In recent years, algorithms, chips, artificial intelligence, etc. have become the "keywords" for the updating and iteration of the automotive industry, which means that the intelligent driving car industry has entered the "second half" of accelerating intelligence. The key elements of competition in the automotive industry have shifted from horsepower to computing power, and have almost become the expectations and consensus of the industry and the public - this was fully reflected at the 2025 World Intelligent Connected Vehicle Conference held recently. It can be foreseen that through deep human-machine collaboration, vehicle functions will be upgraded from "driving tools" to a new space of "smart living". A picture of the future is gradually becoming clear: under the "blessing" of artificial intelligence, advanced intelligent driving cars are like embedded "wind and fire wheels", driving towards people. In the industry's view, the next stage of industrial competition still needs to address challenges such as breaking through key core technologies, clarifying industry standards, and ensuring security capabilities to meet the trend of future industrial transformation. Data shows that from January to July this year, the penetration rate of new passenger cars with L2 level driving assistance functions in China has reached about 63%. The industry expects that the intelligent driving car industry will continue its high-speed growth trend in the next 5 to 10 years. At present, China has initially established a systematic promotion path from regulatory guidance to engineering implementation, such as building an intelligent driving standard system covering intelligent driving classification, communication protocols, testing methods, etc; 32 pilot projects for intelligent driving have been organized and implemented in Beijing, Shanghai, Chongqing and other places; Construct 9 closed testing bases for intelligent driving and set up open testing areas in multiple cities. In recent years, the continuous introduction of multiple policies from the central to local levels has also accelerated the development of the intelligent driving car industry. Du Guangda, Deputy Director of the Science and Technology Department of the Ministry of Industry and Information Technology, stated that end-to-end big models empower the leap of driving automation capabilities, while artificial intelligence big models empower cars to improve quality and efficiency throughout the entire process of research and development, production, manufacturing, and operation management. Multimodal big models support the continuous evolution of intelligent cockpits towards full scenario intelligent services, and artificial intelligence is profoundly transforming the automotive industry. Currently, the global market regards intelligent driving vehicles as the "key territory" of the future industry. In this industry race, the market and the public should also clearly see that technological evolution cannot be blind, and the industry still faces multiple challenges. ——The multidimensional security risks constrain the boundaries of intelligent driving. New risks such as driving system failures, vehicle networking platform attacks, and data breaches cannot be ignored. Qin Tinghui, Deputy General Manager of Zhongdian Taiji (Group) Co., Ltd., and several industry insiders believe that with the evolution of intelligent driving levels, the original boundaries of automotive safety have also been broken, and the vulnerability of vehicle network security has intensified. The diverse and heterogeneous data generated by intelligent connected vehicles are facing new attack challenges in areas such as collection, transmission, and processing. The exposure of in vehicle networks is rapidly expanding, making it difficult for traditional boundary information security protection models to face advanced and persistent dangers. ——The lack of standardization system leads to high "trial and error costs" in the development path of the industry. Many industry insiders and experts believe that there are still some structural contradictions and challenges in building a global standardization system. Zhu Huarong, Chairman of China Changan Automobile Group Co., Ltd., said that the application scenarios of intelligent connected vehicles need to be "standard first". Due to the incomplete global standardization system, there are overlapping, duplication, and even contradictions among some standards, which brings cost pressure and technical difficulties to enterprise production and inspection. In addition, the significant differences in standards among countries also pose challenges for enterprises in terms of repeated certification and multiple overlapping regulations. ——Insufficient technological capabilities and R&D investment of enterprises have become key constraints. It is widely believed in the industry that there is still a significant lack of investment in underlying capabilities such as technology software and system toolchains. A large amount of research and development resources are repeatedly invested in short-term functional development, and the construction of core capabilities lags behind, making it difficult to support the continuous accumulation and efficiency release of system level innovation. An industry insider in the field of intelligent driving vehicles stated that major enterprises adopt a closed development model to build technological barriers, with dispersed research and development resources and inefficient system integration, which seriously restricts the competitiveness of the intelligent connected vehicle industry during critical window periods. To address the weak links in the "second half" competition of the intelligent driving car industry, China should focus on key core technology research, industry standard formulation, and related policy refinement at multiple levels, and give the industry a safe and orderly "acceleration". On the one hand, accelerate the capture of key core technologies and reduce industry research and development costs with the momentum of open source. Zhang Jianyong, Chairman of BAIC Group, suggested deepening technology sharing. In the face of common industry challenges such as perception fusion and high-precision positioning, enterprises should break down technical barriers, form joint research and development mechanisms, and build industry level autonomous driving data pools and testing resource platforms, open simulation scene libraries, and closed testing sites. At the same time, we will promote joint research and development of core key technologies such as chips and operating systems, and overcome common challenges. On the other hand, the government, enterprises and other parties jointly promote the construction of industry standards and accelerate the formation of a standard and regulatory system. Han Xia, former Chief Engineer of the Ministry of Industry and Information Technology and Executive Deputy Director and Secretary General of the Information and Communication Technology Commission of the Ministry of Industry and Information Technology, stated that at the government level, policy guidance and institutional guarantees will continue to be clarified and refined. Through the issuance of policy documents, institutional construction, and other means, security requirements will be clarified, and a collaborative, efficient, and powerful security management system will be built. Many industry insiders believe that policy coordination should also be promoted to break through barriers to cross regional implementation. It is suggested to accelerate the formulation of policies and regulations such as defining the responsibility boundaries of L3 level autonomous driving, and improve supporting policies such as cross-border data flow and security protection systems. (New Society)