Automotive Self driving Chip

Self-Driving Automotive Chip Market Outlook

The global self-driving automotive chip market is projected to reach approximately USD 65 billion by 2035, exhibiting a robust compound annual growth rate (CAGR) of around 27% during the forecast period from 2025 to 2035. This exponential growth is driven primarily by the escalating demand for advanced driver assistance systems (ADAS) and autonomous vehicle technologies, which necessitate highly efficient, reliable, and powerful processing units. Additionally, the increased focus on the integration of artificial intelligence (AI) and machine learning (ML) algorithms into automotive systems for enhanced safety features and user experience is significantly influencing market dynamics. The rising consumer preference for connected vehicles, coupled with government regulations promoting vehicle safety standards, is further propelling the need for sophisticated automotive chips. The ongoing advancements in semiconductor technologies and the growing partnerships between automotive manufacturers and technology companies are also contributing to the market's expansion.

Growth Factor of the Market

The self-driving automotive chip market is experiencing substantial growth due to several key factors. Firstly, advancements in artificial intelligence (AI) and machine learning (ML) are enabling more efficient processing capabilities, which are critical for real-time data analysis and decision-making in autonomous vehicles. Secondly, the increasing adoption of electric vehicles (EVs) is leading to a surge in demand for advanced semiconductor chips that can support the extensive electronic systems present in these vehicles. Moreover, as consumers become more tech-savvy, their demand for connected and automated driving experiences is driving automotive manufacturers to enhance vehicle systems with innovative chip technologies. Additionally, strategic collaborations between tech companies and automotive manufacturers are fostering the development of next-generation chips that meet the rigorous requirements of autonomous driving. Lastly, government initiatives aimed at promoting smart transportation solutions and reducing road accidents are further boosting the demand for self-driving technology, thereby stimulating the automotive chip market.

Key Highlights of the Market

• Projected market size of approximately USD 65 billion by 2035.
• CAGR of around 27% during the forecast period from 2025 to 2035.
• Increased adoption of ADAS and autonomous driving technologies.
• Growing demand for electric vehicles leading to advanced chip technologies.
• Government initiatives promoting smart transportation solutions and safety standards.

By Product Type

Central Processing Unit :

The Central Processing Unit (CPU) is a critical component in the self-driving automotive chip market that manages and executes various vehicle functions and applications. As the brain of the vehicle’s computing system, CPUs play a vital role in processing data from numerous sensors and ensuring seamless communication between different modules. With the increasing complexity of algorithms required for autonomous driving, the demand for high-performance CPUs has surged. Manufacturers are focusing on developing multi-core processors that can handle parallel processing, thereby improving reaction times and reducing latency. This segment is anticipated to witness significant growth as automotive systems evolve, necessitating more robust processing capabilities to support advanced navigation, user interfaces, and safety systems.

Graphics Processing Unit :

Graphics Processing Units (GPUs) are increasingly becoming essential in the self-driving automotive chip market, primarily due to their ability to perform parallel processing tasks efficiently. The demand for GPUs is particularly driven by the need for real-time image processing from cameras and other sensory equipment used in autonomous vehicles. They allow for the rapid analysis of video data, enabling features such as object recognition and environment mapping, which are crucial for safe navigation. As the technology develops, GPUs are being integrated with AI capabilities to enhance their processing power, making them indispensable for future autonomous driving applications. The market for GPUs is expected to grow significantly as vehicle manufacturers seek to implement advanced visual processing solutions in their automotive designs.

Application-Specific Integrated Circuit :

Application-Specific Integrated Circuits (ASICs) are tailored for specific functionalities within the self-driving automotive chip market, providing optimized performance and energy efficiency. These chips are designed to handle specific tasks, such as data processing, signal processing, and control functions, which are integral to the operation of autonomous systems. The use of ASICs allows manufacturers to achieve better performance with lower power consumption, which is essential in the automotive space where energy efficiency is a priority. As vehicles become more sophisticated, the demand for ASICs is expected to increase, driven by the need for customized solutions that can meet the unique requirements of various automotive applications, including safety and navigation systems.

Field-Programmable Gate Array :

Field-Programmable Gate Arrays (FPGAs) offer a flexible and reconfigurable solution for the self-driving automotive chip market, allowing manufacturers to adapt to changing technology requirements and consumer demands. FPGAs can be programmed post-manufacturing, enabling engineers to modify the chip's functionality based on specific application needs without requiring a complete redesign. This characteristic makes FPGAs particularly valuable in the rapidly evolving automotive sector, where technological advancements occur frequently. As the push for autonomous vehicles intensifies, manufacturers are increasingly leveraging FPGAs for tasks such as real-time data processing, sensor fusion, and hardware acceleration of complex algorithms, making this segment poised for robust growth.

Neural Processing Unit :

Neural Processing Units (NPUs) are emerging as a vital component in the self-driving automotive chip market, specifically designed to accelerate machine learning computations. As AI becomes integral to autonomous driving systems, NPUs offer the necessary computational power required for processing vast amounts of data generated by vehicle sensors, enabling real-time decision-making. These chips are optimized for neural network computations, which are crucial for tasks like object detection, classification, and path planning. The increasing focus on AI-driven features in vehicles is driving the demand for NPUs, as they enhance the vehicle's ability to learn and adapt to different driving environments. This segment is expected to grow significantly as vehicle manufacturers prioritize AI capabilities in their automotive designs.

By Application

Advanced Driver Assistance Systems :

Advanced Driver Assistance Systems (ADAS) are a critical application segment within the self-driving automotive chip market, providing essential safety features that enhance vehicle performance and driver awareness. ADAS incorporates various functions such as adaptive cruise control, lane-keeping assistance, and automatic emergency braking, which rely heavily on advanced processing capabilities to function effectively. The increasing focus on vehicle safety and the growing number of road accidents are driving the adoption of ADAS technologies. With the integration of sophisticated sensors and cameras, the demand for high-performance chips that can process data in real-time is surging. As regulatory bodies impose stricter safety standards, the market for chips supporting ADAS applications is expected to grow significantly.

Autonomous Vehicles :

The autonomous vehicle segment represents the forefront of innovation within the self-driving automotive chip market, where chips are essential for enabling fully automated driving capabilities. These vehicles rely on a combination of sensors, cameras, and advanced algorithms to navigate and make decisions without human intervention. The complexity of autonomous driving systems necessitates powerful processing units that can handle extensive data processing and machine learning tasks simultaneously. As automakers invest heavily in autonomous technologies, the demand for specialized chips designed to meet the rigorous requirements of fully autonomous vehicles is increasing rapidly. This segment is anticipated to witness substantial growth as technology continues to advance and public acceptance of autonomous vehicles rises.

Connected Vehicles :

Connected vehicles represent another significant application within the self-driving automotive chip market, focusing on enhancing vehicle communication with other vehicles and infrastructure. These vehicles utilize advanced chip technologies to enable data exchange through various network protocols, improving safety and traffic management. The rise of Internet of Things (IoT) and smart city initiatives is driving the demand for connected vehicle solutions, as they are integral to efficient traffic flow and accident prevention. The chips used in connected vehicles must support high-bandwidth data transmission and processing capabilities to handle the continuous influx of information. As automotive manufacturers aim to enhance vehicle connectivity features, the market for chips designed for connected vehicles is expected to experience strong growth.

Infotainment Systems :

Infotainment systems are becoming an increasingly important application within the self-driving automotive chip market, providing entertainment, navigation, and connectivity features for drivers and passengers. These systems rely on advanced chip technologies to deliver high-quality graphics, audio, and seamless interactivity. As consumer expectations rise for integrated smartphone connectivity and multimedia capabilities, automotive manufacturers are investing in sophisticated infotainment solutions powered by high-performance chips. The demand for user-friendly interfaces and real-time data processing in infotainment systems is driving the growth of this segment, as automakers seek to enhance the overall driving experience and provide added value to consumers.

By Distribution Channel

OEMs :

The Original Equipment Manufacturers (OEMs) distribution channel plays a pivotal role in the self-driving automotive chip market, as these companies design and integrate chips into their vehicles during the manufacturing process. OEMs are increasingly recognizing the importance of advanced chip technologies to enhance vehicle performance, safety, and connectivity features. As the competition in the automotive sector intensifies, OEMs are investing in high-quality chip solutions to differentiate their products and meet consumer demands. This segment is expected to grow significantly as the trend towards electrification and automation continues, driving the need for sophisticated chip technologies in newly manufactured vehicles.

Aftermarket :

The aftermarket segment in the self-driving automotive chip market encompasses the installation and upgrading of chip technologies in vehicles after their initial sale. As consumers increasingly seek to enhance the capabilities of their existing vehicles, the demand for advanced chips in the aftermarket is growing. This segment is characterized by a wide range of applications, including retrofitting older vehicles with modern safety features and connectivity solutions. As technology continues to evolve, more consumers are looking for options to upgrade their vehicles to include advanced features such as ADAS and infotainment systems. Consequently, the aftermarket segment is poised for growth as automotive enthusiasts and everyday consumers embrace the benefits of enhanced chip technologies.

By Technology

5G :

5G technology is revolutionizing the self-driving automotive chip market by enabling faster data transmission and improved connectivity between vehicles and infrastructure. The implementation of 5G networks facilitates real-time communication, allowing vehicles to share critical information with each other and the surrounding environment. This enhanced connectivity is essential for the development of autonomous driving systems, as it supports features such as vehicle-to-vehicle (V2V) communication and vehicle-to-infrastructure (V2I) communication. As automotive manufacturers increasingly integrate 5G capabilities into their vehicles, the demand for chips that support this technology is expected to rise significantly. The ability to process and communicate data at high speeds will be a key driver for the growth of the self-driving automotive chip market.

Artificial Intelligence :

Artificial intelligence (AI) is a transformative technology within the self-driving automotive chip market, driving advancements in autonomous systems and enhancing vehicle capabilities. AI algorithms enable vehicles to learn from their environments, make predictions, and adapt to changing conditions in real-time. The integration of AI into automotive chips allows for efficient processing of data from sensors, cameras, and other sources, significantly improving the safety and performance of self-driving vehicles. As manufacturers strive to enhance their vehicles with intelligent features, the demand for AI-enabled chips is expected to grow. This segment will continue to expand as the automotive industry increasingly prioritizes AI technologies in the development of new vehicle models.

Machine Learning :

Machine learning is increasingly being utilized in the self-driving automotive chip market to enhance decision-making processes and improve system performance. By leveraging machine learning algorithms, vehicles can analyze vast amounts of data, identify patterns, and make informed decisions based on real-time information. The ability to learn from experience allows machines to improve their performance over time, making them crucial for autonomous driving applications. As the complexity of driving scenarios increases, the demand for chips that can efficiently process machine learning algorithms is on the rise. This segment is expected to grow significantly as automotive manufacturers implement more sophisticated machine learning solutions in their vehicles.

Radar :

Radar technology is a vital component of the self-driving automotive chip market, providing essential capabilities for detecting and tracking objects in a vehicle's surroundings. Radar systems are particularly effective in various weather conditions, offering a reliable means of detecting obstacles, other vehicles, and pedestrians. The integration of radar technology into automotive chips enhances the safety and efficiency of autonomous driving systems by enabling real-time data processing and decision-making. As the demand for safer driving experiences continues to grow, the market for chips supporting radar technology is expected to witness significant growth. Automotive manufacturers are increasingly investing in radar solutions to enhance their vehicles' capabilities and ensure compliance with safety regulations.

Lidar :

Lidar technology plays a crucial role in the self-driving automotive chip market by providing high-resolution 3D mapping and object detection capabilities. Lidar sensors emit laser pulses to measure distances and create detailed representations of the environment, allowing vehicles to identify and navigate obstacles effectively. The advanced capabilities of lidar make it an essential component of autonomous driving systems, as it enhances the vehicle's perception of its surroundings. As the technology matures and costs decrease, the demand for chips designed to support lidar applications is expected to rise. The integration of lidar technology in vehicles will be pivotal for advancing the development of fully autonomous driving solutions.

By Region

The self-driving automotive chip market is witnessing remarkable growth across various regions, with North America and Europe leading in terms of technological advancements and adoption rates. North America is projected to dominate the market during the forecast period, driven by the presence of key automotive manufacturers and technology companies investing heavily in autonomous driving technologies. The region's market size is expected to reach around USD 25 billion by 2035, supported by the rapid implementation of advanced driver assistance systems and government initiatives promoting vehicle safety. In Europe, the market is also anticipated to grow significantly, reaching approximately USD 20 billion, as automakers prioritize the development of electric and autonomous vehicles in response to stringent environmental regulations.

Meanwhile, the Asia Pacific region is emerging as a key player in the self-driving automotive chip market, with projections indicating a market size of approximately USD 15 billion by 2035. The growth in this region is propelled by the rising demand for connected vehicles, supported by advancements in technology and increasing urbanization. Countries like China and Japan are at the forefront of developing autonomous driving solutions, thereby creating opportunities for significant market expansion. Latin America and the Middle East & Africa are gradually adopting self-driving technologies, with market sizes expected to reach around USD 3 billion and USD 2 billion, respectively, by 2035, as economic development and technological advancements continue to unfold.

Opportunities

The self-driving automotive chip market presents a multitude of opportunities for growth and innovation as technology continues to advance. One of the most significant opportunities lies in the development of chips tailored for specific applications, such as enhanced vehicle-to-everything (V2X) communication systems. As smart cities and connected environments evolve, there is an increasing demand for vehicles that can communicate with traffic signals, other cars, and even infrastructure. This creates a substantial market for specialized chips designed to facilitate seamless communication, which can enhance traffic flow and improve safety standards. Additionally, the rising focus on sustainability provides opportunities for chip manufacturers to create energy-efficient solutions that not only meet performance requirements but also contribute to reducing the carbon footprint of vehicles.

Moreover, partnerships and collaborations between traditional automotive manufacturers and technology companies are paving the way for innovative chip solutions tailored to meet the needs of autonomous vehicles. By working together, these companies can leverage each other's expertise to develop cutting-edge technologies that enhance vehicle performance and safety. As the demand for autonomous and connected vehicles continues to grow, there will be a greater need for advanced chips capable of processing vast amounts of data in real-time, thereby opening up new avenues for research and development. Furthermore, the emergence of new players in the semiconductor market will encourage healthy competition, driving innovation and potentially leading to more cost-effective solutions for automotive manufacturers.

Threats

The self-driving automotive chip market faces several threats that could hinder its growth and implementation. One of the primary threats is the rapid pace of technological change, which can lead to obsolescence of existing chip technologies. As new advancements emerge, automotive manufacturers may find themselves needing to adopt newer technologies at a faster rate than anticipated, leading to increased costs and challenges in integrating these advancements into existing systems. Additionally, cybersecurity concerns are becoming increasingly prominent, as the integration of chip technology in vehicles opens up potential vulnerabilities to hacking and unauthorized access. Ensuring the security of both hardware and software is crucial to maintaining consumer trust and preventing potential safety hazards.

Another significant threat is the regulatory landscape, which can vary significantly across different regions. As governments implement stricter safety standards and regulations for autonomous vehicles, chip manufacturers may face additional challenges in ensuring compliance while still delivering competitive products. Furthermore, the presence of established players in the semiconductor market could pose a barrier for new entrants, as they may struggle to compete against established brands that have built a reputation for quality and reliability. These factors combined create a complex environment for the self-driving automotive chip market, necessitating strategic planning and innovation to navigate potential pitfalls.

Competitor Outlook

• NVIDIA Corporation
• Intel Corporation
• Qualcomm Technologies, Inc.
• Texas Instruments Incorporated
• Infineon Technologies AG
• STMicroelectronics N.V.
• Analog Devices, Inc.
• Renesas Electronics Corporation
• ON Semiconductor Corporation
• Maxim Integrated Products, Inc.
• Micron Technology, Inc.
• Broadcom Inc.
• Autotalks Ltd.
• Mobileye N.V.
• Samsung Electronics Co., Ltd.

The competitive landscape of the self-driving automotive chip market is characterized by a mix of established semiconductor manufacturers and emerging technology firms specializing in automotive solutions. Major players, such as NVIDIA and Intel, are at the forefront of innovation, continuously investing in research and development to enhance their product offerings. NVIDIA, renowned for its powerful GPUs, has made significant strides in autonomous vehicle technology, with a focus on AI and machine learning capabilities. Their partnerships with leading automakers have positioned them as a key player in the market, driving the adoption of advanced chip technologies in self-driving applications.

Similarly, Qualcomm has established itself as a leader in automotive connectivity solutions, leveraging its expertise in mobile technologies to develop chips that enable seamless communication in connected vehicles. The company’s focus on V2X communication and 5G integration aligns with the growing demand for connected vehicle solutions, further solidifying its position in the market. Additionally, companies like Mobileye, with its advanced driver assistance and autonomous driving technologies, are also contributing to the competitive dynamics of the market. Mobileye's innovative chip solutions, coupled with its extensive experience in computer vision, have made it a prominent player in the development of self-driving technologies.

Furthermore, as the demand for electric vehicles and autonomous driving technologies accelerates, new entrants and startups are emerging in the self-driving automotive chip market, offering innovative solutions and challenging established players. Companies like Autotalks, specializing in V2X communication, are gaining traction as they provide tailored solutions for enhancing vehicle safety and connectivity. This influx of new companies is expected to foster competition and drive innovation, leading to the development of more advanced and cost-effective chip solutions. Overall, the self-driving automotive chip market is poised for significant growth, driven by technological advancements and the increasing adoption of autonomous driving technologies.

• 1 Appendix

  • 1.1 List of Tables
  • 1.2 List of Figures

• 2 Introduction

  • 2.1 Market Definition
  • 2.2 Scope of the Report
  • 2.3 Study Assumptions
  • 2.4 Base Currency & Forecast Periods

• 3 Market Dynamics

  • 3.1 Market Growth Factors
  • 3.2 Economic & Global Events
  • 3.3 Innovation Trends
  • 3.4 Supply Chain Analysis

• 4 Consumer Behavior

  • 4.1 Market Trends
  • 4.2 Pricing Analysis
  • 4.3 Buyer Insights

• 5 Key Player Profiles

  • 5.1 Broadcom Inc.
    • 5.1.1 Business Overview
    • 5.1.2 Products & Services
    • 5.1.3 Financials
    • 5.1.4 Recent Developments
    • 5.1.5 SWOT Analysis
  • 5.2 Mobileye N.V.
    • 5.2.1 Business Overview
    • 5.2.2 Products & Services
    • 5.2.3 Financials
    • 5.2.4 Recent Developments
    • 5.2.5 SWOT Analysis
  • 5.3 Autotalks Ltd.
    • 5.3.1 Business Overview
    • 5.3.2 Products & Services
    • 5.3.3 Financials
    • 5.3.4 Recent Developments
    • 5.3.5 SWOT Analysis
  • 5.4 Intel Corporation
    • 5.4.1 Business Overview
    • 5.4.2 Products & Services
    • 5.4.3 Financials
    • 5.4.4 Recent Developments
    • 5.4.5 SWOT Analysis
  • 5.5 NVIDIA Corporation
    • 5.5.1 Business Overview
    • 5.5.2 Products & Services
    • 5.5.3 Financials
    • 5.5.4 Recent Developments
    • 5.5.5 SWOT Analysis
  • 5.6 Analog Devices, Inc.
    • 5.6.1 Business Overview
    • 5.6.2 Products & Services
    • 5.6.3 Financials
    • 5.6.4 Recent Developments
    • 5.6.5 SWOT Analysis
  • 5.7 Micron Technology, Inc.
    • 5.7.1 Business Overview
    • 5.7.2 Products & Services
    • 5.7.3 Financials
    • 5.7.4 Recent Developments
    • 5.7.5 SWOT Analysis
  • 5.8 STMicroelectronics N.V.
    • 5.8.1 Business Overview
    • 5.8.2 Products & Services
    • 5.8.3 Financials
    • 5.8.4 Recent Developments
    • 5.8.5 SWOT Analysis
  • 5.9 Infineon Technologies AG
    • 5.9.1 Business Overview
    • 5.9.2 Products & Services
    • 5.9.3 Financials
    • 5.9.4 Recent Developments
    • 5.9.5 SWOT Analysis
  • 5.10 Qualcomm Technologies, Inc.
    • 5.10.1 Business Overview
    • 5.10.2 Products & Services
    • 5.10.3 Financials
    • 5.10.4 Recent Developments
    • 5.10.5 SWOT Analysis
  • 5.11 ON Semiconductor Corporation
    • 5.11.1 Business Overview
    • 5.11.2 Products & Services
    • 5.11.3 Financials
    • 5.11.4 Recent Developments
    • 5.11.5 SWOT Analysis
  • 5.12 Samsung Electronics Co., Ltd.
    • 5.12.1 Business Overview
    • 5.12.2 Products & Services
    • 5.12.3 Financials
    • 5.12.4 Recent Developments
    • 5.12.5 SWOT Analysis
  • 5.13 Texas Instruments Incorporated
    • 5.13.1 Business Overview
    • 5.13.2 Products & Services
    • 5.13.3 Financials
    • 5.13.4 Recent Developments
    • 5.13.5 SWOT Analysis
  • 5.14 Maxim Integrated Products, Inc.
    • 5.14.1 Business Overview
    • 5.14.2 Products & Services
    • 5.14.3 Financials
    • 5.14.4 Recent Developments
    • 5.14.5 SWOT Analysis
  • 5.15 Renesas Electronics Corporation
    • 5.15.1 Business Overview
    • 5.15.2 Products & Services
    • 5.15.3 Financials
    • 5.15.4 Recent Developments
    • 5.15.5 SWOT Analysis

• 6 Market Segmentation

  • 6.1 Automotive Self driving Chip Market, By Technology
    • 6.1.1 5G
    • 6.1.2 Artificial Intelligence (AI)
    • 6.1.3 Machine Learning
    • 6.1.4 Radar
    • 6.1.5 Lidar
  • 6.2 Automotive Self driving Chip Market, By Application
    • 6.2.1 Advanced Driver Assistance Systems (ADAS)
    • 6.2.2 Autonomous Vehicles
    • 6.2.3 Connected Vehicles
    • 6.2.4 Infotainment Systems
    • 6.2.5 Others
  • 6.3 Automotive Self driving Chip Market, By Product Type
    • 6.3.1 Central Processing Unit (CPU)
    • 6.3.2 Graphics Processing Unit (GPU)
    • 6.3.3 Application-Specific Integrated Circuit (ASIC)
    • 6.3.4 Field-Programmable Gate Array (FPGA)
    • 6.3.5 Neural Processing Unit (NPU)

• 7 Competitive Analysis

  • 7.1 Key Player Comparison
  • 7.2 Market Share Analysis
  • 7.3 Investment Trends
  • 7.4 SWOT Analysis

• 8 Research Methodology

  • 8.1 Analysis Design
  • 8.2 Research Phases
  • 8.3 Study Timeline

• 9 Future Market Outlook

  • 9.1 Growth Forecast
  • 9.2 Market Evolution

• 10 Geographical Overview

  • 10.1 Europe - Market Analysis
    • 10.1.1 By Country
      • 10.1.1.1 UK
      • 10.1.1.2 France
      • 10.1.1.3 Germany
      • 10.1.1.4 Spain
      • 10.1.1.5 Italy
  • 10.2 Asia Pacific - Market Analysis
    • 10.2.1 By Country
      • 10.2.1.1 India
      • 10.2.1.2 China
      • 10.2.1.3 Japan
      • 10.2.1.4 South Korea
  • 10.3 Latin America - Market Analysis
    • 10.3.1 By Country
      • 10.3.1.1 Brazil
      • 10.3.1.2 Argentina
      • 10.3.1.3 Mexico
  • 10.4 North America - Market Analysis
    • 10.4.1 By Country
      • 10.4.1.1 USA
      • 10.4.1.2 Canada
  • 10.5 Middle East & Africa - Market Analysis
    • 10.5.1 By Country
      • 10.5.1.1 Middle East
      • 10.5.1.2 Africa
  • 10.6 Automotive Self driving Chip Market by Region

• 11 Global Economic Factors

  • 11.1 Inflation Impact
  • 11.2 Trade Policies

• 12 Technology & Innovation

  • 12.1 Emerging Technologies
  • 12.2 AI & Digital Trends
  • 12.3 Patent Research

• 13 Investment & Market Growth

  • 13.1 Funding Trends
  • 13.2 Future Market Projections

• 14 Market Overview & Key Insights

  • 14.1 Executive Summary
  • 14.2 Key Trends
  • 14.3 Market Challenges
  • 14.4 Regulatory Landscape

Segments Analyzed in the Report

The global Automotive Self driving Chip market is categorized based on

By Product Type

• Central Processing Unit (CPU)
• Graphics Processing Unit (GPU)
• Application-Specific Integrated Circuit (ASIC)
• Field-Programmable Gate Array (FPGA)
• Neural Processing Unit (NPU)

By Application

• Advanced Driver Assistance Systems (ADAS)
• Autonomous Vehicles
• Connected Vehicles
• Infotainment Systems
• Others

By Technology

• 5G
• Artificial Intelligence (AI)
• Machine Learning
• Radar
• Lidar

By Region

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East & Africa

Key Players

• NVIDIA Corporation
• Intel Corporation
• Qualcomm Technologies, Inc.
• Texas Instruments Incorporated
• Infineon Technologies AG
• STMicroelectronics N.V.
• Analog Devices, Inc.
• Renesas Electronics Corporation
• ON Semiconductor Corporation
• Maxim Integrated Products, Inc.
• Micron Technology, Inc.
• Broadcom Inc.
• Autotalks Ltd.
• Mobileye N.V.
• Samsung Electronics Co., Ltd.