The autonomous/driverless car market was valued at USD 19.46 billion in 2020 and is expected to project a CAGR of about 18.06%, during the forecast period, 2021-2026.
The outbreak of COVID-19 and the subsequent shutdowns have affected the autonomous vehicle market in several countries. The negative impacts of the pandemic are visible in the total distance covered by the testing vehicle by any country as major players were forced to stop their testing during lockdowns.
Autonomous cars use technologies, like RADAR, LIDAR, GPS, and computer vision, in order to sense their environment. Advanced control systems that are integrated into the car can interpret the sensory inputs to detect the signboards or to avoid the collision.
Although, Level 4 and Level 5 (as scaled by SAE) autonomous cars are unlikely to reach wide acceptance, by 2030, there would be rapid growth for Level 2 and Level 3 autonomous cars, which have advanced driver assistance systems, like collision detection, lane departure warning, and adaptive cruise control. Fully autonomous cars are not going to reach a wide customer base unless they are secure from cyber-attacks. If such concerns are addressed, the autonomous car market is estimated to reach USD 60 billion by 2030.
Major automaker companies, technology giants and specialist start-ups have invested more than USD 50 billion over the past five years, in order to develop autonomous vehicle (AV) technology, with 70% of the money coming from other than the automotive industry. At the same time, public authorities see that AVs offer huge potential economic and social benefits.
Key Market Trends
Lidar technologies will propel the growth of the market
Lidars and cameras are the principal components of the autonomous vehicles, that differentiate it from conventional vehicles, in which Lidar acts as an eye of the self-driving vehicles as it provides them a 360-degree view of the surrounding which help vehicle to drive on its own safety.
Various companies that manufacture this component are entering into partnerships with other companies and entering into a new market. For instance,
- In February 2021, Velodyne Lidar announced that it has signed a five-year sales agreement with ThorDrive to provide Ultra Puck sensors. ThorDrive is using Velodyne’s lidar sensors to power its cargo ground support tractors in an autonomous vehicle program at the Northern Kentucky International Airport. ThorDrive has been using Velodyne lidar sensors since 2010 for developing its autonomous driving technology.
- In January 2021, Innoviz Technologies entered into a partnership with Macnica, to sell InnovizOne, in Japan. InnovizOne is an automotive-grade, LiDAR sensor, apart from that company also has other products in its portfolio like InnovizTwo, a high-performance automotive-grade LiDAR sensor, and Innoviz's perception software, with advanced AI and machine learning-based detection and tracking features. In 2018, InnovizOne has been selected by BMW for its fully electric iX autonomous car program.
North America will dominate the Market
Self-driving cars have already been tested and used in the roads of California, Texas, Arizona, Washington, Michigan, and other states of the United States. Although, their mobility is restricted to specific test areas and driving conditions.
Various technology companies in the country are reaching new milestones in terms of total miles tested. For instance, in 2020, Cruise LLC completed 2020 by doubling its figure of how far its cars can go before a safety driver needs to take over. The company reported 27 disengagements during 770,000 miles during testing in California. During testing in 2020, the human driver had to take over every 28,520 miles, as compared to every 12,221 miles last year.
Similarly, Apple Inc. completed road testing of its self-driving cars in 2020, which experienced more than double miles traveled as compared to 2019 as its autonomous technology improved. The company’s cars drove 18,805 miles in 2020, as compared to 7,544 miles in 2019, according to a report of the California Department of Motor Vehicles.
After various local companies, the country is witnessing the entry of companies from various other countries. For instance, in February 2021, Vietnam's domestic automaker, Vinfast, announced that it had obtained a permit to test autonomous vehicles on public streets in California. The company was seeking this permit to commercialize its electric vehicles in the United States market.
Canada was a lagging in terms of the autonomous-vehicle testing in North America. The University of Waterloo joined forces with Erwin Hymer Group and Blackberry QNX to start testing driverless cars and vans in November 2016.
Whereas, Mexico’s new trade agreement with the United States and Canada is expected to create more opportunities for the transfer of autonomous technology, although there is room for infrastructure improvement.
Many players from the hardware to software firms in the automotive industry started focusing on entering into the growing trend of autonomous driving technology. Thus, partnerships, collaborations, and investments toward the development of autonomous vehicles increased significantly in the automotive industry over the past three years (i.e., 2018-2020). They are likely to continue to grow during the forecast period, primarily owing to the increasing support from governments and private sectors across several countries to promote autonomous driving vehicle technology.
In January 2021, Automotive Grade Linux announced that it has included aicas, AVL, and Citos as new Bronze members. AGL, which is an open-source project at the Linux Foundation that brings together automakers, suppliers, and technology companies to accelerate the development of all technology in the vehicle including autonomous driving.
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1.1 Study Assumptions
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Technology Trends
4.2 Market Drivers
4.3 Market Restraints
4.4 Industry Attractiveness - Porter's Five Forces Analysis
4.4.1 Threat of New Entrants
4.4.2 Bargaining Power of Buyers/Consumers
4.4.3 Bargaining Power of Suppliers
4.4.4 Threat of Substitute Products
4.4.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
5.1 By Type
5.1.1 Semi-autonomous Vehicles
5.1.2 Fully-autonomous Vehicles
5.2.1 North America
5.2.4 Rest of the World
6 COMPETITIVE LANDSCAPE
6.1 Vendor Market Share
6.2 Company Profiles
6.2.1 Uber Technologies Inc.
6.2.2 Daimler AG
6.2.3 Waymo LLC (Google Inc.)
6.2.4 Toyota Motor Corp.
6.2.5 Nissan Motor Co. Ltd
6.2.6 Volvo Cars
6.2.7 General Motors Company
6.2.8 Volkswagen AG
6.2.9 Tesla Inc.
7 MARKET OPPORTUNITIES AND FUTURE TRENDS
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.
The market engineered data is verified and validated by a number of experts, both in-house and external.
REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.