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Welcome... ...to the Q1 2018 issue of Automotive Megatrends Magazine. Enthusiasm and concern abound in any discussion about the evolution of artificial intelligence. From voice-activated virtual assistants playing music on-demand to autonomous cars with decision-making powers that make them better drivers than humans, AI is on its way to a ‘smart’ device near you.
For the auto industry, AI presents a valuable opportunity – and its role in a car is just one aspect of its potential. As our exclusive interview with VW Group’s Chief Information Officer reveals, AI can help in areas such as production forecasting and logistics planning, cyber security, vehicle assembly and even traffic management. As VW’s CIO underlines, AI is a means to an end, not an end in itself. Technology is getting smarter and more intelligent – those who embrace and incorporate AI will find themselves at an advantage. Those who ignore it will have their intelligence questioned.
Martin Kahl, Editor www.automotivemegatrends.com
Welcome
Automotive Megatrends Magazine ISSN: 2053 776X Publisher: Automotive Megatrends Ltd 1-3 Washington Buildings Stanwell Road, Penarth CF64 2AD, UK www.automotivemegatrends.com T: +44 (0) 2920 707 021 support@automotivemegatrends.com Registered number: 08000516 VAT number: GB 171 5423 23 Managing Director: Gareth Davies Editor: Martin Kahl Contributors: Nick Gill Megan Lampinen Martin Kahl Freddie Holmes Xavier Boucherat Venkat Sumantran Charles Fine David Gonsalvez Michael Nash Production: Anmol Mothy
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Contents
There’s a growing role for AI in future mobility
14
22
18 24
How AI will pass its driving test
Get ready for the car that talks back
Low TCO high on the agenda at HD Truck Pune
Autonomous vehicles need lightweight materials
8
Automotive Megatrends Magazine
28
Contents
30 40
34
Could LiDAR be the key to five nines reliability?
48
Absolutely indispensable: future of AVs hinges on AI
53
An inside-out approach to preventing vehicle hacks
Training, not tech, is slowing AV development
60
Digitalisation essential for growth in India’s auto industry
HD mapping ‘takes ADAS to the next level’, says TomTom
Clear vision needed to make AVs a reality
India’s connected car market - a wide open goal
VW says OK to AI
Zenuity CEO on the auto industry's 'fantastic future'
www.automotivemegatrends.com
50 56 63 9
SAFE AND SECURE AUTOMOTIVE SOFTWARE
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THE H FU UTURE OF DRIVING NOW W
automotive.tom mtom.com
Informing the decisions of automotive industry stakeholders since 1992. http://automotiveworld.com
How AI will pass its driving test
Images courtesy of Capgemini
AI and the auto industry
Nick Gill, Chairman of Global Automotive Sector at Capgemini, considers the benefits of artificial intelligence in cars and across the automotive industry rtificial intelligence is learning
A
fundamentally alter the way OEMs do
years it will take over from
road use across the world.
wheel. However, AI in the automotive
Autonomous vehicles
merely passing its driving test. This
In thinking about AI in the automotive
AI
be ignored: autonomous vehicles. As
to drive. Within the next 20
humans as the main entity behind the
industry is more than the technology
piece explores not only the impact of
14
on
driving,
but
how
it
will
business and the laws surrounding
industry, there is one trend that can’t
Automotive Megatrends Magazine
“
AI and the auto industry
While AI learns to drive, the need for humans to pass their tests will diminish. To the joy of teenagers around the world, there will be no need to take a rigorous driving test with the availability of autonomous cars
noted by Tim Cook, the Chief Executive
technology is measured in five levels,
cars. Instead of having to negotiate
vehicles is the mother of all AI projects.
without a steering wheel. Some
users will be freed up to spend their
of Apple, developing autonomous Driverless cars, as they are commonly
“
known, will become commonplace on our roads within the next ten to 15 years. Dozens of automotive and technology
companies
have
cars
currently in development and, while most public debate has focused on
Google and Tesla’s efforts, traditional manufacturers including Audi, BMW,
Ford, Hyundai and GM have all entered
where fundamentally L5 is a car vehicles, like the new Audi A8, claim
to have reached L3 now and we can expect to see L4 cars on the road
within the next few years. However, the technology becoming available will only facilitate the move to autonomous
vehicles,
not
immediately make every car on the
road driverless. The willingness of humans to step into a driverless car
The shift to AI represents a transformative period in the car industry
the autonomous vehicle race. With all
for the first time, coupled with
the road first, at least US$80bn has
the adoption cycle. As with every
these firms trying to get their cars on
been ploughed into research in the past three years.
However, this shift to autonomous
vehicles will not happen overnight. There will be a lengthy and organic
infrequent car purchases will slow technology,
there
will
be
early
adopters, but most consumers will
wait until their car needs replacing
before assessing whether or not to go driverless.
evolution from human-driven cars to
With AI set to change the automotive
The development of autonomous car
changes in the way humans use their
those without any human controls.
www.automotivemegatrends.com
industry, there will also be great
the roads and find parking spots,
travelling time in different ways. For example, passengers could work on
their laptops, catch up with family
and friends over the phone, read a
book or watch a film - the possibilities are endless. We might even start to
see travel time counting towards
working hours, as employees are able to do tasks on the move and get to
the office later. However, as with everything,
there
will
also
be
mitigating factors the automotive industry will need to consider. For
instance, the impact on the insurance industry and the ripple effect to other industries, including hotels.
Manufacturers’ business models
It is not just cars that will be
transformed by AI; manufacturers’
processes, sales and business models will change too. Unlike industries which
are faltering from the pressures of tech
giants and start-ups taking market share because of AI-related innovation, automotive
incumbents
retain
a
distinct advantage. The main reason for
this is the automotive industry’s high cost barrier to entry; any new entrant would have to invest significant
capital in large-scale research and
15
“
AI and the auto industry
While humans get used to the concept of not having to sit behind a steering wheel again, car manufacturers have a great opportunity to grow their businesses on the back of this new technology
manufacturing facilities before being
and machine learning is able to use to
Manufacturers are sitting on a huge
then, producing vehicles at scale
to
already on the road, but are unable to
able to produce their first car. And even
remains a challenge: Tesla, for example, has only managed to produce a very
limited number of cars each quarter up to now.
In manufacturing plants today, there are thousands of robots and cobots (collaborative robots), all with functions
important to the car making process. Each of these collects data which AI
predict failures and enable engineers pre-empt
downtime,
which
improves uptime and productivity. The same is true of when driverless cars go
on the road. Autonomous vehicles also
collect immense amounts of data, enabling engineers to advise when cars are likely to break down and fix faults before they occur.
AI will also enhance manufacturers’ sales
and
marketing
processes.
amount of information from cars
harness it for sales purposes with
insights buried amongst mountains of data. AI will change this. For example,
with the ability to sift through the huge amount of data that their cars produce,
AI will enable marketers to identify
which non-vital functions are most useful to owners and target their campaigns as such. Furthermore, AI will
be able to distinguish the most valuable
Images courtesy of Capgemini
Five senses of AI
16
Automotive Megatrends Magazine
“
AI and the auto industry
Manufacturers are sitting on a huge amount of information from cars already on the road, but are unable to harness it for sales purposes with insights buried amongst mountains of data. AI will change this
sales leads based on past behaviour and propensity to buy, meaning traders can
direct
their
efforts
towards
customers who are most likely to make a purchase.
Advances in AI technology will also spell
change in the way the automotive industry is regulated. Driverless cars
will require legislation updates in order to come onto roads, and across areas
such as driving licences, insurance and the rules of the road. For example,
while adoption is still in progress,
driverless car lanes will be necessary to ensure the safety of all vehicles. There
will need to be rules put in place driverless
vehicles
huge regulatory debate within the
be insured for any injury caused to
become omnipresent.
person who enters a vehicle needs to
themselves while in an autonomous
and
junctions- no one wants to be stuck behind large trucks at the best of times,
but a convoy of eight driverless trucks
could block junctions and stop cars
coming years as autonomous vehicles
car. In addition, premiums should go
The
roads safer and less unpredictable.
industry. While humans get used to the
down as autonomous cars make
Regulation and legislation
around
“
‘passenger insurance’, whereby every
shift
to
AI
represents
a
transformative period in the car
Within the next 20 years it will take over from humans as the main entity behind the wheel. However, AI in the automotive industry is more than the technology merely passing its driving test
from leaving roads at the right point.
Finally, while AI learns to drive, the
concept of not having to sit behind a
be taken by regulators on how AI
will diminish. To the joy of teenagers
manufacturers
More seriously, tough decisions need to
should be programmed in the case of
traffic incidents; when collision cannot be avoided, which car (or person) should come off worse?
Insurance policies, too, will have to
change. While car insurance is
mandatory now, this could change to
www.automotivemegatrends.com
need for humans to pass their tests
around the world, there will be no need to take a rigorous driving test
with the availability of autonomous cars. However, that’s not to say there
won’t be a requirement to have some kind of instruction on how to use
driverless cars and what to do in the case of emergencies. This will be a
steering
wheel
have
again, a
car
great
opportunity to grow their businesses on the back of this new technology. From
providing
the
autonomous
vehicles themselves to improving
manufacturing processes and working with governments to update legislation,
the manufacturing industry is entering a new era of opportunity.
17
In-car virtual assistants
Get ready for the car that talks back OEMs see value in equipping their cars with virtual assistants; will consumers see the benefit, or become frustrated? By Megan Lampinen ood help is hard to find, but it's
G
parking, to playing a certain type of
requirements," explains Fatima Vital,
of virtual assistants. Already
strong interest in help with in-car
at Nuance Communications. Nuance
Alexa and Microsoft’s Cortana have
effectiveness of the system and its
getting easier with the arrival
prevalent on mobile devices, in smart homes and website chat options,
helpful bots like Apple’s Siri, Amazon’s been assisting with various consumer needs. They can adjust home central
heating, play music, provide answers to
problems reported over a hotline or
music. Studies have flagged particularly
diagnostics, such as reporting issues
and helping drivers understand new car features. But with all of these, the
impact on safety can only be realised if it is well designed and optimised for use in the car.
assist in selecting just the right product.
"With an increasing number of features
making their way into vehicle cabins
automotive assistant can proactively
With a little adjustment, they are now
around the world.
There's plenty to help with in the car, from driving-related tasks like finding
the optimal route with the optimal
18
and
functions
in
the
car,
the
Senior Director, Marketing Automotive
has emerged as one of the pioneers of voice
recognition
technology
in
vehicles. Its connected car platform,
Dragon Drive, is embedded within a
and
vehicle's
infotainment
combines
natural
system
language
understanding (NLU) and text-tospeech functionality.
Check list
help the driver explore car functions
"Consumers expect their automotive
taking some of the cognitive load from
preferences and to be aware of their
and solve driving-related tasks, thus the driver. However, this presumes that the
assistant
meets
several
assistants to know them and their
respective context and situation," states
Vital.
For
instance,
the
Automotive Megatrends Magazine
“
In-car virtual assistants
With an increasing number of features and functions in the car, the automotive assistant can proactively help the driver explore car functions and solve driving-related tasks, thus taking some of the cognitive load from the driver. However, this presumes that the assistant meets several requirements - Fatima Vital, Nuance Communications
assistant must distinguish between
the car, etc. "This information has to be
work with suppliers like Nuance to
deliver personalised results. Nuance,
automotive assistant and can play a
that can intelligently route to other
driver and passenger in order to and
many
others,
believe
the
most convenient method for this is voice biometrics.
part of the contextual reasoning of the critical
role
in
reducing
driver
distraction and increasing road safety," emphasises Vital.
Branding
artificial intelligence (AI) is pivotal in
New technology's trickledown effect
must be seamless, easy and non-
started out in the premium segment
this sense. Access to these systems
distracting. NLU goes a long way in
reducing the cognitive load on the driver. For example, the driver could request, 'Find a good parking spot
near my appointment’ and the system would interpret that as an instruction for a covered parking location that
accepts credit cards near a specific office address.
Context is everything. An assistant must consider all relevant information
before it can provide the best response
to the driver. For example, when looking for the parking spot, relevant
information includes the time, the duration of the appointment, the weather, supported payment methods,
opening hours of the car park, size of
www.automotivemegatrends.com
but they are proliferating across all the
segments now, in the form of both
OEM-controlled automotive assistants and access to third party assistants. Many car brands are keen to promote own
assistants,
branded
as
Alongside the likes of Nuance, Apple considerable interest from start-ups.
means these systems may have
their
virtual assistants whenever needed.
and Google, the segment is attracting
Notably, the assistant has to learn user preferences from past behaviour, and
create their own branded assistants
they
automotive
attach
Berlin-based German Autolabs is
combining advances in voice and gesture control technology with AI to develop its digital assistant for drivers. The
company
interoperable,
has
promised
scalable
an
software
platform for cognitive assistance with a retrofit hardware device to make an offering that anyone can access.
great
Start-up iNAGO is also building what
"These car brands want to be in
conversational assistant for automotive
importance to the branding strategy.
control of the holistic user experience
in the car, tightly integrating their brand and design concepts," observes
Vital. "We are also seeing that many of the largest brands both in the premium as well as in the mass market
segments are not willing to give up control over the vehicle experience
and their brand to brought-in third party assistants." In these cases, they
it refers to as a next-generation
applications. Its Intelligent Driver Assistant is designed to provide a safe way for drivers to access connected content and services in the car, as well as stay informed
about their car and control car
features. Other players working on these systems and their supporting technology include Baidu, Maluba, Sensory and VocalZoom.
19
In-car virtual assistants
Towards autonomy
very
digital
Sullivan's Automotive & Transportation
In-car assistants could play a pivotal
status of a safe space and people act
quality of today's digital assistants,
role as the industry moves towards
greater automation. The transition period from today’s cars to fully autonomous vehicles will force driver
and car to cooperate. "Conversational intelligent automotive assistants will
play a crucial role in this," predicts Vital. They could also help with establishing trust in these systems, one of the biggest
potential
challenges
to
acceptance. A recent AAA study in the
US suggested that less than one-fifth of drivers would trust an autonomous
vehicle. Studies from other regions have flagged similar hesitancy.
Nuance has been working with DFKI on this area, looking into the role of
automotive assistants in the transfer of
control
self-driving
between vehicle
driver
and
technology.
Researchers found that the majority
“
of participants preferred integrated, multimodal user interfaces leveraging voice, touch and visual cues.
However, there could be unintended consequences from a proliferation of
the technology. With a focus on personalised service and continuous AI refinements, the digital assistant could
quickly
become
a
companion. Today, the car has the
differently because of that. They sing loudly or they swear at other drivers,
neither of which they would likely do if there were other companions. "If the car starts to listen to you and talk back,
that changes," observes Geraint Jones, Business Development Director at
global branding company Siegel+Gale.
"It alters the relationship between the
space and the driver. It becomes less of a personal space and it becomes more of a public space."
Quality challenges While the potential applications are clearly exciting, technical challenges
could prove stubborn. "The challenge for the industry will be working out the
practice, also has concerns about the noting:
"Trying
to
bring
that
functionality inside the car becomes a difficult task." One of the biggest challenges centres around the systems'
gradual learning curve - the more it is
used, the more accurate it becomes.
But what happens if people don't use it
enough? "Until and unless you feed inputs into that system, it will never learn," Jayaraman tells Megatrends.
There needs to be a willingness to use it often, he continues. “People need to
be aware exactly how it is going to
learn. A Google Assistant is not a 100%
accurate product today, and it's not accurate because people are not
making it accurate. They need to put in that effort to make it more effective."
quality issues, so that people don't
Outside the car
Guest,
Product
Automotive assistants aren't limited to
Access. Even today, Amazon Alexa can
companies are harnessing AI-backed
become frustrated," warns Robert Vice
President,
Management at connectivity specialist struggle to understand commands with
just the minor echo in a home kitchen. Road noise in a vehicle cabin is even harder to deal with.
Krishna Jayaraman, Program Manager - Connectivity & Telematics in Frost &
the inside of the vehicle. Many
assistants to help with customer service. "Virtual assistants are set to
completely change the way that consumers engage with organisations,"
predicts Nuance's Seb Reeve, Director, Strategic Solutions, EMEA. "A big
bugbear of most customers is the
Consumers expect their automotive assistants to know them and their preferences and to be aware of their respective context and situation - Fatima Vital, Nuance Communications
20
Automotive Megatrends Magazine
In-car virtual assistants At CES 2018, Toyota announced that Amazon Alexa will be available on select Toyota and Lexus models with the Toyota Entune 3.0 App Suite and Lexus Enform App Suite 2.0 in 2018. The roll-out will be widened to other models in 2019
amount of time they have to wait to
serving
questions
Should you require assistants…
speak to a human agent – for simple and
queries.
Virtual
assistants are proving themselves a fantastic
investment
for
many
organisations to deal with simpler
tasks, freeing up the phone lines for human agents to more quickly respond
to more complex or emotionally resonant tasks."
customers
previously possible.”
better
than
Digital virtual assistants dominated CES 2018, with voice activation and AI incorporated into the majority of the future technology on display.
The trend is playing out across
Harman demonstrated its Digital
telecommunications to government
other things, Samsung’s relatively new
numerous industries, from banking to
agencies. In the automotive industry,
Kia recently launched the chatbot Kian via its Facebook Messenger page. Harnessing tools that understand and
Cockpit, which features, amongst
Bixby
virtual
assistant.
Nuance
unveiled a new “cognitive arbitrator” that combines conversational and
cognitive AI capabilities to connect disparate
virtual
assistants
and
related functions and services; this
would enable consumers to have different services in the home, on
mobile devices and in their cars, and move seamlessly between them. And Nvidia showcased new technology
that OEMs can use to develop highly advanced AI virtual assistants, which can
use
everything
recognition,
mood
from
analysis
facial
and
distraction monitoring to location-
based individualised content delivery.
can respond to natural language, Kian
Even at CES, however, the fallibility of
specifications, pricing, financing, special
marketing discovered when the
can answer questions about model offers, etc. Notably, he learns as he
goes along. “As more shoppers use
the technology was clear, as LG's VP of company’s
new
CHLOi
home
assistant robot failed during an on-
the system, it learns to anticipate
stage demo. Clearly, the technology
answers and gets smarter over time,”
control of a vehicle to use virtual
questions, provides more specific explained
Martin
Schmitt,
Chief
Executive and Co-Founder of CarLabs, the specialist that worked with Kia in
developing the technology. “Having access to that level of shopper data is a
powerful tool for understanding and
www.automotivemegatrends.com
exists to enable a human driver in assistants to control infotainment and
communication. However, it will be some time before a human can reliably
converse
with
a
digital
assistant in control of a vehicle – just ask CHLOi.
21
HD Truck Pune
Low TCO high on the agenda at HD Truck Pune The idea of a Goods and Services Tax hung over India’s truck industry for more than a decade; now it’s here, and at the heart of road freight stakeholders’ long-term strategies. But fleets won’t benefit from the new tax regime without trucks that deliver low total cost of ownership. GST, TCO… six letters that shaped the debate at HD Truck Pune, a one-day conference organised by Automotive Megatrends. Martin Kahl identified 5 big themes at the event HEAvy TRuCKS GETTING HEAvIER Larger trucks running longer distances
expectation that road freight in India
shifting greater loads further and more
heavyweight vehicles for long-haul
can significantly increase efficiency, quickly than fleets of smaller vehicles. With GST comes the opportunity to run
bigger, longer, heavier and more powerful
22
trucks.
There’s
an
will transition to greater use of routes, said Vinay Raghunath, Partner
Automotive Practice at EY, “with low payload
vehicles
for
last
connectivity at the other end.”
mile
Automotive Megatrends Magazine
HD Truck Pune
LOw TCO HIGH ON THE AGENDA
In trucking, low cost doesn’t mean low
going
cheap doesn’t mean cheerful. What’s
has always been,” commented Asia
total cost of ownership (TCO), and
needed is an Indian trucking culture that develops and demands affordable
over cheap. “I don’t think technology is
to
change
the
industry
drastically - it will be economics, as it Motor
Works
President
A.
Ramasubramanian. “It’s nice if we can
launch vehicles ahead of their time,
CONNECTED TRuCK MARKET - A wIDE OPEN GOAL
India’s connected truck market is wide
Most Indian fleets still use the most
discussion featuring GM, KPIT and
tracking. Meanwhile, mature markets
open, was the verdict of a panel Numadic. Once fleets understand the upside of telematics, the potential for
India’s trucking industry is vast, with benefits for all stakeholders – and, of course, consumers.
COwL TRuCKS - REALLy?
basic of connected services: vehicle
but if we want them to sell, it has to be profitable for the customer.”
Technologies that boost efficiency and
reduce TCO are exactly what the fleet buyers want.
capabilities from a business value perspective,” said EY’s Raghunath.
are exploring how to benefit from new
“There’s a huge business opportunity,”
and blockchain. The truck sector needs
matter of how quickly we can capture
technologies like autonomous driving “to figure out how to upscale … and understand
the
implications
of
said KPIT’s Sourabh Jha, “and it’s just a that with telematics and connected technologies.”
The complexity of India’s truck industry
keep costs low by buying cowl trucks.
cheap,
continued existence of cowl trucks.
but also a lucrative line of business for
performance and safety. The Indian
is
brilliantly
exemplified
by
the
While some in the industry are exploring
how to catch up with Europe, North America and Japan, others still seek to
Astonishingly, cowls are not only legal, the same OEMs that would benefit from selling higher value trucks. Cowls – more
or less unique to the Indian market – are
but
compromises
the
list
includes
of
no-frills
comfort,
government acted swiftly on certain
banknotes – is it prepared to make a similar move to kill off the cowls?
DRIvERLESS TRuCKS - PART OF THE FuTuRE, wAy OFF IN THE FuTuRE There’s no doubting that autonomous
would
major
AMW’s Ramasubramanian wants to
long way off, says Joerg Mommertz,
development of an appropriate legal
800,000 units. But in a market already
trucking is coming to India - but it’s a Chairman and MD of MAN Trucks
India. Driverless trucks would solve the country’s driver shortage, but it
www.automotivemegatrends.com
also
infrastructure
require
overhaul,
a
and
the
framework – three issues not unique
to India, but certainly much harder to overcome than in other markets.
see the Indian truck market grow to short of drivers, finding over 800,000 new drivers looks like an impossibility. But if they were driverless trucks…
23
Images courtesy of Covestro
Lightweight materials
Autonomous vehicles need lightweight materials In a world of autonomous vehicles, composite materials may replace heavy metals as crash safety requirements fall, and surface durability needs rise. By Freddie Holmes
T
he debate is open as to when
and where autonomous cars will roam city streets, but
suppliers
are
eyeing
new
opportunities to shake up the way in
which these vehicles are made. Tier 1
polymers expert Covestro believes
that as the risk of a crash occurring
24
falls, so too will the requirement for
on how material selection is likely to
protect
automation increases.
metal structures that are designed to occupants
velocity collisions.
during
high
Speaking in Shanghai at Covestro’s
Chinese
R&D
headquarters,
a
number of experts shared their views
diverge from the norm as vehicle Indeed,
Bill
Russo,
an
ex-Vice
President at Chrysler and current
Chief Executive of business advisory ďŹ rm Automobility, believes that OEMs
Automotive Megatrends Magazine
“
Lightweight materials
Having just one autonomous vehicle on the road is not sufficient in order to transition away from today’s high strength materials. But if every vehicle is autonomous, then it is possible
may no longer need to meet the crash
potential for high-speed collisions still
crash on an Autobahn when designing
of
requirements of a 200kph (125mph)
cars for inner city travel. “For urban
mobility, cars are over engineered,” he remarked at the event. Kevin
Shen,
President
of
CHJ
Automotive – a Chinese start-up that
aims to build its own ride-share cars
and operate as an ‘EV mobility
rife. As Holly Lei, Senior Vice President Commercial
Operations,
PCS
Singapore. Japan's Prime Minister has
just one autonomous vehicle on the
fleets to operate during the country’s
at Covestro, pointed out: “Having
Summer Olympics in 2020. CHJ
strength materials. But if every
autonomous shared car fleet will be
vehicle is autonomous, then it is
possible, and I believe this trend will
in urban areas, you need the right tool
Asian markets have become a popular
That being said, experts recognise
that substituting today’s high strength
stated intentions for autonomous
road is not sufficient in order to
transition away from today’s high
eventually come.”
for the use case.”
company to operate a driverless taxi
fleet as part of a pilot programme in
(Polycarbonate Plastics), APAC China
provider’ – agreed, suggesting that
“you don’t need large high speed cars
start-up NuTonomy became the first
Automotive’s Shen predicts that an
operating on city streets in China as
early as 2025. Volvo Cars plans to test
test bed for autonomous driving
systems. In August 2016, Boston-based
metals with lightweight composite
panels would not be viable
where
autonomous
both
and
non-autonomous
vehicles share the road,
with
the
Could body panels be used as displays or even TV screens? Covestro thinks so. (Pictured: Covestro's K2016 EV concept)
www.automotivemegatrends.com
25
“
Lightweight materials
If strength requirements are lower due to these sensors and software, you can integrate many things within the panels themselves
autonomous driving cars on Chinese public roads as part of its Drive Me initiative – which began in December
2017 in Sweden – with members of
the public behind the wheel. Covestro’s
Lei
is
confident
that
autonomous vehicles in some form
will hit the road “soon”, and notes
growing
interest
in
composite
substitutes for body panels, windows and interiors for this specific reason.
“Our customers believe this will be a
future trend, and will begin looking at
how to invest in these solutions.
Because in three years’ time, this may be a reality,” she said. “If that is the
case, I do not think it will be necessary
for body parts to have as much
strength. As such, composites could be the solution.”
A clear solution to the blind spot
But what about the interim period,
“
codenamed K2016 EV – which uses ‘bold’ material solutions both for the
interior and exterior. As part of this
concept, polycarbonate wrap-around
Replacing glass
High-performance plastics will replace
traditional metals as well as glass
glazing is used to replace the various
inside the vehicle. Polycarbonates are
traditional
block
windows that would feature on a vehicle.
This
enabled
not only shatterproof, but can also harmful
UV
radiation
–
It’s not too difficult to imagine the use of displays as whole body panels, potentially allowing occupants to watch TV directly from the car door
Covestro’s designers to create a
transparent A-pillar, which “improves
passenger and driver vision,” according to Lei. What’s more, the overall solution
important in a car that will feature
wrap-around
windows
and
thus
greater exposure to sunlight. Lei
believes that more displays will be
with road safety not yet perfected and
is around 50% lighter than a traditional
glass window approach.
integrated within the car in future, and
cars and pedestrians? The use of
All-plastic cars have been investigated
“With autonomous vehicles and all of
remove blind spots, commonly linked
in the 1960s with high-strength
car, we don’t see boundaries any
human drivers still struggling to spot
plastic windows and pillars could to the cause of pedestrian collisions.
Covestro has worked with designers from the Umeå Institute of Design in
Sweden to develop an autonomous
electric
26
vehicle
(EV)
concept
–
before – the Bayer K67 was developed
plastics and foams, for example. Highperformance polyurethane materials are already used widely within new
vehicles, accounting for around 18% of the weight of an average mid-size car.
potentially take up entire panels.
these new electronics entering the
more
from
an
application
perspective,” said Lei. “If strength
requirements are lower due to these
sensors
and
software,
you
can
integrate many things within the
Automotive Megatrends Magazine
Lightweight materials panels
themselves.
It’s
not
too
difficult to imagine the use of displays
as whole body panels, potentially allowing occupants to watch TV directly from the car door.”
Lei also envisions a seamless, glass-
like display that sweeps around the
interior of the car, as opposed to the
‘stuck-on’ infotainment screen found
in many cars today. Future cockpit concepts from interior suppliers such as Yanfeng Automotive Interiors
and OEMs including Volvo Cars
already depict the use of several
screens within the car, both for the
driver and passengers. But Lei
believes these screens are likely to
merge into a single panel thanks to
cost-effective
and
dent-resistant
polycarbonate materials.
As can be seen with existing displays
used daily by consumers, such as
smartphones, tablets and laptops,
these surfaces need to be highly
durable and scratch resistant. This is
of particular importance in a rideshare application where the potential
for damage is high. Users do not own the equipment, and are less likely to
take care when entering or exiting the vehicle, or in using the applications.
Recent reports from French media
have already highlighted that ride-
share vehicles as part of the Autolib scheme
have
been
subject
to
vandalism and misuse. However, Covestro’s Lei believes that existing
polycarbonate materials will be able
to stand up to the test, based on the
fact that they are already used for exterior
headlamps
applications and
such
windows,
as
for
example. Hard coatings can also be
applied to further strengthen these
materials, for additional chip and wear
resistance. “All of those difficulties
have
already
affirmed Lei.
been
overcome,”
www.automotivemegatrends.com
The Covestro K2016 autonomous EV concept was developed by Covestro in partnership with designers from the Umeå Institute of Design in Sweden 27
Connected Car Pune
India’s connected car market - a wide open goal ‘Connected car’ – two simple words that mask the vast number of complex technologies, applications and business models involved. At Connected Car Pune, a one-day Automotive Megatrends conference, stakeholders debated the way forward for connectivity in India, and India’s role in connecting the automotive world. Martin Kahl presents his top 5 talking points from the event MASSIvE POTENTIAL
In terms of connectivity, India presents
cars to be connected “within a few
data, says Deepak Jain of Bain &
cars in India are connected, said
Agarwal, CTO Global Delivery Services
less than 10% of the data collected in
a massive opportunity. Just 1.4% of
Sheetal Patil, Global Product Manager for Infotainment at Visteon, growing to
just 4% over the next five years. Maruti Suzuki VP Tarun Aggarwal expects all
years”, as does Microsoft, with Ankur projecting that by 2025, new car
connectivity will be at 100%. But that still
means
a
decade
of
low
penetration, and a mine of untapped
CONNECTIvITy - MADE IN INDIA
Company, with OEMs currently using
India today. Imagine if more of the data
already collected were analysed - and then consider the potential if data were farmed from all of the cars in the parc…
Connectivity may appear to be a low
expect in-car connectivity. Cell phones
Subramanian,
country’s automotive industry has it
connectivity, and that’s why Indian OEMs
a live Q&A that India’s automotive
priority for India’s car buyers, but the high on the list. Indian consumers are
used to an always-online lifestyle, and
28
and aftermarket devices provide basic need to own the connected car, said Microsoft’s
Agarwal.
Ola’s
Anand
Senior
Director
of
Marketing Communications said during
industry stakeholders “need to figure
out how to make innovations through
Automotive Megatrends Magazine
Connected Car Pune
frugal hardware” – a skill for which India
should
IT
Manager, Infotainment. Combine all of
Krishna
also a healthy start-up culture, noted
in the development of connected vehicle
is renowned, and it’s already happening. Prasad,
Director
Delphi
Technical Center India believes India
exploit
“its
classical
competence in data protection.” There’s Visteon’s Sheetal Patil, Global Product
SHARED MOBILITy - IT’S NOT FOR EvERyONE
these skills and India could be invaluable technology – for India and globally.
As ride-hailing giant Ola has proven,
shared rides within five years, but
are already platforms for individuals
potential for on-demand mobility
aspiration in India. The idea of sharing
use. I’m not sure those are extremely
connectivity enables mobility - and the
services in India is only just being realised.
Mature
markets
are
exploring mobility within a wider, evolving ‘sharing economy’, and Ola’s Subramanian
expects
almost
a
quarter of all miles driven to be
vehicle
ownership
remains
an
that hard-earned metal with strangers - even if it sits unused save for a few
hours each day - is yet to find favour in
India,
as
noted
by
Magesh
Srinivasan, Global Head – Connected Car & A.I. at HCL Technologies. “There
yOu wANT EvS? yOu GOTTA GET CONNECTED!
to loan out their car when it is not in
successful in India. Here, people regard cars as a source of personal
pride – not everyone is gung-ho about sharing.” An important reminder of cultural subtleties, even in such a global industry.
Think of a bustling Indian city, and you
need to be irresistible, creating a major
wants to achieve electrification, it has
pollution. To improve air quality, the
data is mission-critical,” believes HCL’s
Electrification and connectivity go
immediately think of congestion and government has ambitious electric
vehicle (EV) targets for 2030. To get
consumers to go electric, the products
opportunity for connectivity. “In EVs,
Srinivasan. “You have to be connected to know the state of charge and
distance to empty. If the government
CONNECTIvITy SAvES LIvES
to start thinking of connectivity.” hand-in-hand: produce a desirable connected EV, and consumers will want to buy into that experience.
When India’s appalling road safety
use of sensors - in the road, in cars,
all of this is relatively easy to
by Santosh Kulkarni, Partner and VP
pedestrians; analysis of sensor data
of the solution; it won’t fix bad roads,
statistics are laid bare, as they were at IBM Global Business Services, it’s clear that drastic change is required
- and connectivity could be at the
heart of that change. Widespread
www.automotivemegatrends.com
in
street
furniture,
worn
by
to identify traffic jams, breakdowns,
traffic incidents and even road
conditions; vehicle-to-vehicle (V2V) communication to prevent collisions;
implement. Connectivity is just a part and it won’t (directly) improve air
quality, but get it right, and it will play a major role in preventing crashes, thereby saving lives.
29
LiDAR
Could LiDAR be the key to five nines reliability? LiDAR looks set to be an essential feature of tomorrow’s cars, and suppliers are jostling for position as costs drop. By Xavier Boucherat
L
proven
Predictably, sound bites from the
with early applications including
reactions from some, including GM’s
iDAR
has
been
a
technology since the 1960s,
mapping
for
architectural
and
archaeological purposes – the Apollo
15 mission, NASA’s ninth manned mission to the moon, made use of
LiDAR to map the lunar surface. But it wasn’t until the turn of the millennium
that the automotive industry started to pay heed. LiDAR’s potential for
Scott Miller, Director of Autonomous
Vehicle Integration, who in late 2017 said the Tesla chief’s autonomous driving claims were “full of crap”.
Essential for autonomy
continuous and highly accurate 3D-
Jason Eichenholz, Co-Founder and
involved in early autonomous vehicle
developer Luminar Technologies,
scanning made it attractive to those development. Since
then,
the
technology
has
improved, and top-mounted LiDAR has become a near regular sight on
the public roads used for testing by the likes of Waymo. These systems are
far from mass-producible however, at
one point costing US$75,000 a unit. The issue of cost means the debate continues over whether LiDAR really
has a place in the automotive
industry. One notable voice which continues to snub the technology is Tesla Chief Executive Elon Musk - at a
2015 press conference he dismissed
LiDAR as unnecessary, and in 2017 went on to claim that SAE Level 5 autonomy can be achieved on Tesla
vehicles through a combination of far
cheaper sensors such as radar and camera, all within two years.
30
Tesla chief have prompted strong
Chief Technology Officer at LiDAR says there can no longer be any
debate. “LiDAR is absolutely needed for truly autonomous driving,” he says.
That
statement
was
underlined by a US$36m investment
in Luminar by Toyota Research
Institute (TRI) in September 2017, and Luminar LiDAR will appear in Toyota’s
Platform
2.1
and
3.0
autonomous test vehicles. “As soon as
autonomous
vehicles
start
moving off closed tracks and into the real world, they need to be five
nines reliable,” notes Eichenholz, referring to the need for 99.999% reliability. “For that, you need LiDAR. Cameras
and
radars
lack
the
performance needed to react in time to the edge cases seen in real
world driving scenarios – for this, cars need to be able to see in 3D like humans do.”
Automotive Megatrends Magazine
LiDAR
Continental believes five nines performance requires sensor fusion, combining a 2D sensor with radar and LiDAR By edge cases, Eichenholz is referring
adapt makes humans well-suited to
provided
spontaneously arise on the road, such
cannot be said for machines.
around them, and make decisions
“
to unexpected situations which can
as a child walking out from between
dealing with these situations. The same
two parked cars, road-works shutting
“What happens if, for example, a car
painted the same colour as the sky
road, but is sticking three feet out into
down a traffic lane, or a semi trailer pulling in front of a driver – a situation which a 2D scanner might have trouble interpreting correctly. The ability to
by
LiDAR
means
that
vehicles too can understand the world before it’s too late.”
has pulled over on to the side of the
Tom
the driving lane?” he continues. “As
Continental’s Segment High Resolution
humans, we can see that, and make
an adjustment. High-fidelity vision
Laux,
Development
Head
and
of
Business
Sales
for
Flash LiDAR, says that whilst it is not up
to suppliers to define whether the
Humans do not lend equal weight to everything. Our visual cortex means we can quickly evaluate, prioritise and focus on what’s relevant. iDAR does the same to dynamically track targets and objects of interest, whilst always critically assessing general surroundings - Luis Dussan, AEye
www.automotivemegatrends.com
31
“
LiDAR
The 3D FLASH LiDAR fires a single laser pulse for every frame. The laser pulse is like the flash on a camera. As a result, it doesn’t matter if it’s dark, or raining. The flash is an illuminator - Tom Laux, Continental
industry requires LiDAR, it is clear that
still hit performance requirements.
assumed that moving to an alternative
achieved via a single sense function.
start squeezing costs when the
was
five nines performance can’t be
“What’s needed is the combination of three sensors,” he suggests: “That is, a 2D sensor, like a camera, to image the
colour of signals, traffic signs and lane
markings. Then a radar to determine velocity, and finally a LiDAR to give accurate angular resolution and 3D
imaging in a far more precise manner.”
Low-cost quality
level which OEMs could take seriously?
The answer lies in solid-state solutions, which Laux defines simply as free of moving parts. This reduces cost by
integrating all mechanical parts into a
microchip – as Laux explains, anything using
semiconductor
performance
is
there.
Luminar’s
system, explains Eichenholz, is built
base
manufacturing technology is subject to
the same cost curve based on the size of the manufacturing environment. “In
other words,” he says, “the more you
“One of the key performance targets is detecting a target that’s only 10%
object, like a tyre or a person wearing a black hoodie, at 200 metres. That
The
of mechanical parts, meaning far better reliability.
But, says Eichenholz, the idea of ‘solidstate’ shouldn’t be over-emphasized – what’s important is that suppliers deliver scalable systems that can be
manufactured at volume which can
32
says
ground up,” he says, “and have gone
manufacturability. Our laser sources, for
example,
are
very
scalable
because they’re the same that are
used in telecommunications devices, hence why we’re at 1550, and using laser diodes and InGaAs receivers.”
number is one we receive from every
Continental, too, is leveraging InGaAs
seconds.”
originally
customer, roughly equivalent to seven Laux
agrees
that
the
industry’s figure falls between 200 and 250 metres. In addition to this, systems must be immune to outside
interference from weather, and other LiDAR
systems.
To
meet
the
performance requirements within cost, suppliers have to innovate.
architecture change, increasing the
time.”
That,
deep into the supply chain to optimise
began, including range issues.
other key benefit is the removal
over
expensive.
challenges it encountered when it
the company to tackle the numerous
Building from the ground up has led
become
too
Eichenholz, was a false assumption.
“We’ve built our system from the
produce, the less expensive these things
like indium gallium arsenide (InGaAs)
from the ground up. This has helped
reflective,” he says. “This means a dark
But how to bring down the cost to a
built
Laux agrees, suggesting you can only
Luminar to make a fundamental
wavelength of the laser from 905
nanometres to 1550 nanometres,
in its Hi-Res 3D FLASH LiDAR system, developer
developed
Advanced
by
LiDAR
Scientific
Concepts prior to its acquisition by the Tier 1 giant. “The 3D FLASH LiDAR
fires a single laser pulse for every frame,” explains Laux. “The laser pulse is like the flash on a camera,
and as it leaves the rod, it passes through something called a diffuser,
which spreads the light across the field of view of the receiver object. As a result, it doesn’t matter if it’s dark,
or raining. The flash is an illuminator.”
enabling ten times more power whilst
Lacking intelligence?
human
905
Meanwhile, San Francisco start-up AEye
Eichenholz, was a result of using silicon
artificial intelligence (AI) it uses in its
remaining within safety limits for the eye.
nanometre
The
original
requirement,
says
receivers in the LiDAR system. It was
is drawing attention to the embedded
solid-state offering. “LiDAR on its own
Automotive Megatrends Magazine
“
LiDAR
LiDAR is absolutely needed for truly autonomous driving. As soon as autonomous vehicles start moving off closed tracks and into the real world, they need to be five nines reliable - Jason Eichenholz, Luminar Technologies
lacks intelligence,” says Luis Dussan,
making significant investments in
sub-US$100
systems don’t take into account how a
aforementioned
The California-based company uses
Founder and Chief Executive. “Existing scene evolves or what the mission is. They look everywhere, always, in a fixed
scan mode, collecting as much data as
possible without discretion. 75% to 95% of data is discarded because it’s
useless, and collecting unneeded data
creates a huge strain on bandwidth, which
translates
into
a
delayed
LiDAR specialists. As well as TRI’s investment
in
Luminar, Ford and Baidu have invested
acquired
in
Velodyne,
Pasadena
GM
has
start-up
Strobe, Osram has taken a 25.1%
Ibeo
human visual cortex, which brings
for being the first production model to
scan pattern. “As humans, we do not
lend equal weight to everything
around us,” says Dussan. “Our visual cortex means we can quickly evaluate, prioritise
and
focus
on
what’s
relevant. iDAR does the same to
dynamically track targets and objects
of interest, whilst always critically assessing general surroundings.” The bandwidth savings, says Lussan, and
for easier integration and lower cost.
can be achieved. “LiDAR is a material
will see a real drop in pricing over the
The 2018 Audi A8 grabbed headlines
system is not restricted to a fixed laser
called optical phase arrays, allowing
science,” he says, “and thus I expect we
Hamburg-based
(Intelligent
higher resolution to key objects. The
smaller sensors and a technology
Automotive Systems.
of
AEye’s
Detection and Ranging) imitates the
production volumes are ramped up.
Laux is confident that acceptable costs
40%
A material science
system
assuming
stake in Leddartech, and ZF controls
response time – a critical safety liability.” iDAR
system,
next
at its unveiling in Barcelona in 2017
offer SAE Level 3 autonomy, and came fitted with a LiDAR. Valeo is the
supplier, and the first to put a system
five
to
seven
years
as
manufacturing suppliers catch on. Even compared to five years ago there
has been progress – at one point,
components would cost in the region of four to five thousand US dollars. This is not the case nowadays.”
out on the road. Since then, the
But,
how low suppliers can bring down the
“There are many people who are
discussion has revolved around just price.
But
just
what
might
an
acceptable cost look like? Continental and ZF reportedly have their sights set
on no more than a few hundred dollars per unit.
concludes
Eichenholz,
the
industry must proceed with caution. pushing for lower cost, with no idea of
what the trade-offs are in terms of performance,” he says. “In terms of
the base technology, there’s been little
innovation in LiDAR technology for ten years, and costs have been bought
the resulting improvement in safety
The potential drop in cost was a topic
the safe, timely rollout of failsafe
laser start-up with backing from
As the industry moves towards
mean cheaper laser arrays, and that
less of an option. A race to the
means his company hopes to catalyse commercial autonomous vehicles.
The importance of LiDAR to the development
of
ADAS
and
autonomous drive technology is clear, with OEMs and suppliers
www.automotivemegatrends.com
at CES 2018. TriLumina, a US-based Denso, said its use of micro-lenses will
total system costs could be brought down
to
Quanergy,
US$200.
a
Meanwhile
solid-state
LiDAR
developer, claimed it has a path to a
down by sacrificing performance.”
autonomy, failure becomes less and bottom in terms of price could
produce systems which, where selfdriving vehicles are concerned, are not fit for purpose.
33
VW Group on AI
VW says OK to AI Martin Kahl discusses AI and enterprise robotics with Dr Martin Hofmann, Volkswagen Group’s Chief Information Officer
S
top anyone in the street and ask them whether they’ve ever encountered artificial intelligence,
and they’ll probably cite an entertaining
experience goading a voice assistant
such as Alexa or Siri. Some might mention a frustrating experience with
telephone call centre automation,
others an online ‘help’ chatbot. The fact that many customers would mention these, where once they would probably
only have referenced a sci-fi movie or two, underlines how far into our lives AI has already advanced.
But what relevance does Alexa’s ability to talk back have for the
automotive industry? And why would car manufacturers be interested?
BMW, Daimler, Toyota, Hyundai and Kia are just some of the vehicle manufacturers working on AI, initially for
in-vehicle
infotainment
and
ultimately for autonomous drive applications.
So,
too,
is
the
Volkswagen Group. But whilst product
VW Group believes artificial intelligence can improve efficiency across the company - but CIO Dr Martin Hofmann insists that AI is simply a means to an end, not an end in itself
is integral to a car manufacturer’s
they’re sensing and their objectives.’
such a company can do with AI.
large organisations can speed up
business, there’s so much more that PwC defines AI as ‘a collective term for computer systems that can sense
their environment, think, learn, and take action in response to what
34
Deploying AI in corporate processes, data analysis and the calculations
required for forecasting, increase
efficiency, and free up employees’
time to focus on tasks where they can add real value.
welcome to the machine
The secret lies in the algorithms that facilitate machine learning, says Dr
Martin Hofmann, Chief Information Officer at Volkswagen Group. “Machine learning
algorithms
process
vast
Automotive Megatrends Magazine
VW Group on AI quantities of data by detecting patterns.
Based on these patterns, and changes in these patterns, the algorithms can
make independent predictions. And based
on
these
predictions,
machines can make decisions.” Computers crunched
have
numbers
for
the
decades
to
produce
outcomes beyond the capabilities of human calculation, but the rate at
which this can now be done is such that IBM’s Watson is able to read
millions of pages per second. Apply this to corporate data, and it’s easy to see how a business could operate far more efficiently. And it is here where a
major
Volkswagen
organisation stands
to
such
reap
as
the
commercial benefits of researching, adopting and ultimately deploying AI in key areas of the business.
AI could boost global GDP by 14% by 2030, believes PwC, adding US$15.7trn to the global economy. That figure, the company notes, is greater than
the current output of China and
India combined, and includes a US$6.6trn contribution from increased productivity.
“For us, the key question is, can
we augment the human being by
giving that person added artificial intelligence?” says Hofmann. “Consider, for example, the laborious data
analysis required to predict vehicle
sales, including all the different components in all of the different countries in which we sell. This is a multi-dimensional problem, and today
this is done with Excel sheets and
VW established Data:Lab Munich in 2014 with the support of Volkswagen Innovation Fund, a joint initiative of VW and the Works Council In this example, a machine learning
robotics.
detect patterns, and then make
repeat a sequence of instructions.
algorithm would process the data, predictions or recommendations.
“Our human sales planners would receive
pre-defined
scenarios
recommended by the AI engine,”
AI
would
be
making life easier and enabling humans to handle complexity.”
250 different models. It's nearly
of human-like robots with human-like
market for a specific configuration.”
www.automotivemegatrends.com
Machine learning algorithms learn on their own, interpret and ‘understand’ the data they are provided.
the potential for AI in manufacturing.
recommendation.
Servers processing data; it’s much less
we are going to sell in a specific
programmed to follow and endlessly
choose whether or not to follow that
we’re in 120 countries, we sell 10 impossible to accurately predict what
machines
As well as improving corporate and
then consider scenario A, B or C, and
Deep thought
million vehicles a year, and we make
are
explains Hofmann, “and they can
human brains,” he notes. “Now think of the complexity of our business:
Robots
perception. It also underlines how learning
for
Production
management
loves
automation – it increases speed,
efficiency, accuracy, quality and safety (just ask the fingerless metal press operators of as recently as three
glamorous than the popular concept machine
strategic processes, VW Group sees
enterprise
robotics differs from manufacturing
decades or so ago). But classic automation can only do so much – repetition and strict adherence to specific lines of code can be limiting.
Automation for the next generation
needs to be smart, and that’s where AI comes in.
35
VW Group on AI
Forget human-like robots with human-like perception - AI in manufacturing is all about providing human operators with intelligent ‘cobots’ that can “take over the heavy duty, physically demanding and repetitive tasks that humans shouldn't do", says VW Group CIO Dr Martin Hofmann According to a 2017 discussion paper
we’re always looking for robots that can
This whole HRI concept allows us to
“Advances in AI technologies will enable
demanding and repetitive tasks that
and to let humans collaborate more
published by McKinsey Global Institute,
the industry to leverage rapid growth in
the volume of data to optimize processes in real time. They can
shorten development cycles, improve engineering efficiency, prevent faults, increase safety by automating risky
take over certain heavy duty, physically humans shouldn't do.” An AI-enabled robot could learn to accommodate
The idea of collaborative robots in
misplaced component.
too early to know whether these cobots
to
adjust
its
movements
for
a
Thus, another area being explored by
and increase revenue with better sales
interaction, or HRI. “Volkswagen is
lead
identification
and
price
optimization.” With the addition of AI,
suggests McKinsey, manufacturing can be smarter, more nimble, and less prone to error.
“Put simply, we want to make robots
intelligent so that they don't need permanent human input to do their
task,” says Hofmann. “In return, they will take over many of the tasks that
human beings do today that we perceive to be repetitive or stressful.
Ergonomics is a big issue for us, and
36
easily with machines.”
anomalies, such as identifying the need
activities, reduce inventory costs with
better supply and demand planning,
make robotics much more flexible
VW
Group
is
human
robotic
the first company to have developed learning
technology
algorithms
where the robots identify and learn human
movement
and
human
intention in a manufacturing setting,”
explains Hofmann. “A robot can hand over
components
to
a
human
operator and, depending on how they move, it might slow down or
move differently. And that's done by sensing
and
learning
human
behaviour. When another worker
comes along, such as at shift change, the robot will adjust to that person.
manufacturing is not new, but it’s still
are an accepted feature on the factory floor. “It will happen in the near future,”
assures Hofmann. “We’re piloting it in a
live environment, learning from it, and then we will scale it.” Crucially, however, these intelligent cobots would only be deployed to help – not replace – human
operators. “AI must always help humans in a meaningful way. Intelligent robots
will
learn
to
optimise
themselves, but always to support the
human being. In our body shop, we
have a high degree of automation. with robots, but now we're talking about
using human and robot collaboration
for the assembly of very critical vehicle components, for example. It’s a true collaboration,” he insists. According to
Automotive Megatrends Magazine
VW Group on AI
VW's Data:Lab in Munich is "probably the biggest accumulation of AI talent in the automotive industry in Europe right now" - Dr Martin Hofmann, VW Group PwC, labour productivity improvements
tasks is limited and clearly defined,”
created
of all GDP gains from AI over the period
specific task, and to accomplish this
initiative of VW and the Works Council
are expected to account for over 55% 2017-2030.
Google Home or Alexa, so their
To pick up on an earlier point, AI is
increasingly being used in call centres on
customer
service
task the robot learns how best to do
it. You can say anything you want to
Answering machine and
he explains. “Here, the robot has a
chat
websites. It’s clever, but it's often clunky, and consumers quickly see
through the pretence of human
algorithms need to cope with many
different variations of possibilities.
There, the technology is not as advanced as it should be. But for a specified range of functions, such as a factory setting, it works really well.”
interaction. What implications does
Data:Lab
robots that have to make decisions
One of the challenges for a traditional
them is moving in order to complete a
is to ensure that, when taking on an
this have for the AI in production line based on how the operative next to complex procedure?
It’s very different, assures Hofmann. “In a call centre, customers could
AI-sized
challenge,
it
has
the
capabilities to operate at the bleeding edge of the technology.
present a million different scenarios.
In 2014, the company established its
the AI operates in a professional
specialise in AI, automotive data
In the case of manufacturing robotics,
environment where the number of
www.automotivemegatrends.com
Data:Lab in Munich, specifically to
science and machine learning. It was
investment
from
Volkswagen Innovation Fund, a joint which
supports
the
company’s
initiatives beyond its core business
areas. The primary aim is to improve efficiency and accelerate corporate procedures
by
identifying
those
processes best suited for AI. It also
works on a number of other areas, ranging from cyber security to traffic flow optimisation. “It's
organisation as large as Volkswagen
with
probably
the
biggest
accumulation of AI talent in the automotive industry in Europe right
now,” says Hofmann. Headed up by
Patrick van der Smagt, a professor from Technical University of Munich, a 70-strong team of physicists, computing
linguists,
AI
experts,
robotic experts and mathematicians works
on
machine
learning
algorithms that can identify and
predict patterns. This includes a small team which conducts fundamental
37
VW Group on AI
VW Group is exploring collaboration between humans and intelligent robots in vehicle assembly. "It's a true collaboration," says Group CIO Dr Martin Hofmann. [Pictured: VW Golf production at Wolfsburg] research, publishes papers, liaises
focuses on electronics, and picture
a serious challenge. I think AI is a
also
managed
better and more comfortable, and
with academia, and files patents. “We support
many
universities
around Europe, and collaborate with
partners from the tech industry. And
a second team in San Francisco keeps us in the loop,” Hofmann adds.
“The AI research team is tasked with looking five to seven years ahead. The
pattern
recognition. by
Audi,
They
which
are
is
responsible for autonomous driving
development within the VW Group. Those researchers are located in
Munich, in the same building. They exchange people and projects, but these are two separate organisations.”
other 60 people work on applied AI,
Mostly harmless
algorithms throughout the corporation.
A major area of concern for the
implement these algorithms in the
the very real threat of malicious
tasked
with
implementing
the
And our 12 brands develop and
different locations in the world where we have operations.”
There's a difference between the
development of AI for business purposes and the development of AI for autonomous driving – and while the researchers do work together, “we keep them separate,” says Hofmann. “The
38
autonomous
vehicle
group
development of AI is, unsurprisingly,
outside intervention. VW, however,
sees hacking, data theft and cyber crime not just as a threat to AI, but also an opportunity, something that AI
can be used to tackle. “It’s a critical
issue,” agrees Hofmann. “Just as with
any technology, there's a fine line between use and misuse. The Internet
is one of man’s biggest technological
advances, yet the Dark Web presents
tremendous opportunity to make life make driving safer. But we are not
naïve –there will be forces out there misusing that same technology.”
Putting the AI into creativity
Readers will no doubt be familiar with the Turing Test, developed in
1950 by Alan Turing to assess a machine’s
ability
to
convince
someone that they are interacting
with another human rather than a machine. Advances in AI suggest that it is no longer a question of if, but
when, AI can convincingly pass the Turing Test, and thus begin to threaten those in executive positions,
assembly line roles or even, perhaps,
journalism. Time will tell whether
human creativity is something that can ever be achieved by AI.
Automotive Megatrends Magazine
VW Group on AI
Using the AI research that comes out of Data:Lab Munich, the 12 VW Group brands "develop and implement these algorithms in the different locations in the world where we have operations” - Dr Martin Hofmann An AI robot might be conducting this interview a few years from now,” chuckles Hofmann. “It’s a good point,
and yes, it is a question of creativity,
which is based on experience. But experience is nothing more than data interpreted,
and
machines
are
outpacing everything we know. In the long term, there will be a coexistence of algorithms and machines that do
specific tasks better than humans do today. But the moment there is no
data available, or a prediction cannot be
made,
creativity
that's
comes
where
in
–
human
with
the
possibility of failure.” AI should not fail, and algorithms are written such that
the failure rate is minimised to near-
Don’t panic
that is helpful and respectful to
is particularly pertinent to a company
representatives is very strong.”
The notion that AI might threaten jobs such as Volkswagen, a traditional and leading
German
the company, and the collaboration with
our
unions
and
employee
company,
The typical consumer referred to at the
powerful Works Council. It would be
AI as an advanced voice-controlled
headquartered in Germany with a
reasonable to expect the Volkswagen workforce
to
be
concerned
and
suspicious about the development of AI, and the implications for the
company’s 640,000-strong workforce. Were it not for the aforementioned
involvement of Volkswagen Innovation Fund, Hofmann’s response might come as a surprise.
outset will, for some time yet, think of
jukebox, or a frustratingly inflexible callcentre automaton; a typical VW Group assembly line operator, however, might
soon see AI as something that makes
their job easier, and those teams in
production forecasting or logistics planning might find the data they work
with more detailed than before and surprisingly accurate.
zero, he points out. “But humans do
“From a very early stage, our employee
For the VW Group, AI is a key
end of the day, at least in a decision-
involved, and they are co-driving this,”
it’s not an end, but a means to an end.
fail, something which we accept. At the making process, the final call should, in critical cases, lie with a human being. That is an ethical discussion which will run and run.”
www.automotivemegatrends.com
representatives in the unions became he reveals. “They know that if we don't
apply new technologies, we would be at a competitive disadvantage. But
we are using AI and applying it in a way
competitive factor for future business;
And for Hofmann, the choice is
simple: develop artificial intelligence in-house, or prepare to depend on the intelligence of others.
39
AVs need AI
Absolutely indispensable: future of AVs hinges on AI Autonomous driving presents one of history’s greatest computing challenges, one which traditional algorithms cannot hope to answer – but deep-learning could hold the key. By Xavier Boucherat
S
peaking at CES 2018, NVIDIA Chief Executive Jen-Hsun Huang described
challenge
the
involved
in
computing
enabling
autonomous driving as the greatest of
its kind. The company estimates the computing demands of a driverless
vehicle are between 50 and 100 times more intensive than those placed on
NvIDIA
the most advanced cars available today. “The number of challenges necessary
the time, monitoring multiple sensors,
bring autonomous vehicles to the
ones, made using software no-one has
to solve in order for the industry to world is utterly daunting,” he said.
“We’ve built PCs, laptops, consoles and the world has never known – it’s on all
are
vehicles represent a level of complexity
bridge a gap of this magnitude? Many now
adamant
that
artificial
intelligence (AI) will be indispensable
when approaching the questions of autonomous
where
HQ in Santa Clara, CA
what
ever known how to write.”
How, then, does the industry plan to
Jen-Hsun Huang
Recent funding activity
decisions must always be the right
super computers, but autonomous
Chief Executive Established
and because lives are at stake, its
1993
NVIDIA announced revenue of US$2.64bn in its Q3 FY2018 results, up 32%
NVIDIA’s push on automotive AI tech included numerous announcements at CES 2018: Uber will use NVIDIA AI algorithms in its self-driving fleets; VW’s I.D. Buzz will use deep-learning enabled by the NVIDIA DRIVE IX platform for co-pilot and autonomous drive applications; and Aurora will use NVIDIA’s Xavier platform to develop autonomous tech
modern
vehicles.
vehicle
has
“A
up
typical
to
100
Electronic Control Units (ECU),” explains Danny Shapiro, NVIDIA’s Senior Director
of Automotive, “but whilst these are
performing important functions that have societal benefits, they’re running set algorithms, meaning they perform
fixed tasks. And there’s no way that
computer vision using fixed algorithms
can handle the diversity of things that happen on the road.”
Bence Varga, Head of European Sales
at AI software company AImotive,
agrees, arguing that any discussion of
autonomous vehicles must have occupant and road-user protection at
its core. “From a safety perspective,”
he says, “traditional computer vision algorithms working via a decision-tree
basis have severe limitations. Due to
the diminishing return inherent in development of those solutions, it
40
Automotive Megatrends Magazine
“
AVs need AI
We’ve built PCs, laptops, consoles and super computers, but autonomous vehicles represent a level of complexity the world has never known - Jen-Hsun Huang, NVIDIA
becomes increasingly difficult to draw
typically uses an algorithm called
between actual output, and the
recognise a car from different angles,
parameters within an artificial neural
on huge amounts of real data which,
up algorithms which, for example, can or one that’s partially occluded.”
AImotive has developed aiDrive, a
software suite that uses AI in enabling self-driving capabilities.
Superhuman
Changing weather, varied surfaces,
road closures, diverse driving cultures – the sheer number of variables on the road is enormous, but humans, with
an
advanced
set
of
interconnected senses and decision-
back-propagation,
which
adjusts
network to minimise the difference
DRIvE.AI
desired output, with the latter based in effect, train the system.
Chief Executive
Sameep Tandon
where
HQ in San Francisco, CA
Established
Recent funding activity what
2015
In its last round of funding, Drive.ai secured US$15m from investors including Grab, an Uber rival in Southeast Asia. Since its foundation in 2015, Drive.ai has raised an estimated US$77m
originally inspired by findings in
Founded by alumni from Stanford University’s Artificial Intelligence Lab, Drive.ai develops AI software for AVs. The group has made waves since announcing it had signed a partnership to provide Lyft with aftermarket self-driving kits. Funding from Grab, and a new office in Singapore, also hint at global ambitions
www.automotivemegatrends.com
41
making abilities, are well-placed to adapt. The industry has therefore
turned to deep learning technology, which as co-founder of drive.ai Tao Wang explains, involves concepts neural science. Modern deep-learning
AVs need AI The introduction of deep-learning into the vehicle, says Wang, represents the automotive industry taking the next
step using a technology with which it already has some experience. “AI has
already made its way into the automotive industry,” he suggests.
“Adaptive cruise control, for example, is a form of AI on its own, albeit with
limited operational domains. Features like ACC provide additional value to end
customers.
sector
is
The
automotive
undergoing
AuRORA
Chief Executive
Chris Urmson
where
HQ in Mountain View, CA
Established
Recent funding activity what
drastic
transformation with the rise of electric
vehicles and ride-sharing, and AI can
help the sector catch up with the pace of the new era and stay relevant.”
But what are the challenges for
suppliers looking to enter the market and
work
with
the
automotive
industry? The view across the board
2017
April 2017 funding round secured just over US$3m. Unclear whether recent tie-ups with VW and Hyundai brought in new funding Founded by previous employees of Google, Tesla and Uber’s self-driving programmes, the exact nature of Aurora’s work is secretive, but the industry is clearly impressed: the group announced partnerships with VW and Hyundai at CES 2018. VW’s Moia electric ride-sharing car and Hyundai’s new fuel-cell vehicle, the Nexo, will use Aurora’s tech. Aurora’s use of NVIDIA’s Xavier platform suggests a clear interest in AI
ranges and in harsh conditions, such as vibration, shock, dirt and dust.
is plain to see – meeting the stringent
The goal is ISO26262 certification, an
industry. For NVIDIA, says Shapiro,
focus
safety standards of the automotive
this has been a decade-long process since the company first turned its
attention to products besides graphic processors.
New
manufacturing
facilities were sought, and changes were made to ensure that products could operate at all temperature
AIMOTIvE
automotive-specific standard with a on
safety-critical
systems.
NVIDIA’s scalable Xavier processor, capable of 30 trillion operations per
second and now being used to develop platforms by the likes of selfdriving developers Aurora, meets the
mark. Work continues for companies like AImotive to make the grade.
Laszlo Kishonti
where
HQ in Budapest, Hungary; additional testing in Mountain View, CA, and Helsinki, Finland
Recent funding activity what
42
‘opacity’
of
reasoning
when
AI
decision-making systems are in play, given the sheer complexity of the technology
involved.
“There
are
currently some opaque areas where
the reasoning behind AI decisionmaking is concerned,” says Varga.
“Ongoing research is looking in detail
at this question, and new answers will continue to arise. To ensure safety we
conduct, together within our partners, in-depth inspections and benchmarks
of all systems. Our neural networks
are trained on annotated test data
Chief Executive Established
Other concerns include the potential
2015
US$38m in January 2018, with investors including B Capital Group and Cisco Investments. Previous investors include Robert Bosch Venture Capital
AImotive’s aiDrive is a ‘full-stack’ software suite for AVs using cheap and readily available camera sensors. It uses four engines – the first two localise the vehicle in its surroundings, before the motion engine plots a trajectory, which is then executed via a drive-by-wire system in the control engine. AI is imperative in object detection, classification, lane detection and other tasks
from all around the world to ensure they
generalise
properly
in
all
situations.” Simulations are key in this regard, with millions of scenarios digitally
rehearsed
tested on the road.
before
being
believes
such
Drive.ai’s
Wang
emerging
technology,
concerns are applicable to any and
that
acceptance will only come with proof of safety. “Deep learning is not
exactly opaque,” he suggests, “as there are means to visualise what
the neural network is ‘thinking’, and informing people of the new
kind of knowledge will be crucial in
Automotive Megatrends Magazine
AVs need AI making them comfortable with a new technology.
But whilst it will be important for
OEMs to understand AI, says Varga, of equal importance will be for AI to understand humans. “This means the system will have to predict what
other actors on the road are going to do, and plan accordingly,” he says. “The sensor setup we are creating,
including cameras supported by
ARGO AI
Chief Executive
Bryan Salesky
where
HQ in Pittsburgh, PA, with hubs across the USA
Established
Recent funding activity what
That,
capabilities
coupled
to
with
understand
Ford acquired Argo AI for US$1bn in August 2017. Salesky has said he hopes to help the OEM deliver AVs by 2021
Ford snapped up the AI start-up in 2017, not even a year after it was founded by Bryan Salesky and Peter Rander, formerly of the Uber Advanced Technologies Group. Argo is developing a full-stack AI solution (a ‘virtual driver system’) for AVs with responsibility for everything from sensors to software. To this end, Argo acquired LiDAR developers Princeton Lightwave in October 2017
other sensors, won’t have blind spots.
2016
AI’s
and
generalise its environment, will lead
to a superhuman driver that’s safe to share the road with.”
Skynet? unlikely
automotive industry likely to play an
concerned,
Of course, not all the headlines
how
and utter science fiction.”
about AI are positive. Notable figures
increased role in AI development, closely
should
OEMs
pay
attention to the thought of new,
the
idea
of
an
autonomous vehicle rebellion is pure
potentially lethal safety concerns?
Shapiro agrees: “Some people’s view
repeatedly
The good news, says Varga, is that an
Terminator movies”, he says, adding
with AI isn’t malice, but competence,”
AI, he suggests, is worlds behind
including theoretical physicist Steven Hawking and Tesla Chief Executive Elon
Musk
have
expressed concern. “The real risk
said Hawking in 2015. “A super intelligent AI will be extremely good
at accomplishing its goals, and if
those goals aren’t aligned with ours, we’re
in
trouble.”
AEyE
With
the
apocalyptic situation is unlikely. Current the
Artificial
drive,” he says. “It cannot modify itself, nor reprogram itself. As far as we’re
where
HQ in Pleasanton, CA
what
that AI systems already outperform human beings in terms of detection,
tracking and understanding distance and speed. “What’s more, they don’t
get distracted,” he says, “nor do they
experience road rage, nor anger, and they don’t get drunk.” Far from posing
a risk, AI already has the potential to deliver huge safety benefits.
Luis Dussan
Recent funding activity
Intelligence
‘singularity’. “Our AI is trained only to
Chief Executive Established
General
thought of when discussing the
of AI seems to be based on the
2013
June 2017 funding round secured over US$16m, with investors including Tyche Partners and Intel Capital
AEye develops LiDAR that uses embedded AI which adapts to real-time demands. The result is iDAR, a LiDAR system capable of targeting and identifying only the objects that matter, thus delivering more intelligent information to an AV. At CES 2018, AEye announced AE100, a costoptimised solid state LiDAR system
www.automotivemegatrends.com
Moving forward, he says, NVIDIA is
confident the checks, balances and tools are in place to ensure that AI won’t create problems. “We can test and validate to see where applications work
and
where
they
fail,”
he
concludes. “And then, we can go back, analyse, and adjust. We have great
ways of analysing and diagnosing the neural networks, and understanding
how they perform, and they will only continue to improve.” AI, it seems, will prove an ongoing project which, all
going well, will perfect itself over time, for the potential benefit of billions.
43
Smart mobility, intelligent mobility
There’s a growing role for AI in future mobility AI and deep learning will become indispensable for future mobility, write venkat Sumantran, Charles Fine and David Gonsalvez
A
ny visitor to CES in Las Vegas
automotive industry found itself
International
safety, fuel efficiency and emissions.
or
the
North
American
Auto
Show
(NAIAS) in Detroit in January 2018 would have noticed that the terms artificial intelligence (AI) and deep learning
have
been
convincingly
embraced within the lexicon of the automotive industry.
It is perhaps useful to adopt a Janus outlook to this trend, reflecting on its historical evolution and anticipating its future role as the automotive industry prepares for an epochal transformation.
In many ways, the role for a ‘brain’ within
the
automobile
gained
momentum in the 1970s, as the
44
facing challenges on three fronts: In each case, it appeared that traditional
mechanical
systems
needed to be aided with contextual
information and with it, the ability to modulate or adapt their response. For
example,
the
steel
safety
structure was, by itself, inadequate to achieve the desired levels of occupant
safety. This safety cell needed to be augmented by airbags whose manner
of deployment needed to be tailored, based
on
occupants
and
the
dynamics of the crash. Similarly, the
pursuit of fuel efficiency gains and emission reduction, to meet newly mandated
norms,
led
to
the
conclusion that carburation and fuel
Automotive Megatrends Magazine
Smart mobility, intelligent mobility
Volkswagen and Toyota have telegraphed their interest in deploying autonomous driving technologies to shared-use vehicles management required more precise dynamic control, based on engine operating
conditions,
transient torque demand.
load,
and
These functions were enabled by a combination of electronic processors
and software. Keeping pace with advances in electronics, these systems
became more accurate, employed
more memory and faster processors.
If one were to use the number of lines
“
of software code as a surrogate
measure for system capability, purely
for the sake of sizing the problem, between 1970 and 1990, the number
of lines of software code in a typical luxury
car
grew
ten-fold
from
operating with about 100,000 lines to about a million. In 1990, as a
reference, the International Space
Station operated with a similar quantum of software code.
In many ways, this era triggered the trend for the 1990s, as the role for
‘intelligence’ on board vehicles was
engaged to serve many functions. Increased use of electronics in the
automobile was typically aimed at four
main
automating
aspects tasks
of
that
driving:
were
considered chores, such as shifting gears, or parallel parking in crowded
city streets; improving the driving experience and reducing stress, such
as using adaptive cruise control to
driver with features like electronic
stability program (ESP). The parallel adoption of electronics in many interior systems also meant that on-
board intelligence was employed for
functions such as climate control, entertainment,
navigation
and
communication. A modern day luxury
sedan, like the current generation Mercedes-Benz S-Class incorporates almost all of the above features and then some. It requires over 100 processors or controllers and 200
million lines of software code to keep the car operating as intended.
maintain safe following distances;
The current frontiers of technology
that monitored themselves and could
autonomous driving, connectivity to
reducing maintenance cost with cars delay the next routine service; and expanding the capabilities of the
focus
on
three
capabilities
other vehicles and infrastructure, and electrified drivetrains. Collectively,
As data and information play a rapidly growing role in mobility, AI and deep learning will become indispensable for the operation of our future mobility architecture
www.automotivemegatrends.com
–
45
“
Smart mobility, intelligent mobility
Collectively, autonomous driving, connectivity to other vehicles and infrastructure, and electrified drivetrains have placed huge demands on AI and deep learning
these systems have placed huge
driving, they are aided by vast quanta
is driven in autonomous mode, may
Autonomous
consider how much easier it is to
control of the car. While the former
demands on AI and deep learning. driving,
often
characterised by the hierarchical levels
of autonomy as defined by SAE, demands sensing,
that
the
perceiving,
sequence
of
cognition,
judgement and taking action be managed in all sorts of driving and traffic conditions.
Machines have already surpassed human beings in their sensory
capabilities, as we have seen with LiDAR, cameras and accelerometers.
Similarly, their ability to manage
subtle, precise and timely action surpasses human limits – most modern
fighter
aircraft
are
dynamically unstable by design, and
cannot be ‘hand-flown’ even by
of data to ease the task. It is useful to
drive in well-known surroundings as
opposed to driving through a new locality where the streets and traffic patterns are unfamiliar. In the latter
situation, one is forced to rely on
sensory inputs and rapidly adjust
one’s actions while driving – a more challenging
task.
Detailed
and
frequently updated maps and traffic information, often aggregated from
numerous other road users, render much of the driving environment ‘known’
even
before
the
car
of
the
encounters that area. With this, the path
planning
task
autonomous car is executed with fewer uncertainties.
expert pilots, except in limited
The roadmap to autonomous driving
However,
of the protagonists are willing to
portions of their flight envelope. the
sequence
of
huge
challenges
for
perception, cognition and judgement presents machine
intelligence.
path
traverse
On-board
systems in the car must plan the to
in
the
given
conditions, follow rules of the road,
and respond to movements by pedestrians and other vehicles in near proximity. This domain remains the biggest challenge today, as
technology advances to offer Level 5 fully
autonomous
driving
capabilities. To allow machines to manage these complex aspects of
46
faces a critical fork in the road. Some
accept current limitations in sensing
and AI (as with Level 3 autonomy), and allow for some situations where the
car’s ‘brain’ can be overwhelmed by the
complexities
of
the
driving
condition, such as poor visibility, ambiguous traffic patterns, etc. In such circumstances,
the
machine
is
expected to hand over control to the
be ill-prepared to hurriedly assume group addresses a less complex problem and assumes some of the
risk, the latter group is compelled to
tackle the far more complex challenge
of preparing the car to handle all sorts of
conditions
and
operate
fully
independent of the driver. It is likely that this latter approach will perhaps find initial use in contained and wellregulated
traffic
Singapore’s
effort
environments.
to
pilot
such
mobility within an industrial park is one example.
Even as these challenges are being mastered,
the
next
horizon
of
challenge for AI and deep learning is emerging. Across the globe, the effects
of urbanisation are causing population
densification in cities. Serving the
mobility needs of dense populations, while avoiding high economic and social costs related to congestion in city streets, is a topic that sits high on
the list of most city administrators.
Many cities have embarked on policies aimed at reducing vehicular traffic and
encouraging ride-sharing or use of mass transit.
human driver. Others, such as Google
Operators such as Via and Chariot now
inherent in such a scenario. The
cities with conventional 8-12 seat vans
and Cruise, are wary of the danger
human driver, who has been lulled into a state of relaxation while the car
offer ride-share services in many global with human drivers. Planning the journey for each vehicle, as it seeks to
Automotive Megatrends Magazine
“
Smart mobility, intelligent mobility
Machines have already surpassed human beings in their sensory capabilities, as we have seen with LiDAR, cameras and accelerometers. Similarly, their ability to manage subtle, precise and timely action surpasses human limits
serve multiple users, optimising routes,
autonomous drive mode for the
and vehicle-to-infrastructure (V2I)
adjusting for dynamic traffic conditions
journey is shared and used by
infrastructure
pick-up and drop-off points, while
and user convenience, also demands use of AI and deep learning tools. These operators are finding that for
each rider, they may need to compute over 10,000 scenarios before they may
vehicle, but also manage how each
multiple commuters. AI and deep learning will find a critical role in
managing both vehicle and shared fleet operations.
match the prospective rider to a
A further horizon is also now coming
one seeks to personalise such travel
administrators
specific vehicle and a specific route. As requests, based on user profiles and preferences, the task becomes even more complicated.
Many experts predict that the truly impactful
transformation
with
autonomous driving will only be
realised when these autonomous
cars become a part of shared-use
fleets in urban environments. It is telling that both Volkswagen and Toyota’s recent auto show exhibits
featured autonomous cars intended
into view. In many global cities, investments
are
towards
making
employing
sensors and using data to render their cities
‘smart’,
organisms
with
to
mimic
health,
living
safety,
dynamically
played by these technologies will be further amplified as they are also
employed in logistics fleets that are a growing fraction of city traffic. We may not be far away from the day when
users
and
their
vehicles
about
routes,
dynamically negotiate with cities and city
infrastructure
parking, and user fees to determine and select the best options.
As data and information play a rapidly
traffic lights, parking availability, road
learning will become indispensable
are expected to stream data related to congestion, and increasingly dynamic road-use pricing, thereby expanding the range of relevant information that will be processed within the context of each journey. Going
industry must not only solve the
adoption of vehicle-to-vehicle (V2V)
www.automotivemegatrends.com
to
interoperate with vehicles. The role
sanitation, and mobility. These cities
for shared rides in city fleets. To
make these solutions work, the
communication, one may expect city
forward,
technologies
as
evolve
vehicular
with
wider
growing role in mobility, AI and deep for the operation of our future mobility architecture. The authors have recently produced a book, “Faster, Smarter, Greener: The future of the Car and Urban Mobility” published by the MIT Press
47
Zenuity, year two
Zenuity CEO on the auto industry's 'fantastic future'
“It’s the future, but it’s happening now,” says Dennis Nobelius, Chief Executive of the Autoliv-Volvo Car joint venture Zenuity in conversation with Michael Nash
T
he building blocks for the highly autonomous car are hugely
complex, cemented in infinite
lines of code, huge collections of data
and artificial intelligence (AI). Bringing
this all together is no easy feat, but it is one that Zenuity hopes to do with the help of its parent companies.
Established in January 2017, Zenuity is
an equal joint venture (JV) between safety and electronics supplier Autoliv and
Geely-owned
Volvo
Cars.
Headquartered in Gothenburg, Sweden,
it has facilities in Munich and Detroit. Zenuity
specialises
systems
(ADAS)
in
developing
software for advanced driver assistance and
autonomous
driving. According to Chief Executive
Dennis Nobelius
Dennis Nobelius, Zenuity’s primary goal
Volvo Cars and Autoliv in the field of
take it further. Sometimes we change
and intelligent mobility.”
the engineers that developed those
project, other times we continue and
is to create “inspiring technology for safe Speaking to Megatrends, Nobelius
describes how the company is going about
achieving
its
goal,
and
discusses the industry trends that
are already having an enormous impact on the vehicles of tomorrow.
active safety, and we also have many of technologies working for us. A third of our workforce is from Autoliv, a third
from Volvo Cars, and everyone else
direction entirely and start a new
make small tweaks. We’re very flexible and fast in our ideas and innovations.
is new.
Are you limited in terms of your
Does this background allow you to
by Autoliv and volvo Cars?
act and react more quickly to
customer base due to being owned
certain issues or industry trends?
That’s another thing that sets us
out from other companies that
I’d say that we are working at a different
we have all the experience and
autonomous driving software?
using different tactics. Every six weeks,
what are
makes
Zenuity
developing
ADAS
stand
and
I think one of the major strengths of
our company is that we have all the
intellectual property and patents from
48
pace from many other companies, and we come together and decide whether
or not the project we have been focusing on has reached the point that
we wanted it to, and whether or not to
apart from competitors. Even though
patents from our parent companies,
we are free to work with any OEM
that we like. This gives us the
opportunity to work with the best hardware, for example, or fastest innovators in the industry.
Automotive Megatrends Magazine
Zenuity, year two what
are
the
major
trends
currently governing advancements
in ADAS and autonomous driving? I’d say the first big trend is working with
synthetic data, which is artificially generated data. The second is the use
of artificial intelligence (AI). We realise that we must be effective with the data
that we generate and handle, and AI is really transforming the way we use that data and, therefore, how we operate software.
Are there any early examples of this?
Tesla’s latest range sensor is operated
by neural networks, and I think we will
different types of autonomous cars
what the driver is looking at, and will be
able
to
predict
and
offer
information on what they would like to see, making the driving experience much more comfortable.
For safety-critical systems like steering
our own code from scratch. We’re now
more time. We’re already doing object
we are working with AI to produce and make sense of code. It’s the future, but
driving cars?
AI-based systems will be able to tell
driver monitoring, for example. These
It’s happening very fast. We used to talk deep into software 2.0 – which means
on the development of selfThat’s a difficult question to answer,
will we ever see AI used in features
about software 1.0 – which is writing
services will have a big impact
soon see more examples related to
How rapidly is AI developing in the automotive industry?
Do you think the rise of mobility
such as braking and steering?
it will come, but it will definitely take
identification, using cameras and AI to tell the driver what they are seeing.
but I can envisage that there will be used in cities compared to the ones
used on the highway. Those operating in the city will replace taxis and will have
a flexible layout, allowing users to stretch out and read, or access emails.
At the moment, however, we’re focused on self-driving vehicles for highway commuting. If you drive an hour to
work each morning, 80% of that will be
on boring roads, so the car could take over. It will still have a steering wheel,
and the looks and driving feel will still matter. These factors will be less important for the autonomous cars in
it’s already happening now.
what
How could data be used differently
automotive applications?
where do you see the automotive
AI consumes considerable processing
years?
to enhance vehicle design?
One of the big things we hope to see is the sharing of data between different OEMs. If they do this then
the data becomes more valuable and progress with software development
will speed up. But we need to be intelligent about what we share and
are
the
challenges
to
consider when developing AI for
power in the car. A number of current
the cities.
industry heading in the next ten
evolutions will help, such as more
If you had asked me that 20 years ago,
to gather a number of petabytes of
precise answer. But today, there are so
powerful computers. Also, if you need data with AI, it can become extremely costly and take a long time.
I would have been able to give you a many disruptive trends that it makes it almost impossible to tell.
with whom. So for example, slippery
what are your expectations for the
What we will probably see is more
feature in Nordic countries, and it
market?
Today, the car looks like a car because
road alert is a really important
makes sense to share this data to
future of the self-driving vehicle
catch the dangerous spots. But it
First of all, I think there will only be a
Italy, for example.
2023, because of the huge effort
wouldn’t make sense to do this in The smart use of data and AI is vital in autonomous driving, and I think the higher the self-driving level, the more AI-based it will become. We are starting
to see AI feature heavily in different software components to enable handsoff driving, taking in information from the hardware.
www.automotivemegatrends.com
few autonomous driving systems after involved when making them. Only a few players will have the resources
and capability to provide robust and safe systems, so there will be a
streamlining of the industry. I don’t think a start-up with 500 employees
will be able to go it alone, and so we will probably see much more in the way of partnerships too.
variety in transportation models.
of legal demands such as passive safety requirements. But with new
technologies, we can totally remodel
transportation, the Waymo self-driving bubble-like vehicles being a prime
example. Forecasting and prediction
will play a greater role in transport too. So, for example, if there is a big concert or event in town, the vehicles
will be aware, and automatically
reroute to ensure the traffic flow is more efficient. It’s a fantastic future where we are headed.
49
Automotive cyber security
An inside-out approach to preventing vehicle hacks As the auto industry evolves beyond simple one-time software deployment, it’s time to develop end-to-end cyber security solutions. By Megan Lampinen
I
ncreasingly complex automotive
vehicles on the road today, and the
development
independent vendor for embedded
systems
pose
and
serious
security
challenges. Today's vehicle system
engineers are faced with millions of lines of code - many times more than
the average passenger aircraft. At the same time, a growing number of
“
features and functions are being placed on a single electronic control unit (ECU). The resulting complexity of
consolidation and mix of critical and non-critical functions makes for a demanding environment.
It's an environment that Green Hills Software has been navigating for the
past 30 years. Software created with the
Green
Hills
Platforms
for
Automotive is found in millions of
company claims to be the largest software solutions. During its three decades, the core objectives have
remained relatively steady - cut manufacturing costs,
speed
maximise
and
up
product
development
time-to-market, reliability
and
optimise product lifetime in the
market. However, the specifics of its approach have been refined and reshaped by emerging trends.
Software-based separation
One of the biggest trends in the current automotive industry is the consolidation of functionality from
Pursuing hardware-based separation is often a non-starter for new automotive designs because manufacturers want fewer central processing units (CPUs) in the car, not more
50
Automotive Megatrends Magazine
“
Automotive cyber security
Most people involved in creating a security architecture will leverage multiple layers of security to build defence in depth. More often than not, security architects build defence from the outside, working in
multiple
ECUs
to
fewer,
more
powerful ECUs. "Pursuing hardwarebased
separation
non-starter
for
is
new
often
a
automotive
designs because manufacturers want fewer central processing units (CPUs) in the car, not more," explained Joe Fabbre,
Director
of
Platform
Solutions at Green Hills Software. "The Integrity Real Time Operating
System (RTOS) forms the foundation for providing provable softwarebased separation."
This is the agship of Green Hills Software's Designed
operating
around
a
systems.
partitioning
architecture, Integrity promises reliable, secure and real-time performance for
embedded systems. "It has been evaluated against the most rigorous safety and security standards in the
Layered security
on
refers
security.
The 'soft underbelly' in this case to
vulnerable
operating
systems, which could undermine strength in a multi-layered defence
strategy. "Most people involved in
creating a security architecture will leverage multiple layers of security to
build defence in depth. More often than not, security architects think
about building defence in depth from the outside, working in," Fabbre explained. For example, a system
designer may deploy a firewall to limit network access as an outer
layer of defence. He may then
additionally deploy an intrusion detection
system,
just
in
case
an attacker penetrates the first layer of defence.
world," added Fabbre. He describes it
"Adding more layers makes it more
any project looking to build a safe and
system, and allows more time for
as "the key enabling component" for secure software architecture based on
the idea of separation. "We can build security with an 'inside out' approach
because we have a proven, stable foundation, as opposed to a soft underbelly," he noted.
www.automotivemegatrends.com
diďŹƒcult for a hacker to penetrate the detection and recovery in the event of
a system compromise," he pointed out. One of the big factors driving this
approach is the enormous and complex software that runs in these
systems. Notably, it frequently runs
operating
systems
such
as
Android, Linux, or Windows that were just not designed for high levels of "Vulnerable
operating
systems are the soft underbelly of this multi-layered
defence
in-depth
strategy. They get hacked all the time,
and once an attacker gains access, it
is usually fairly easy to perform a privilege escalation and completely take control of the system," cautioned
Fabbre. "Therefore, security architects build layer after layer to protect this vulnerable foundation."
An inside-out approach
Green Hills Software applies a fresh approach
to
building
security
architectures for automotive systems.
"We build them from the inside out. We start by identifying the security critical and safety critical components
that are present in the system. We build those components with great
care and scrutiny. We keep them small and simple so that they can be evaluated to make sure they perform reliably
and
do
not
have
vulnerabilities," Fabbre outlined.
any
51
Automotive cyber security The code for those components
hack that made headlines nearly
"One of the benefits of the separation
exhaustively
followed. Even the Tesla Model S is
future proof system designs," Fabbre
is
reviewed
critical
by
tested.
experts
components
and
Importantly, are
kept
separated from the larger, more
complex pieces of code in the system. This can be achieved through either
three years ago, plenty more have not immune, as Chinese hacking firm
Keen Security Lab demonstrated in September 2016.
hardware-based or software-based
"The combination of all of these
Cyber security
priority for OEMs," Fabbre pointed
separation of those components.
“
out. Green Hills offers products to
Several other industry trends are
playing directly into the Green Hills corporate strategy, including the rapid rise in connected cars and
advanced driver assistance systems
(ADAS). This will only increase with the
move
towards
trends is making cyber security a top
eventual
autonomy. BI Intelligence expects
address cyber security concerns with
the added bonus of its expertise in
architecture is that OEMs can use it to told Megatrends. "The software that
provides the user experience needs to
be agile. It should be able to be updated to keep a modern look and feel,
leverage the latest mapping technology, and so on. In contrast, the software that
interacts with critical components in the
car should be very stable and should not change much, if at all, over time."
security
The company leverages its separation
Services (ISS) is a wholly-owned
virtualisation to consolidate those two
building
safety
and
architectures. Its Integrity Security subsidiary
focused
on
providing
embedded security products and services for the protection of smart devices from cyber security attacks.
architecture
in
combination
with
worlds on the same ECU. Additionally,
the ISS subsidiary provides firmware over-the-air update systems as well as key and certificate management.
Automotive software now has a life beyond just a one-time deployment. As software lives on after start of production, OEMs need an end-to-end solution for secure distribution of new features and security updates
road by 2020 - just two years away.
Timeline challenges
exact predictions vary, but the trend
Not only do software developers need
communication between cars and
automotive grade but they also need to
381 million connected cars on the Gartner puts it at 250 million. The is clear. Vulnerabilities in the secure the
Internet,
other
cars
infrastructure pose real risks. "We’ve
seen
many
and
high-profile
exploits of automotive systems in the last several years," noted Fabbre.
While it was Charlie Miller and Chris Valasek's white hat Jeep Cherokee
52
to
ensure
their
technology
"Automotive software now has a life beyond just a one-time deployment," is
fit into the automotive clockspeed. That means the systems developed today must work seamlessly with the vehicles
that roll off the production line six or
seven years down the line. Predicting the challenges so far down the line is very difficult at best, but Green Hills has a few tricks up its sleeve.
he emphasised. "As software lives
on after start of production, OEMs
need an end-to-end solution for secure distribution of new features and
security
updates.
The
combination of our device lifecycle management
cryptography,
systems
operating
with
our
systems,
and virtualisation technology provide all of the foundational components to
build
future-proof,
automotive systems."
secure
Automotive Megatrends Magazine
Algorithms and machine learning
Training, not tech, is slowing AV development Algorithms are the biggest secret behind the autonomous car – but for the foreseeable future, those algorithms need to learn what humans already know. Randi Barshack of CrowdFlower talks to Michael Nash about training machines to learn
A
of
some more background information
mathematical equations in
be vital for the development of
lgorithms
are
capable
solving the most complex
nanoseconds. They are part of our
everyday lives, crucial to the Internet, Netflix
and
even
home
management systems.
energy
They will also play a fundamental role in the autonomous vehicle. However, these algorithms need to be
highly
intelligent
to
ensure
that the vehicles can operate safely and efficiently.
Based in San Francisco, CrowdFlower
provides a human-in-the-loop (HITL) platform that helps data scientists to
collect, clean and label data. This can
autonomous vehicles.
Secret training “The connected and autonomous
vehicle is a huge topic of discussion
in both the artificial intelligence (AI) industry
and
the
automotive
industry,” she observed. “Some would
argue that the newest models on the market are not even cars, but moving
computers. The dirty little secret is
that these vehicles need to be trained so that the algorithms they use can perform in the real world.”
then be used for machine learning.
The misconception here, continued
Back in June 2017, the company
written by engineers, and then simply
announced that it had received
US$20m in funding, most of which was provided by Industry Ventures. The investment has been used to
extend the functionality of its platform and hire new data scientists, machine learning experts and engineers. Speaking
Barshack,
to
Megatrends,
Vice
Randi
President
of
Marketing at CrowdFlower, provided
www.automotivemegatrends.com
on the platform and how it could
Barshack, is that algorithms are
used in autonomous vehicles to bring an
unprecedented
level
of
intelligence. “But an algorithm on its own is just theoretical potential,” she emphasised. “It can avoid hitting a
tree or a pedestrian, but it needs to be taught what a pedestrian or a tree is. This seems so counterintuitive to us
as humans because its second nature for us, but for a computer, it’s extremely challenging.”
53
“
Algorithms and machine learning
We’re not really waiting for any additional technology. The bottleneck at this point is the training. It’s just a matter of how much manpower can we throw at this
Using
CrowdFlower’s
platform,
a
person takes an image or a video clip obtained by the various cameras and
sensors on a vehicle and then draws
boxes around various sections to ensure the algorithm can distinguish between a pedestrian and a tree, for
example. The input is then fed back to the algorithm as ‘training data’.
“So we are literally training the algorithm to be more intelligent,”
Barshack continued, adding, “The way the algorithm absorbs information is very similar to having a three-year-old
child learning from the images that we provide.”
“
about an autonomous vehicle on the
an animal or a human. This training
confused when it came across a
we have to account for every
road in Australia that got very
kangaroo, and couldn’t tell if it was
is an on-going, iterative process, as possible scenario.”
An algorithm on its own is just theoretical potential. It can avoid hitting a tree or a pedestrian, but it needs to be taught what a pedestrian or a tree is
The range of scenarios However, this education programme
can take a significant amount of time and effort, as the algorithms need to
be highly accurate to ensure that autonomous vehicles are safe and robust. “If we expect cars to be
autonomous then they must be
able to firstly identify a road sign, and then secondly be able to tell what that road sign says so as to react accordingly.”
Furthermore, there is a huge variety
of potential scenarios that could
unfold whilst driving. “There’s a story
54
Images courtesy of CrowdFlower
intelligent,” she said. “They must be
Automotive Megatrends Magazine
Algorithms and machine learning highly
the expertise of Cruise Automation
technology. The bottleneck at this
trained. Barshack also provided an
have self-driving vehicles ready by
of how much manpower can we
However,
it’s
not
just
autonomous vehicles that need to be example whereby lane keep assist (a driver assistance system featured in
most new vehicles on the market today) malfunctions.
“The lane assist feature will provide
an alert when a driver crosses the
to do so. Ford is preparing to
2021, and is currently testing its
technology through partnerships
Creating jobs
other vehicle manufacturers have
With
Pizza and Postmates, and various referenced later dates.
“We’re seeing what I would call an arms
position,” she noted. “But if there’s a
observed. “The company or companies
piece of garbage in the road and it
“
happens to be yellow, it may or may not think I’m crossing a lane marker.”
All these random scenarios could have
a big impact on the way that self-
driving cars function, and in some
race
in
the
industry,”
Barshack
that own the ability to power fully
autonomous vehicles are going to win. I think it’s probably common knowledge
in the automotive industry that if you’re not in the area yet, you are not preparing for the future.”
cases, they could potentially cause the
Many
manner. Therefore, extensive training
vehicle technology on public roads. A
vehicle to react in a dangerous
throw at this.”
with the likes of Lyft, Domino’s
lane marker, and will also pull the steering to correct the vehicle’s
point is the training. It’s just a matter
companies
already
have
permits to test their autonomous
the
widespread
rollout
of
autonomous vehicles on the horizon, some
industry
watchers
have
suggested that thousands if not
millions of jobs could be threatened. Taxi drivers, for example, could be
replaced by self-driving cars that are much safer and cheaper to use, and a similar scenario could happen with heavy-duty vehicles.
However, Barshack thinks that the
job market will simply evolve: “There are already so many people getting
worried about what taxi drivers or
truckers will do, but the reality is
If we expect cars to be autonomous then they must be intelligent. They must be able to firstly identify a road sign, and then secondly be able to tell what that road sign says so as to react accordingly
of the algorithms is important both in
recent
of the technology as well as its safety.
showed that the likes of Waymo, GM
terms of the robustness and efficiency
The bottleneck
by
the
California
autonomous mode.
added, and at least during the early
operating
in
“I think the computing capabilities
is hoping to lead the pack. The
provide 360-degree vision and to
company has revealed plans to launch a
commercial
fleet
of
so-called
robotaxis in 2019, and is leveraging
www.automotivemegatrends.com
not disappearing.”
Self-driving vehicles will require
successfully
when it comes to the deployment of
autonomous cars, but General Motors
that the job opportunities are shifting
and Nissan self-driving vehicles have been
OEMs have various timeframes in mind
report
Department of Motor Vehicles (DMV)
are all there, such as the ability to
process high resolution images very
rapidly,” Barshack stated. “We’re not
really waiting for any additional
people stages
to
of
train
market
them,
she
introduction,
specialist operators will be needed to sit in the vehicles and take control when needed. This is already the
case for platoons of trucks that are currently being trialled on public roads today.
55
Industry 4.0
Digitalisation essential for growth in India’s auto industry Siemens wants to bring Industry 4.0 to India, which comes with its own unique challenges. Done right, however, it could revolutionise the country’s supplier base. By Xavier Boucherat
I
ndustry 4.0 is a broad church. The
computing. Lending it a precise
and
technologies and concepts, from
without having to take regional
emerging economies are to take
term denotes a wide variety of
connected factories, to cyber-physical systems
56
to
advanced
cloud
definition is complicated enough differences into account, such as the varying levels of access to technology
resources,
or
the
unique
conditions in individual markets. But if
advantage of Industry 4.0, these are all essential considerations.
Automotive Megatrends Magazine
“
Industry 4.0
Today’s suppliers are being hit by huge challenges on the development front, as they are no longer making single-science products, but multidisciplinary ones which combine electronics, hydraulics, mechanics and software Senior
developed world, there are relatively
Digital siblings
Industry Software Solutions. Dutta has
mass transformation will not happen
One thing that Dutta is keen to stress
suppliers
most important consideration in
So
says
Director,
Guatam
Marketing
Dutta, at
Siemens
responsibility for the Indian region, where automotive growth continues at an impressive pace. OEMs such as Maruti Suzuki, the nation’s largest, are
expected to set sales records for
FY2018. But whilst Dutta doesn't
believe that an Indian vision for Industry 4.0 differs greatly from its German counterpart, its framework
does need to be squared with what he
few OEMs building in India. And so if only they and a few hundred adopt
the
digital
technologies. It needs to be the 10,000 suppliers enabling it all, making
anything and everything from sheet metal parts, to castings, to forgings, to
small electronics and assemblies – these all need to come together in the automotive value chain.”
calls an ‘Indian reality’.
In short, the Indian automotive
In India, he explains, there is an
pyramid
extremely large and mature base of
Tier 1 and Tier 2 suppliers, with
examples along the entire length of
the value chain, from steering and safety supplier Rane Group, to rearview mirror manufacturer SMR. These
suppliers, he says, serve OEMs all over
the
world,
and
their
industry bottom heavy, a wide-based filled
with
important
suppliers who, nevertheless, work with limited resources and under huge
price
pressure.
Simply
suggesting an operation ditch its existing set-up and purchase a set of
new machines, says Dutta, is not a viable option.
manufacturing operations reflect this.
As such, Siemens’ job is to find a way
real difference lies.
machinery. “For example,” he says,
Beneath them, however, is where the “There is a huge tail of Tier Three, Four
and Five suppliers which need to transform the way they do business,
and adopt digital technologies if the
Indian automotive environment is ever going to undergo a real digital transformation,”
says
Dutta.
“Compared with markets in the
www.automotivemegatrends.com
of
enabling
inputs
on
dated
“there are sensor technologies that can
be
retrofitted
today
which
will allow current analogue machines
is that technology itself is not the Industry 4.0, because technology is always changing. What is more important, he says, is framework,
which in Siemens vision is composed of three major components. Each corresponds with the three major
parts of a vehicle’s life, namely design, production and use. Digitalisation
creates for each of these a digital twin – a virtual copy of a real-world
machine or system. Changes in the latter can be immediately mirrored in
the former, and simulations can be run within a digital twin to improve efficiency and solve problems.
A digital product twin, for example, assists designers by helping them quickly come to terms with customer
requirements and bring products to market quickly. This could also include digital
validation
tools,
allowing
designers to validate something before its even manufactured.
helping
Of the three twins, digital product
But exactly what systems could
Dutta, with the concept having
to
collect
digital
data,
owners to make quicker decisions.”
this data be fed into which, in turn,
could revolutionise the country’s automotive sector?
twins are the most mature, says existed for over ten years. However, systems integration, he says, means
that digital product twins are more
57
Industry 4.0
“
Essentially, the machine is learning decisions made by human beings, and in turn, it will create and find solutions to its own scenarios using logic from past scenarios important than ever for suppliers,
Suppliers
requirements continue to tighten.
twins. Even a simple system like a
particularly “Today’s
“
as
time-to-market
suppliers
are
being
hit by huge challenges on the development front,” he says, “as they
are no longer making single-science products,
but
multidisciplinary
ones which combine electronics,
hydraulics, mechanics and software. Today, OEMs want subsystems off their suppliers.”
will
also
benefit
from
increased use of digital production windshield
wiper,
says
Dutta,
including
suppliers
from
the lower tiers, all with different
delivery timelines. Digitalisation could synchronise these timelines.
by the inclusion of a feature such as
Digital production twins also allow for
to rain. The system then requires
making substantial investments in a
automatic wiping when it starts sensors to detect changes in weather, and software to instruct the wipers
how to run. The supplier is then
working with perhaps three different
For OEMs, mass customisation is one of the big drivers behind digitalisation. One line for one platform is no longer good enough
58
is
suddenly made far more complicated
teams,
simulation of a factory line prior to system. This assists in detecting
faults, and in the future, sensor data
on the line can suggest actions to improve efficiency and output. This will be a priority for OEMs, says
Dutta, as they are the ones who have the
most
manufacturing
issues,
particularly at a time when customers are asking for customisation at massmanufacturing prices.
“For OEMs, mass customisation is one of
the
big
drivers
behind
digitalisation,” says Dutta. “One line
for one platform is no longer good
enough. They need to monetise their capital
investment
infrastructure
can
by
ensuring
manufacture
Automotive Megatrends Magazine
Industry 4.0 multiple
models
and
variants.”
Digitalisation makes this possible by enabling OEMs to explore complex manufacturing layout options.
“
The
final
twin
is
the
digital
performance twin, which Dutta says will underpin some of the emerging
megatrends seen in the automotive industry, which in turn will change
the way other real-world businesses operate. “The world is now looking
at extreme electrification of vehicles,
The world is now looking at extreme electrification of vehicles, as well as greater autonomy, and a shift towards shared mobility. These new technologies on the road need to be supported throughout their lifecycle
as well as greater autonomy, and a
and used by the production twin to
simply millions of combinations,
says, “and so whilst digital product
manufacturing methods.
were all available digitally, they might
and digital production twins are important,
they
aren’t
enough.
These new technologies on the road
need to be supported throughout their lifecycle. This is what the performance twin enables.”
The performance twin could enable an age of what Dutta calls ‘prescriptive maintenance’, preventative
as
opposed
maintenance.
to
By
combining data on the part with data
on the driver’s style and usage on the
road, a performance twin can schedule maintenance months in advance. In
can
turn,
the
signal
performance
issues
with
twin
the
production twin. Data gathered on the road can be sent into the cloud,
www.automotivemegatrends.com
improve on existing designs and
Leaving the decision making to the machines?
realities and scenarios, and if they
require very little redefining in future. A machine could look at a problem
and, delving into a digital library, see how it was solved in the past.”
But as Dutta correctly observes, data
This is the role of machine learning in
must first become information, and
the machine is learning decisions made
does not equal knowledge. Data information must be interpreted before it becomes knowledge. To
date, this has largely been the job
of humans, but artificial intelligence
(AI) and machine learning could
take on fundamental design and manufacturing decision-making tasks. “Imagine how many decisions are being taken every day to meet certain requirements
in
the
automotive
industry,” says Dutta. “There must be
Industry 4.0, says Dutta. “Essentially,
by human beings,” he explains, “and in turn, it will create and find solutions to
its own scenarios using logic from past scenarios.”
Improvements
in
capabilities could prove exponential, and
as
Dutta
concludes,
this
learning
and
Images courtesy of Siemens AG
shift towards shared mobility,” he
demonstrates the intrinsic relationship between
machine
Industry 4.0 - without digitalisation, machines would have neither the data nor the means to receive it to strengthen their performance.
59
High-definition maps
HD mapping ‘takes ADAS to the next level’, says TomTom Enabling an autonomous vehicle to know precisely where it is in real time via HD mapping will not only assist with navigation, but also consumer adoption of autonomous driving. By Freddie Holmes
E
partially
are the road markings obscured, is
work in tandem with various other
system today can be both
that its high-definition (HD) map
autonomous system. “We don’t see HD
xperiencing automated
a
highway
driving
rewarding and stressful at times. While
in most scenarios these systems are highly
capable
within
lanes,
at
controlling
acceleration, braking and steering
“
any
sudden
or
unexpected changes to the driving environment can occasionally spook the system.
One of the factors behind this issue is
that the car currently relies on visual
there ice on the road? TomTom believes
technology can make all the difference and avoid situations where the car deems it necessary to disengage a partially or fully automated feature, and
hand control back to the driver without warning.
While
these
systems
emphasise that driver monitoring is
required at all times, such instances can erode
consumer
confidence
automated capabilities.
in
information, with very little context
TomTom recognises that HD maps are
on up the road; is the bend too tight,
and as such have been designed to
about what it might encounter further
not a silver bullet to the issue, however,
technologies as part of a complete maps as standalone products. They
don’t exist in a vacuum and must be
used as part of the automated system
in a vehicle,” explains Tomaso Grossi, Senior Product Marketer at TomTom
Automotive. “We believe in a closed loop system, whereby we produce the
most accurate, robust and reliable maps in the Cloud, deliver these
systems to the car, and then leverage multiple sources – such as different types of vehicle sensors – to ensure
this map is up-to-date, safe and matches reality.”
HD map information helps to take ADAS to the next level; if you can build a system that leverages HD maps to make the car safer, more comfortable and more aware, then trust and driver adoption in these systems will increase
60
Automotive Megatrends Magazine
“
High-definition maps
The ability to scale up and produce these maps in a highly efficient way whilst maintaining accuracy, robustness and reliability is key
Constantly evolving One
of
the
issues
with
in-car
navigation systems today is the lead-
time between a change to the road network – be it traffic, road works or a crash – and an update being validated
and issued. For the driver, this means that the in-vehicle map frequently becomes out of date, and TomTom believes this needs to change.
“The map is a living and ever-changing,
ever-updating system,” says Grossi.
“We’re exploring and experimenting
map with lead times of just under a
sufficient for most roads. “There will
primary goal in some instances. For
the class of road and where these
week, but real-time updates are the example, it is not strictly necessary for real-time updates to the entire map in
one go; certain sections of road
networks change far less frequently than
others.
Controlled
access
highways, for instance, are the least variable types of roads, with the
addition of new lanes and lane markings
occurring
quite
rarely.
Conversely, city roads tend to see the highest variation of changes.
with multiple sources to keep the map
While the ideal goal is for real-time
to feed it back into vehicles, ideally in
has found that – based on its
up to date, and using data in the Cloud real time.” Initial targets are to be able
to completely refresh and validate the
www.automotivemegatrends.com
updates across the board, TomTom expertise in navigation maps – a cycle time of a few days or even a week is
be different lead times depending on roads are located,” explains Grossi.
“Depending on how often these roads change, we’ll need to have the map
updated as quickly as possible. We already are taking this challenge head
on with the typical maps we use in navigation systems today.”
TomTom has been collecting data through its RoadDNA technology, one of the core elements to HD mapping, which will allow autonomous vehicles
to become aware of their environment,
location and path on the road. Certain
roadways in mainland Japan, the US
and Western Europe have already been mapped out using this technology, and
61
High-definition maps TomTom believes its HD map technology can avoid situations where the car deems it necessary to disengage a partially or fully automated feature, and hand control back to the driver without warning
it is being leveraged by several OEMs’
autonomous prototype vehicles. As it
stands, just over 380,000 kilometres of roadways across these regions have HD
map coverage, up from 250,000 kilometres globally as of March 2017.
TomTom is not the only player developing
advanced
mapping
technology, and a handful of start-ups are investigating how such systems can
support autonomous vehicle systems. Localised HD map coverage may benefit
Building trust
dangers, but also leverage real-time
There are three primary use cases for HD
maps:
supporting
accurate the
localisation,
environmental
perception of vehicle sensors, and the
ability to plan the path of the vehicle as
accurately
and
efficiently
as
possible. In short: to ensure the car knows where it is, where it is going, and any issues that may affect its course on the road.
understanding of road conditions out of sight. While autonomous vehicles of Level 4 and 5 capability on the scale developed
by
the
Society
of
Automotive Engineers (SAE) are some way off, there will be many drivers
today that desire an improved semiautonomous
experience.
Grossi
advises that TomTom’s HD maps and RoadDNA software can also assist the advanced driver assistance
systems (ADAS) that underpin highway
those testing vehicles in specific areas,
“It’s about making the system safer,
deployment of autonomous vehicles,
into the system,” says Grossi. “Most
“Our technology extends the car’s
autonomous systems on the market
and allows it to anticipate what might
but in order to facilitate widespread these maps need to go national, if not global in future.
“The ability to scale up and produce
these maps in a highly efficient way whilst
maintaining
accuracy,
robustness and reliability is key,” says
Grossi. “If you look at the current
more comfortable, and building trust people
that
have
tried
semi-
today, or who have had a ride in an autonomous
vehicle,
are
very
enthusiastic about the technology. But
at the same time, they are also aware of the limitations.”
ecosystem of autonomous driving,
Regulations and technical developments
important. New players are entering
systems is expected to be one of the
maps are becoming increasingly
this area, but many of these start-ups
have an approach that is maybe not as scalable. When it comes to OEM
demands, they might fall short in terms of scalability and robustness.”
62
aside, trust in autonomous driving main factors that influences consumer
adoption of the technology. HD maps are believed to be a vital element to
the overall system in ensuring that the
car can not only anticipate potential
pilots today.
view beyond the range of it sensors, happen. The car may be travelling at
a particular speed toward a certain
curvature in the road, and it would be more comfortable and safer if the car
slowed
down
in
advance,
rather than reacting at the last
minute,” he concludes. “HD map information helps to take ADAS to the next level. If you can build a
system that leverages HD maps to make
the
car
safer,
more
comfortable and more aware, then
trust and driver adoption in these systems will increase.”
Automotive Megatrends Magazine
Sensor cleaning
Clear vision needed to make AVs a reality So simple, yet so critical - keeping optical sensors clean means keeping vehicle occupants safe. By Megan Lampinen
I
promise
approached with a request to help
more relaxing in-car experience,
military vehicles. This was part of the
ntelligent
vehicles
tremendous safety benefits and a
but their intelligence relies entirely on accurate data. Sensors are the star
players in today's highly automated vehicles,
providing
pivotal
visual
information on the surroundings and environment. But if anything were to
Defense Advanced Research Projects Agency
(DARPA)
Challenge,
a
competition around revolutionary
research in support of autonomous ground vehicles.
interfere with the provision of that
"We started playing around and
capabilities could not perform.
and technology to that application,
data,
these
numerous
smart
'Sensor malfunction active safety functions disabled'
The problem is, things do happen to these sensors in the course of vehicle
use. Mud splatters up on them. Bird
applying our traditional nozzle designs
but they never really reached a point of
commercialisation,"
explained
dlhBOWLES' Russell Hester, Director of Business Development. "It wasn't
until about five years ago that we started to see an interest in cleaning the cameras on modern vehicles."
droppings fall from above. Even heavy
Early adopters
message: 'Sensor malfunction - active
Ford was an early adopter and the
sensors clean is a serious business,
wash nozzle. The system uses the
rain has been known to prompt the
safety functions disabled'. Keeping and one in which dlhBOWLES has invested
significant
time
and
resources. The company started out
providing the nozzles that spray cleaning fluid on the windshield and headlamps but took a new direction in
2004. At that time, the US government
www.automotivemegatrends.com
clean the sensors on autonomous
first to launch the company's camera
same traditional washer fluid for cleaning the cameras as it does for
cleaning the windshield. As this
contains an antifreeze component, it can help with the removal of ice and
snow as well as elements like mud, dirt, insects and pollen.
63
Sensor cleaning Obscured sensors can be as dangerous as a malicious hack
“
There will come a time when the sensors themselves will self-evaluate and they will be able to detect that there’s something obscuring their view, activate the washer pump, and the washer pump will spray off that debris
"Ford has now begun to proliferate
have a rear camera. That camera will
dlhBOWLES isn't the only company
platforms," Hester added. So, too,
Attention has recently begun to turn
technology, but it does believe it has
that
on
many
of
its
vehicle
have a handful of others. Today, dlhBOWLES cleaning
provides
systems
for
camera
about
25
vehicle platforms in production. New legislation in the US could prove a
major boom in business - as of May
2018, all new vehicles are required to
64
need to be kept clean somehow. to other optical sensors, namely LiDAR, that are finding their way onto
vehicles in support of advanced driver assistance systems (ADAS). "We are
applying that same methodology and philosophy to clean those optical sensors," Hester noted.
out
there
providing
cleaning
an edge on the competition, as its
system consumes less fluid than competing technology. "That might
not sound significant, but when you’re
dealing
with
the
weight
associated with carrying around
extra washer fluid in the sensor
Automotive Megatrends Magazine
“
Sensor cleaning
When a bug is splattered on the windshield, a human driver can move his head and look around the bug. But for a camera or sensor, that single insect can obscure the entire sensor or half the sensor, easily. If that’s a critical sensor that the vehicle is using to navigate, it’s driving blind
systems, that becomes a larger issue
perhaps the OEMs… They would be
said,
he
camera algorithms are doing the
or how the OEMs themselves decide to
for the vehicle platform engineers," emphasised.
Its
system
consumes, on average, about 30% less than rival offerings.
Most of the camera wash systems today are manually activated by the
driver but this will change. "There will come a time when the sensors themselves will self-evaluate and they will be able to detect that there’s
something obscuring their view," predicted Hester. "At that point they will activate the washer pump, and
then the washer pump will spray and clean off whatever that debris is."
Ford already offers automatic lens washers with the front and rear
cameras on its Edge and Explorer
models, and the technology was
flagged by Forbes as one of the 'hottest new-car features' at the end 2016.
The
responsibility
object
detection.
for
providing that functionality doesn't lie
with dlhBOWLES, however. "That would probably fall to the sensor
supplier, the camera manufacturer or
www.automotivemegatrends.com
That
same
programme would be responsible for deciding
Towards autonomy
of
writing that software and ensuring the
when
the
sensor
was
the
specific
way
that
the
customers are packaging the sensors style the sensors into the vehicle might pose their own challenges."
operating in a degraded state,"
No room for mistakes
Lead Engineer - Camera & Sensor
There's little room for mistakes in this
straightforward, in that it is continually
system
elaborated Zach Kline, dlhBOWLES' Wash.
"LiDAR
is
a
little
more
providing distance measurements. If you have a persistent reading one inch in front of a sensor, then it can determine there is something on the lens and it needs to self-clean."
However, very little change would be required in the technical functionality
of the cleaning system to make it applicable
for
fully
autonomous
vehicles. "If you took a current Ford
area, as a malfunctioning cleaning could
implications.
have
"When
a
serious
bug
is
splattered on the windshield, a human
driver can move his head and look
around the bug. But if you’re talking about a camera or a sensor, that
single insect can obscure the entire
sensor or half the sensor, easily. If
that’s a critical sensor that the vehicle
is using to navigate, it’s driving blind," warned Kline.
or BMW sedan and you wanted to
Obscured
would take very little from a sensor
even more so. As an example, Kline
make that an autonomous vehicle, it cleaning standpoint to get that up
to snuff. That’s where our decades
of experience comes into play optimising the spray and integrating
the new cleaning system into the preexisting system," said Hester. "That
sensors
can
be
as
dangerous as a malicious hack - or
likens mud on a sensor to deliberate road
sign
manipulation.
Vehicle
detection systems must be able to
see clearly any road signs before they can correctly classify them. Hacks
have shown that something as simple
65
“
Sensor cleaning
Those situations with graffiti or stickers on a road sign are clearly very difficult for the vehicle to sort out. The same problem exists if you have a smudge of dirt on the camera as it’s looking at a stop sign. That just highlights the importance of keeping that sensor clean all the time
as graffiti or stickers placed over a
Sensor fusion is another big trend
on using three LiDARs and six HD
into incorrectly classifying or ignoring
dlhBOWLES'
portions of the vehicle," explained
sign can trick an autonomous vehicle
it. "Those situations with graffiti or stickers on a road sign are clearly
very difficult for the vehicle to sort
“
that
could
potentially
strategy,
shape
and
the
redundancy provided could help with challenging situations.
out. The same problem exists if you
"There could conceivably be a bit of
as it’s looking at the stop sign," he
sensor
have a smudge of dirt on the camera
explained. "And it’s not just that one
stop sign, it’s every stop sign the vehicle sees. That just highlights the
importance of keeping that sensor clean all the time."
debris within the view of the optical and
it
could
potentially
misunderstand what an object is
cameras at different views on different Hester. "That redundancy will be absolutely necessary in addition to what we believe is necessary with the cleaning systems that we produce."
In the interim
due to that. However, sensor fusion
Before fully autonomous vehicles
can generate a three-dimensional
however, there will be an interim
is
being
discussed,
where
you
landscape of the surroundings based
There could conceivably be a bit of debris within the view of the optical sensor and it could potentially misunderstand what an object is due to that
make their way onto public roads, period in which cars operate at lower
levels of autonomy. In these cases, drivers will need to actively monitor the
vehicle
while
it
performs
certain functions itself. It is in this
interim environment that dlhBOWLES sees
considerable
its technology.
potential
for
"The vehicle will need to verify that the driver is awake or at the very
least is present. There will be
cameras on the inside of the vehicle
to do that, and there could be some scenarios where we take our air-blow
nozzles and clear potential dust or
debris that occur on the inside for these sensors," concluded Hester.
66
Automotive Megatrends Magazine