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ADAS 自動駕駛車

市場調查報告書

商品編碼

1844049

中國自動駕駛乘用車市場，2024-2030年

Passenger Vehicle Autonomous Driving Market, China, 2024-2030

出版日期: 2025年09月03日 | 出版商:

Frost & Sullivan | 英文 47 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

自動駕駛導航加速自動駕駛的轉變

自動駕駛汽車可以部分輔助或完全自動駕駛，它們透過整合人工智慧（AI）、電腦視覺、雷達系統、監控設備和 GPS 來運作。

中國自動駕駛市場正處於快速成長階段，市場滲透率位居全球前列。本研究採用L0-L5分級體系，分析自動駕駛技術在中國新客車市場的滲透率。

在中國新客車市場，L3級自動駕駛技術由於法規約束和技術限制尚未實現商業化，具備L4級自動駕駛能力的車輛仍然較少，因此本研究主要關注L3級以下的自動駕駛解決方案。

本研究檢驗了中國國內主要目標商標產品製造商（OEM）、電動車 OEM、新興企業和國際 OEM 提供的自動駕駛解決方案。

分析範圍

自動駕駛汽車可能需要部分駕駛輔助，也可能完全自動駕駛。這些汽車透過協調整合人工智慧（AI）、電腦視覺、雷達系統、監控設備和 GPS 來運作。
中國自動駕駛市場正經歷快速成長，市場滲透率位居全球前列。本研究採用L0-L5級自動駕駛汽車分類體系，分析中國新客車市場對自動駕駛技術的採用情況，並深入分析L0-L3級自動駕駛汽車市場。
由於法規約束和技術限制，L3級自動駕駛技術在中國新客車市場尚未商業化落地，搭載L4級自動駕駛能力的車輛仍鳳毛麟角。因此，本研究主要關注L3級以下的自動駕駛解決方案，特別是中國OEM自動駕駛解決方案的市場現況。
本研究致力於客車 ADAS 市場，檢驗中國國內主要 OEM、電動車 OEM、新興企業和國際 OEM 提供的自動駕駛解決方案。

三大策略要務對自動駕駛產業的影響

創新經營模式

為什麼
中國客車市場正向電動化和智慧轉型。為了適應這項轉型，傳統汽車廠商必須重新定義收益來源。中國自動駕駛市場的崛起凸顯了這些新經營模式的重要性。
自動駕駛可能會再形成消費者的期望，包括個人化服務和共用出行，推動客車 ADAS 市場的成長。
Frost的觀點
共享出行在中國的日常交通中扮演著關鍵角色，創新的經營模式（如自動駕駛叫車服務）可以幫助原始設備製造商抓住共享經濟的成長機會，尤其是在 L0-L3 自動駕駛汽車市場。
汽車製造商可以利用營運資料提供附加價值服務（例如即時導航和交通資訊），並與政府合作推動智慧城市計畫。

顛覆性技術

為什麼：
人工智慧演算法、感測系統、高畫質地圖等顛覆性技術改變汽車產業的競爭格局。這些技術將顯著提升自動駕駛系統的安全性和可靠性，推動其在中國客車市場的廣泛應用，並影響中國自動駕駛汽車交易金額的預測。
Frost的觀點
百度、華為、阿里巴巴等中國科技巨頭已成為自動駕駛創新的關鍵參與者，推動中國自動駕駛市場的發展。
顛覆性技術的發展需要與快速發展的法律規範相協調。

地緣政治混亂

為什麼：
地緣政治不確定性，包括美國和中國之間的貿易緊張局勢以及半導體法規，對汽車供應鏈構成了重大挑戰，高階晶片和感測器尤其容易受到衝擊。
Frost的觀點
中國汽車原始設備製造商和科技公司應優先考慮供應鏈多元化，以降低地緣政治風險。增加對國內晶片生產的投資對於減少對海外供應商的依賴並確保長期韌性非常重要。

促進因素

中國政府正透過強而有力的政策支持和法律規範推動自動駕駛的發展。「中國製造2025」等計畫正聚焦在智慧電動車領域，尤其是自動駕駛和純電動車（BEV）。這些舉措將為產業發展提供指南和政策支持，並將影響中國自動駕駛市場的成長。
隨著都市化以及人們對環境問題的日益關注，中國對智慧出行解決方案的需求日益成長。自動駕駛汽車是緩解大城市交通堵塞和污染的潛在解決方案。例如，百度Apollo Go已在11個城市進行載人測試和營運服務。 Apollo Go正朝著成為全球最大的自動駕駛出行服務提供者的目標邁進，鞏固其在L0-L3自動駕駛汽車市場的地位。
百度、華為、阿里巴巴、騰訊等中國科技巨頭正大力投資人工智慧和機器學習，這加速自動駕駛技術的發展，提高自動駕駛系統的安全性和可靠性，這也將對客車ADAS市場產生影響。
BYD、HIMA、NIO、Li Auto等本土汽車品牌正快速崛起。這些品牌致力於ADAS（高級駕駛輔助系統）與自動駕駛系統的融合，尤其是L2+等級自動駕駛。這些汽車品牌通常擁有強大的自主研發能力，為自動駕駛技術的資料累積和持續改進奠定了基礎，這對於中國OEM自動駕駛解決方案市場非常重要。

成長抑制因素

儘管政府大力推動，自動駕駛市場仍面臨一定的監管和安全挑戰。目前，中國缺乏統一的全國自動駕駛汽車測試和部署框架，導致各省之間存在差異，這可能會影響中國的自動駕駛市場。
儘管人工智慧技術不斷發展，但實現在所有條件下安全自動駕駛所需的準確性和可靠性仍然充滿挑戰。中國的整體道路基礎設施，尤其是農村地區，尚未完全支援自動駕駛汽車。此外，包括5G網路和車聯網（V2X）通訊技術在內的智慧基礎設施應用仍處於起步階段。這些因素增加了在城市環境中實現L2+及以上自動駕駛能力的難度，尤其是考慮到中國自動駕駛汽車的GMV預測。
自動駕駛解決方案的開發和實施，不僅需要主機廠升級內部營運、加強研發投入，還需要交通基礎設施的現代化，以支援電動化和智慧型系統。這需要主機廠、自動駕駛服務提供者、政府機構、交通部門以及相關企業之間的通力合作。然而，這種合作的成本高昂，對自動駕駛技術的廣泛應用，尤其是中國主機廠自動駕駛解決方案市場的成長構成了挑戰。
《資料安全法》和《資料安全管理暫行條例》對自動駕駛相關資料的收集、儲存和使用提出了更嚴格的規定，要求企業確保資料安全，防止資料外洩和濫用，增加了合規成本。

自動駕駛類別
各車型的自動駕駛能力：轎車
各車型的自動駕駛能力：SUV
BYD的自動駕駛能力
GAC Group自動駕駛能力
HIMA自動駕駛可用性
Li Auto自動駕駛可用性
NIO 自動駕駛可用性
Geely自動駕駛可用性
Xiaomi自動駕駛可用性
FAW-VW自動駕駛可用性
SAIC自動駕駛可用性
BMW自動駕駛可用性
Mercedes-Benz自動駕駛可用性
Tesla自動駕駛可用性

自動駕駛領域的成長機會

成長機會1：為電動車配備自動駕駛功能
成長機會2：SUV需求不斷擴大
成長機會3：加速監理與政策發展

附錄與後續步驟

成長機會的益處和影響
後續步驟
附表
免責聲明

作者：陳明立

調查範圍

分析範圍

自動駕駛領域

成長環境：自動駕駛領域的轉型

戰略要務 8

三大策略要務對自動駕駛產業的影響

簡介目錄

Product Code: PFUK-46

Navigate on Autopilot Accelerates the Shift Towards Autonomous Driving

An autonomous vehicle requires either partial driver assistance or may achieve fully autonomous driving. These vehicles operate through the coordinated integration of artificial intelligence (AI), computer vision, radar systems, monitoring devices, and GPS.

The autonomous driving market in China is experiencing rapid growth, with market penetration rates ranking among the highest globally. This research utilizes the L0 to L5 classification system to analyze the penetration of autonomous driving technology in China's new passenger vehicle market.

Restrained by regulatory constraints and technological limitations, L3 autonomous driving technology has not been commercialized in China's new passenger vehicle market. Vehicles equipped with L4 autonomous driving capabilities remain rare. Therefore, this research primarily focuses on autonomous driving solutions below L3 solutions.

This study examines the autonomous driving solutions provided by the leading Chinese domestic original equipment manufacturers (OEMs), EV OEMs, start-ups, and international OEMs.

Scope of Analysis

An autonomous vehicle requires either partial driver assistance or may achieve fully autonomous driving. These vehicles operate through the coordinated integration of artificial intelligence (AI), computer vision, radar systems, monitoring devices, and GPS.
The autonomous driving market in China is experiencing rapid growth, with market penetration rates ranking among the highest globally in the China autonomous driving market. This research utilizes the L0 to L5 classification system to analyze the penetration of autonomous driving technology in China's new passenger vehicle market, including insights into the L0-L3 autonomous vehicle market.
Restrained by regulatory constraints and technological limitations, L3 autonomous driving technology has not been commercialized in China's new passenger vehicle market. Vehicles equipped with L4 autonomous driving capabilities remain rare. Therefore, this research primarily focuses on autonomous driving solutions below L3 solutions, particularly in the context of the Chinese OEM autonomous driving solutions market.
This study examines the autonomous driving solutions provided by the leading Chinese domestic original equipment manufacturers (OEMs), EV OEMs, start-ups, and international OEMs, with special emphasis on the passenger vehicle ADAS market.

The Impact of the Top 3 Strategic Imperatives on the Autonomous Driving Industry

Innovative Business Models

Why:
The Chinese passenger vehicle market is transitioning toward electrification and smart technology. In response to the transition, traditional OEMs must redefine their revenue streams. The rise of the China autonomous driving market emphasizes the importance of these new business models.
Autonomous driving will reshape consumer expectations, such as personalized service and shared mobility, fueling growth in the passenger vehicle ADAS market.
Frost Perspective:
Shared mobility plays a critical role in China's daily transportation. Innovative business models (e.g., autonomous ride-hailing services) will enable OEMs to capture growth opportunities in the share economy, particularly within the context of the L0-L3 autonomous vehicle market.
Automotive OEMs can leverage operational data to provide value-added services (e.g., real-time navigation, traffic updates) and collaborate with governments to advance smart city initiatives.

Disruptive Technologies

Why:
Disruptive technologies, including AI algorithms, sensing systems, and high-definition mapping, are altering the competitive landscape of the automotive industry. These technologies can significantly enhance the safety and reliability of autonomous systems, resulting in wider adoption in the Chinese passenger vehicle market, impacting the autonomous vehicle GMV forecast China.
Frost Perspective:
Chinese tech giants such as Baidu, Huawei, and Alibaba are emerging as key players in autonomous driving innovation, driving advancements in the China autonomous driving market.
The development of disruptive technologies must align with rapidly evolving regulatory frameworks.

Geopolitical Chaos

Why:
Geopolitical uncertainties, including US-China trade tensions and semiconductor restrictions, pose significant challenges to the automotive supply chain. High-end chips and sensors are particularly vulnerable.
Frost Perspective:
Chinese automotive OEMs and technology companies should prioritize supply chain diversification to mitigate geopolitical risks. Increasing investment in domestic chip production will be critical to reducing dependence on foreign suppliers and ensuring long-term resilience.

Growth Drivers

The Chinese government promotes the development of autonomous driving through strong policy support and regulatory frameworks. Initiatives such as the Made in China 2025 plan focus on the intelligent and EV sector, especially self-driving and battery electric vehicles (BEVs). These initiatives will provide guidance and policy support for industry development, impacting the growth of the autonomous driving market in China.
With increasing urbanization and environmental concerns, demand for smart mobility solutions in China is growing. Autonomous vehicles are potential solutions for reducing traffic congestion and pollution in major cities. For example, Baidu's Apollo Go has launched passenger testing and operational services in 11 cities. Apollo Go is becoming the world's largest autonomous driving mobility service provider, solidifying its role in the L0-L3 autonomous vehicle market.
Chinese tech giants such as Baidu, Huawei, Alibaba, and Tencent are heavily investing in AI and machine learning. These investments are accelerating the development of autonomous driving technologies, enhancing the safety and reliability of autonomous driving systems, which will impact the passenger vehicle ADAS market as well.
Domestic automotive brands such as BYD, HIMA, NIO, and Li Auto are rapidly emerging. These brands are focusing on integrating advanced driver assistance systems (ADAS) and autonomous driving systems, especially in Level 2+ driving. These auto brands usually possess strong in-house R&D capabilities, laying the foundation for data accumulation and continuous improvement of autonomous driving technologies, crucial for the Chinese OEM autonomous driving solutions market.

Growth Restraints

Despite the government's active propaganda, the market still faces certain regulatory and safety challenges. There is currently no unified national framework for the testing and deployment of autonomous driving vehicles in China, leading to variations across provinces that can affect the China autonomous driving market.
Although AI technology is advancing, achieving the precision and reliability required for safe autonomous driving under all conditions remains challenging. The overall road infrastructure in China, particularly in rural areas, is not yet equipped to support autonomous driving vehicles fully. Moreover, the widespread implementation of smart infrastructure, including 5G networks and vehicle-to-everything (V2X) communication technology, is still in development. These factors increase the difficulty of realizing Level 2+ and above autonomous driving functions in urban environments, particularly in the context of the autonomous vehicle GMV forecast China.
The development and implementation of autonomous driving solutions require not only internal upgrades and enhanced R&D efforts from OEMs, but also the modernization of transportation infrastructure to support electrification and intelligent systems. This requires coordinated collaboration among OEMs, autonomous driving service providers, government entities, transportation agencies, and related enterprises. However, these collaborative efforts involve substantial cost, posing challenges to the widespread adoption of autonomous driving technologies, especially relating to the growth of the Chinese OEM autonomous driving solutions market.
The implementation of data security law and provisional regulations on data security management has led to strict regulations on the collection, storage, and use of data related to autonomous driving. These regulations require companies to ensure data security to prevent breaches and misuse, thereby increasing compliance costs.