Tuesday, October 4, 2016

Autonomous Cars Part 1-- And Now for Something Completely Different: The Autonomous Accident

Kaivan Karimi
SVP of Strategy and Business Development
BlackBerry Technology Solutions (BTS)

A few weeks ago a self-driving Tesla Model S in Autopilot mode crashed into a large semi-trailer in Williston Florida This is pretty much what lawyers call a case of first impression, and rightfully so.  This unprecedented event brought up a bunch of questions, and it is clear that we are now on the cusp of the autonomous (i.e. robot-driven) automotive future.  With that comes a completely different mix of risks, liabilities, safety concerns, responsibilities, ownership models, insurance platforms, and regulatory oversight. 

Car crashes are, and should be, a big deal. They are the number one reason for death among young people and number five overall, claiming over 32,000 American lives each year. Some news outlets have questioned the sanity of allowing driverless cars on the road all together. Fairly or unfairly, the whole notion of driverless cars is experiencing knee-jerk reactions. It is easy to see why the first known death caused by a self-driving car in the history has focused everyone’s attention on autonomous vehicles.

This incident is much like how Bridget Driscoll made the history in 1896 by being the first pedestrian being struck and killed by a gas-powered car (at a top speed of four miles per hour).   Thanks to the sensationalism of the press, the Florida crash got much more coverage in the news cycles than the more positive story about the Missouri man who used his Tesla Model X in autopilot mode to get to the hospital when he suffered from a debilitating blood clot on the highway.  Tesla Autopilot saved his life, and that is real (and good) news.  Nothing like that has happened before—a robot saving a man’s life.  Amazing.

These issues have made so much headlines that it made it to the white house, and president Obama wrote an op-ed mostly in support of the technology.  President Obama wrote that safer, more accessible driving, and less congested, less polluted roads are what harnessing technology for good can look like referring to self-driving car technologies. He also said that we have to get it right. Americans deserve to know they’ll be safe today even as we develop and deploy the technologies of tomorrow.
The accident has given rise to discussions about what types of sensors should have been in place to avoid that accident.  Also, as you would expect, there is a lot of questioning by legislators about the need for such technology, and how it can be regulated. A proper outcome of the crash has been awareness that autonomous driving is a public safety issue.  This is multi-faceted and includes technology (i.e. hardware, software, and architecture), economics, policy implementation, liability, and oversight factors.

I started following the development of autonomous vehicles when I first heard about Google’s so-called “self-driving car” project back in 2009. While I knew about DARPA’s initiative around this idea in mid 2000s, a commercial entity like Google picking up the project lends real credibility. Back in the 2010-2011 timeframe, my team and I were working on Freescale’s MCU strategies, and through that I got to understand the role of Active Driver Assistant System (ADAS) and the numerous architectural considerations and technologies needed to make autonomous driving a reality. 

Now at BlackBerry, I am working with our QNX software team on ADAS development. The QNX perspective, of course, comes from the software side with expertise in instrument clusters, functional safety, hypervisor  infotainment, and telematics. When you add that to  Certicom’s cryptographic security expertise,  and BlackBerry’s Over-the-Air (OTA),  updates for automotive security life cycle management, you have what you need for safety and security of the software-defined autonomous future. The evolution to connected autonomous vehicles is transitioning through different stages that in fact were defined by the U.S. Department of Transportation's National Highway Traffic Safety Administration.
SAE has defined levels as well.  

                                                           Source: NHTSA

Most car OEMs that we are working with have autonomous driving pilot programs in place. That is no surprise.  Even before the Tesla Autopilot accident, it was hard to open a technology magazine or website and not see a mention of self-driving cars and various pilot programs around the world. Cars are becoming cool again due to new technological evolution.   This is similar to how cellphones became cool in the early 2000s when the emergence of 3G made the notion of smartphones real.   Cars are much more than a phone, obviously, and the sky is the limit.  Software, semiconductor, networking, cryptography, sensors, communications, electric/hybrid engine, charging, display, augmented reality, smart highways, retail, and other technologies all converge on the car platform.  These things are quickly redefining the car, the highway, ownership models, insurance, and society itself. 
Some of the items to consider are the forms that vehicles will adopt due to automation, such as autonomous cars,  to  self-driving busses  , self-driving trucks,  and DARPA’s 132-foot long Sea Hunter unmanned Submarine-Hunter Drone .

Hardware + Software

Self-driving vehicles, or self-propelled anything, are based on an intimate relationship between electronics hardware and software to create not only a perceiving, processing, and actuating system, but a system that is safe, secure, and reliable.   While that last part seems obvious, it is not all that easy to accomplish.   Safety, security, and reliability come only from careful design based upon experience—experience that can make hardware and software work seamlessly.

Starting with the hardware, if you look at automotive microprocessors and microcontrollers, you can see that their complexity has skyrocketed to meet real time requirements of active safety elements such as vision processing, sensor fusion, and control algorithms, while still maintaining stringent power budgets.

Advanced driver assistance systems (ADAS) are the backbone of autonomous vehicles, obviously, and that it is based upon multiple application cores and hardware accelerators.   ADAS, software platforms must provide high performance by combining symmetric multiprocessing on application cores with support for built in accelerators such as vision processing engines or graphics processing units (GPUs).   Examples of applications range from four camera surround view systems, to a single camera forward facing collision avoidance system, to a sensor fusion hub.
Of course, the most important aspect of anything automotive is safety.  The old adage of safety first is still valid, and getting even more so as robotic cars start to drive themselves.  Therefore, there has to be real safety know-how at the core of the design and implementation of ADAS.  This is where safety standards compliance comes in.  The QNX Platform for ADAS is a great example of safety-centered software for the autonomous car.   The platform is certified by TÜV Rheinland to ISO 26262 ASIL-D.

More details will be addressed in a future blog, but are presented here to illustrate that software must be compliant with safety standards if it is to be taken seriously.  How safety is achieved by a software architecture is by ensuring that system faults in one area do not affect other areas.   This is accomplished by using a microkernel architecture the operating system (OS) to create isolation of failed components, and allowing them to be restarted dynamically while the rest of the system continues to operate. This type of adaptive partitioning technology safeguards the operation of the safety-critical components by ensuring they are never starved of CPU cycles. With a microkernal approach, traditional OS services can be contained in separate, hardware-protected address spaces in the same manner as applications.

The next blog will focus on the individual subsystems used in an ADAS platform in the connected autonomous car.    In addition, other connected autonomous car technologies will be covered in subsequent blogs, including security, Domain/Area-controller evolution, more about safety, and other technologies needed, plus use-case and financial considerations related to autonomous cars.   The story of the software-defined automotive future is just starting to be written.   For more see the QNX web site.


Kaivan Karimi is the SVP of Strategy and Business Development at BlackBerry Technology Solutions (BTS). His responsibilities include operationalizing growth strategies, product marketing and business development, eco-system enablement, and execution of business priorities. He has been an IoT evangelist since 2010, bringing more than two decades of experience working in cellular, connectivity, networking, sensors, and microcontroller semiconductor markets. Kaivan holds graduate degrees in engineering (MSEE) and business (MBA). Prior to joining BlackBerry, he was the VP and General Manager of Atmel wireless MCUs and IOT business unit.

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