services
The Gartner Consumer Trends in Automotive online survey, conducted from April 2017 through May 2017, polled 1,519 people in the U.S. and Germany, found that 55 percent of respondents will not consider riding in a fully autonomous vehicle, while 71 percent may consider riding in a partially autonomous vehicle. Gartner, Inc. is a global research and advisory company [http://www.gartner.com/technology/home.jsp].

The Gartner survey say that “…concerns around technology failures and security are key reasons why many consumers are cautious about fully autonomous vehicles. Fear of autonomous vehicles getting confused by unexpected situations, safety concerns around equipment and system failures and vehicle and system security are top concerns around using fully autonomous vehicles,” explains Mike Ramsey, research director at Gartner. Survey respondents agreed that fully autonomous vehicles do offer many advantages, including improved fuel economy and a reduced number and severity of crashes. Additional benefits they identified include were having a safe transportation option when drivers are tired and using travel time for entertainment and work.

The survey also found that consumers who currently embrace on-demand car services are more likely to ride in and purchase partially and fully autonomous vehicles. “This signifies that these more evolved users of transportation methods are more open toward the concept of autonomous cars,” said Mr. Ramsey.

Next time: More on widespread ADS/ADAS (advanced driver assistance systems) efforts worldwide.