Automotive Megatrends Magazine - Q1 2018

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ARE WE READY FOR AUTOMOTIVE AI?


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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


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THE H FU UTURE OF DRIVING NOW W

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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


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