National University of Singapore students presented on autonomous vehicles, including their evolution, enabling technologies like sensors and connectivity, infrastructure needs, and entrepreneurial opportunities. Key points discussed include autonomous vehicles producing large amounts of data, 5G enabling low latency required for applications, dedicated lanes and platooning potentially increasing road capacity, and autonomous vehicles reducing fuel costs, traffic, and accidents while creating new business models.

1. National University of Singapore
Kartikey Joshi
Dhivya Sampath Kumar
Rahul Mehta
Shiva Muthuraj
Autonomous Vehicles (AVs)
Technology,
Economics, and
Opportunities

2. Evolution of Autonomous Vehicles [AVs]
Technologies enabling AVs
Connectivity for AVs
Infrastructure for AVs
Applications & Entrepreneurial Opportunities
Outline

3. Knight Rider will soon become a reality
Autonomous car
in Knight Rider,
1982
Autonomous Vehicles and Cars??

4. Vehicles are evolving rapidly
Cheaper electronicsTechnological innovations
Drivers to evolution
1807 2030?
Sensor prices reducing over last 25 years

5. Connected Vehicles
220 million connected vehicles by 2020
Market growing with CAGR = 45%
Who is interested?
Autonomous VehiclesEvolution continues
$2.3 Trillion market by 2020
180,000 autonomous vehicles by 2020
Market growing with CAGR = 271%
Why autonomous?
- Safer roads
- Lighter cars
- Faster transportation
- Better productivity
- Added streams of revenue
- Entrepreneurial opportunities
Vehicles are evolving rapidly

6. How can we reduce the cost?
- Reduce number of vehicles
AV : With 90% AV penetration, number of cars on the
road reduces by 42.6%
Passenger cars are idle for >90% of time
- Reduce congestion/increase throughput
AV : eco driving to maximize vehicle flow
- Reduce accidents
AV : eliminate human error
Why Autonomous Cars?
per-mile extra costs per automobile
~1.2 billion cars in the world
~20,000 miles average annual car usage
Range of potential fuel economy improvements for
conventional, hybrid & autonomous cars
Human error causes 90-93% road accidents
Extra costs from car usage > 2Trillion USD!
GDP of India ~ 2Trillion USD

7. Key sensors/components for AVs
Advanced driver assistance

8. Technological/Economical facilitators:
Market value of sensors for AVs
- Big chunks of share taken up
by Ultrasound sensors,
cameras, Radars, Surround
cameras
- Long distance cameras and
LIDAR show growth but share
is much smaller
- Are there cost drivers to
market share?
- Are there technology barriers
to market share?
Global Advanced Driver
Assistance Market
-Market is expected to reach
$60.14 Billion by 2020
Growing at a CAGR of 22.8%

9. Rising Sophistication of Sensors
- Level 1 and Level 2 require the sensors that dominate market
share
- Level 3 onwards, no additional type of sensors incorporated
- LIDAR, Long distance camera, IR cameras incorporated beyond
level 3
- Ultrasonic, Radar and surround camera technologies are well
developed
- LIDAR required for higher level of automation
- Cost of LIDAR is major roadblock
Sensor capabilities in
providing assisted driving

10. Why LIDAR for AVs?
- Most accurate perception sensor, provides:
• 3D shape with height/width information
• Distance with high accuracy
• Orientation
- Currently LIDAR is only acceptable technology for object detection in
autonomous vehicles.
- Sensors that help avoid collision with 99% accuracy are NOT
acceptable

11. Real time 3D mapping with LIDAR

12. - Costs of LIDAR are reducing : research impetus
- From $70,000 to $8000 in 3 years (Velodyne)
- More players entering market for LIDAR development
- Prices may be driven by competing technologies also such as wireless
communication systems, dedicated roads for AVs etc.
- Quanenergy has announced solid state LIDAR priced at 250$
- By 2018, prices expected to reach 100$ !!
Cost barriers to LIDAR adoption?
Velodyne Puck ($8000)

13. Cost of Self-Driving Car Feature Self-Driving Car Volume Forecast
Autonomous Vehicles - Falling Cost, Rising Volumes
• Cost is key hurdle of Google’s self driving car
• Cost ~ $200,000 to build in 2014
• By 2015, cost reduced to $50,000
• Further reduction as technology matures and volume increase
• Look out for cost to reach $7000. Will lead to rapid adoption
What are the other major drivers for AVs? Leverage connectivity?

14. Connectivity for Autonomous Vehicles

15. Revenue Opportunities by vertical IoT segment
According to harbor research,
global IoT market could hit $ 1
trillion in 2020 with CAGR of
30% over the period of 2014-
2020 with applications in every
sector of economy
Question to North
American auto industry:
What percentage of
cars will include the
following components
in future?

16. Simplified Automated Vehicle Model
IoT sensor fabric for
V2V
Everything in the mesh
can see each’s sensor
data mesh across Cloud,
3G, DSRC, Wifi,
6LoWPAN
Intelligent Vehicles are a set
of agents which integrate
multi-sensor fusion-based
environment perception,
modeling, localization and
map building, path
planning, decision making
& motion control
Connected Car is a big data
Problem
• New cars produce 5GB/hr
sensor data
• 60M cars manufactured
each year
• If driven 4hrs a day then
438 exabytes

17. Automotive: Big Data User on the IoT
• Cloud services reduce the
time to market and
simplify updates.
• Network rollouts of 5G
have been very fast and
are still accelerating.
• In ten years, everything
will be Cloud.”
Connected car/AVs subscriptions forecast
Acceleration in connected car sales, from 10M
subscriptions today to nearly 40M in less than 5 yrs
Car on the Cloud

18. Autonomous cars will produce 1GB data/sec
Data accumulated from other cars/systems – cloud access
The transportation industry has an annual business potential
of 720-920B USD through Big data
Smart car of the future is part of a gigantic data-collection
engine
Data sources:
- Interact with other cars
- Learning algorithms – AI, neural networks
- IOT and cloud access with other devices
Real time route optimization : traffic data, population/
demand data, public transport data
Big Data for Autonomous Vehicles
Open data can help unlock up to $5
trillion in economic value

19. Technological facilitators: Bandwidth evolution
-Need to manage huge amounts of data
-Ethernet cuts cabling costs while
increasing data transfer speeds
-Ethernet penetration in new vehicles
will grow from 1% in 2014 to 40% in
2020
-OPEN (One-Pair Ether-Net) Alliance
now has over 200 members after being
founded in 2010 by BMW, Broadcom,
Freescale, Harman and Hyundai.
-Better network security features
protect the car from malicious attacks,
eavesdropping and the installation of
non-service-approved devices.
Evolution of Network Bandwidth
Source: 2013 Broadcom Corp.

20. Typical Mobile Bandwidth &
Latency - Existing Networks (2013)
Theoretical Bandwidth &
Latency
Bandwidth & Latency
-The table shows the
estimated bandwidth and
latency required for AVs. For
ex. The Multimedia section
would require high bandwidth
which can be performed with
medium latency.
-From the graph below, it can
be seen that with 5G services
in future [2020s] the latency is
expected to fall below 0.1 ms
- AVs can become the main
market for 5G services [IoT]

21. How much Data and what to look for?
Exponential data growth between
2010 and 2020
- Predictive capacity planning
Excess capacity reduces profitability, capacity
shortage impact quality
Big data to predict trends in advance to boost
profits
Demand for food delivery in a certain area during
peak hours?
Demand for cabs for commuting during peak
hours?
Find out co-travellers for car pooling?
Demand for parking spaces at a given place/time?
Waiting time at fuelling station for cars?

22. Who is interested in big data for automotive domain?
… Across core competencies and many more
Nokia navigation system
Currently Nokia is developing an interface for route
planning which accounts for traffic and road conditions

23. Optimized routes : Many intangible benefits such as lesser traffic mishaps, lesser time
of travel, more productive individuals.
As much as a day per week can be saved on time through route optimization :
Happier employees
Value to business?
By analyzing over 14 Million taxi trips taken in
New York City it was found that if people are
willing to experience up to five minutes delay,
almost 70% of the rides could be shared.
~70% lesser pollution, ~70% more free roads
Fuel savings also through optimized routes at
peak hours
UPS (United Parcel Services) saves 50M USD in
fuel through route optimization and gains ~35M
hours of idling time (Forbes magazine)
Source: Big data lab

24. Big data in AVs to provide better data:
- Collecting valuable information about customer behaviour and choices.
- Identify customers on an individual basis by knowing where customers are likely to go
and what places they like to visit.
- Take customer service to a level such as partnering with hotels, restaurants, retail
outlets and offering special discounts.
Safety and smaller insurance costs:
- AVs will know in advance about road breakdowns, slipper roads, ice/potholes ahead
- Ability of vehicles to communicate with each other is a key factor in all of this
- Smaller insurance premiums
- Data analytics to provide predictive capabilities to AV intelligence systems
Smaller parking spaces: In the US there are 4X parking spaces as the number of cars.
Business value through usage of space for revenue generation.
- Data analytics provide insights on the optimum requirement
- Vehicles on road that need parking can be segregated from those that may only ferry
from source to destination
Value to business?

25. Why Publish/Subscribe for Sensor Networks
• Sensors and apps may be added/removed
at any time
• Bridging of heterogeneous wireless
networks
• Inherently multicast
• Real-time delivery of data ex. Alarm events
IoT Protocols

26. What can go Wrong? Functional Safety
• Functional safety is the absence of unreasonable risk due to hazards caused
by malfunctioning behavior of electrical/electronic systems
-Hazards: potential source of harm
-Harm: physical injury or damage to the health of people
• Failures are main impairment to safety:
-Systematic: failures that can only be eliminated by a change of the design or
manufacturing process
-Random: failures that can occur unpredictably during lifetime

27. Researchers hacked a model S, but Tesla’s already released a patch
Wireless Car Hackers

28. Connected Car and Cyber Security
Remote reprogramming
If the car makers can do remotely reprogram
computers, so could hackers. With public signals, such
as for “smart” traffic lights that communicate with
cars, on the horizon, the public cloud will be a major
source of vulnerabilities
Vulnerabilities of
diagnostic interface
Vulnerabilities of
Onboard networks,
devices & Apps
Vulnerabilities over
V2I communications
Malware attacks thro
Communication
channels
Vulnerabilities
of V2V
Communications
Vulnerabilities
of local
communications
Possible security approaches
• With fixed designs, heavy onboard processing
and large database is required that raise
trustworthiness issues if downloaded from the
cloud. With a heuristic protection approach,
there is even heavier processing needed.
• With cloud-based system there could be a
communications overload imposed on the in-car
hardware, with long delays for file execution.
• A continuous connection from the car to the
cloud would be impractical. The software still
would have to determine the trustworthiness of
threat messages and decide which malware it
sees is relevant to the car.
• Virtual private networks (VPNs) provide good
security and can be turned on, on a needed basis.
Long life for vehicle modules necessary
Replacement parts pose problem. There
might have to be configuration keys that
would allow parts to interact with the rest
of the system, and the parts would have to
be programmed to the same level of
security, a how-to-do question for
aftermarket manufacturers.

29. Security to the vehicle, Entry Point, Into Vehicle
• Bridge between external &
internal networks
• Reduce the attack surface
area − Isolate trusted
resources in hardware
• Gateway functionality −
Aggregate many protocols down
to a few (e.g. CAN, Ethernet)
• Secure comms link up the tree −
Physical: Central / Domain GW −
Virtual: e.g. Chassis ECU (PSI5)
• Security features become
greater proportion of cost

30. • An integrated network of driverless vehicles could include self-driving taxis and autonomous car sharing.
• A network of autonomous vehicles could make it viable to introduce smart expressway lanes, on which the
vehicles move in platoons to increase throughput of the roads.
• Smart parking systems could also be implemented, whereby driverless vehicles drop their passengers off,
go find a parking space themselves and park closely to each other.
• This saves space while potentially rendering parking offences a thing of the past. Other applications may
include driverless commercial vehicles that ply in the middle of the night to optimize road space.
• This would save manpower on drivers and minimize traffic congestion.
Singapore's Next Step to dedicated Highway lanes for AVs
Roads
for AVs

31. Dedicated Roads for AVs
• To improve safety, we need to accumulate the number of sensors which increase
cost and vulnerability because of the complexity
• Dedicated roads lead to less number of sensors in the AV resulting in lower cost
• Allow vehicles / infrastructure to communicate and respond.
• Elimination of traffic lights via Intersection movement assist
• Higher Speeds and Fuel Efficiencies by dedicating roads to AVs
• Less Traffic light delays from 100% human to fully autonomous
Average safe inter-vehicle distance (m)
Vehicle speed (km/hr)
Highway capacity (vehicles/hour/lane)
Vehicle speed (km/hr)
Highway capacity
(vehicles/hour/lane)
% communicating vehicles

32. • Average Annual Kilometers travelled by cars = 17500 Kms
• Average fuel efficiency = 6 litres per 100 KMs
• Total fuel estimate per car annually= 1050 Litres
• Taking 3% inflation rate with current price of fuel 2.15 S$ per litre resulting in cost of
Petrol per Litre = 2.5 S$ (Total cost equal to 2625 S$)
• Potential Fuel Economy of Level 4 AVs with dedicated Lanes = 150 miles Per Gallon
• Total fuel estimate per car annually for Level 4 AVs = 290 Litres resulting in higher annual
cost savings (Total cost equal to 725 S$)
Average Annual KMs Travelled per Vehicle in
Singapore
2013 2014
Cars 17,800 17,500
Private Hire Buses 51,800 54,400
School Buses 54,100 53,400
Light Goods Vehicles (<=3.5 tons) 30,000 30,500
Heavy Goods Vehicles (> 3.5 tons) 38,100 39,900
Motorcycles 12,900 12,800
Current Scenario in Singapore
Index - Singapore
• Traffic Index: 159.12
• Time Index (in minutes): 42.29
• Time Exp. Index: 2,358.07
• Inefficiency Index: 167.38
• Traffic CO2 Emission Index : 3,062.13
Due to travelling to work/school, per passenger is produced yearly 734.91 Kg of CO2. It
is needed 8.57 trees for each passenger to produce enough oxygen to cover that.

33. Cost of Road Accidents
• 160 Fatalities = 4394880 USD
• 9800 Injuries = 68600000 USD
Fatal Serious
Injury
Slight
Injury
Property
Damage
Per Casualty
Lost Output 902,362 47,578 5,468
Medical Costs 12,760 30,668 4,656
Pain, Grief, Sufferings 358,124 87,069 1,779
Total 1,273,246 165,315 11,903 0
Per Accident
Administrative Cost 22,044 3,425 2,278 445
Property Damage 5,424 5,424 5,424 5,424
Total 27,468 8,849 7,702 5,869
Summary of costs per casualty or per accident ($)
Road Accident Casualties in Singapore
2013 2014
Fatalities 160 154
Injuries 9,751 9,835
• Cost of Car Insurance - quite variable over the lifetime of your policy as driving experience, policy
amendments and accidents have an effect on your premiums.
• For a safe driver, the insurer gives 10% No-Claim Discount (NCD) after every year - without incident (up to
the maximum 50%).
• Based on an initial car insurance annual premium of S$3,600 (excess S$1,000) for a comprehensive policy,
overall insurance premiums over 10 years will be…Overall cost of your auto insurance =
S$24,520 (factoring NCD)
• Morgan Stanley indicate that human error has been the main determinant in over 90 percent of these
accidents which will be eliminated for AVs with dedicated lanes
• Insurance cost going down to 90 percent – resulting in 245 S$ roughly
Accidents and Insurance statistics for Singapore
Transactions on the Built Environment vol 64, © 2003 WIT Press, www.witpress.com, ISSN 1743-3509

34. You will spend more time doing the things you love, not driving
What else, if not driving?

35. Productivity gains
Will improve productivity as people will be able to work in their cars in route to work, meetings, etc.
• Singapore's GDP per Hour = 41.46 USD
• Average Speed of Cars = 51 Km/hr
• Results in 350 Hours per year equivalent to 14511 USD (doesn’t consider the parking time)
Congestion savings-Referring to reports by European commission that congestion costs 1 percent of
GDP
Road Traffic Conditions in Singapore
2013 2014
Average Daily Traffic Volume
Entering the City
289,000 300,400
Average Speed during Peak Hours (km/hour)
Expressways 61.6 64.1
Arterial Roads 28.9 28.9

36. Mercedes-
Benz E300
Hybrid (Cat
B, hybrid)
Taxes in Singapore
• If a car's engine capacity is 1,600cc, the Road Tax is S$ 600 per year while the same which is roughly
3500 Pounds.
• AVs with dedicated roads will dramatically reduce the number of accidents leading to go for even pod
like cars weighing just 250 pounds and requiring much lower engine cc requirements.
• Also carbon emission will be much lower comparatively in the range of A1.
• The poor traffic index of Singapore will be improved drastically
Engine Capacity (EC)
in cc
From 1 July 2008 to
31 July 2015, and
from 1 August 2016
From 1 August 2015
to 31 July 2016 (with
20% rebate
EC <= 600 S$ 200 X 0.782 S$ 200 X 0.6256
600 < EC <= 1000 [S$ 200 + S$ 0.125 (EC –
600)] X 0.782
[S$ 200 + S$ 0.125 (EC –
600)] X 0.6256
1000 < EC <= 1600 [S$ 250 + S$ 0.375 (EC –
1000)] X 0.782
[S$ 250 + S$ 0.375 (EC –
1000)] X 0.6256
1600 < EC <= 3000 [S$ 475 + S$ 0.75 (EC –
1600)] X 0.782
[S$ 475 + S$ 0.75 (EC –
1600)] X 0.6256
EC > 3000 [S$ 1525 + S$ 1(EC –
3000)] X 0.782
[S$ 1525 + S$ 1(EC –
3000)] X 0.6256
Road Tax in Singapore
CEV Tax in Singapore

37. • Increase in vehicle population with drastic decline in the annual travel distance
• More use of public transport , Increased fuel price and less availability of parking space
• Resulting in less utilization of vehicle and more parked vehicles
Utilization of Cars in Singapore
Average Distance Travelled annually
Vehicle Population – Fatal and Injury
accident rate statistics

38. • Land used for Parking lots and cost charged to each user.
• Estimated that motorists spend on average at least 20 minutes to
secure a parking space in crowded areas, and 30 per cent of all
traffic in cities consists of people looking for parking.
• During peak hours, at an estimated 95 per cent motorists find it
difficult to find available spots that are hidden from view.
• Sulfation in batteries
Parking Woes in Singapore
Percentage of Time Cars are Driven Vs Parked

40. Farebox ratio is computed by total fare revenue over total operating cost. In rail comparison, depreciation cost is excluded
from operating cost. This indicator measures the financial viability of an operator without subsidy. A ratio above 1 suggests
that the operator is able to recover its operating cost (excluding depreciation of rail assets) with fare revenue.
Farebox ratio of Public Transport in Singapore
Singapore public transport has improved operating efficiencies due to their discounts during off peak travels and travel
passes. Still the farebox ratio is close to 1 and inclusion of depreciation would bring it less than 1 (indicating Loss)
Total no. of commuters exiting the 16 city centre stations on weekdays OFF-PEAK monthly travel pass

41. Heat Map of Taxis in Singapore
• Strategic use of data based on heat map to increase the efficiency of heavy vehicle transportation
• AVs used at public transport on the rest of the less crowded areas

42. Shared Autonomous Vehicles
Shared Autonomous Vehicles (SAVs): On-demand
chauffeur, minus the driver.
Pooled Shared Autonomous Vehicles (PSAVs): SAVs that
service multiple rides simultaneously.

43. • Personal travel costs will dramatically reduce
• Will be cheaper than the current public transport system
Shared Autonomous Vehicles

44. Estimated Cost Statistics of AVs
12:00 AM – 07:30 AM Available for Customers
07:30 AM – 08:00 AM Stand by for owner
08:00 AM – 08:30 AM Drive owner to work
08:30 AM – 09:00 AM Drive spouse to work
09:00 AM – 09:30 AM Drive kids to school
09:30 AM – 04:30 AM Available for Customers
04:30 AM – 05:00 AM Pickup kids from school, drive to soccer practice
05:00 AM – 05:30 AM Stand by for kids
05:30 AM – 06:00 AM Pickup kids from soccer practice, drive home
06:00 AM – 06:30 AM Drive owner home from work
09:00 AM – 09:30 AM Drive spouse home from work
12:00 AM – 07:30 AM Available for Customers
Reserved for owner
Shared car service hours
Schedule for an Individually Owned, Part Time Shared Autonomous Vehicle

45. • Optimizes supply chains and logistics operations of the future, as
players employ automation to increase efficiency and flexibility.
• In combination with smart technologies could reduce labour costs
while boosting equipment and facility productivity.
• A fully automated and lean supply chain can help reduce load sizes
and stocks by leveraging smart distribution technologies and smaller
AVs.
Autonomous Vehicles on Logistics

46. Driverless Car “Platooning”
The above graph is based on measurements
performed on a demonstrator system
consisting of five vehicles: a lead truck (LV), a
following truck (FV), and three following cars.
Fuel consumption by vehicle spacing and
platoon size % Fuel saving for a full platoon
Decreaseinfuelconsumption
Spacing in vehicle lengths

47. Driverless Logistics
• Labor savings would arise as driverless vehicles reduced the need for drivers.
• Fuel consumption savings would arise because computer-controlled vehicles drive in a more
efficient manner than those driven by people, thanks in particular to the practice of ‘platooning’.
• Insurance savings would arise if driverless vehicles proved less accident-prone. Insurers, who
bear the cost of accidents, would see those costs fall, and would be able to pass on the benefit
to the haulage industry in the form of lower premiums.
• Vehicle utilization savings would stem from the fact that driverless vehicles would be free of the
constraints imposed by restrictions on driver working hours and would thus be able to operate
more hours in a given day or week, and to drive through the night with greater safety for other
road users.
• The figures in the table below are the estimated annual cost savings per year by year 10 of
having introduced driverless haulage vehicles.
Low Case (where the saving to the haulage industry over ten years is at the lower end of
expectations)
High Case (where the saving is at the upper end of expectations)
Base Case, which sits between the two.
Labor Costs Fuel Costs Insurance Costs Vehicle Utilization
Low Case £734m £631m £853m £8.4bn
Base Case £1.5bn £1.4bn £1.1bn £1.7bn
High Case £2.2bn £2.2bn £1.7bn £1.7bn

48. Total savings in £ billions for Logistics Industry
Year 1 2 3 4 5 6 7 8 9 10 Total
Low Case Labor, fuel,
insurance
0 0.2 0.5 0.7 1 1.2 1.5 1.7 2 2.2 11.1
Vehicle
Utilization
0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 8.4
19.5
Base Case Labor, fuel,
insurance
0 0.4 0.9 1.3 1.8 2.2 2.7 3.1 3.6 4.0 20.1
Vehicle
Utilization
1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 13.5
33.6
High Case Labor, fuel,
insurance
0 0.7 1.4 2 2.7 3.4 4.1 4.8 5.4 6.1 30.6
Vehicle
Utilization
1.7 1.7 1.7 1.7 1.7 1.7 1.7 1.7 1.7 1.7 16.9
47.5
The financial impact of introducing a significant number of driverless heavy goods
vehicles on the UK haulage industry will be between £19.5bn and £47.5bn over the next
ten years, with total cost savings of £33.6bn over the ten year period as the base case.

49. How the Financial Impact of Driverless Technology
Could Affect The Consumer
• The annual savings from lower fuel, insurance and labor costs (base case)
would amount to over half of a person’s weekly retail expenditure or almost
one and a half weeks’ worth of groceries.
• In a High Case scenario, the savings roughly equate to a week’s total retail
expenditure or two week’s food shopping.
All items Food only
UK retail sales - £bn
Per annum 373.5 151.8
Per week 7.2 2.9
Annual Savings by scenario - £bn
Low Case 2.2 2.2
Base Case 4 4
High Case 6.1 6.1
Annual savings by scenario – as multiple of weekly totals above
Low Case 0.3x 0.8x
Base Case 0.6x 1.4x
High Case 0.9x 2.1x

50. Opportunities just ahead

51. Opportunities through AVs

52. • Connected-safety features bring in the most
revenue of all of today’s connected-car
services, at $13 billion. These features alert
customers of road conditions, weather,
collision-avoidance.
• Entertainment is one of the most popular
features available for the connected car
generating $13 billion in revenue in 2020.
Connected Car Revenue from providing systems
Mobility management
Functions that allow driver to
reach destination quickly, safely
in a cost-efficient manner
Ex: Current traffic information,
Parking lot/garbage assistance,
optimized fuel consumption
Vehicle management
Functions that aid driver in
reducing operating costs &
improving ease of use
Ex: Vehicle Condition & service
reminders, remote operation,
transfer of usage data
Entertainment
Functions involving
entertainment of driver &
passenger
Ex: Smartphone interface,
WLAN hotspot, Internet, social
media, Mobile Office
Safety
Functions that warn driver of
external hazards & internal
response of vehicle to hazards
Ex: Collision protection, hazard
warnings, emergency functions
Driver assistance
Functions involving partially or
fully automatic driving
Ex: Operational assistance or
autopilot in heavy traffic/
highways
Well-being
Functions involving driver’s
comfort & ability & fitness to
drive
Ex: Fatigue detection, automatic
environment adjustments for
alert, medical assistance
Product Categories

53. • Self-driving technology will create a new opportunity for the automotive value chain.
• Software will be the biggest autonomous vehicle value chain winner with $25 billion in revenues in 2030, a 28% CAGR.
• Optical cameras and radar sensors will amount to $8.7-billion and $5.9-billion opportunities in 2020.
• Computers will be the biggest hardware on board autonomous cars, amounting to a $13-billion opportunity.
• Prospective suppliers in the value chain should anticipate significant changes in both the inside and outside of the
vehicle over time, inevitably creating opportunities for new entrants. The electronics and software will become 50% of
car cost by 2030.
Software will capture the largest slice of autonomous car opportunity
Forecasted Revenues and Different Modules

54. Value
Value Players and Start-ups of Connected Cars
Worldwide distribution of
connected car start-ups
[Based on a sample of 250 start-ups]
Segment breakdown of connected car start-ups
Industrial Chain for Automotive
2022 2035
Margins are low for
Google, Apple etc. to
become car
manufacturers,
however they could sell
an autonomous pack to
transform each new
vehicle in a fully
autonomous car

55. References
1. M. Gerla; E. K. Lee; G. Pau; U. Lee, “Internet of vehicles: From intelligent grid to autonomous cars and vehicular clouds”,
IEEE World Forum on Internet of Things (WF-IoT), 2014, On page(s): 241– 246
2. Falchetti, Angelo; Azurdia-Meza, Cesar; Cespedes, Sandra "Vehicular cloud computing in the dawn of 5G", Electrical,
Electronics Engineering, Information and Communication Technologies (CHILECON), 2015 CHILEAN Conference on, On
page(s): 301 – 305
3. De Felice, M.; Calcagni, I.V.; Pesci, F.; Cuomo, F.; Baiocchi, A. "Self-Healing Infotainment and Safety Application for VANET
dissemination", Communication Workshop (ICCW), 2015 IEEE International Conference on, On page(s): 2495 - 2500
4. Cogill, R.; Gallay, O.; Griggs, W.; Chungmok Lee; Nabi, Z.; Ordonez, R.; Rufli, M.; Shorten, R.; Tchrakian, T.; Verago, R.; Wirth,
F.; Zhuk, S. "Parked cars as a service delivery platform", Connected Vehicles and Expo (ICCVE), 2014 International Conference
on, On page(s): 138 - 143
5. http://www.strategyand.pwc.com/reports/connected-car-2015-study
6. http://zackkanter.com/2015/01/23/how-ubers-autonomous-cars-will-destroy-10-million-jobs-by-2025/
7. http://www.cbronline.com/news/internet-of-things/m2m/autonomous-driverless-connected-cars-where-are-smart-iot-
cars-taking-us-4759452
8. http://blog.bosch-si.com/categories/mobility/2013/06/connected-cars-whats-in-store/
9. http://articles.sae.org/13081/
10. http://www.infinitumstore.com/articles/cars-are-parked-95-of-the-time-how-this-affects-you
11. http://robotenomics.com/2014/02/26/morgan-stanley-the-economic-benefits-of-driverless-cars/
12. http://ec.europa.eu/transport/themes/strategies/doc/2011_white_paper/white_paper_2011_ia_full_en.pdf
13. A Report by AXA, “The Future of Driverless Haulage, ” September 2015 [Online]. Available:
http://www.axa.co.uk/uploadedFiles/Content/Newsroom/Media_Resources/Reports_and_Publications/PDF_files/The%20F
uture%20of%20Driverless%20Haulage(1).pdf.
14. https://wiki.smu.edu.sg/1213t2is415g1/IS415_201213_Term2_Assign2_Anthony_Sugiarto
15. http://www.smarteranalyst.com/2015/05/28/barclays-and-goldman-sachs-weigh-in-will-tesla-motors-inc-tsla-or-google-
inc-goog-win-the-self-driving-car-race/
16. http://www.lta.gov.sg/ltaacademy/doc/J14Nov_p05Tan_AVnextStepSingapore.pdf