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The Future of Autonomous Cars

The Future of Autonomous Cars

The Future of Autonomous Cars is a strategy report from Berg Insight analysing the latest developments on the selfdriving car market worldwide.

This strategic research report from Berg Insight provides you with 250 pages of unique business intelligence including 5-year industry forecasts and expert commentary on which to base your business decisions.

Highlights from this report:

Insights from numerous executive interviews with market leading companies.
New data on car populations and new car registrations worldwide.
Comprehensive overview of the autonomous car value chain and key applications.
In-depth analysis of market trends and key developments.
Updated profiles of 14 major car OEMs and their autonomous car activities.
Detailed view on the involvement of IT and technology companies in this industry.
Market forecasts by region lasting until 2030.


Executive summary

Ever since the introduction of the first automobile one thing has remained constant despite the evolution of performance and appearance – cars have always had a driver. The concept of driverless vehicles opens up for new potential applications as well as business models. In fact, the removal of the driver is arguably the most significant and transformative innovation ever faced by the automotive industry. Some of the potential benefits that follow are safer, more efficient and more convenient journeys. Self-driving cars open up completely new ways to deal with transportation – fleets of autonomous cars could in the future handle entire cities’ need for personal mobility with much fewer vehicles than are used today. SAE International has developed a six level standard (0–5), where semi-autonomous functionality starts in the second level. The third level is the first to provide some actual autonomy in the sense that the driver can divert attention from the road although he or she must be able to regain control of the vehicle with some seconds of prior warning. The fourth level provides full autonomy in specific use cases of various complexity.

In 2015, the first semi-autonomous (SAE Level 2) car models were introduced on the market and reached sales of an estimated 194,000 cars. This number is forecasted to increase by almost 57 percent to reach new registrations of about 304,000 Level 2 capable vehicles in 2016. By 2030 an estimated 43 million cars will be sold featuring Level 2 capability and the active installed base will have reached about 177 million cars.

The total number of new registrations of autonomous (SAE Level 3 and 4) cars is forecasted to grow at a compound annual growth rate (CAGR) of 62 percent from 0.2 million units in 2020 to reach 24 million units in 2030. The active installed base of autonomous cars is forecasted to have reached about 71 million at the end of the forecast period. SAE Level 3 and 4 cars will constitute about 16.5 million and 7.8 million of the cars sold in 2030. However, Level 4 sales are expected to overtake Level 3 in the years following 2030. Cars with Level 5 capability are not expected to emerge before 2030 and potentially much later.

There are two approaches to the development of autonomous cars – the evolutionary and the revolutionary. Most of the incumbent car manufacturers are pursuing an evolutionary approach which relies on step-by-step developments. The first step for the evolutionary pathway is to make Level 3 cars available in 2020. This initial system is likely to only feature autonomous mode on freeways. By 2022, the evolutionary approach is expected to reach the next milestone with the rollout of Level 4 capable cars. These cars will be able to drive completely autonomously without ever requesting the driver to intervene but initially only on specific freeways and thus the driver will have to take over control when the car is exiting the freeway. Most of the new entrants like the IT companies as well as startups are instead targeting a revolutionary approach. The revolutionary approach argues that Level 3 is unsafe due to the repeating control exchange between driver and vehicle and therefore aims directly for Level 4 focusing on city-based low-speed autonomous cars. These cars are expected to be introduced in 2022. However, the initial revolutionary Level 4 cars will only be available in specific environments such as in downtown shopping areas.

Most carmakers are today developing autonomous car technology and they are joined by software companies, Tier-1 suppliers, government initiatives and startup firms. The diversity of the actors is important since a range of various technological advancements are necessary along with regulatory changes to realize self-driving cars. Fully autonomous cars are closely related to artificial intelligence and this is therefore one of the most researched fields among carmakers and other institutions working on self-driving vehicle projects. Recent progress in the field of artificial intelligence and specifically in deep learning has made the development of autonomous cars seem more likely to occur soon.

It is important to recognize that autonomous cars will not arrive overnight. Even when a ready solution is available and regulations have been adapted to it, the roll out of self-driving vehicles to the broad market will take many years. The luxury car market will be the first segment to offer autonomous car technologies. This trend can already be seen with automakers like Tesla, BMW and Mercedes-Benz offering autopilot features in their cars.

These features, however, are not truly autonomous yet since they require the driver to stay attentive at all times. Moreover, the automakers are starting to see competition from new entrants like Google, Uber and Baidu which all aim to develop self-driving cars. About the Authors Ludvig Barrehag is an M2M/IoT Analyst with a Master’s degree in Management and Economics of Innovation from Chalmers University of Technology. His areas of expertise include autonomous cars and related markets and technologies. Johan Fagerberg is co-founder and an experienced analyst with a Masters degree in Electrical Engineering from Chalmers University of Technology. His areas of expertise include location-based services and wireless M2M/IoT markets, with a special focus on fleet management and car telematics. Berg Insight offers premier business intelligence to the telecom industry. We produce concise reports providing key facts and strategic insights about pivotal developments in our focus areas. Berg Insight also offers detailed market forecast databases and advisory services. Our vision is to be the most valuable source of intelligence for our customers.

Executive summary
1 Introduction to autonomous cars
1.1 Definitions and classifications
1.2 Brief history of autonomous cars
1.3 Current state of self-driving cars and key stakeholders
1.3.1 Automotive manufacturers
1.3.2 Tier-1 automotive suppliers
1.3.3 Technology companies
1.3.4 Connectivity service providers
1.4 Key market drivers
1.5 Key market barriers
1.6 The global passenger car market
1.6.1 Car segments
1.6.2 Passenger cars in use by region
1.6.3 New passenger car registration trends
1.7 Market trends
1.7.1 Hybrid electric, plug-in hybrid electric and all-electric vehicles
1.7.2 Car sharing and personal transportation as a service
1.8 User segments for autonomous driving
1.8.1 Luxury segment
1.8.2 Commuters
1.8.3 Young drivers
1.8.4 Paratransit
1.8.5 Delivery fleets
1.8.6 Transportation on demand
2 Advanced driver assistance systems
2.1 Introduction to the most common ADAS
2.1.1 Adaptive cruise control
2.1.2 Cooperative adaptive cruise control
2.1.3 Lane departure warning
2.1.4 Lane keeping assist
2.1.5 Autonomous emergency braking
2.1.6 Collision avoidance system
2.1.7 Blind spot monitor
2.1.8 Rear cross traffic alert
2.1.9 Forward cross traffic alert
2.1.10 Turning assist
2.1.11 Road sign detection
2.1.12 Other ADAS
2.2 Specific semi-autonomous use cases
2.2.1 Parking assist
2.2.2 Traffic jam assist and highway autopilot
2.2.3 Platooning
3 Autonomous car technologies
3.1 Sensors
3.1.1 Cameras
3.1.2 Lidar
3.1.3 Radar
3.1.4 Ultrasonic and infrared sensors
3.1.5 Inertial navigation system
3.2 Telematics
3.2.1 Mobile connectivity
3.2.2 Location tracking
3.2.3 Digital maps
3.2.4 V2V and V2I communication
3.3 Computing platform
3.3.1 Sensor fusion
3.3.2 Interpretation and decision making
3.3.3 Computer vision
3.3.4 Artificial intelligence
3.3.5 Machine learning
3.3.6 Deep learning
3.4 Execution and related technologies
3.4.1 Electronic control unit
3.4.2 Human machine interface
3.4.3 Driver monitoring systems
3.5 Summary of the current state of autonomous car technologies
4 Autonomous car initiatives
4.1 Overview of current projects
4.2 Jaguar Land Rover Automotive
4.2.1 Overview of Jaguar Land Rover passenger car models
4.2.2 ADAS offerings
4.2.3 Approach to autonomous cars
4.2.4 Autonomous technology activities
4.2.5 Competitive positioning in the autonomous car market
4.3 Volvo Car Group
4.3.1 Overview of Volvo passenger car models
4.3.2 ADAS offerings
4.3.3 Approach to autonomous cars
4.3.4 Autonomous technology activities
4.3.5 Competitive positioning in the autonomous car market
4.4 Tesla Motors
4.4.1 Overview of Tesla passenger car models
4.4.2 ADAS offerings
4.4.3 Approach to autonomous cars
4.4.4 Autonomous technology activities
4.4.5 Competitive positioning in the autonomous car market
4.5 Mercedes-Benz
4.5.1 Overview of Mercedes-Benz passenger car models
4.5.2 ADAS offerings
4.5.3 The upcoming E-class models
4.5.4 Approach to autonomous cars
4.5.5 Autonomous technology activities
4.5.6 Competitive positioning in the autonomous car market
4.6 Audi
4.6.1 Overview of Audi passenger car models
4.6.2 ADAS offerings
4.6.3 Approach to autonomous cars
4.6.4 Autonomous technology activities
4.6.5 Competitive positioning in the autonomous car market
4.7 BMW
4.7.1 Overview of BMW passenger car models
4.7.2 ADAS offerings
4.7.3 Approach to autonomous cars
4.7.4 Autonomous technology activities
4.7.5 Competitive positioning in the autonomous car market
4.8 General Motors
4.8.1 Overview of the main GM passenger car brands
4.8.2 ADAS offerings
4.8.3 Approach to autonomous cars
4.8.4 Autonomous technology activities
4.8.5 Strategic investments
4.8.6 Competitive positioning in the autonomous car market
4.9 Ford Motor Company
4.9.1 Overview of Ford passenger car models
4.9.2 ADAS offerings
4.9.3 Approach to autonomous cars
4.9.4 Autonomous technology activities
4.9.5 Competitive positioning in the autonomous car market
4.10 Toyota Motor Corporation
4.10.1 Overview of Toyota and Lexus passenger car models
4.10.2 ADAS offerings
4.10.3 Approach to autonomous cars
4.10.4 Autonomous technology activities
4.10.5 Competitive positioning in the autonomous car market
4.11 Honda Motor Company
4.11.1 Overview of Honda and Acura passenger car models
4.11.2 ADAS offerings
4.11.3 Approach to autonomous cars
4.11.4 Autonomous technology activities
4.11.5 Competitive positioning in the autonomous car market
4.12 Hyundai Motor Group
4.12.1 Overview of Hyundai and Kia passenger car models
4.12.2 ADAS offerings
4.12.3 Approach to autonomous cars
4.12.4 Autonomous technology activities
4.12.5 Competitive positioning in the autonomous car market
4.13 Renault-Nissan Alliance
4.13.1 Overview of Nissan Motor Company
4.13.2 Overview of Nissan and Infiniti passenger car models
4.13.3 Overview of Renault Group
4.13.4 Overview of Renault and Dacia passenger car models
4.13.5 Nissan and ADAS developments
4.13.6 Renault and ADAS developments
4.13.7 Approach to autonomous cars
4.13.8 Nissan and autonomous technology activities
4.13.9 Renault and autonomous technology activities
4.13.10 Competitive positioning in the autonomous car market
4.14 Fiat Chrysler Automobiles
4.14.1 Overview of Fiat Chrysler Automobiles passenger car models
4.14.2 ADAS offerings
4.14.3 FCA and autonomous driving
4.15 Groupe PSA
4.15.1 Overview of Peugeot and Citroën passenger car models
4.15.2 ADAS offerings
4.15.3 Approach to autonomous cars
4.15.4 Autonomous technology activities
4.15.5 Competitive positioning in the autonomous car market
4.16 Google
4.16.1 Approach to autonomous cars
4.16.2 Autonomous technology activities
4.16.3 Google Chauffer software
4.16.4 Competitive positioning in the autonomous car market
4.17 Apple
4.17.1 Apple’s vehicle project
4.18 Uber Technologies
4.18.1 Approach to autonomous cars
4.18.2 Uber and autonomous cars
4.18.3 Competitive positioning in the autonomous car market
4.19 Baidu
4.19.1 Approach to autonomous cars
4.19.2 Autonomous technology activities
4.19.3 Competitive positioning in the autonomous car market
4.20 Additional car OEM initiatives
4.21 Car manufacturers not yet betting on autonomous car technology
4.22 Supplier and technology company initiatives
4.22.1 Autoliv
4.22.2 Bosch
4.22.3 Continental
4.22.4 Delphi Automotive
4.22.5 ZF TRW
4.22.6 Mobileye
4.22.7 Nvidia
4.22.8 Velodyne LiDAR
4.22.9 Additional supplier initiatives
5 Regional developments
5.1 USA
5.2 European Union
5.3 Germany
5.4 United Kingdom
5.5 Sweden
5.6 China
5.7 Japan
5.8 South Korea
5.9 Singapore
6 Benefits of autonomous cars
6.1 Safety
6.2 Convenience
6.3 Traffic efficiency
6.4 Mobility
6.4.1 Benefits for people unable to drive
6.4.2 Public driverless fleets of cars
6.5 Sustainability
6.5.1 Electric autonomous vehicles
6.5.2 Increased efficiency
6.6 Impact on city infrastructure
7 Barriers and challenges
7.1 Technology reliability
7.2 Mixed vehicle environment
7.3 HMI challenges to accomplish Level 3
7.4 Standards and collaborations
7.5 Regulations and liabilities
7.5.1 International conventions on road traffic
7.5.2 Liability
7.6 Public acceptance
7.7 Car longevity
8 Market forecasts and trends
8.1 Car sales forecast
8.2 Autonomous car sales forecast
8.2.1 SAE Level 1
8.2.2 SAE Level 2
8.2.3 SAE Level 3
8.2.4 SAE Level 4
8.2.5 SAE Level 5
8.3 Regional market developments
8.3.1 SAE Level 2, Level 3 and non-driverless Level 4
8.3.2 SAE Driverless Level 4
8.4 Market drivers and barriers
8.4.1 Competitive environment
8.4.2 Technology environment
8.4.3 Regulatory environment
8.4.4 Macroeconomic environment
8.5 Value chain analysis
8.5.1 Automotive industry players
8.5.2 IT industry players
8.5.3 Automotive suppliers
8.5.4 Transport service players
8.6 Future industry trends
8.6.1 Forecasting the autonomous car market beyond 2030
8.6.2 The overall impact of autonomous cars on society
8.6.3 Data ownership and privacy protection strategies
8.6.4 How will the rollout of self-driving cars affect the insurance industry?
8.6.5 Self-driving cars and the Internet of Things
8.6.6 New mobility services and business models for fully autonomous cars
Glossary
Index
List of Figures
Figure 1.1: SAE classification of levels of autonomy
Figure 1.2: Performance and adoption barriers
Figure 1.3: Car parc by region (World 2008–2014)
Figure 1.4: Passenger car parc density by region (World 2015)
Figure 1.5: New car registration data (World 2008–2015)
Figure 1.6: Top 10 countries by new passenger car and light truck registration (2015)
Figure 1.7: Top selling highway capable all-electric cars (World 2015)
Figure 1.8: Registered highway capable BEVs and PHEVs (World 2015)
Figure 1.9: Car sharing and mobility service companies (World Q4-2015)
Figure 3.1: Sense-Plan-Act process
Figure 3.2: Typical lidar 3D depiction integrated with a digital map
Figure 3.3: Relationship between fields in computer science
Figure 3.4: Conceptual structure of a simple neural network
Figure 3.5: Graphical representation of underfitting and overfitting
Figure 4.1: Top 20 passenger car manufacturers by revenues (World 2015)
Figure 4.2: Top 6 luxury car manufacturers by new registrations (World 2015)
Figure 4.3: Land Rover remote control app
Figure 4.4: Drive Me project routes for autonomous mode
Figure 4.5: Tesla Autopilot display
Figure 4.6: F 015 Luxury in Motion interior design
Figure 4.7: Audi RS 7 autonomous race car
Figure 4.8: BMW VISION NEXT 100 concept car featuring heads-up display
Figure 4.9: Chevrolet Tahoe modified vehicle at the DARPA Urban Challenge
Figure 4.10: Ford Fusion Hybrid autonomous test car
Figure 4.11: Honda Wander Stand concept vehicle
Figure 4.12: The empty car convoy
Figure 4.13: Nissan IDS Concept interior when in self-driving mode
Figure 4.14: 2017 Chrysler Pacifica Hybrid
Figure 4.15: Google autonomous prototype
Figure 4.16: Volvo Cars XC90 equipped for Uber’s autonomous ride-hailing program
Figure 4.17: Baidu’s autonomous BMW Gran Turismo test vehicle
Figure 4.18: Nvidia Drive PX2
Figure 4.19: Velodyne HDL-64E LiDAR
Figure 7.1: Traffic in Ho Chi Minh City
Figure 8.1: Global passenger car and light truck sales by region (2015–2030)
Figure 8.2: Luxury car sales (World 2016–2030)
Figure 8.3: Autonomous car sales and active installed base by level (World 2015–2030)
Figure 8.4: Autonomous car SAE level 2 sales by region (2015–2030)
Figure 8.5: Autonomous car SAE level 3 sales by region (2015–2030)
Figure 8.6: Autonomous car SAE level 4 sales by region (2015–2030)
Figure 8.7: Technology adoption lifecycle model
Figure 8.8: Long term outlook on passenger car and autonomous car sales
Figure 8.9: Evolutionary pathway of Internet of Things use cases
Figure 8.10: Potential paths to shared ownership of autonomous cars

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