The autonomous/driverless car market was valued at USD 5.68 billion in 2018 and is expected to project a CAGR of 31.50%, during the forecast period, 2019-2024.
- 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 a 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.
Scope of the Report
Autonomous or driverless cars are vehicles that are capable of maneuvering on their own or by human assistance by sensing its nearby environment.
The autonomous cars have been segmented by type.
Key Market Trends
Cyber Security and Safety Concerns are Hindering the Market Growth
Cyber security is going to be a key consideration for the developing autonomous vehicle technology, as it is not just concerned with the vehicles themselves, but is also related to the whole environment that will be developed to support such vehicles. A connected and automated vehicle system is a cyber-physical system, with components of both the physical and virtual worlds. The safety stakes are high, as these systems are hard to protect. There are also risks associated with the networks that connect vehicles. The network systems include the financial networks that process payments, roadside sensor networks, and the electricity infrastructure or traffic control features.
One of the major cyber security risks associated with autonomous vehicles is hacking.
- For instance, in 2015, researchers Charlie Miller and Chris Valasek demonstrated that they were able to hack a Jeep Cherokee and control it remotely. The incident led to the recall of 1.4 million cars by Fiat Chrysler.
- Additionally, in early 2017, the Chinese researchers exposed the vulnerabilities in Tesla Model X. They were able to take control of the vehicleÕs brakes, remotely, open the trunk and the doors, and take control of the radio. The researchers hacked the vehicle through Wi-Fi and cellular connections, using malware, which was sent to the carÕs web browser in a series of circuitous computer exploits.
Apart from cyber security issues, safety concerns pertaining to accidents have always been the prime concern for both the consumers and the international authorities, such as NHTSA. There has been two major accidents in early 2018, which increased the safety concerns regarding these vehicles Š
- A woman in Arizona was hit and killed by a self-driving Uber car
- A Tesla Model X on autopilot hit a highway divider before bursting into flames
Semi-Autonomous Vehicles Dominating the Market
Following the SAE (Society of Automotive Engineers) International automated driving standards, cars with level 1 to level 3 automation features have been considered under the market segment of semi-autonomous cars.
- Level 1 automation (also known as Driver Assistance) has been available on cars for several years, handling driving modes like steering or throttle and brake, but never both. The level 1 cars must need driver attention to take over those functions if called upon by the vehicle. Some of the features seen in level 1 cars are parking assistance, adaptive cruise control, and lane keeping assistance.
- Level 2 automation (also known as Partial Assistance) has a suite of driver assistance technologies including Traffic Aware Cruise Control and Autosteer with lane change, which enables automatic steering on undivided roads but with speed limitations
- Level 3 automation is referred to as conditional automation. In Level 3 automation, the autonomous cars driving system performs all the dynamic driving tasks with the expectation that the human driver will respond appropriately to a request to intervene.
North America and Europe covered more than half of the global semi-autonomous cars market in 2018 and likely to continue to increase their market share, during the forecast period, owing to the increasing launch of semi-autonomous car models and increasing development towards vehicle semi-autonomous systems among players in the automotive industry.
Major players operating in the global autonomous/driverless cars market include Uber Technologies Inc., Daimler AG, Google Inc., Toyota Motor Corp, Nissan Motor Co. Ltd, Volvo Cars, General Motors Company, Volkswagen AG, Tesla Inc., and BMW.
Volvo and Chinese internet service provider, Baidu, have joined hands to develop and mass produce self-driving electric cars in China. Volvo will offer its expertise in advanced technologies in the auto industry, whereas Baidu provides its autonomous driving platform, Apollo.
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1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Technology Trends
4.3 Market Drivers
4.4 Market Restraints
4.5 Industry Attractiveness - Porter's Five Force Analysis
4.5.1 Threat of New Entrants
4.5.2 Bargaining Power of Buyers/Consumers
4.5.3 Bargaining Power of Suppliers
4.5.4 Threat of Substitute Products
4.5.5 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 Mergers & Acquisitions
6.3 Company Profiles
6.3.1 Uber Technologies Inc.
6.3.2 Daimler AG
6.3.3 Google Inc.
6.3.4 Toyota Motor Corp.
6.3.5 Nissan Motor Co. Ltd.
6.3.6 Volvo Cars
6.3.7 General Motors Company
6.3.8 Volkswagen AG
6.3.9 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.