智能化指引中国汽车未来，2025新能源智能汽车新质发展论坛召开

Core Insights - The 2025 New Energy Intelligent Vehicle Development Forum emphasized the importance of intelligentization as a new productive force in the automotive industry, focusing on safety and efficiency innovations [1][3]. Industry Trends - The Chinese automotive industry is expected to accelerate the adoption of advanced driver assistance systems (ADAS) and cultivate a culture of intelligent driving, aiming for L3 and higher levels of automation by 2030 [3]. - The cost structure of vehicles is projected to shift significantly, with mechanical components decreasing from 70% to below 30%, while electronics and software will account for 70% of vehicle costs [3]. Company Strategies - Companies like Jianghuai Automobile and Lantu are focusing on high-quality development and technological innovation to break free from low-level competition [5][7]. - The collaboration between Jianghuai Automobile and Huawei since 2019 has led to deep integration across the entire value chain, exemplified by the launch of the "Respect" brand [7]. Technological Innovations - The integration of AI in vehicle systems is becoming standard, with challenges in hardware-software separation being highlighted by industry leaders [7]. - Great Wall Motors introduced an end-to-end driving assistance model that emphasizes safety through a combination of data-driven approaches and safety protocols [7]. Supply Chain Dynamics - The automotive supply chain is undergoing a transformation, with more chip manufacturers involved in early-stage vehicle design to meet rapid iteration and quality demands [10]. - The software supply chain in China has matured, enabling quick adaptation to chip and electronic architectures [10]. Academic Contributions - Experts from universities are proposing innovative ideas in key areas such as intelligent driving safety and electric drive systems, contributing to the industry's development [11][13]. - The concept of "cognitive-driven" technology is being introduced to enhance the safety and decision-making capabilities of intelligent vehicles [11].