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Ecordia Participates in the International Automotive Intelligent Cockpit Conference 2025

Suzhou, China – September 15, 2025 – The closed-door meeting of the International Automotive Intelligent Cockpit Conference 2025, themed "Tackling Key Intelligent Cockpit Technologies and Promoting Industrial Collaborative Development," was successfully held in Xiangcheng District, Suzhou. Hosted by the China Society of Automotive Engineers (CSAE), the meeting gathered over 40 industry representatives from universities, research institutes, OEMs, component suppliers, and inspection agencies. As an active participant and technology explorer in the automotive intelligent cockpit field, Ecordia was invited to attend. The participants engaged in discussions on technological breakthroughs, industrial collaboration, and ecosystem building, injecting new insights into the high-quality development of intelligent cockpits.

The closed-door meeting was co-chaired by Professor Guo Gang, Chairman of the CSAE Intelligent Cockpit Sub-committee and Professor at the School of Mechanical and Vehicle Engineering, Chongqing University, and Professor Cao Dongpu, Chief Researcher at Tsinghua University's National Key Laboratory of Intelligent Green Vehicles and Transportation and Changjiang Scholar Distinguished Professor. Attendees included Deputy Secretary-General Gong Jiejie and Deputy Secretary-General Lu Lili of CSAE, alongside representatives from Tongji University, the Human-Computer Interaction Laboratory of the Institute of Software, Chinese Academy of Sciences, Great Wall Motors, GAC R&D Center, Dongfeng Motor R&D Headquarters, Hongsheng Electronic, Banma Network, Jilin University, Institute of Psychology, Chinese Academy of Sciences, Zhejiang Digital Content Research Institute, FAW, SAIC Motor, Li Auto, Chery, Volkswagen Group China, Huawei, Xinghe Zhilian, BDStar Navigation Intelligent & Connected, PATEO, Mjia Technologies, Thunder Soft, Desay SV, SemiDrive, Qualcomm, New Unisplendour Group, Neusoft Group, Maxieye Tech, CarSmart, Ecordia, China Automotive Technology and Research Center, China Automotive Engineering Research Institute, and Xiangyang Da'an Automotive Proving Ground. Over 40 representatives from universities, research institutes, OEMs, components, and inspection agencies gathered to engage in in-depth exchanges on core intelligent cockpit topics.

Focusing on AI Cockpit Technology Innovation, Exploring Product Practice Directions

During the topic introduction session, Li Shuling, Head of Intelligent Cockpit Experience Design at Li Auto, presented on "The Integration of User Experience and Quality Management under the Evolution of Intelligent Cockpit Interaction," covering trends in cockpit interaction evolution, new challenges for quality in the AI era, and paths for AI-driven quality management. Addressing the topic "Application and Development of Large Models in Intelligent Cockpits," Professor Ma Jun, Dual-appointed Professor at Tongji University's School of Automotive Studies and College of Design and Innovation, discussed the value of small scenarios, the construction of data flywheels for automakers, and support from open-source tools. Cai Ming, CPO of Banma Zhixing, elaborated on the logic behind building AI-driven cockpit services, promotion paths, commercial value, and the significance of deploying large models on the device side. Professor Cao Dongpu, Changjiang Scholar Distinguished Professor and Chief Researcher at Tsinghua University's National Key Laboratory of Vehicles and Transportation, introduced the "Construction of the Intelligent Cockpit Group Standard System," covering the significance of group standards, mining real needs, and challenges and key points in construction.

Discussing Key Topics to Consolidate Industry Practical Wisdom

During the discussion session, participants held lively discussions on three main topics:

How to use user evaluations to establish quality traceability mechanisms, identify software/hardware issues, and balance the timeliness and comprehensiveness of software iterations.

How large models can achieve closed-loop training and deployment integrated with domain controllers, and how the industry can establish a data-model-service ecosystem and define model development paths.

How intelligent cockpit group standards can complement national and industry standards, adapt to rapid technological iteration, and which key areas urgently require standardization.

The discussions yielded key consensus points:

The foundation for intelligent cockpit quality traceability and optimization lies in systematically integrating multi-source user feedback and relevant data to provide comprehensive support for quality analysis. The core is technological empowerment—using AI and other intelligent means to translate fragmented user experience feedback into actionable R&D and mass production standards. The key link is building a closed-loop mechanism, i.e., establishing a full-process management system from data collection and demand interpretation to link optimization and effect verification. This system ultimately enables reverse optimization, tracing post-market quality issues back to early R&D and production stages, providing methodological support for the continuous improvement of intelligent cockpit quality.

The deployment of large models in cockpits relies on an "End-Cloud Collaboration" architecture to balance real-time interaction and complex services. Building a data-model-service closed loop, standardizing interfaces, and developing a scenario-based ecosystem are key development focuses. In the future, general models and vertical domain-specific models will develop in parallel, forming a new service ecosystem centered on mobility scenarios with multi-agent collaboration, accelerating the evolution of the intelligent cockpit into a "third space" that understands users and provides services.

Group standards should assume the roles of "Rapid Responder" and "Innovation Guide," complementing national and industry standards to collectively ensure safety, promote technological innovation, and enhance international competitiveness. To cope with rapid technological iteration, establishing a "standards first, products later" mechanism and an annual dynamic update model is recommended to ensure standards remain flexibly aligned with cutting-edge developments. Focusing on safety, intelligence, and experience dimensions, it is essential to strengthen regulations for implicit safety and large model security, advance intelligent agent evaluation and multimodal cognitive foundation construction, improve virtual-real integration testing standards, unify terminology, and expand experience-related standards. This provides normative support and innovation leadership for the high-quality development and global expansion of intelligent cockpits.

Deepening Industry Collaboration and Strategizing the Future of Intelligent Cockpits

The successful convening of this closed-door meeting significantly enhanced communication and exchange within the intelligent cockpit field, laying a solid foundation for the work of the CSAE Intelligent Cockpit Sub-committee in the coming year. It holds great importance for building industry consensus and guiding industry development. Through its participation, Ecordia not only deepened connections with industry partners but also gained clearer direction regarding technological challenges and ecosystem building for intelligent cockpits. Moving forward, Ecordia will actively participate in the various initiatives of the CSAE, continue to leverage its technical strengths, closely follow the trend of AI empowering cockpit innovation, and actively engage in the industry collaboration and standard construction led by the CSAE, contributing further to the high-quality development of China's automotive intelligent cockpit industry.