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.
