Research on Overseas Layout of Intelligent Driving: There Are Multiple Challenges in Overseas Layout, and Light-Asset Cooperation with Foreign Suppliers Emerges as the Optimal Solution at Present 2026 is expected to be the first year for Chinese intelligent driving suppliers to go overseas. In terms of market capacity, China’s high-level intelligent driving market may eventually accommodate no more than five suppliers. This directly speeds up the pace of elimination and capital integration in the industry. It is even more difficult for second tier intelligent driving suppliers to survive independently. A typical example is PhiGent Robotics, which is to be acquired by NavInfo. Some leading intelligent driving suppliers have secured orders from overseas automakers, but the implementation will basically not start until after 2027. This does not help much for second- and third-tier suppliers that are facing cash flow shortages. The Chinese intelligent driving market is highly competitive, so Chinese suppliers are also seeking overseas market opportunities. However, there are many challenges in overseas layout of intelligent driving. For instance, in the overseas layout, issues related to data compliance and closed loop, localized development of intelligent driving experience and trust barriers, and comprehensive alignment between R&D process and safety culture all require significant investment of resources and funds to address. I. Challenges in Overseas Layout of Intelligent Driving Challenge 1: Localization of User Experience and Trust Barriers When Chinese companies lay out intelligent driving overseas, they are first confronted with the huge differences in driving cultures across regions. For example, European drivers drive at high speeds but strictly abide by rules, and regulations such as "overtaking on the left" must be rigorously?followed. Secondly, the level of emphasis on ADAS functions varies from region to region. In Southeast Asia, for example, there are a large number of motorcycles and unique vehicles like tuk-tuks on roads. Intelligent driving systems need to detect these small, fast-moving targets and tolerate somewhat unordered and unregulated traffic systems to avoid much too frequent warnings. Drivers in Japan and South Korea generally follow rules well, but due to the narrow roads, intelligent driving systems need to be proficient in narrow-road driving and adopt a conservative driving style. In fierce market competition, domestic intelligent driving products in China generally tend to attract consumers by stacking functions. However, this strategy may not work in overseas markets. Challenge 2: Data Compliance and Closed Loop in Overseas Layout of Intelligent Driving To promote and use intelligent driving systems in overseas markets, first of all, data collection and storage must comply with local regulations. Different countries and regions have their own strict data protection laws, such as the General Data Protection Regulation (GDPR) in the European Union. These laws set high requirements for the definition of "personal data" and how to collect, process, and store the data. When intelligent driving companies collect data on roads, it is inevitable to collect sensitive information such as license plates and facial images, so data desensitization has become a necessary step. Moreover, most regulations require data to be stored locally, which means companies have to build or rent data centers overseas. All of which drives up operating costs. Furthermore, data transmission and processing are also severely restricted. The iteration of intelligent driving technology and the optimization of algorithms are highly dependent on massive amounts of real-world data. Chinese R&D teams need to transmit the driving data collected overseas back to China for analysis and model training. However, cross-border data transmission is supervised more strictly. Many countries, out of consideration for data sovereignty and national security, explicitly prohibit or strictly restrict the export of key data. This forces intelligent driving companies to establish local data processing and algorithm training teams overseas. Challenge 3: Comprehensive Alignment between R&D Process and Safety Culture Conflict in R&D Process Status Quo in China: During R&D, requirements often change, development and testing are often carried out simultaneously, and document flow is not very complete. Domestic companies pursue the speed of function launch to seize the market as soon as possible. International Requirements: Companies must strictly follow standardized development processes and comply with standards such as ASPICE and ISO 26262. Detailed documents, strict reviews, and traceable evidence are required for every step from requirement analysis, system design, coding to test verification. Core Conflict: International customers cannot accept "black-box" software with unclear requirement traceability, incomplete test documents, and inability to prove the functional safety level. What they buy is not just the function, but a complete set of auditable and reliable development processes. Conflict in Safety Culture Status Quo in China: Safety assessment, testing, and verification are often conducted in the later stage of product function development, with the goal of ensuring that the product meets the regulatory certifications and standards required for launch on market. International Requirements: Safety is not a single link but a culture. Safety considerations are integrated into every link from the initial product design, requirement analysis, coding to test verification, emphasizing proactive risk prediction. Core Conflict: For example, if a Chinese company discovers a defect in a corner case, and the probability of this case occurring is extremely low, it may temporarily set it aside to avoid affecting delivery. However, European automakers will regard this as a major process loophole, and will take measures and spend more time solving it, and may even suspend the project. II. Cooperation Paths with Foreign Suppliers and Cases For Chinese second and third-tier intelligent driving suppliers that are already facing cash flow shortages, each challenge in overseas layout may become a financial burden that crushes them. Therefore, cooperation with foreign suppliers allows for "light-asset" operation. 1. Solutions to Legal and Regulatory Certification and Map Data, and Cases Foreign supplier partners, with their deep understanding of local traffic regulations, access standards (such as UNECE regulations in the EU), and certification processes, can guide targeted functional adjustments to products and collaborate with local authoritative testing institutions (TüV SüD, TüV Rheinland, etc.) to assist in handling cumbersome application and testing procedures, thereby greatly shortening the certification cycle. The mainstream HD map providers in Europe are HERE and TomTom. Yaxon Connect?has forged a close partnership with HERE Technologies since 2023. The two parties have jointly provided Chinese automakers with one-stop overseas solutions integrating "compliant access + technology upgrade + localized adaptation" in three major fields: Intelligent Speed Assistance (ISA), ADAS HD maps, and overseas navigation. In 2023, Yaxon Connect developed and adapted its self-developed ISA map engine to help export automakers obtain EU ISA system certification. In 2024, the two parties jointly launched an e-Horizon (EHP) and Map Engine based on the ADASIS V2 protocol. This solution has been applied to the Predictive Adaptive Cruise Control (PACC) system of leading automakers, which can effectively reduce energy consumption by 8%-12%. Up to now, the cooperation achievements of the two parties have been successfully implemented in multiple leading commercial bus and truck OEMs in China, and the products have been exported to such markets as the EU, South Africa, Australia, Mexico, and South America. 2. Solutions to Data Collection, Storage, and Cross-Border Transmission, and Cases After front-end data collection, the raw data is initially cleaned and structured via edge computing devices deployed on test fleets, and then stored in local data centers of international cloud service providers. This directly complies with the mandatory regulations of many countries that require sensitive geographical and personal information to be stored locally. After the data is stored in overseas local data centers, the next key steps are "data preprocessing" and "compliant cross-border transfer". Automakers will use the local teams and platforms of their partners to desensitize and annotate the data stored in their partners’ cloud. By technical means, personally recognizable information such as facial images and license plates is erased, leaving only key features such as driving scenarios and behaviors for algorithm training. When such data is needed for model training, instead of transmitting terabytes of original video or radar point cloud data, the "feature data" or "training sets" that have undergone desensitization, annotation, and preliminary model preprocessing are transmitted across borders. This processed data package significantly reduces transmission costs and time, and its content complies with the cross-border flow requirements of data protection regulations such as GDPR. Case of XPeng P7 European Version XPeng has used the regional data centers of Amazon Web Services (AWS) in Europe to build a complete set of independent back-end services for its Internet of Vehicles (IoV) platform targeting the European market. For all XPeng vehicles sold in Europe, the data is transmitted and stored directly on AWS servers located within the EU through secure Internet of Things (IoT) channels from the moment of collection. XPeng uses AWS IoT services to manage the connections of tens of thousands of vehicles, Amazon S3 to store massive driving data, and data processing services such as EMR and EKS (Elastic Kubernetes Service) to process, analyze, and train models on these data locally in Europe. XPeng has established a "European data security domain" that is isolated from its business in Chinese Mainland both physically and logically. The data of European users - from generation, transmission and storage to processing and final destruction - is totally completed within this closed loop, thus ensuring compliance with GDPR at the architectural level. 3. Overseas Technology Implementation Paths and Cases Chinese intelligent driving suppliers license their core technologies such as software algorithms, which have been verified with massive data, to overseas automakers or mobility platforms. The two parties jointly conduct secondary development and adaptation for specific scenarios in the target market to ensure the localization and compliance of the technical solutions overseas. Chinese intelligent driving suppliers can also receive feedback of overseas road data. Most intelligent driving companies going overseas have adopted a "two-legged" strategy, that is, promoting the R&D and implementation of both L2/L2+ and L4 simultaneously. The former can quickly generate cash flow and accumulate experience through mass production cooperation with OEMs; the latter cooperates with mobility platforms to operate Robotaxis in specific areas (Operational Design Domain, ODD) to obtain massive driving data at low cost. In the future, in addition to technology licensing, there may be more in-depth binding models such as the establishment of joint ventures and equity investment to jointly explore overseas markets. Cooperation Case between and Uber: Uber's global platform is used as a commercial outlet for 's intelligent driving technology. The two parties have jointly launched Robotaxi services in markets other than China and the United States, and plan to officially put them into operation next year. Europe, especially Munich, Germany, is the first stop and test site of this overseas layout plan. Their cooperative test fleet has already taken to road. Uber has 150 million monthly active users in Europe, which greatly reduces the difficulty and cost for to explore the overseas market independently. Moreover, the actual operations in Europe not only allow to obtain valuable overseas road data to feed back into its technical algorithms, and accelerate the operation of the "data flywheel", laying the foundation for the future overseas layout of the "other leg" (referring to the R&D and implementation of L4), but also help to enhance its international value and evaluation in the capital market.