While we might not be the ones physically driving our cars in the future, rapid advancements in enabling technologies are already driving the automotive industry towards autonomous and semi-autonomous vehicle systems. For example, radar, vision and lidar sensors; the expanding capacity and capability of microcontrollers; faster-responding actuators and controllers; and the promise of machine learning via complex, artificial-intelligence driven software are all moving driverless vehicles ahead. The National Highway Traffic Safety Administration (NHTSA) reports that the continuing goal of automotive technology is to deliver increasing safety benefits and Automated Driving Systems (ADS) where fully automated cars and trucks will drive us, instead of us driving them. Enabling technologies have been incrementally introduced and accepted ranging from cruise control to lane assist technology.
According to MarketsandMarkets, in terms of volume, the number of semiautonomous cars was estimated to be 20.3 million units in 2021 and is expected to reach 62.4 million units by 2030, at a CAGR of 13.3%. Additionally, there are approximately 1,400 self-driving cars in the U.S. – these differ from semiautonomous that include only one or more autonomous features such as RADAR, LIDAR, cameras or ultrasonic sensors. When quantified from a revenue perspective, Allied Market Research reports that global autonomous vehicle market size is forecast to be valued at $76.13 billion in 2020, and is projected to reach $2,161.79 billion by 2030, at a CAGR of 40.1% from 2021 to 2030.
While sensors play many roles in the automotive market, autonomous and semi-autonomous vehicles are a driving force in their use. These vehicles combine sensors and software to control, navigate, and drive the vehicle, and use LiDAR and RADAR sensors for its operation. The majority of self-driving systems create and maintain an internal map of their surroundings, based on a wide array of sensors. BCC Research reports that the global market for automotive sensors should grow from $25.9 billion in 2020 to $78.9 billion by 2025, at a CAGR of 13.4% from 2020 to 2025.
Regionally speaking, by 2030, Asia Pacific is estimated to account for the largest market share of the semi-autonomous vehicles market, followed by Europe and North America. With respect to the North American region, semi-autonomous vehicles volumes have increases in recent years, with OEMs catering not only to the domestic demand but also to the overseas demand. Moreover, in 2025 the region is likely to lead the autonomous vehicles market in terms of volume followed by Europe and Asia Pacific, as key technology innovators such as Google, Microsoft, and Delphi automotive are significantly investing in and testing the technology to commercialize the same.
However, barriers in this market include the lack of infrastructure to support autonomous cars in developing nations, concerns regarding cyber security and safety of the personal data of the users, and consumers’ hesitation to accept fully autonomous cars are some of the restraints that might hinder the growth of autonomous and semi-autonomous vehicles. Frost & Sullivan reports that while technology development and the lack of a robust regulatory framework are the greatest obstacles in this market today, the need to understand consumer demand and the use of data for generating revenues will be the key challenge to address for OEMs in the future. To achieve this, analysts believe that OEMs will need to focus on developing flexible, autonomous platforms capable of providing multiple vehicle types for specific use cases to be successful in the future.
To address these future needs several groups have put together roadmaps, in 2021 the U.S. Department of Transportation (USDOT) developed the Automated Vehicles Comprehensive Plan to advance the Department’s work to prioritize safety while preparing for the future of transportation following the 2020 publication of the USDOT and the White House Office of Science and Technology Policy Ensuring American Leadership in Automated Vehicle Technologies: Automated Vehicles 4.0 (AV 4.0). Energy use and savings is also a key factor in any discussion of autonomous vehicles, as such Sandia National Laboratory formed a working group of academic, government and commercial partners, including engineers from the University of Michigan, Carnegie Mellon University, Arm, Hewlett Packard Enterprise, Intel Corp. and the U.S. Council for Automotive Research. The group identified four areas seen as critical to energy-efficient computing in automated vehicles, including computer chips, sensors, system architecture, and algorithms, all of which need to be considered when trying to improve computational energy efficiency. The group’s The Energy Efficient Computing R&D Roadmap Outline for Automated Vehicles identifies areas of R&D necessary to attain the high computational performance with low power consumption that will be required to achieve automated driving in retail vehicles.
