Self-Driving Cars Industry Size

The report "Self-Driving Cars Market by Level of Autonomy (L1, L2, L3, L4, L5), Mobility (Personal & Shared), Component (LIDAR, Radar, Camera, GNSS & IMU, SOC), Vehicle Class (A&B, C&D, E&F), Autonomous Driving System (Perception & Sensing, Compute & AI, Localization & Mapping, Planning & Decision Making, Vehicle Control, Safety & Redundancy), EV (BEV, PHEV, FCEV), and Region - Global Forecast to 2035", is projected to grow from 31,509 thousand units in 2026 and to reach 51,213 thousand units in 2035, at a Compound Annual Growth Rate (CAGR) of 5.5% during the forecast period.

Browse 250 market data Tables and 75 Figures spread through 300 Pages and in-depth TOC on "Self-Driving Cars Market by Level of Autonomy (L1, L2, L3, L4, L5), Mobility (Personal & Shared), Component (LIDAR, Radar, Camera, GNSS & IMU, SOC), Vehicle Class (A&B, C&D, E&F), Autonomous Driving System (Perception & Sensing, Compute & AI, Localization & Mapping, Planning & Decision Making, Vehicle Control, Safety & Redundancy), EV (BEV, PHEV, FCEV), and Region - Global Forecast to 2035"
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Self-driving cars are progressing from controlled testing toward commercial deployment, supported by advances in AI, computing architecture, and vehicle automation. The commercial operation of Level 4 robotaxis in multiple cities is accelerating investment in autonomous driving technologies, including perception, sensor fusion, decision-making software, and high-performance computing. These developments are also influencing passenger vehicle programs, where automakers are expanding Level 2+ driver assistance and developing new off-driving capabilities. Over the next few years, progress in AI models, simulation-based validation, and sensor integration is expected to improve system performance and support the wider deployment of automated driving across vehicle segments. Volkswagen is developing localized AI driving solutions in China through its CARIZON joint venture with Horizon Robotics, aligning its technology strategy with local market requirements. These strategies reflect a broader shift toward controlling software development, computing costs, and system integration. The competitive advantage will depend on how effectively automakers scale validated driving functions across vehicle portfolios, improve affordability, and meet regional regulatory requirements without compromising safety performance.

Hyundai Motor Group Builds an AI Data Strategy to Accelerate Self-driving Technology

• In September 2026, Hyundai Motor Group activated its Data Flywheel strategy, linking real-world driving data collection, AI training, simulation, validation, and software deployment. The group is targeting NVIDIA-based Level 2+ production vehicles in the first half of 2028 and Level 2++ vehicles in the second half of 2028, followed by proprietary Atria AI-powered Level 2++ vehicles in the second half of 2029.
• Hyundai’s two-track strategy allows it to deploy technology developed with NVIDIA while continuing to develop its own end-to-end Atria AI system through 42dot. By standardizing sensor systems across Hyundai, Kia and its technology subsidiaries, the group aims to improve data consistency and software reuse across vehicle platforms. This approach can reduce duplicated development efforts and accelerate the identification of difficult driving scenarios, although the commercial advantage will depend on translating larger data volumes into measurable safety and performance improvements.

Personal mobility is estimated to hold the largest share during the forecast period.

Personal mobility is emerging as a commercial opportunity in the self-driving cars market, as OEMs focus on making automated driving a practical feature that improves convenience and strengthens premium vehicle differentiation. According to China’s Ministry of Industry and Information Technology, 69.15% of passenger cars sold in January and February 2026 had Level 2 driving assistance, up 10 percentage points year on year. The US National Highway Traffic Safety Administration (NHTSA) added pass or fail assessments for advanced driver assistance systems to its New Car Assessment Program, encouraging automakers to improve safety features that protect drivers and pedestrians. The near-term opportunity lies in expanding assisted driving capabilities across urban roads and highways, while improving the reliability of AI-based perception, navigation, and decision-making. In January 2026, Mercedes-Benz presented MB. DRIVE ASSIST PRO on the new CLA, combining navigation with Level 2 driving assistance for supported urban journeys, with the system already available in China and a US launch planned for later in 2026. The development highlights how OEMs are leveraging automated driving capabilities to enhance the vehicle ownership experience and create opportunities for software-based feature upgrades. For automakers, the competitive advantage depends on delivering reliable automation across more vehicle models and price points, turning driving convenience into a stronger purchase incentive.

The Level 3 segment is to witness the fastest growth in the self-driving cars market during the forecast period.

The Level 3 segment is expected to be the fastest-growing segment in the self-driving cars market as automakers move beyond Level 2 driver assistance toward conditional automation. Adoption remains concentrated in specific driving conditions because Level 3 systems must operate within defined conditions and transfer control back to the driver when required. For instance, in December 2025, China approved its first two Level 3 passenger car models from Changan Automobile and BAIC's ARCFOX brand. The Changan model was approved for operation during highway traffic congestion at speeds of up to 50 km/h on designated roads in Chongqing, while the ARCFOX model was permitted to operate at speeds of up to 80 km/h on designated roads in Beijing. These restricted approvals show that Level 3 deployment is progressing through controlled operating conditions rather than unrestricted use. Automakers that align system capabilities with approved road conditions and reliable driver handover requirements will be better positioned to expand Level 3 passenger car offerings.

North America is expected to grow significantly during the forecast period.

North America is strengthening its position in the self-driving cars market as automakers expand AI-based driving assistance and autonomous mobility programs. A key focus is extending automation to complex urban environments while maintaining driver supervision in passenger vehicles. In May 2026, Stellantis partnered with Wayve to integrate Wayve’s AI Driver into its STLA Auto Drive platform, targeting supervised, hands-free driving across urban and highway routes, with North American deployment planned from 2028. In a separate development, Volkswagen Group’s MOIA America partnered with Uber to introduce autonomous ID. Buzz vehicles in Los Angeles, with on-road testing and plans to launch ride-hailing services by the end of 2026. The two initiatives highlight distinct development paths in the region: integrating AI-powered driving capabilities into passenger vehicle platforms and deploying autonomous electric vehicles for commercial mobility services. Progress will depend on system validation, regulatory approvals, operational safety, and the ability to handle diverse traffic conditions.

Key Players

The major players in the self-driving cars market include Toyota Motor Corporation (Japan), Volkswagen Group (Germany), BYD Co., Ltd. (China), Stellantis (Netherlands), and Hyundai Motor Group (South Korea). Their strategies focus on AI-driven systems, software integration, and wider deployment of automated driving. For instance, in July 2026, Stellantis partnered with Mobileye to integrate cloud-enhanced ADAS into selected future vehicles from 2027, using crowdsourced road data to improve hands-free driving availability and performance. These developments highlight OEM priorities in AI-based decision-making, computing efficiency, and cloud-enabled driving features. Competitive advantage will depend on scaling Level 2+ capabilities across high-volume models while controlling costs, maintaining system reliability, and preparing vehicle platforms for higher automation.

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