Investment Rating - The report maintains a positive investment recommendation for companies with full-stack self-research capabilities, such as Li Auto, Xpeng Motors, and Xiaomi Group, as well as those with a combination of self-research and third-party collaboration like BYD, Geely, and Great Wall Motors [4][6]. Core Insights - The report emphasizes that intelligent driving has evolved from a technical highlight to a critical factor for product differentiation among automakers and a core support for the commercialization of mobility services [1][11]. - The competition in the intelligent driving sector is intensifying, driven by advancements in AI models and the need for enhanced computational power in both vehicle and cloud environments [2][3][57]. - The commercialization process of intelligent driving is accelerating, with increased regional pilot programs and favorable policies driving the adoption of L3 intelligent driving technologies [4][15]. Summary by Sections 1. Introduction - The report provides a comprehensive analysis of the evolution of intelligent driving technology architecture, focusing on algorithm development trends and the current state of computational power and data layout [11]. 2. AI Model Restructuring Competition - The VLA (Vision-Language-Action) technology is highlighted as a core focus in current intelligent driving solutions, integrating perception, cognition, and action [12]. - The demand for computational power is surging, with the need for real-time decision-making capabilities in dynamic environments [57][58]. - Major automakers are racing to enhance their computational capabilities, with Tesla leading through its integrated technology stack and data feedback loops [3][13]. 3. Core Self-Research Automakers - Tesla's end-to-end architecture and high-efficiency data loops have established its leading position in the intelligent driving industry [3][14]. - Domestic automakers are accelerating their technological advancements but still face generational gaps in data feedback capabilities and algorithm integration [3][14]. 4. Acceleration of Commercialization - The report notes that the "intelligent driving equity" trend is expected to drive the adoption of advanced driving features in lower price segments, enhancing consumer sensitivity to intelligent driving technologies [4][15]. - The Robotaxi market is projected to reach several hundred billion by 2030, with significant potential for growth [4][15]. 5. Investment Recommendations - The report suggests that the establishment of a clear responsibility system under top-level policies will facilitate the maturation of intelligent driving technologies, with L3 standards becoming increasingly reliable [4]. - Companies with differentiated advantages in algorithms, computational power, and data are expected to reshape brand value and gain competitive advantages in the intelligent driving market [4].

Core Viewpoint - The development of intelligent driving technology has become a significant indicator of automotive companies' capabilities, but it has also led to industry chaos and safety incidents, prompting regulatory bodies to enhance safety standards [2][3] Group 1: Industry Challenges - The industry faces three main bottlenecks: technical issues, testing and inspection challenges, and ecosystem deficiencies [3] - Technical challenges include the ongoing debate between vision-based and LiDAR-based solutions, which distracts companies and affects performance in complex scenarios [3] - The lack of clear standards for assisted driving levels leads to marketing exaggerations, causing misuse by consumers [3] - Testing resources are fragmented, with companies duplicating efforts in building testing facilities, leading to inefficiencies [4] - The traditional testing methods are inadequate for the needs of intelligent connected vehicles, necessitating the development of new technologies [4] Group 2: Regional Development and Investment - The East China region, as a major automotive cluster, accounts for over 35% of the national automotive industry, with cities like Shanghai and Suzhou at its core [5] - China Automotive Research Institute (CARI) is investing over 2.3 billion yuan to establish a headquarters in Suzhou, aiming to support the automotive industry's high-end, intelligent, and green upgrades [5][6] - The headquarters will feature over 1,000 advanced R&D and testing facilities, providing comprehensive support across the automotive supply chain [6] Group 3: Collaborative Ecosystem - CARI's headquarters aims to create a collaborative ecosystem involving local governments, testing institutions, and enterprises to enhance the automotive industry's development [7][8] - The establishment of the "Suzhou New Energy Vehicle Public Service Platform" will provide integrated testing and certification services, promoting high-quality development in the intelligent connected vehicle sector [8] - Collaboration with universities and technology companies is emphasized to accelerate research and innovation in key areas such as vehicle-grade chips and intelligent driving systems [9][10]