The global autonomous vehicle processor market size was valued at USD 6.85 billion in 2021 and is projected to reach USD 44.30 billion by 2030 at a CAGR of 23.05% from 2022 to 2030. Due to its ability to perceive its surroundings, an autonomous vehicle or driverless vehicle is able to operate itself and carry out required functions without human intervention. It uses artificial intelligence (AI) software, light detection & ranging (LiDAR), radio detection & ranging (RADAR), and cameras to sense the environment and navigate by constructing an active 3D map of that environment. Numerous sensors, such as RADAR, are utilised by the majority of autonomous driving systems to create and maintain an internal map of their surroundings. From semi-autonomous, which requires driver assistance, to fully autonomous, there are a variety of levels of autonomy. The Society of Automotive Engineers (SAE) defines six levels of driving automation, from level 0 (completely manual) to level 5 (highly automated) (fully autonomous).
A self-driving vehicle is a combination of various networking systems and sensors that aid the computer in driving the vehicle. Significant technological advancements, such as sensor processing, adaptive algorithms, high processing maps, and improved AI, have helped companies increase their production capacity and advance the autonomous vehicle market.
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Autonomous vehicles have brought numerous advantages to existing road networks. These vehicles have a number of advantages over conventional vehicles, including increased safety, decreased fuel consumption, and reduced traffic congestion and emissions. A self-driving vehicle is equipped with multiple sensors, including LiDAR, RADAR, a camera, and GPS, which aids in the processing of traffic data in a timely manner and reduces M2M latency. Additionally, this superior connectivity enables and incorporates advanced AI-based traffic management and navigation services via smart streets that connect to sensors in autonomous vehicles, optimised traffic signals, predictive merging, and slowdowns.
In September of 2018, AB Volvo created the next-generation transport solution for commercial vehicles, which includes an autonomous system. In order to provide the most efficient and safe transportation possible, vehicles are coordinated by ensuring parameters such as location, battery charge, and load. In addition, safety improved as traffic became more organised and lane changes occurred less frequently. Consequently, as a result of these technological advancements in the automotive industry regarding connectivity and security, the demand for autonomous vehicles increased substantially. The global market growth is bolstered by factors such as an increase in safety, a decrease in traffic congestion, the expansion of connected infrastructure, and the shift from ownership to mobility as a service (MaaS).
Several industries are currently interested in the concept of routine task automation. Consequently, as a result of the rapid adoption of the Internet of Things (IoT), the global transportation infrastructure is evolving rapidly. Digital platforms have been developed by companies such as Cisco and IBM to automate street and traffic lights, optimise garbage collection, and enhance surveillance. In addition, connected infrastructure includes parking garages, toll booths, smart streets and traffic lights. Autonomous vehicles are capable of interacting with intelligent street lights to alleviate traffic congestion.
In 2018, the Audi A8 was the first production vehicle to be equipped with an automated driving system capable of connecting to a variety of communication networks. In addition, public authorities are encouraging the emergence of connected technologies that can generate new revenues in the areas of mobility, environment, and public health. According to the KPMG consulting firm, the Netherlands is the most prepared nation for the new infrastructure. It could serve as a model for other nations and speed up the global adoption of this technology. Consequently, the expansion of connected infrastructure is anticipated to increase demand for autonomous vehicles.
Autonomous vehicles have numerous components, each with distinct data management requirements that interact with other intelligent transportation systems and generate voluminous amounts of data, necessitating a system for data storage and processing. In addition, autonomous vehicles necessitate a great deal of computational power because the amount of data generated is enormous. In addition, training requires a large number of datasets. The neural networks of autonomous vehicles must be trained on representative datasets, which include examples of all conceivable conditions such as driving, weather, roads, and other situational conditions. Moreover, Global market growth is hindered by factors including high manufacturing costs and data management difficulties.
As a result of the rapid development of autonomous vehicles, numerous nations have enacted laws and regulations regarding the technology. The purpose of these guidelines is to address safety, liability, privacy, and security in relation to next-generation automobiles. In China, for instance, the Ministry of Industry & Information Technology, Ministry of Public Security, and Ministry of Transport have enacted regulations for the administration of autonomous vehicle road testing. As part of the country's overall plan to reorient its economy toward a high-tech industrial model that includes autonomous vehicles and related technologies, the focus is primarily on the autonomous driving industry. In addition, the U.S. Department of Transportation (USDOT) collaborated with a broad coalition of industry, academic, state, local, safety, advocacy, and transportation stakeholders to develop the Automated Vehicles Comprehensive Plan to support the safe development & testing and integration of automated vehicle technologies. Consequently, the modernised regulatory environment and supportive government regulations electrify market opportunities for autonomous vehicles.
The global autonomous vehicle processor market share is segmented by level of automation, component, application, propulsion type, vehicle type, and region. Depending on the level of automation, it is categorised into level 1, level 2, level 3, level 4, and level 5 automation. As per application, it is classified into civil, defence, transportation & logistics, and construction. By the propulsion type, it is divided into semi-autonomous and fully autonomous. On the basis of vehicle type, it is bifurcated into passenger cars and commercial vehicles. Region-wise, the market is analysed across North America, Europe, Asia-Pacific, and LAMEA.
The majority of semi-autonomous car models currently available are sedans. Similarly, the majority of level 2, level 3, and level 4 automobile developments target sedan segments. Mercedes-Benz, a German automobile manufacturer, equipped its V-class sedan with Baidu Apollo for extensive testing in the National Pilot Zone (Beijing and Hebei). In March 2021, Honda introduced the first semi-autonomous level 3 vehicle to the Japanese market. The vehicle is a luxury sedan that can operate autonomously under certain circumstances. In light of the developments and emphasis on sedans, this segment would continue to dominate the market.
Various governments, including those of the United States, Canada, China, India, South Korea, Japan, and European nations, have exempted BEVs from road or registration taxes. According to BEV sales reports of electric vehicles in numerous regions, these programmes are proving to be successful. BEVs are electric vehicles that obtain their power from chemical energy stored in rechargeable battery packs. The growth and success of BEVs are dependent on battery technology innovations. Consequently, numerous players in the automotive industry are developing battery technology. This will result in the BEV market is a significant market for autonomous vehicles.
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By 2030, Asia-Pacific is anticipated to have the largest market share, followed by Europe and North America. The Autonomous Vehicle Market is driven by the increasing demand for a safe, efficient, and convenient driving experience, the rising disposable income in emerging economies, and stringent safety regulations across the globe. The market in Asia-Pacific is anticipated to expand at the fastest rate over the forecast period due to the increased partnerships between autonomous vehicle technology providers in this region.