ADAS and Autonomous Driving Technology Market, Edition 2019

Penetration & Sales Demand (Level 1+2; Level 3 – Highway Autopilot & Long-haul Platooning; Level 4 – Highway Autopilot, Park Assist, Urban Autopilot – Robotaxis, Shuttles, Pods); Market Size, Sales, & Pricing Analysis of AV Sensors (Camera, Radar, LiDAR)

Published: 10 Jul 2019

Key Highlights


This is a second edition of ADAS and autonomous driving technology market in the series. The first edition of this research report was the most recognized research study for its exhaustive and comprehensive analysis. This report is an updated version of edition 2018 with updated market numbers and forecast with detailed analysis on the trend and timelines of autonomous vehicles launch. 

  • More than 300 pages of analysis 
  • More than 250 companies analyzed across supply chain 
  • 180+ data tables on penetration, sales demand, and pricing
  • 150+ deep-level infographics on the market 
  • More than 120+ interviews conducted with key players 
  • Deep company profiles of more than 30 key players 
  • AV development analysis of 20 OEMs & 30 Tier 1 suppliers
  • Regulatory framework across automotive markets
  • Safety ratings by automotive regulatory authorities
  • Breakdown and analysis of 5 AV building blocks 
  • Market penetration and sales forecast by levels of automation
  • Camera, radar, LiDAR, ultrasonic sensors market analysis

Exhaustive Coverage


This research study focuses on two major parts of autonomous driving industry. First is the ADAS and autonomous vehicles demand forecast, launch timelines, and competition among the OEMs and new autonomous vehicle companies. Second is the ADAS and autonomous driving technology analysis – enabling technologies, their shipments, total addressable market, pricing trends, and autonomy package (sensor suite) cost across levels of automation. 

Autonomous vehicles demand

Market penetration, sales demand, and forecast of vehicles featured with different levels of automation. The levels of automation and autonomy packages covered in this research are – 

Level 1 – ADAS features – with warning/alert systems such as blind-spot detection, rear-view parking system, among others
Level 2 – Partial automation features – such as automatic cruise control, lane departure warning, emergency braking, among others
Level 3 – Conditional automation features – such as traffic jam assist and autopilot/propilot
Level 4 (highway traffic) – High automation features – such as highway autopilot and automated valet parking
Level 4/5 (urban slow-moving traffic) – Full automation features – such as automated valet parking and urban autopilot


ADAS, Partial Automation, Conditional Automation, and High to Full Automation in Passenger and Commercial Vehicles

The report focuses on penetration of automation features in both passenger and commercial vehicles industry. The passenger vehicles breakdown is by automation features developed and integrated by traditional OEM players in their production vehicles and automation in the form of robotaxis by new robotic vehicle companies. Similarly, in commercial vehicles automation in the LCVs (for delivery applications), autonomous shuttles, autonomous pods (goods delivery), and autonomous trucks (long-haul platooning applications)

CAV Enablers

The connected autonomous vehicles (CAV) enablers are categorized under four major layers. 

1. Perception technologies for road environment sensing including radar (long-range, short-range, and medium-range radars), cameras (in-cabin monitoring with driver monitoring system, gesture recognition, TOF camera, thermal/night vision/infrared imaging, monocular camera, stereo camera, triple/trifocal camera, surround-view camera system, forward ADAS/main camera), and LiDARs (mechanical scanning, MEMS solid state, OPA, 3D flash, and FMCW, among others). 
2. Contextual information technologies for positioning and mapping including HA-GNSS, HD maps, and V2X communication
3. AI algorithms for learning the environment used in ML data annotation, testing, validation, and verification of AVs 4. Processing hardware including vision processors, AI chips, among others


Enabling Technologies - Camera, LiDAR, Radar, GNSS, HD Maps, V2X, Processors, and AI - Machine Learning for ADAS and Autonomous Driving

The report gives a detailed analysis on each of these four technology blocks, their sub technologies, and their sub-component’s market size, shipment, and pricing forecast. 

Industry analysis 

Regulatory frameworks developments to enable autonomous driving across leading automotive markets (China, United States, and countries in Western Europe) and evaluating the impact on the launch timelines 
Assessing ADAS functions and autonomy packages of OEM brands by models and trim levels to anticipate who will lead in the AV development race 
Assessing autonomous driving solutions from new autonomous vehicles companies such as Waymo, Baidu, Uber, Lyft, and 15 others to understand the shared AV and robotic vehicles ecosystem 
Accessing ADAS and autonomous technology development platforms and solutions by Tier 1 suppliers such as Valeo, Bosch, Continental, Autoliv, Veoneer, among 30 others  
Partnerships, Collaborations, and M&As in the ADAS and autonomous driving industry in last couple of years 
Investments tracker in leading and emerging companies in the ADAS and autonomous driving industry in last couple of years
Supply chain analysis to understand who is supplying to whom in the multi-layer ecosystem 

Market Overview


Looking the industry from the optimistic view, automation has already arrived – in the form of level 2 cars. The first step has already been taken by few OEMs in successfully building level 3 car, although it is yet to be on roads. However, with huge investments and funding going on in the industry, there is no stopping for fully autonomous cars to be a reality. 

Autonomous vehicles in the form of shuttles, pods, and robotaxis are already developed and being used in closed environment. This shows that the industry is technologically equipped in developing such vehicles. Of course, there are many milestones yet to be achieved, but the industry is moving rapidly and competing in developing autonomous cars.
The market numbers are evident and support the claims of autonomous cars being a close reality. In 2018 itself, approx. ~XX million passenger cars were equipped with level 1 and 2 features of automation (advanced assistance). This number is estimated to grow to ~XX million this year (2019), at a rate of XX percent. Apart from this, there are ~XX thousand robotic vehicles globally with high autonomous features.


Expected penetration and demand of ADAS and autonomous vehicles across different levels of autonomy


The future scenario is expected to upend where every car will compulsorily have some or the other ADAS feature integrated. By 2030, ~XX million cars will be ADAS featured, ~XX million cars will be with Level 2 capability, ~XX million cars with Level 3 features, XX thousand cars will be highly autonomous, and XX thousand robotic vehicles.
Highly automated vehicles are expected to first hit the roads of developed economies such as United States, Japan, and countries of Western Europe. China being one of the potential markets other than developed markets, will soon commercialize driverless cars with shared mobility services

Many OEMs are reluctant to move further towards L3 automation. Few OEMs will not launch level 3 vehicle, preferring to jump straight to level 4 to avoid re-engagement and liability issues. However, one of the early movers in the premium brands segment such as Audi has already developed a level 3 car – Audi A8, and is testing on the Western European roads. Level 3 cars are expected to be commercialized by 2021 in Western Europe and United States.
Post 2023, OEMs are expected to start production of L4 autonomy featured passenger cars. Such cars will be initially featured with only highway autopilot. Fully autonomous cars are still a distant future expected only after 2030 for closed environment driving.
OEMs will become mobility service providers to retain the customer relationship and offset the risks of decreased car shipments

The industry always craves for technology innovations that could address the current challenges and reduce the time to market for highly autonomous vehicles
OEMs will retain the control over building the cars, while technology companies such as Google, Uber, and Intel among others could be those that build the intelligence behind them, including the relationship with passengers. Deep learning and AI are the core innovations ahead of sensors.
In urban environment, HD maps will have the edge in providing high level of accuracy. Elsewhere, high accuracy GNSS positioning will be required.
Adding level 3 assistance in vehicles will cost XX% more than installing level 2 features - level 4 will be a further XX% more expensive!
Sensor companies are putting forth highly advanced, low cost and effective solutions that holds potential to change the current market trends. These include MEMS based LiDAR, high-resolution imaging radar, thermal cameras, DMS, gesture recognition, ToF imaging solutions, and many more.
Sensor fusion of radar, camera, and LiDAR is expected to drive the autonomous driving market post 2021 with average semiconductor content cost of $1000. Artificial intelligence will play a vital role in future driverless cars in conjunction with sensor fusion for successful operation of highly autonomous and driverless cars
Total analog semiconductor content market in autonomous driving industry is expected to cross $XX billion by 2030

Majority of Tier 1 suppliers are currently developing Level 2 and above solutions and incorporating artificial intelligence for surround mapping. Tier 2 and other technology players will play a major role in transforming the complete automotive industry as the industry moves on the path of driverless, connected, shared mobility, and electrification of the vehicles. Tier 1, Tier 2, and other technology suppliers will benefit the most from this growth 

Level 4 automation will shift the way OEMs market and sell vehicles. The car will become a second office or living room.
OEMs will become peer-to-peer car sharing platforms, encouraging owners / lessees to share their cars to make them more affordable. Going further, automation will blur the lines between ownership and sharing when owners will share and then use other shared cars if their own is not available.

Luxury OEM brands such as BMW, Daimler (Mercedes Benz), Audi, Volvo, and Tesla, among others are leading the race for developing and bringing Level 2 to Level 5 cars on roads. All these luxury brands have announced their driverless cars prototypes/concept cars
OEMs such as Volkswagen, Ford, Hyundai, Renault-Nissan, Honda, and GM are trying to develop cost effective high automation solutions for shared mobility and private ownership purpose
All the companies have already launched Level 2 cars, and few are skipping Level 3 and jumping to Level 4 technology cars while many are following the SAE levels of automation
Among the Tier 1 suppliers Bosch, Continental, Aptiv, Denso, Veoneer, Magna, Valeo, and Hyundai Mobis are few of the leading players in the market
Mobileye, an Intel company, is the leading vision-sensing provider. Mobileye’s partnerships with GM, Intel, Wabco, BMW, Delphi and Volkswagen will bring new business opportunities Nvidia has emerged as a key supplier of deep learning and processing components to Tesla, Honda, Volvo, Audi, Daimler, BMW, VW, and Baidu

Vision sensors, radar, LiDAR sensor players and start-ups are gaining momentum to gain huge market share in coming 5 years owing to the emergence of highly autonomous solutions

AI technology providers are expected to have huge market opportunities in coming years. Shared mobility services, robotic vehicles, pods, and shuttle providers such as Uber, Waymo, Lyft, NAVYA, Easy Mile, Auro, Local Motors, Grab, May Mobility, SB Drive, and Didi among many others are collaborating with OEMs to make shared robotic cars available on the roads by 2023 

Key Questions Answered


  • What is the status of vehicle automation in 2018 and 2019? And how will it change over the period of next 20 years?
  • Which markets are currently leading in vehicle automation and which markets are expected to make significant difference in the future?
  • Which type of ADAS and Level 2 solutions are currently being developed by the Tier 1 suppliers and what kind of sensors are being used in such solutions?
  • What is the penetration rate of SAE Level 1 and 2 in car sales across different markets in 2016 and 2017? And what is the expected penetration rate of SAE Level 3 and above solutions across different geographies and markets between 2019 and 2030?
  • Which OEMs lead L2 deployment in 2018 and 2019 and why?
  • What changes in 2019 in terms of deployment of L2 and L3?
  • What are the regulatory and engineering challenges carmakers face for the deployment of higher level of vehicle autonomy?
  • What is the status of autonomous driving regulation in major car markets?
  • What are the differences in the legal and regulatory framework in Europe and the United States and how this will it affect L3-5 deployment?
  • Which geography presents the most favorable environment for deployment of Level 3- 5?
  • What breakthroughs are required in the area of SW/HW and validation for L3-5?
  • How carmakers, Tier-1s and new-entrants, including tech giants plan to overcome the challenges and commercialize autonomous driving?
  • How do leading OEMs plan to achieve L4/5 capabilities and when?
  • What are the major OEM strategies, new business models and key collaborations?
  • Why leading Tier-1s are well positioned to monetize ADAS growth?
  • Who will lead and who will follow in the autonomous vehicle race?
  • What are the trends by ADAS levels in Top Premium OEMs’ model range during 2018-19?
  • Which are the recent mergers and acquisitions by the players across the ecosystem that has the potential to highly impact the autonomous driving market?
  • What are the different sensor fusion technologies expected to launch in the recent future?
  • Which type of sensors market among camera, radar, ultrasonic, and LiDAR will be highly profitable?
  • What are the sales, market size, and pricing trend of sensing technologies in ADAS and autonomous driving market from 2019 to 2030?
  • Which type of emerging sensing technologies will be a threat for the current technologies in the market? 

List of Companies


Waymo

Tesla

Uber

Lyft

Audi

BMW

Volvo

Autoliv

Valeo

Aptiv

Ford

Volkswagen

Renault - Nissan - Mitsubishi

Bosch

Continental

Veoneer


















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