中國獨立OEM的ADAS和自動駕駛技術（2026年）

從2023年到2025年，中國客車自動駕駛系統的結構呈現明顯的階段性升級和結構性更新趨勢。非自動駕駛等級（NL）和低階自動駕駛（L1）的裝置量下降，並逐漸退出主流市場。這印證了自動駕駛正逐步成為客車的標準配備。同時，基礎級高階自動駕駛（L2）仍然是業界的絕對基石。雖然預計2025年其裝置量將略有下降，但基礎市場仍保持穩定，產業成長的重點明顯轉向高階駕駛輔助。其中，L2.5高速公路自動駕駛（NOA）和L2.9城市自動駕駛（NOA）是核心成長引擎，預計到2025年其裝置將顯著成長，高等級NOA功能的滲透率也將快速提升。另一方面，L2+的安裝數量略有下降，顯示其功能價值正被L2.5和L2.9等更先進的解決方案所取代。整體智慧駕駛市場呈現明顯的趨勢：「低階產品淘汰，基礎市場趨於穩定，高階產品快速擴張」。

從OEM的結構來看，在自動駕駛升級方面，「激進式跳躍」與「保守式漸進式進步」之間存在著明顯的差異。

獨立品牌跳過低級別，大力發展高級別自動駕駛技術。非自動駕駛（NL）的比例從2022年的60.9%驟降至2025年的36.0%，低階自動駕駛（L0-L1）幾乎降至零（1.3%）。同期，高階自動駕駛（L2及以上）的比例加倍，達到62.7%。其中，L2.9級城市自動駕駛的搭載率從2022年的2.1%飆升至2025年的17.2%，實現了從「非自動駕駛為主流」到「高等級自動駕駛為主流」的重大結構性轉變。

相較之下，合資企業和外資品牌採取了更保守的策略，穩步更新換代，逐步演進。雖然非自動駕駛的佔比已從40.0%下降至14.5%，但低階自動駕駛（L0-L1）仍維持著16.4%的相當可觀的佔有率。儘管高級自動駕駛（L2及以上）的比例已上升至69.0%，但整個市場仍呈現多級自動駕駛並存的分散趨勢，包括非自動駕駛、低級自動駕駛和高級自動駕駛，這與獨立OEM品牌採取的激進路線形成了鮮明對比。

2026年預計將成為中國汽車產業的關鍵轉捩點，屆時自動駕駛能力將從「量變」轉向「質變」。 ResearchinChina系統性地整理了15家中國獨立OEM 2023年至2026年的自動駕駛策略、策略佈局、技術路線和實施進展，並總結出以下四個關鍵見解。

洞察1：自動駕駛競爭的核心已轉向底層架構的世代創新。該行業已全面進入由大規模模型驅動的物理人工智慧時代，摒棄了依賴規則編程來實現類人決策的傳統駕駛輔助模式。

洞察 2：自動駕駛功能已經從「不需要高精度地圖的城市 NOA」發展成為「D2D（門到門）」的標準配備。

洞察 3：L3 技術預計將於2026年實用化，最初尋求商業化的轉折點，而 L4 預計將在2027年至2030年間達到頂峰。

洞見 4：隨著駕駛座與駕駛的融合預計將加速，汽車正迅速演變為人工智慧超級代理。

本報告對中國汽車行業進行調查分析，提供了有關獨立OEM 的ADAS和自動駕駛技術的資訊，包括按級別分類的安裝數量和搭載率、佈局和趨勢，以及來自各公司的產品資訊。

目錄

第1章 中國獨立OEM ADAS市場現狀

• 中國市場高級駕駛輔助系統（ADAS）安裝數量：依智慧駕駛等級分類（2023-2025年）
• 獨立公司和合資公司/外國品牌ADAS系統的數量和搭載率：按智慧駕駛等級分類（2023-2025年）（1）-（2）
• ADAS的三大主要發展趨勢：獨立品牌與合資/外資品牌
• 獨立品牌ADAS功能的數量與搭載率：依功能分類（2023-2025年）（1）-（2）
• 獨立品牌L2及以上ADAS系統的數量及搭載率：（2023-2025年）
• 獨立品牌中安裝的L2/L2+ ADAS系統數量：依品牌分類
• 獨立品牌 L2/L2+ ADAS搭載率：依品牌分類
• L2.5車型銷售及滲透率：依價格分類（2023-2025年）
• L2.5車型銷售及滲透率：依品牌分類（2023-2025年）
• L2/2.5/2.9 車型 ADAS 安裝編號和 ADAS 供應商清單：依品牌（1 至 2）
• 獨立品牌中安裝的L2/2.5/2.9 ADAS 系統數量：依型號分類
• 獨立品牌安裝的L2/L2+/2.5/2.9 ADAS 系統數量：依價格
• 獨立品牌 L2/L2+/2.5/2.9 ADAS搭載率：以價格計
• 中國客車市場L2/L2+ ADAS供應商的市場佔有率
• 中國客車市場中L2.5/L2.9 ADAS供應商的市場佔有率
• 中國客車市場智慧駕駛普及率：依層級分類（2023-2030年）

第2章 中國獨立OEM ADAS/自動駕駛系統的佈局與發展趨勢

• 各OEM對ADAS發展方向的展望（2026年）
• 端到端的大規模模型
• OEM L3/L4 佈局

第3章 中國傳統獨立OEM 的ADAS/自動駕駛系統

• Dongfeng
• SAIC
• BYD
• GAC
• Geely Auto
• FAW Group
• BAIC Group
• Changan Automobile
• Great Wall Motor
• Chery
• IM Motors

第4章 新興OEM品牌中的高級駕駛輔助系統/自動駕駛

• Xiaomi
• Leapmotor
• XPeng Motors
• Li Auto
• NIO
• Harmony Intelligent Mobility Alliance（HIMA）

Research on OEMs' Intelligent Driving: Era of Physical AI, Standard Configuration of D2D, and Initial Exploration of L3 Commercial Pilot Projects

From 2023 to 2025, the intelligent driving installation structure of passenger cars in China has shown a clear trend of stepped upgrading and structural substitution. Non-intelligent driving level (NL) and low-level intelligent driving (L1) have seen declining installation volume, and have gradually withdrawn from mainstream market, confirming that intelligent driving is fully becoming a standard configuration for passenger cars; basic high-level intelligent driving (L2) remains the absolute foundation of the industry. Although its installation volume slightly declined in 2025, the basic market is stable, and the industry's growth focus has clearly shifted to higher-level assisted driving. Wherein, L2.5 highway NOA and L2.9 urban NOA have become the core growth engines, with their installation volumes achieving a substantial jump in 2025 respectively, and the penetration rate of high-level NOA functions rises rapidly. Yet the installation volume of L2+ has shrunk slightly, indicating that its functional value is being replaced by more complete high-level solutions such as L2.5/L2.9. The overall intelligent driving market presents a clear pattern of "low configuration clearance, stabile basic market, and high-level outbreak".

In terms of OEM structure, independent brands and joint venture/foreign brands show a distinct differentiation of "radical skipping" and "conservative progressive progress" in intelligent driving upgrading:

Independent brands have skipped low-level and vigorously developed high-level intelligent driving. The proportion of non-intelligent driving (NL) dropped sharply from 60.9% in 2022 to 36.0% in 2025, and low-level intelligent driving of L0-L1 was almost zero (1.3%). In the same period, the proportion of high-level intelligent driving such as L2 and above doubled to 62.7%. Among them, the installation rate of L2.9 urban NOA has risen from 2.1% in 2022 to 17.2% in 2025, realizing a leapfrog structural shift from "dominated by non-intelligent driving" to "dominated by high-level intelligent driving".

In contrast, joint venture/foreign brands have adopted a conservative route of steady substitution and hierarchical iteration. The proportion of non-intelligent driving has dropped from 40.0% to 14.5%, but low-level intelligent driving of L0-L1 still retains a considerable share of 16.4%. Although the proportion of high-level intelligent driving of L2 and above has risen to 69.0%, the overall market still maintains a decentralized pattern of coexistence of multiple levels including "non-intelligent driving + low-level + high-level", forming a sharp contrast with the radical route of independent OEM brands.

2026 will become a key inflection point for China's automotive industry to move from "quantitative change" to "qualitative change" in intelligent driving capabilities. By systematically sorting out intelligent driving strategies, strategic layout, technical routes and implementation progress of 15 Chinese independent OEMs from 2023 to 2026, ResearchinChina has summarized four core insights.

Insight 1: the core of intelligent driving competition has shifted to generational innovation of underlying architectures. The industry is fully entering the era of physical AI driven by large models from traditional assisted driving relying on rule programming, realizing human-like decision.

The essence of physical AI is to deeply integrate physical laws, large models and world common sense into intelligent driving system, fundamentally solving the shortcoming of traditional AI's "physical blindness". Traditional artificially rule-driven intelligent driving can only identify targets such as vehicles, pedestrians and traffic cones, lacking an understanding of physical world and causal logic, and unable to predict behavioral intentions. It is prone to jamming, sudden braking, misjudgment and other problems in long-tail scenarios not covered by rules.

Physical AI intelligent driving, through multi-modal perception, not only identifies pixel information, but also understands 3D space, depth, motion state, object material and physical properties in an integrative way, accurately grasps spatial constraints, motion trends and causal relationships, realizes intention prediction and risk deduction, and completes low-latency execution of perception-inference-control through end-to-end closed loop, making decision closer to the fluency and robustness of human driving.

Intelligent driving algorithms in physical AI era can be roughly divided into the following routes:

VLA (Vision-Language-Action) route: integrates vision, language and action modalities to realize end-to-end intelligent decision from environmental perception and instruction understanding to behavior execution. Representative companies: Li Auto, XPeng, Deeproute.ai, Xiaomi, etc.

World Model route: Constructs an abstract representation of the virtual world by learning dynamic laws of the environment, and optimizes decision strategy of the Agent through low-cost simulation and deduction. Representative company: NIO

One-Model E2E + Reinforcement Learning + World Model: Directly maps raw input to action output, omits the link of manual feature design, and independently and iteratively optimizes decision strategy with the help of environmental reward signals. Representative companies: Momenta, SenseAuto

Hybrid Mode: For example, Geely launched the World Action Model, integrating VLA + End-to-End Safety Adversarial Model + World Model

Li Auto's intelligent driving technical route has undergone several switches: from HD map-dependent, rule-based solution to "end-to-end" -> "dual-system solution (end-to-end + VLM) -> VLA -> MindVLA-01". Li Auto's core of intelligent driving in 2026 is to fully switch to the MindVLA-01 unified foundation model, taking end-to-end VLA + world model + closed-loop reinforcement learning + self-developed chips as the path, aiming to build a general Agent in the physical world, and it will be mass-produced and launched on all-new L9 in 2026 Q2.

MindVLA-01 takes the native multi-modal MoE-Transformer as the unified foundation, and fuses three modalities of vision, language and action at the bottom; realizes accurate environmental perception through 3D space understanding (3D ViT + feedforward 3DGS); has multi-modal prediction and in-depth thinking with the help of predictive latent world model; relies on unified action generation (Action Expert + parallel decoding + discrete diffusion) to output automotive-grade stable control; and realizes rapid model iteration and efficient on-vehicle deployment through large-scale closed-loop reinforcement learning (MindRL) and the software and hardware collaboration of self-developed Mach chip, and comprehensively builds a physical AI intelligent driving brain integrating "seeing - thinking - acting".

Insight 2: intelligent driving functions are evolving from "HD map-free urban NOA" to standard configuration of "Door-to-Door (D2D)".

Emerging OEMs such as XPeng and Li Auto launched parking space -> city -> highway uninterrupted D2D intelligent driving in January 2025. Major mainstream OEMs have accelerated the implementation of D2D from 2025 to 2026, and the industry has entered the era of full-process intelligent driving from "segmented assistance".

In terms of technical routes, emerging OEMs generally adhere to the strategy of independent R&D and tackling key problems to seize technological high ground. XPeng, NIO and Li Auto all adopt a combination of independent algorithms and high-compute chips, relying on about 1000TOPS-level computing power to support full-scenario map-free D2D, with significant technological leadership. Among them, Li Auto plans to launch the self-developed and mass-produced intelligent driving chip Mach 100 for the first time on All-new Li Auto L9 Livis in Q2 2026. The chip adopts a data stream native architecture, which can be deeply adapted to the MindVLA-01 VLA large model, with a single-chip computing power of up to 1280TOPS. In terms of the computing power of self-developed chips (Li Auto Mach 100 (1280TOPS) > NIO (1000TOPS) > XPeng (750TOPS)), the independent R&D camp overall enjoy a bigger lead than the cooperative camp.

Traditional OEMs are more inclined to a pragmatic path of strategic cooperation and rapid implementation. Huawei's partners such as SAIC and BAIC directly use Huawei ADS 4.0 + Ascend chips to realize rapid adoption of D2D functions, with high technology multiplexing rate; Chery and BYD adopt mature solutions such as Horizon and NVIDIA, focusing on cost-effective D2D to cover the mainstream vehicle market of RMB150,000-300,000. It is worth noting that D2D functions do not rely on extremely high computing power. Third-party chips of 200TOPS level (such as Huawei Ascend 610, single Orin-X) can support the full-scenario link, and higher computing power is mostly reserved for technical redundancy and subsequent high-level autonomous driving upgrades.

For chip pattern, the D2D intelligent driving market presents a tripod pattern among NVIDIA, Huawei and Horizon, and self-developed chips are becoming the core technological moat of leading emerging OEMs. NVIDIA is still the absolute mainstream of general-purpose chips in the industry, with Thor-U prevailing among cooperative models at 700TOPS level. Huawei has deeply bound with traditional OEMs with its "chip + ADS full-stack solution" and quickly cut into high-end intelligent driving market. Horizon focuses on mid-end and mainstream mass market, achieving extensive coverage with cost-effective solutions. Simultaneously, self-developed chips have become a key to the differentiation of emerging OEMs, realizing the maximization of model efficiency and intelligent driving experience through deep customized collaboration of computing power and algorithms.

In the future, driven by the maturation of end-to-end large model technology, the cost reduction of intelligent driving chips and scenario closed loop, D2D is expected to evolve from a high-end optional configuration to a mainstream standard configuration, and become the core competitiveness benchmark of intelligent vehicles from 2027 to 2028. With the standardization of D2D functions, competition will shift from "available or unavailable" to "good or bad". The adaptability to extreme scenarios (mountain cities, underground garages, rain and snow weather), zero disengagement and cost control will become core decisive factors.

Insight 3: L3 technology is ready in 2026, exploring the commercial inflection point initially, and L4 will usher in a boom period from 2027 to 2030.

(1) Initial exploration of L3 commercial inflection point: in March 2026, Changan Automobile obtained the official special license plate for L3 autonomous driving, which means that "verification of L3 technology maturity is completed and it has entered the early stage of mass production and commercialization". Previously, vehicles of L3 and above could only operate in closed parks or specific test areas. After obtaining the official license plate, vehicles are allowed to carry out on-road use pilots on expressways and urban trunk roads in Chongqing (such as Inner Ring Expressway and Yudu Avenue). At present, these vehicles are operated by Changan's mobility company, and consumers can now experience them by ride hailing instead of buying them directly. This method can reduce the uncertainty of initial implementation through professional management. As of April 2026, two OEMs, Changan and BAIC, have obtained the official special license plate for L3, with the qualification for commercial pilots on public roads.

(2) OEMs' strategic deployment of L3/L4 intelligent driving: two major routes of L3 skipping and L3+L4 parallel development

At present, the industry has formed two clear strategic paths for high-level intelligent driving:

One is L3 skipping route: take Robotaxi as the core breakthrough, skip L3 mass production in strategy and directly develop L4 technology. Although L3 is compliant, the investment (computing power/redundancy) in it is close to L4 but the experience is limited, leading XPeng/BMW to choose to skip L3. Taking XPeng as an example, it plans to launch 3 mass-produced OEM L4 Robotaxis in 2026, start the normal road test of L4 autonomous driving in H1 2026, officially launch the demonstration operation of Robotaxi in H2 2026, complete the tripartite verification of technology, customers and business, and realize non-safety officer commercial operation in 2027.

The second is L3+L4 parallel development route. The core choice of current mainstream OEMs follows a steady rhythm of "qualification verification -> mass production internal testing -> L3 launch -> L4 implementation", covering both private passenger cars and Robotaxi tracks simultaneously, with a complete technical route and clear mass production rhythm.

In terms of time layout, 2025-2026 is a critical period for L3 road testing, mass production & access and product delivery. SAIC, Geely, BAIC and GAC have clarified product technical readiness of L3 intelligent driving capabilities for private vehicles in 2026 (pending legal permission), marking 2026 as the "mass production first year" of China's L3 autonomous driving. Car owners will legally obtain the right to take their hands off the steering wheel on specific roads (highways/expressways) for the first time. 2026 is the starting point for large-scale operation of Robotaxi. Mainstream OEMs (SAIC, Geely, BYD, BAIC, GAC) all anchor the substantive commercial implementation of L4 in 2026, and focus on core areas of first-tier cities such as Shanghai, Shenzhen and Beijing.

In the medium and long term, 2027-2030 is a window period for the implementation of L4 in complex scenarios and the wide adoption in private cars. Changan and Dongfeng have clarified large-scale mass production of L3/L4 by 2030, indicating that the industry will fully penetrate from the "business/operation end" to "consumer users" in the next 5 years.

Insight 4: Cockpit-driving fusion is expected to accelerate, and automobiles are evolving rapidly into AI Super Agents.

The ultimate form of intelligent vehicles is a digital living body and mobile intelligent terminal with autonomous capabilities. At present, the industry is gradually developing from the architecture of separate cockpit and driving domains to the direction of cockpit-driving fusion, cockpit-driving integration and chassis full-domain fusion, and eventually moving towards the form of intelligent mobile robots with autonomous decision and autonomous execution capabilities.

In March 2026, IM Motors launched the IM Ultra Agent, an AI super agent which realizes in-depth collaboration of three domains of intelligent driving, intelligent cockpit and chassis based on IM Fusion Nova architecture. At the hardware level, full chassis-by-wire is the foundation for realizing full-domain vehicle control. IM Motors LINGXI Digital Chassis adopts full-stack wire-controlled solution, with four-wheel steering response time as low as 20ms, and response efficiency about 4 times that of traditional steering system. It is also equipped with an aviation-grade triple safety redundancy architecture, with the system failure probability lower than 10FIT, providing a stable and reliable hardware foundation for high-level intelligent driving and vehicle dynamic control.

At the software level, vehicles are equipped with Alibaba Tongyi Qwen large model, providing multi-modal interaction and continuous evolution capabilities for IM Ultra Agent. IM AD ZETA, an intelligent driving system jointly developed with Momenta, adopts a new-generation reinforcement learning large model as the physical AI foundation oriented to L4 autonomous driving, realizing the integrated upgrade of perception and decision capabilities on vehicles. The large model can realize real-time linkage between decision layer, intelligent driving domain and chassis domain, and support one-sentence voice commands directly to vehicle control, making cross-domain collaboration and full-scenario assisted driving move from concept to practical application.

When intelligent driving, intelligent cockpit and chassis are integrated, a single AI command can coordinate the intelligent cockpit and intelligent driving AI large models:

Scenario example: During the evening rush hour after work, the user issues the instruction: "I'm too tired, want to go home, and buy a cup of hot Americano by the way, preferably without getting off the car to pick it up."

The on-device Alibaba Tongyi Qwen AI large model completes natural language understanding and user intention disassembly, dividing the requirements into three categories:

Vehicle control requirements: "I'm too tired" -> activate the seat massage function, executed by vehicle control Agent;

Life service requirements: "Buy a cup of hot Americano" -> purchase hot Americano coffee, link with IM Motors' takeaway Agent to complete coffee selection, payment and pick-up point association;

Mobility path requirements: first go to the pick-up point, then return to the destination to go home.

Finally, the IM AD ZETA intelligent driving large model unifies overall planning, completes dynamic path planning, real-time road condition prediction and full-process intelligent driving execution, realizing a one-stop experience of "picking up food without getting off the car + automatic homecoming".

From 2023 to 2025, Chinese passenger car intelligent driving market has completed the initial iteration from "available or unavailable" to "good or bad". The installation structure presents a clear pattern of " stabile basic market and high-level outbreak", and the route differentiation between independent and joint venture brands has become more prominent. In 2026, a key inflection point for China's automotive intelligent driving to move from "quantitative change" to "qualitative change", underlying architecture has fully entered the era of physical AI, with multiple technical routes such as VLA and world model developing in parallel. D2D functions are developing faster from high-end optional configuration to mainstream standard configuration, L3 autonomous driving is ushering in initial commercial exploration, and cockpit-driving fusion is promoting the steady evolution of automobiles into AI Super Agents. The dual paths of chip self-development and strategic cooperation are reshaping the industry competitive pattern. It is foreseeable that in the next two years, the competition in intelligent driving capabilities will no longer be limited to the simple stacking of algorithms and computing power, but will more depend on enterprises' systematic construction of physical world understanding, data closed-loop efficiency, depth of software and hardware collaboration and breadth of scenario coverage. In this process from quantitative change to qualitative change, the real decisive factor will belong to those players who can take the lead in realizing in-depth integration of "cognitive intelligence" and "action intelligence".

Table of Contents

1 Status Quo of Chinese Independent OEM ADAS Market

ADAS Installation Volume by Intelligent Driving Level in Chinese Market, 2023-2025

ADAS Installation Volume and Installation Rate of Independent + Joint Venture/Foreign Brands by Intelligent Driving Level, 2023-2025 (1)-(2)

Three Major Development Trends of ADAS: Independent Brands VS. Joint Venture/foreign Brands

ADAS Function Installation Volume & Installation Rate of Independent Brands, 2023-2025: By Function (1)-(2)

L2 and Above ADAS Installation Volume and Installation Rate of Independent Brands, 2023-2025

L2 and L2+ ADAS Installation Volume of Independent Brands: By Brand

L2 and L2+ ADAS Installation Rate of Independent Brands: By Brand

Sales Volume and Penetration Rate of L2.5 Models (by Price), 2023-2025

Sales Volume and Penetration Rate of L2.5 Models (by Brand), 2023-2025

L2/2.5/2.9 ADAS Installation Volume and ADAS Supplies List: By Brand (1)-(2)

L2/2.5/2.9 ADAS Installation Volume of Independent Brands: By Model

L2/L2+/2.5/2.9 ADAS Installation Volume of Independent Brands: By Price

L2/L2+/2.5/2.9 ADAS Installation Rate of Independent Brands: By Price

Market Share of L2 and L2+ ADAS Suppliers in Chinese Passenger Car Market

Market Share of L2.5 and L2.9 ADAS Suppliers in Chinese Passenger Car Market

Penetration Rate of Intelligent Driving by Level in Chinese Passenger Car Market, 2023-2030E

2 ADAS/Autonomous Driving Layout and Trends of Chinese Independent OEMs

• 2.1 ADAS Evolution Direction of OEMs in 2026
• ADAS Capabilities Evolution Direction of OEMs in 2026 (1)-(6)
• Insight 1: Paradigm Revolution of Underlying Technology, from "Modular Rules" to "Physical AI"
• Case: NIO World Model (NWM)
• Insight 2: In 2026, Urban NOA Will Be Popularized towards Lower-end Market, Becoming A Core Competitive Element in Mainstream Market
• Case: BYD Shifts from "Optional Configuration for Single Model" to "Standard Configuration for All Models"
• Insight 3: In Terms of Evolution Direction, Intelligent Driving Experience Shifts to Further Improving Experience Value of Safety, Human-like Smoothness and High Efficiency
• Insight 4: In Terms of Function Form, Evolve from "HD Map-Free Urban NOA" to "Standardization of Door-to-Door (D2D) + L3 Technology Readiness"
• Comparison between D2D Intelligent Driving Solutions
• Core Trends and Insights of D2D Intelligent Driving industry
• Insight 5: Cockpit-Driving Fusion Is Expected to Accelerate, and Automobiles Will Evolve into AI Super Agents
• In Terms of Evolution Strategy, Multi-Brand OEMs Adopt A Hierarchical Intelligent Driving Strategy (Dual Track of Independent R&D + Multiple Suppliers) to Match Brand Positioning
• 2.2 End-to-End Large Models
• Benchmarking Comparison between End-to-End Large Models Adopted by OEMs in 2026
• Comparison of End-to-End Large Models Upgrade Solutions between Representative Third-Party Intelligent Driving Suppliers
• End-to-End Has Become the Mainstream of Intelligent Driving Technology, and End-to-End Large Models Have Evolved into Multiple Routes during 2025- 2026
• Afari Technology: End-to-End Intelligent Driving Large Model
• Geely: Launched the World Action Model (WAM) in 2026
• Deeproute.ai: Hardcore Technical Innovation in 40B VLA Foundation Model
• VLA Route (1)-(2)
• 2.3 OEMs' L3/L4 Layout
• Comparison of Milestone Timeline of OEMs' L3/L4 Layout, 2023-2030E (1)-(2)
• Panoramic Insight into L3/L4 Autonomous Driving Layout of Chinese OEMs (1)-(2)
• OEMs' Strategic Choices in L3/L4 Intelligent Driving: Parallel Development and Skipping
• Multiple Considerations of Some Leading OEMs Adopting Dual-Route Layout of L3 and L4 in Terms of Technology, Capital and Strategy (1)-(2)
• Driven by Both Policy and Technology: China's L3/L4 Autonomous Driving Market Enters the Fast Lane of Large-Scale Commercialization from 2025 to 2030
• Simultaneous Upgrading of Four Major Technical Modules Promotes Stepped Implementation of Autonomous Driving from L3 to L5
• Industry Experts' Prediction on Development of L3 Conditionally Autonomous Driving (1)-(2)
• Five Major Challenges Facing the Large-Scale Implementation of L3
• Technical Challenges Facing L3 Implementation (1)-(3)
• Four Major Characteristics of Chinese OEMs' L3 Layout
• L3 Technical Path Presents A "Tripod" Pattern: Independent R&D, Dual Track of Joint R&D + Independent R&D, External Suppliers (1)-(3)

3 ADAS/Autonomous Driving of Chinese Traditional Independent OEMs

• 3.1 Dongfeng
• Profile
• Organizational Structure and Business Layout
• Sales Volume and Production Volume Comparison for Passenger and Commercial Vehicle Models of Various Brands, 2024 vs 2025
• Passenger Car Brand Matrix
• Intelligent Driving Strategic Plan (2026-2030E)
• Launched the Tianyuan Intelligent Driving Four-Level Product Matrix in 2025: Realizing Full Coverage from L2 to L4/L5
• Comparison of Intelligent Driving Configuration of the First Mass-Produced Models of Tianyuan T100/T200/T500
• Tianyuan Intelligent Driving Technical Architecture: R-Aid
• Intelligent Driving Strategy: Short-Term Dual Track of Independent R&D + External Procurement, and Gradual Implementation of Independent R&D Substitution in the Medium and Long Term
• Deepening Cooperation with Huawei (1)-(2)
• Layout and Important Nodes of Voyah L3 Intelligent Driving
• Technical Architecture of Voyah L3 Intelligent Driving: Tianyuan Intelligent Driving System
• Voyah Qingyun L3 Architecture
• Details of Voyah L3 Intelligent Driving System: Hardware Configuration
• Kunpeng L3 Intelligent Safety Driving System (1)-(2)
• L4 Autonomous Driving Layout 1: Robotaxi
• L4 Autonomous Driving Layout 2: Sharing Bus
• L4 Autonomous Driving Layout 3: Urban Last-Mile Delivery
• 3.2 SAIC
• Profile (1)-(2)
• ADAS Strategic Plan and Analysis, 2026-2027E
• L3/L4 Intelligent Driving Strategic Plan and Analysis
• Next-Generation Electronic Architecture
• ADAS Layout: Gathering " Horizon Robotics, DJI, Huawei, Momenta" in the Intelligent Driving Field
• Strategic Cooperation with Horizon
• Comparison of Representative Models for Momenta Intelligent Driving Solutions: Buick Electra L7 vs Volkswagen ID.ERA 9x
• Panoramic View of Intelligent Driving Products of Shangjie Brand and Expansion Strategy in 2026
• Comparison of Representative Models of Zhuoyu Technology Intelligent Driving Solutions: Baojun Yunhai Vs Baojun Xiangjing
• SAIC-GM-Wuling and Huawei Launched Baojun Huajing S in 2026
• Intelligent Driving Ecosystem Partners
• 3.3 BYD
• Intelligent Driving Plan in 2026 (1)-(2)
• Reached Strategic Cooperation with Nvidia on L4 Robotaxi in 2026
• Key Points of 2025 Intelligent Driving Strategy
• Three Sets of Intelligent Driving Solutions of "DiPilot" Realize Full Coverage from Low-End to High-End, Accelerating the Arrival of Intelligent Driving Equalization Era
• Universal Intelligent Driving Strategy
• Pioneered the Front View Tri-Camera to Create A "Super Perception Matrix"
• Layout in Intelligent Driving (1): Intelligent Computing Center
• Layout in Intelligent Driving (2): Pre-Research on World Model
• Adjustment of Intelligent Driving Team's Organizational Structure (1): Integration of Two Intelligent Driving Departments to Concentrate Resources and Accelerate Universal Intelligent Driving
• Adjustment of Intelligent Driving Team's Organizational Structure (2): Establishment of an Advanced Technology R&D Center to increase investment in AI and Large Models
• Evolution of Dipilot Intelligent Driving System (1)-(2)
• Intelligent Driving Suppliers for the Implementation of NOA
• Representative Urban NOA Enabled Model 1: Denza N7 and Sensor Configuration
• Representative Urban NOA Enabled Model 1: Denza N7 Realized HD Map-Free CNOA at the End of 2024
• Representative Urban NOA Enabled Model 1: Intelligent Driving Function Iteration Direction of Denza N7 in 2025
• Representative Urban NOA Enabled Model 2: Yangwang U8
• Intelligent Driving Ecosystem Partners
• 3.4 GAC
• "Smart Mobility 2027" Strategy
• Overview of H1 2025 Operations
• Product Matrix
• Intelligent Driving Business Layout: Investment and Cooperation (2017-2023)
• Intelligent Driving Business Layout: Investment and Cooperation (2024-2025)
• Evolution of ADiGO Intelligent Driving System (ADiGO1.0->ADiGO6.0)
• Iteration History of Intelligent Driving System: Details of Hardware, Software Algorithms and Sensor Configuration
• Launched Five Major Intelligent Driving Platforms in 2025
• Software Algorithms/Intelligent Driving System Suppliers of L2.9 Models and Urban NOA
• Through the Layout of "Dual-Gradient Intelligent Driving Suppliers + Scenario-Price Precise Matching", Realize "High-End Positioning + Public Popularization" of Urban NOA
• Established Aistaland and Adopted the "GAC Intelligent Manufacturing + Huawei Intelligence" Mode to Develop High-End Market and Improve the Brand Matrix
• The First Model of Aistaland F03 Is Expected to Be Launched in Q2 2026
• Momenta 5.0 One-Model E2E Algorithm Is Available to 150,000 RMB-Level Models and Implements Urban NOA Functions
• Trumpchi Xiangwang S7 Will Be Equipped with Momenta R6 Reinforcement Learning Large Model
• L3/L4 Autonomous Driving Product Layout Plan (1)-(2)
• Robotaxi Layout (1)-(2)
• Computing Power Cluster Construction
• Evolution History of ADIGO Intelligent Driving System: Launched L3 Intelligent Driving System ADGO GSD in 2025
• L3 Progress and the First Representative Model Hyptec A800
• L3 Intelligent Driving Adopts Dual-Track Strategy of "Independent R&D-Oriented + Cooperation-Assisted"
• Adopts Multi-Brand Hierarchical Layout to Accelerate Popularization of Intelligent Driving
• L3 Intelligent Driving System Design: Global Safety Technology
• L3 Intelligent Driving System Design: Dual Redundancy Design of Eight Key Systems
• L3 Intelligent Driving System Design: Active and Passive Fusion Safety (1)-(2)
• L3 Intelligent Driving System Design: Battery Safety
• L3 Intelligent Driving System Design: Intelligent Chassis Safety
• Passed the Approval of Access and Road Traffic Pilot for Intelligent Connected Vehicles, Becoming One of the First Batch of OEMs in China Approved to Carry Out L3 Autonomous Driving Road Traffic Pilots
• Intelligent Driving Ecosystem Partners: "Multi-Supplier Hierarchical Binding + Full-Scenario Technology Coverage" (L2+/L2.5/L2.9/L3/L4)
• 3.5 Geely Auto
• Geely China Production Base Layout and 2025 Financial Data Comparison Between Geely, BYD and Chery
• Global AI 2.0, 2026
• Intelligent Vehicle Global AI 1.0 Strategy, 2025
• Product Portfolio Matrix of Various Brands (1)-(2)
• Reintegrated Sub-Brands to Create "One Geely"
• Merged with Zeekr into A Single Entity to Create "One Geely"
• Adjustment of Intelligent Driving Organizational Structure in 2025: Implementation of the "One Intelligent Driving" Strategy (1)-(2)
• Afari Technology: Core Carrier of Geely Group's Intelligent Strategy
• Afari Technology: Product and Technology Evolution Roadmap of Autonomous Driving from L2+ to L4
• AI Computing Power Base: Xingrui Intelligent Computing Center 2.0
• Xingrui AI Large Model: Three Major Basic Models
• Xingrui AI Large Model: Six Major Capability Models
• Qianli Haohan Intelligent Driving System: Accelerating Technology Equalization in 2026
• Qianli Haohan Intelligent Driving Solutions (H1-H9) Adopt A Differentiated Hierarchical Strategy in Terms of Intelligent Driving Chips and Software Algorithm Suppliers
• Evolution Route of Zeekr Intelligent Driving Solution (1): Entering the End-to-End Era, Realizing Highway NZP + Memory NOA
• Evolution Route of Zeekr Intelligent Driving Solution (2): Realizing HD Map-Free NZP + Parking Space to D2D NOA Assistance
• Zeekr End-to-End System: Two-Model Solution
• Zeekr Officially Launched End-to-End Plus: Introducing Digital Perception Network Based on Multi-Modal Large Language Model
• Zeekr End-to-End System Plus
• Iteration History of Zeekr Intelligent Driving System
• Galaxy Adopts A Hierarchical Deployment Strategy, and Some Models Realize HD Map-Free Urban NOA
• Evolution of Lynk & Co Intelligent Driving Solutions (1)-(2)
• L3/L4 Layout: Push Highway L3 and Realize Robotaxi Trial Operation in 2026 Under the Condition of Legal Permission
• At the Technical Evolution Level, L3 Is the Core Key for Zeekr's Next Breakthrough
• Four Pillars of L3 Breakthrough: Collaborative Closed Loop of Data, AI Large Models, Simulation Technology and Computing Power
• Zeekr L3 Intelligent Driving: Hardware Layout
• Zeekr L3 Intelligent Driving: End-to-End Large Model
• Differences in the Development Concepts of L2 and L3 and Above Autonomous Driving
• Zeekr 9X Glory: The First Model for Zeekr L3 Implementation
• Strategic Ecosystem Partners of Intelligent Vehicle
• 3.6 FAW Group
• Overview of Domestic Passenger Car Products
• "SIGHT 531" Development Strategy of R.Flag Technology
• Overview of "Si-Nan Intelligent Driving" System
• "Si-Nan Intelligent Driving" System
• Models with the Implementation of "Si-Nan Intelligent Driving" System and Key Configuration
• Zhuoyu End-to-End 4.0 System Was First Equipped on Hongqi "Si-Nan Intelligent Driving" in 2026
• The 2026 "Hongqi 9 Series" Models Will Adopt Huawei Hi Mode
• EEA: Development History and Planning
• EEA: FEEA 3.0 Feiren Architecture (Quasi-Central Computing)
• Self-Developed 5nm Five-Domain Fusion Chip: Hongqi No.1
• Intelligent Driving Cooperative Suppliers: Acquired 35.8% of the Shares of Zhuoyu Technology and Became Its Largest Shareholder
• L3/L4 Deployment History and Strategic Planning
• ADAS Road Test: Demonstration Base
• 3.7 BAIC Group
• Overview of Domestic Passenger Car Products
• History and Planning of Technical Layout in Intelligent Driving
• Functional Configuration and Intelligent Driving Solution Suppliers of L2 and Above Models
• "Yuanjing Intelligent" Global Technology System: Three-Layer Fusion System
• "Yuanjing Intelligent" Global Technology System: Intelligent Driving and Intelligent Cockpit System
• "Yuanjing Intelligent" Global Technology System: The First Equipped Model 2026 BAIC Arcfox Alpha T5
• Established A Joint Venture with Horizon, Beijing Zhiyu Technology Co., Ltd., to Develop Urban NOA System
• L3 Autonomous Driving Technology Layout and Implementation Plan
• BAIC Arcfox Alpha S (L3 Version) Approved for L3 Autonomous Driving Road Traffic Pilot
• L4 Autonomous Driving Robotaxi Technology Layout and Implementation Plan
• Summary of Important Partners in Intelligent Driving Technology
• 3.8 Changan Automobile
• Intelligent Driving Layout: "Beidou Tianshu" 1.0 Strategy
• Intelligent Driving Layout: "Beidou Tianshu" 2.0 Strategy
• L3/L4 Layout Plan, 2026-2030E
• Obtained the L4 Self-Developed Robotaxi Test License in 2026
• "1+N+X Future Mobility Ecology" Plan, 2025-2032E
• Intelligent Driving Technology Generational Roadmap
• Intelligent Driving Technology Strategy
• Vehicle Matrix
• SDA Architecture
• Three Major New Energy Brands: Dual-Track Intelligent Driving Mode of "In-Depth Independent R&D + Development Cooperation" (Function Progress / Time Node)
• Four Generations of Intelligent Driving Independent R&D Platform Iteration Road: Representative Models Nevo Q05/E07
• Nevo Series: Comparison of Corresponding Hardware Configuration for Representative Models on Highway/Urban NOA Functions
• Nevo Equipped with End-to-End System: BEV+LLM+GoT
• Deepal Intelligent Driving System
• Iteration History of Deepal Intelligent Driving System
• Future Evolution Plan of Deepal Autonomous Driving System
• Evolution of Avatr Intelligent Driving Functions
• Leading the L3 Intelligent Driving Access List
• Intelligent Driving Solutions for L3 Models
• Deepal L3 Road Test in Chongqing
• Obtained the official Special License Plate for L3 in 2025
• Ecosystem Partners in Intelligent Driving
• 3.9 Great Wall Motor
• Operations
• Product Matrix
• Intelligent Driving Positioning and Planning of Five Major Brands Under the Company
• Intelligent Driving Computing Power Deployment and Prospect
• Development History and Planning of Coffee Intelligent System
• Intelligent Driving Large Model: SEE End-to-End Large Model
• Intelligent Driving Large Model: Introducing Deeproute.Ai's VLA Large Model
• VLA Intelligent Driving Large Model
• Progress and Planning of Urban NOA Implementation
• 3.10 Chery
• Profile
• Product Matrix and Models
• Evolution History of Intelligent Driving System
• Launched Four Versions of Falcon Intelligent Driving System in 2025
• Progress of Intelligent Driving End-to-End Large Model (1)-(2)
• Comparison of Intelligent Driving Suppliers, Intelligent Driving Chip Vendors and Intelligent Driving Solutions of Models with NOA Functions Under the Company in 2025
• Intelligent Driving infrastructure: Tianqiong Intelligent Computing Center, Data Storage Center, Digital Scenario Library
• Intelligent Driving Plan in 2026
• Realization Mode of Intelligent Driving AI Equalization
• 3.11 IM Motors
• Profile
• Full-Stack Layout Strategy of Intelligent Driving
• Z-ONE Tech's First-Generation Central Brain ZXD1
• Second-Generation Central Brain ZXD2: Based on Horizon J6+ Qualcomm
• ADAS System: IM AD
• Technical Advantages of IM AD
• Key Points of Cooperation with Momenta in ADAS
• IM AD End-to-End 2.0 Intelligent Driving Large Model
• Core Technologies of IM AD End-to-End 2.0 Intelligent Driving Large Model
• Comparison of Application Scenarios of IM AD End-to-End 2.0 Intelligent Driving Large Model
• Evolution of ADAS System (1)-(2)
• L3 Autonomous Driving Technology Development Plan
• Technical Base for L2/L3/L4: analysis of End-to-End Large Model (1)-(2)
• Technical Base for L2/L3/L4: Domain Controller and Sensor Hardware Configuration
• Technical Base for L2/L3/L4: Safety Redundancy
• Technical Base for L2/L3/L4: Digital Chassis (1)-(2)
• L4 Robotaxi Layout Progress

4 ADAS/Autonomous Driving of Emerging OEM Brands

• 4.1 Xiaomi
• Profile
• Strategic Plan in 2026
• Comprehensive analysis of New Car Plan in 2026
• Comparison of Product Positioning and Model Parameters of New Cars in 2026 (1)-(2)
• Changes in Organizational Structure of Intelligent Driving
• Intelligent Driving Technical Route: Full-Route Pre-Research, Not Betting on A Single Technology
• Comparison of VLA and End-to-End Routes
• Evolution Trend of Intelligent Driving Algorithms: from Modular End-to-End to Introducing World Model + Reinforcement Learning into End-to-End Architecture
• Launched XLA Cognitive Large Model in 2026
• Evolution Roadmap of Intelligent Driving System
• HAD Enhanced Version (1)-(2)
• L3 Test Licenses and Models of Chinese OEMs
• 4.2 Leapmotor
• Profile
• Independent R&D of Autonomous Driving
• Product Matrix
• Layout and NOA Progress in Intelligent Driving Field (1)-(2)
• D19 Adopts Deeproute.Ai's VLA Large Model to Realize D2D Full-Scenario NOA, Expected to Be Launched in April 2026
• Flagship SUV Model: D19
• Comparison of Hardware Configuration and ADAS Functions of Representative Models (2024 vs 2026)
• "Chip Replacement" of Intelligent Driving Chips (Non-D19): from NVIDIA Orin-X to Qualcomm 8650
• D19's Chip "Replacement": from Qualcomm 8295P + Intelligent Driving 8650 -> Dual 8797 Chips
• Adopt the Mode of Self-Developed Intelligent Driving System
• Evolution of Leapmotor Pilot (1)-(2)
• Evolution Characteristics and Trends of Leapmotor Pilot System
• Evolution of LEAP Platform Architecture: from LEAP3.5 to 4.0, 2025-2026
• LEAP4.0 Central Domain Control Architecture Introduces PCle Switch
• Topology Speculation of Ethernet Switch Part of LEAP4.0 Architecture
• LEAP3.5 Platform Architecture (1)-(2)
• LEAP3.0 Platform Architecture (1)-(2)
• Strategic Ecosystem Partners of Intelligent Driving
• 4.3 XPeng Motors
• Profile
• Strategic Transformation
• Four Major Business Lines
• Autonomous Driving Product Plan, 2025-2026
• L4 Intelligent Driving Layout in 2026: Robotaxi
• Launched the Second-Generation VLA
• The Second-Generation VLA
• World Base Model (1)-(2)
• Cloud Factory
• Comparison of Cloud Computing Power Scale and Intelligent Driving Data Reserve Progress of Various OEMs
• The Logic Behind Self-Developed Turing Chip
• Unified AI Technology Stack AI Computing Platform: Self-Developed Turing Chip
• Turing Chip Parameters and Bandwidth Bottlenecks
• First Half of the Intelligent Driving Evolution Route: Overview
• Second Half of the Intelligent Driving System: XNGP (1)
• Second Half of the Intelligent Driving System: Full-Scenario AI Autonomous Driving Has Become the Fourth Development Stage of XNGP
• One of Intelligent Driving Key Points in 2025: Stepping into D2D Full-Scenario NOA
• One of Intelligent Driving Key Points in 2025: Shifting from Developing New Cities to Optimizing the Driving Experience of Intelligent Driving
• Intelligent Driving Experience Upgrade in 2025: Focusing on Three Core Directions of D2D + Human-Machine Co-Driving + Small Road NGP
• Launched Intelligent Driving Vehicles with L3 Computing Power
• Realize HD Map-Free Urban NOA Through Vision-only Route and Achieve the Implementation of L3 Intelligent Driving Capabilities
• Evolution History of XNGP Intelligent Driving System
• Key Technological Breakthroughs from the Evolution of XNGP3.0 to 5.0
• Urban NOA Representative Models and Hardware Configuration Solutions, 2023-2024
• Urban NOA Representative Models and Hardware Configuration Solutions, 2025
• Layout of AI-Defined Vehicle Transformation
• Launched Intelligent Driving Vehicles with L3 Computing Power
• G7 Ultra Hardware Configuration Solution
• Evolution of End-to-End Large Models
• End-to-End Large Models: Xbrain+Xnet+Xplanner (1)-(2)
• 4.4 Li Auto
• Profile
• Key Layout of Intelligent Driving in 2026: Upgrading from "Assisted Driving" to Embodied AI (Physical AI), and Automobiles Are the "Largest Robots"
• Organizational Structure Adjustment
• Intelligent Driving System Is Divided into Two Major Product Lines: AD PRO and AD MAX (1)-(2)
• Details of AD Pro Platform
• AD Max Intelligent Driving System Evolution Direction in 2024
• AD MAX Intelligent Driving System Evolution Direction in 2025
• Details of Representative Models and Full-Stack Software and Hardware Configuration of AD MAX System
• ADAS Adds the VLA Command Function, A Watershed for Intelligent Driving from "Assisted tool" to "Intelligent Partner" (1)
• Value of VLA Command Function
• Evolution Roadmap of Intelligent Driving End-to-End Large Model (1)-(2)
• Launched the New Generation Unified Architecture MindVLA-01 in 2026 (1)-(2)
• the Next-Generation Unified Architecture MindVLA-01 (1)-(3)
• VLA Driver Large Model (1)-(2)
• Core Capabilities of VLA Large Model
• Evolution Direction of VLA Large Model Capabilities
• Training Process of VLA Driver Large Model
• Disassembly of the Technical Architecture of VLA
• MindVLA Core Technologies
• VLA Driver Large Model Application Scenario 1: Opening Up the "Last 100 Meters" of Charging
• VLA Driver Large Model Application Scenario 2:
• End-to-End Solution (1): Iterative Evolution of System 1
• End-to-End Solution (2): System 1 (End-to-End Model) + System 2 (VLM)
• 4.5 NIO
• Profile
• Technology Platform Evolution (1)-(2)
• from Modeling to End-to-End, the World Model Is the Current Dominant Technical Paradigm
• Details of Intelligent Driving System
• Intelligent Driving Technical Architecture NAD Arch 2.0 (1)-(2)
• Comparison of Banyan and Cedar Systems
• Panoramic View of Intelligent Driving Capability Upgrade of Banyan System Based on NT2.0 Platform, 2024-2025
• Panoramic View of Intelligent Driving Capability Upgrade of Cedar System Based on NT3.0 Platform, 2025 (1)-(2)
• Iteration Process of NOP NOA Assistance
• Adjustment of Intelligent Driving Organizational Structure, 2024-2025
• World Model NWM
• World Model 2.0
• Comparison of End-to-End Model and World Model
• Comparison of VLA and World Model
• 4.6 Harmony Intelligent Mobility Alliance (HIMA)
• L3/L4 Intelligent Driving Implementation Plan in China
• Solutions to Break the Situation in the Face of Technical and Commercial Closed-Loop Challenges
• Qiankun Intelligent Driving Full-Dimensional Safety System: CAS 4.0
• L3 Intelligent Driving: Sensor Hardware Configuration (1)
• L3 Intelligent Driving: Sensor Hardware Configuration (2): High-Precision Solid-State Lidar
• L3 Intelligent Driving: Sensor Hardware Configuration (3): In-Cabin Laser Vision Limera
• ADS 4.0 (1): WEWA Architecture
• ADS 4.0 (2): WEWA Architecture
• ADS 4.0 (3): Comparison Between L3 Intelligent Driving Version and Autonomous Driving Version
• ADS 4.0 (4): Comparison of Intelligent Driving Versions
• L3 Intelligent Driving: Self-Developed Operating System AOS + Launch of Hybrid Redundancy Architecture to Build an Autonomous Driving Safety Base
• Digital Chassis Engine XMC (1)
• Digital Chassis Engine XMC (2): Disassembly of Core Advantages
• Intelligent Driving Route Evolution Chart (ADS1.0->ADS4.0)
• Mass-Produced Models and Customers