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2136503

自動駕駛網域控制器和中央運算單元 (CCU) 市場報告，2026 年

Autonomous Driving Domain Controller and Central Computing Unit (CCU) Industry Report, 2026

出版日期: 2026年09月27日 | 出版商:

ResearchInChina | 英文 650 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

自動駕駛網域控制器（ADCU）研究：單晶片CCU解決方案正在汽車中快速部署。

在中國乘用車市場，量產型自動駕駛系統正逐步從L2級過渡到L2.5/L2.9級。 2026年起，部分L3級自動駕駛系統將透過嵌入式硬體逐步實現量產與實用化。此外，汽車製造商（OEM）正積極推動L4級無人駕駛計程車的推出。小鵬汽車和吉利汽車已相繼推出無人駕駛計程車，並計畫在2027年至2028年間與第三方合作營運無人駕駛計程車。

強制國家標準《智慧網聯汽車－自動駕駛系統安全要求》（GB 44721-2026）預定於2026年7月30日發布，並於2027年7月1日正式生效。 2026年將是L3級自動駕駛系統大規模商業部署的第一年，預計高級ADCU的出貨量將持續成長。

「星銳」將智慧駕駛座和自動駕駛兩大關鍵運算任務整合於單晶片之上。與同類「自動駕駛晶片+駕駛座晶片」方案相比，它節省50%的空間，減少30%的零件數量，縮短56%的軟硬體整合時間，將前置作業時間從18個月縮短至8個月，並將單車成本降低1500至4000元人民幣。地平線機器人計劃於2026年10月開始生產“星銳”，並於明年開始量產。

第一個採用該晶片的專案已經與 PATEO CONNECT+ 和 BICV 等公司建立了合作關係，並將為中國一家主要的新能源汽車 OEM 製造商提供服務。

隨著「集中式+區域式」架構的日益普及，單晶片CCU解決方案的滲透率正在迅速提高。

2025年是單晶片解決方案量產的元年，Arcfox aT5和東風日產N6引領了量產和實用化。 2026年，高通SA8775/SA8797和黑芝麻武當C1296等單晶片解決方案進入量產階段，地平線機器人的「星光」也憑藉其生態系統優勢進入市場。 2027年至2028年，隨著「中心+區域」架構的普及，單晶片解決方案將迅速成為主流。到2030年，單晶片解決方案的市佔率預計將達到15.3%，並有望應用於359.9萬輛汽車。

目前，Bosch、ThunderX、AutoLink World 和 DeepRoute.ai 正在銷售基於高通驍龍 8797 的 CCU（智慧駕駛控制單元），預計將於 2026 年至 2028 年間量產並應用於車輛。 ThunderX 和 BICV 正在對基於 Horizon Robotics “Starry” 晶片進行相容性測試。黑芝麻的「武當 C1296」已被東風汽車的「天元智慧座艙 Plus 平台」採用，並計畫首先搭載於東風 eπ007 車型。預計未來該晶片將應用於東風汽車所有車型，並計劃於 2026 年至 2027 年間實現多款車型的量產。

Leapmotor D19 是全球首款搭載高通 SA8797 晶片的汽車，於 2026 年 4 月正式發布。其核心控制單元 (CCU) 整合了兩顆高通驍龍 8797 晶片，實現了 1280 TOPS（基於 4 位元稀疏運算）的綜合運算效能和高達 540 GB/s 的記憶體頻寬。這使其成為目前量產車中最強大的駕駛座和駕駛整合解決方案之一。雙晶片協同工作實現了以下優勢：

CPU：2x18 Oryon，160 SpecInt2k17rate。負責系統流暢運作和多工處理。

GPU：2x770FPSMan3.0。負責螢幕圖形渲染、AR顯示和3A品質處理；

NPU：640 TOPS（單核心），1280 TOPS（雙核心），用於增強 AI 基礎模型和自動駕駛決策；

記憶體：駕駛座48GB，自動駕駛64GB。 LPDDR5x提供540GB/s的超高速頻寬，確保功能同時執行無延遲；

安全性：它整合了一個符合 ASIL-D 標準的硬體安全島，確保了汽車行業最高級別的功能安全，並提供了防止車輛失控和故障的基本保護。

基於雙8797晶片和超大容量內存，Leapmotor D19搭載LEAP 4.0，透過駕駛座與駕駛的融合實現了突破性的協同效應。它打破了傳統車輛模式中駕駛座與自動駕駛深度協調的壁壘，使「一腦掌控車輛智慧」成為可能。

動態分配算力：系統會根據駕駛場景自動分配雙8797晶片的算力。在娛樂場景下，優先考慮駕駛座的GPU/CPU性能；在自動駕駛場景下，則增強NPU的算力，從而高效利用晶片性能。

雙向資料互通性：駕駛座與自動駕駛系統深度整合，導航資訊、自動駕駛影像和娛樂內容無縫渲染和切換，自動駕駛狀態與叢集和CID即時同步；

在所有領域實現毫秒響應：車載傳輸確保從感知和決策到執行的整個過程中沒有延遲。

單顆驍龍8797晶片的AI運算能力最高可達640 TOPS（基於4位元稀疏運算）。在雙晶片結構中，一顆晶片專用於駕駛座任務，例如語音互動、環境照明和HUD投影；另一顆晶片則負責自動駕駛任務，例如感知融合、路徑規劃和車輛監控。高速通訊透過統一的中間件實現，每顆晶片都在虛擬機器管理程式支援的穩定環境中運作。

駕駛座部分，QAM8797P 配置了 48GB LPDDR5X 記憶體和 128GB UFS 快閃記憶體；而自動駕駛部分，則配置了 64GB LPDDR5X 記憶體和 256GB UFS 快閃記憶體。 QAM8797P 背面共有 10 個電源管理積體電路 (PMIC)，包括 8 個 XPMAU0102、1 個 XPMAU0101 和 1 個 XTI TPS659472E。此外，還有 4 個解串器晶片。這些晶片據推測均為 ADI MAX96724，但其中一個也可能是 MAX96714。側視攝影機、前置立體攝影機和後視攝影機各分配了兩個 MAX96724 解串器，而環景顯示攝影機則分配了一個 MAX96724 解串器。此外，DMS 由一個 MAX96714 或 MAX96724 解串器提供支援。 D19 共有五個螢幕：CID 顯示器、叢集螢幕、AR HUD 顯示器、天花板螢幕和 DLP 投影機。它包含四個串列晶片，叢集螢幕和 AR HUD 可以共用一個串列晶片。 Wi-Fi 和藍牙模組採用 Quectel AF67E，乙太網路切換器採用 Realtek RTL9071CP。 MCU 採用 Renesas U2A16，安裝在單獨的 PCB 板上。

在2026年9月的Leapmotor技術日上，Leapmotor正式發表了其全新的車輛架構「LEAP 5.0」。 LEAP 5.0是一款中央域控制的電子架構，採用真正集中式、整合化的控制模式。中央網域控制器負責統一決策，其他網域控制站則僅執行任務。車輛的線束長度控制在500公尺以內。該架構是對LEAP 3.0和LEAP 4.0的改進，也是業界首個能夠同時實現48V電源和10GbGigabit的集中式、整合化電子架構。架構包含三大核心軟硬體功能：

該車輛採用 48V 電源供電。與傳統的 12V 電源相比，線束重量減輕了 50%，使其能夠支援底盤線控和高功率車載功能。

該車輛採用非對稱以太網，下行鏈路速度為 10G，上行鏈路速度為 100M，並採用統一的車載通訊協定，從而減少了閘道器處因協議轉換而造成的損耗。

由「車聯網代理作業系統」驅動的汽車代理可確保低延遲運行和資料隱私。雲端代理負責處理複雜的推理和長期記憶，並透過輕量級迭代，使車輛能夠持續學習並適應使用者習慣。

ADCU 正在不斷升級和迭代改進，一些 OEM 廠商已經開始開發自己的高效能自動駕駛晶片。

力汽車目前提供兩種版本的ADCU：「AD Pro」和「AD MAX」。

AD Pro 最初使用 Horizon Robotics 的 J5 作為其核心，但現在採用 Horizon Robotics 的 J6M。

AD MAX 最初基於 NVIDIA Orin-X，但後來改用 NVIDIA Thor-U。

同時，力奧用自研的Mach M100晶片取代了NVIDIA Thor-U。 Mach M100採用自主研發的NPU、應用CPU、多媒體IP、安全模組和標準I/O介面，支援高水準的NOA（網路營運自動化）以及未來的L3/L4（三層/四層）功能。單顆Mach M100晶片的有效運算效能可達1280 TOPS，約為NVIDIA Thor-U的三倍。此外，雙晶片配置的有效運算效能可達NVIDIA Thor-U的5至6倍。

MACH M100晶片正快速擴大產能。理想汽車透露，截至2026年8月，其MACH M100晶片出貨量已超過5萬顆。目前，其第二款自主研發晶片「Mach 200」正處於流片階段，預計2027年開始量產。該晶片單顆算力超過2000 TOPS，製造流程已升級至3nm。理想汽車的晶片發展藍圖非常清晰，從駕駛座開始，逐步擴展到自動駕駛，並最終實現駕駛座與駕駛的融合。

自2024年初圖靈晶片開始量產以來，小鵬汽車計劃對其中央運算域控制器（XCCP）進行重大升級，以確保所有小鵬汽車都配備圖靈晶片。升級後的控制器有四種配置（高、中型、低）：

這種配置將一顆圖靈晶片與一顆聯發科MT8676（Fibocom AN762S）晶片結合在一起。採用此配置的典型車款是MONA 03 MAX。

這種配置將兩顆圖靈架構晶片與一顆聯發科MT8676處理器結合在一起。 MONA 03 Ultra SE就採用了這種配置。

在採用三顆圖靈架構晶片的配置中，兩顆專用於 XCCP，一顆專用於 VLMU。像 G7 這樣的中階機型使用聯發科 MT8676，而像 X9 和 GX 這樣的高階機型則使用高通 SA8295。

小鵬汽車的無人計程車使用了四顆圖靈晶片，並額外增加了一顆作為自動駕駛的冗餘系統。這種方案最大限度地提高了圖靈晶片的出貨量，分散了晶片研發成本和非經常性工程成本，簡化了硬體系統設計，並透過允許研究成果應用於各種應用情境來降低研發成本。

首款相容車型小鵬G7 Ultra搭載三顆圖靈AI晶片，有效算力高達2200+ TOPS，記憶體容量達216GB，並配備業界首個L3級運算平台。本地化VLA+VLM的到來：VLA-OL首次為自動駕駛注入“動態活力”，使其自動駕駛能力上限較業界MAX車型提升十倍以上。 VLM是車輛理解外部世界的AI大腦，是下一代人車互動與控制操作系統的入口，並將成為下一代自動駕駛汽車（AIDV）的標配。

VLA-OL 完全本地運行，功能更強大，無需網路連接，可在全球範圍內快速部署。它還具有高影格速率、低延遲和長序列處理能力。透過與 4D 視訊串流和 360° 全方位感知進行感知融合，它能夠提昇在低光源、逆光、雨雪等複雜環境下的環境感知能力，幫助自動駕駛系統更精準地應對路況。未來，該模型將支援三大關鍵場景：救護車識別與避讓、擁塞路段的合理變換車道以及道路坍塌的規避。

根據小鵬汽車2026年3月20日舉行的財報發表會訊息，小鵬汽車圖靈晶片累計出貨量已突破20萬顆。預計從2026年第二季起，圖靈晶片將應用於所有車型（包括Max），年出貨量預計將接近100萬顆。由於汽車業務的大規模量產，圖靈晶片的單顆製造成本已降至2500-3000元人民幣。

在小鵬G7中，XCCP看起來像一個盒子，但實際上是由兩個固定的盒子上下疊放組成。基板搭載了一顆圖靈架構晶片和64GB儲存空間。 LPDDR5記憶體推測為美光D8CWL，UFS快閃記憶體為美光SH021，容量為256GB。小鵬G7的XCCP採用了兩台MCU（英飛凌TC397），駕駛座則使用了一顆瑞薩U2A16。這顆U2A16可能也負責閘道器處理。 U2A16上的QSPI NorFlash快閃記憶體由宏碁（Macronix）製造。瑞薩RAA271084作為符合ASIL-D標準的電源管理積體電路（PMIC）專用於U2A16，確保系統符合ASIL-D標準。

基於聯發科MT8676晶片的Fibocom AN762S-CN是一款新一代多模智慧5G Sub-6通訊模組，內建Android系統。 AN762S-CN採用60 x 60 x 5.0 mm（暫定）SiP封裝，支援客戶彈性開發終端。它支援5G Sub-6、LTE、WCDMA和GSM等網路標準，同時支援Wi-Fi 6E、藍牙5.3和多衛星群GNSS。 AN762S-CN已通過AEC-Q104認證。其CPU算力為170K DMIPS，GPU算力為1.8 TFLOPS，NPU算力為20 TOPS。

在互連方面，該設計採用最先進的 10G 乙太網路連接多個圖靈晶片。具體而言，採用了博通 BCM89890（10G 乙太網路 PHY 晶片）。乙太網路切換器採用英飛凌 88Q6113，支援兩個 10G 連接埠。 3-Turing 和 4-Turing 配置可採用英飛凌 MVQ6223，該晶片具有八個 10G 端口，並可實現 90G 無阻塞交換容量。這代表了目前汽車產業可達到的最高性能水準。

2026年5月，比亞迪發表了中國首款4nm製程自動駕駛晶片「玄機A3」。該晶片已量產，支援L3和L4級自動駕駛。透過三顆晶片的高效協同，在兼顧功耗控制和算力利用率的前提下，實現了超過2100 TOPS的總合力。

比亞迪計劃推出「DiPilot（L3/L4）」平台架構，該架構擁有10層冗餘。此外，它為自動駕駛系統的各個方面提供多重備份，從感知層的感測器冗餘，到計算層的SoC和MCU冗餘，再到控制層的演算法和電源冗餘，甚至包括執行層的轉向、制動、解鎖、通訊和泊車等冗餘。同時，它是全球首個搭載超過1000通道LiDAR、1000fps全域百葉窗相機和雙長波紅外線攝影機的系統。超過1000通道的LiDAR具備4K影像級偵測能力和600公尺的超遠探測距離。全域百葉窗相機實現了1000fps的超高影格速率和小於1ms的超低延遲，確保了L3級功能的冗餘性。

如何在中國為乘用車實施EEA和運算平台
2023-2030年中國乘用車在東亞早期地區（EEA）的普及率（預測）
中國配備自動駕駛系統的乘用車數量及其滲透率
2023-2030年中國配備自動駕駛系統（L0-L4）的乘用車數量（預測）
中國乘用車ADCU市場規模及滲透率
2023-2030年中國乘用車ADCU出貨量（預測）
中國國內乘用車ADCU市場規模，2023-2030年（預測）
中國乘用車ADCU的發展趨勢：中央運算平台的整合
2025-2030年中國國產乘用車中央運算平台（一體機、單晶片）滲透率預測。
適用於中國國產乘用車的ADCU—典型的單晶片解決方案
中國乘用車ADCU供應商及其SoC市場佔有率
2023-2026年上半年國產乘用車ADCU供應商出貨量
2023-2026年上半年中國乘用車ADCU SoC安裝數量
2026年上半年中國乘用車ADCU SoC裝機量細分
2025年中國國產乘用車ADCU SoC安裝數量細分
2024年中國國產乘用車ADCU SoC安裝數量細分
2023年上半年至2026年國產乘用車ADCU SoC出貨量
按價格區間分類的中國乘用車ADCU和SoC供應商市場佔有率
2023-2026年上半年國內乘用車銷售量（依價格區間/自動駕駛等級分類）
2023-2026年上半年中國乘用車自動駕駛硬體配置狀況
2023年上半年至2026年中國國產乘用車自動駕駛網域控制器硬體與主控SoC的市佔率
主要ADCU和SoC的成本
硬體物料清單成本估算

第2章：高階、中階及低階自動駕駛晶片平台及ADCU解決方案

高階（L2.9/L3）自動駕駛晶片平台與ADCU解決方案
NVIDIA Thor-U/X
Qualcomm Snapdragon 8797
Horizon Robotics Starry
Horizon Robotics Journey 6P (J6P)
Huawei MDC
中級（L2/L2.5）自動駕駛晶片平台和ADCU解決方案
NVIDIA Orin-X/Y/N
Qualcomm Snapdragon 8775/8650
Mobileye EyeQ6/EyeQ5
Horizon Robotics Journey 6E/6M (J6E/J6M) Horizon Robotics Journey 5 (J5) Xinxin Hangtu BMC X7
Black Sesame Huashan A1000/A2000
Black Sesame Wu-Tang C1000
SiEngine SE1000/AD1000
Renesas R-Car X5
低階（L2以下）自動駕駛晶片平台和ADCU解決方案
Horizon Robotics Journey 6B（J6B）
TI TDA4
Renesas R-Car V3H/V4H
AXERA M
ORITEK Longquan 560
一級供應商的ADCU和系統解決方案概述
來自各OEM廠商的ADCU及系統解決方案
自動駕駛解決方案和SoC選擇策略（包括正在進行的專案）：比亞迪系統（比亞迪）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：比亞迪系統（陽旺、方城寶、騰紮）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：Leapmotor、AITO、MAEXTRO
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：理想汽車
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：蔚來汽車
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：小鵬汽車
自動駕駛解決方案和SoC選擇策略（包括正在進行的專案）：小米、Zeekr
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：吉利系統（吉利）
自動駕駛解決方案和SoC選擇策略（包括正在進行的專案）：奇瑞系統（EXEED、JETOUR、iCAR）
自動駕駛解決方案和SoC選擇策略（包括正在進行的專案）：奇瑞系統（富威、奇瑞、LUXEED）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：廣汽集團（Aion、傳訊集團、Hyptec、AISTALAND）
自動駕駛解決方案和SoC選擇策略（包括正在進行的專案）：廣汽集團（Aion、傳訊集團、Hyptec）
自動駕駛解決方案和SoC選擇策略（包括正在進行的專案）：上汽集團（榮威、MG、瑞星汽車、上汽（上捷））
自動駕駛解決方案和SoC選擇策略（包括正在進行的專案）：上汽集團（IM Motors）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：北汽集團（ARCFOX、BAIC）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：長安汽車（Avatr、Nevo、Deepal）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：長城汽車（哈佛、WEY、Tank）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：東風汽車（東風、EPICLAND）
自動駕駛解決方案和SoC選擇策略（包括正在進行的專案）：Voyah、一汽紅旗
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：BMW（中國）、特斯拉、賓士（中國）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：大眾汽車（中國）
自動駕駛解決方案和SoC選擇策略（包括正在進行的項目）：奧迪（中國）、豐田（中國）和本田（中國）

第3章：國內外OEM廠商的ADCU解決方案

NIO
XPeng
Li Auto
Xiaomi Auto
Leapmotor
BYD
Geely
Chery
FAW Hongqi
GAC Group
SAIC Motor
BAIC Group
Changan
Great Wall Motor
Dongfeng Motor
SAIC-GM
Harmony Intelligent Mobility Alliance (HIMA)
BMW
Volkswagen
Audi
Mercedes-Benz
Toyota
Honda
Tesla

第4章：國內ADCU供應商

Desay SV
Zhuoyu Technology
Jingwei Hirain
iMotion
Freetech
Hangsheng Electronics
ECARX
Huawei
Neusoft Reach
Lenovo Vehicle Computing
Luxshare Precision
Huaruijie Technology
Huaruijie Technology
Autolink
Technomous
ADCU Matrix
Baidu Apollo
Yihang.AI
NavInfo
Hyperview
Motovis
MINIEYE
Joynext
ThunderX
MAXIEYE
Pony.ai
Z-ONE
neueHCT
FINEST Automotive Technology
Nullmax
DeepRoute.ai
BICV

第5章：海外ADCU供應商

Bosch
Aptiv
ZF
Valeo
Magna
AUMOVIO
Visteon
Astemo

簡介目錄

Product Code: CL016

Autonomous Driving Domain Controller (ADCU) Research: One-Chip CCU solutions are quickly available in vehicles

In China's passenger car market, autonomous driving systems involved in mass production have gradually shifted from L2 to L2.5/L2.9. Some L3 autonomous driving systems have gradually seen mass production and application through embedded hardware since 2026. In addition, OEMs are actively deploying L4 robotaxis. XPeng and Geely have successively launched robotaxis, and plan to cooperate with third parties in robotaxi operation in 2027-2028.

The mandatory national standard "Intelligent and Connected Vehicle - Safety Requirements for Automated Driving System" (GB 44721-2026) was released on July 30, 2026, and is scheduled to be officially implemented on July 1, 2027. 2026 marks the first year for large-scale commercial deployment of L3 autonomous driving systems, and high-level ADCUs will continue to see increase in volume.

"Starry" integrates the two major computing tasks of smart cockpit and autonomous driving through a single chip. Compared with the competitive "autonomous driving chip + cockpit chip" solution, the space can be saved by 50%, the components can be reduced by 30%, the software and hardware integration time is shortened by 56%, the R&D delivery cycle is compressed from 18 months to 8 months, and the cost per vehicle is reduced by RMB1,500 to 4,000. Horizon Robotics plans to start the production of "Starry" in October 2026, with mass production scheduled next year.

The first project adopting this chip has confirmed partnerships with PATEO CONNECT+, BICV, etc. to serve a leading new energy vehicle OEM in China.

With the popularization of the "central + zone" architecture, the penetration rate of One-Chip CCU solutions is rapidly increasing

2025 marked the first year of mass production for One-Chip solutions, with Arcfox aT5 and Dongfeng Nissan N6 taking the lead in mass production and application. In 2026, One-Chip solutions such as Qualcomm SA8775/SA8797 and Black Sesame Wudang C1296 entered mass production, and Horizon Robotics Starry made its foray into the market with its ecosystem advantages. From 2027 to 2028, with the increasing penetration rate of the "central + zone" architecture, One-Chip solutions will prevail quickly. It is expected that by 2030, One-Chip solutions will account for 15.3%, and be installed in 3.599 million vehicles.

Currently, Bosch, ThunderX, AutoLink World, and DeepRoute.ai have launched CCUs based on Qualcomm Snapdragon 8797, which are expected to be mass-produced and applied to vehicles from 2026 to 2028. ThunderX and BICV are conducting chip adaptation tests based on Horizon Robotics Starry. Black Sesame Wudang C1296 has been designated for Dongfeng's Tianyuan Intelligent Cockpit Plus Platform and will be the first mounted on Dongfeng eπ007. It is expected to be installed on all of Dongfeng's vehicle models in the future, and mass production is planned for multiple vehicle models from 2026 to 2027.

As the world's first vehicle model equipped with Qualcomm SA8797, Leapmotor D19 was officially launched in April 2026. Its CCU is equipped with two Qualcomm Snapdragon 8797 chips, with a comprehensive computing power of 1280TOPS (based on 4-bit sparse computing) and a memory bandwidth of up to 540GB/s. It is one of the cockpit-driving integration solutions with the strongest computing power in current production vehicles. After dual-chip collaboration is attained:

CPU: 2x18Oryon, 160SpecInt2k17rate, responsible for smooth system and multi-task operation;

GPU: 2x770FPSMan3.0, responsible for screen graphics rendering, AR display, and 3A image quality;

NPU: 640TOPS (single), 1280TOPS (dual), empowering AI foundation models and autonomous driving decision-making;

Memory: 48GB memory in the cockpit, 64GB memory in autonomous driving; LPDDR5x provides 540GB/s ultra-high bandwidth, ensuring that functions can run simultaneously without lag;

Safety: Built-in ASIL-D compliant hardware security island, highest automotive-grade functional safety level, underlying protection against runaway and faults.

Relying on dual 8797 chips + ultra-large memory, Leapmotor D19 is equipped with LEAP 4.0, pioneering cockpit-driving integration super synergy, breaking the barriers of traditional vehicle model cockpit and autonomous driving in-depth synergy, and enabling "a cerebrum to control the vehicle intelligence."

Dynamic allocation of computing power: The system will automatically allocate the computing power of the dual 8797 chips according to the car scenario. The entertainment scenario focuses on the cockpit GPU/CPU performance, and the NPU computing power is enhanced in autonomous driving to efficiently utilize the chip performance;

Two-way data interoperability: The cockpit and the autonomous driving system are deeply integrated, navigation information, autonomous driving pictures, and entertainment content are seamlessly rendered and switched without any sense, and the autonomous driving status is synchronized to the cluster and CID in real time;

Full-domain millisecond-level response: In-board transmission and no delay in the entire process from perception, decision-making to execution.

The AI computing power of a single Snapdragon 8797 chip is up to 640TOPS (based on 4-bit sparse computing). In the dual-chip architecture, one chip focuses on cockpit tasks such as voice interaction, ambient lighting, and HUD projection; the other handles autonomous driving tasks, including perception fusion, path decision-making, and vehicle monitoring. High-speed communication is realized via unified middleware, and each chip operates in a stable environment supported by Hypervisor.

For the cockpit, QAM8797P is paired with 48GB LPDDR5X and 128GB UFS; for autonomous driving, it is configured with 64GB LPDDR5X and 256GB UFS. QAM8797P has 10 PMICs, including 8XPMAU0102, 1XPMAU0101, and 1XTI TPS659472E on the back. There are four chips for deserialization. It is estimated that all of them are ADI MAX96724, but one of them may be MAX96714. The side view, front stereo and rear view cameras are involved with two MAX96724 deserializers, the surround view camera corresponds to one MAX96724 deserializer, and the DMS is supported by one MAX96714 or MAX96724 deserializer. D19 has 5 screens, namely CID, cluster screen, AR HUD, ceiling screen, and DLP projector. There are 4 serial chips, and the cluster screen and AR HUD may share one serial chip. The WiFI and Bluetooth modules are Quectel AF67E, and the Ethernet switch comes from from Realtek RTL9071CP. The MCU, namely Renesas U2A16, is on another PCB.

At the Leapmotor Tech Day in September 2026, Leapmotor officially released a new vehicle architecture - LEAP 5.0 . As a central domain control electronic architecture, LEAP 5.0 adopts a truly central integrated control mode. The central domain controller makes unified decisions, and the other domain controllers only execute tasks. The vehicle wiring harness is controlled within 500 meters. This architecture is iterated from LEAP 3.0 and LEAP 4.0. It is also the first centrally integrated EEA in the industry that simultaneously implements 48V power supply and 10 Gigabit Ethernet for the vehicle. The architecture has three core hardware and software capabilities:

The vehicle is powered by 48V. Compared with traditional 12V power supply, the wiring harness is 50% lighter and can support chassis-by-wire and high-power in-vehicle living functions;

The vehicle boasts asymmetric Ethernet, with 10G downlink, 100M uplink, a unified vehicle communication protocol, reducing gateway protocol conversion loss;

Powered by vehicle-cloud agent OS, the automotive agent ensures low-latency operation and data privacy. The cloud agent handles complex reasoning and long-term memory, and enables the vehicle to continuously learn and adapt to user habits through lightweight iteration.

ADCUs are upgraded and iterated, and some OEMs begin to develop high-computing-power autonomous driving chips by themselves

Li Auto currently has two versions of ADCUs: AD Pro and AD MAX:

AD Pro originally used Horizon Robotics J5 as its core, but has resorted to Horizon Robotics J6M.

AD MAX originally took NVIDIA Orin-X as the core, but has adopted NVIDIA Thor-U instead.

At the same time, Li Auto has replaced Nvidia Thor-U wit its self-developed Mach M100. Mach 100 includes the self-developed NPU, application CPU, multimedia IP, security modules and standard I/O interfaces, oriented towards high-level NOA and future L3/L4 capabilities. The effective computing power of a single Mach 100 chip reaches 1280TOPS, which is about 3 times that of Nvidia Thor-U, while the effective computing power of a dual-chip combination can be 5 to 6 times that of Nvidia Thor-U.

MACH M100 is ramping up rapidly. Li Auto disclosed that over 50,000 MACH M100 chips had been delivered as of August 2026. Currently, the second self-developed chip Mach 200 has entered the tape-out stage and is expected to be mass-produced in 2027. The computing power of a single chip exceeds 2000TOPS and the manufacturing process has upgraded to 3nm. Li Auto's chip roadmap is very clear: starting from the cockpit, extending to autonomous driving, and then to cockpit-driving integration.

Since the mass production of Turing chips in early 2024, XPeng has been planning to make a major revision to its central computing domain controller, or XCCP, so that all vehicle models of XPeng will be equipped with Turing chips, with four configurations (high, medium and low):

One Turing chip is paired with MediaTek MT8676 (Fibocom AN762S). The typical vehicle model with the configuration is MONA 03 MAX.

Two Turing chips are paired with MediaTek MT8676. MONA 03 Ultra SE has such a configuration.

There are three Turing chips, two of which are placed in the XCCP, and one is placed alone in the VLMU. Mid-range vehicle models such as G7 are also equipped with MediaTek MT8676, and high-end vehicle models like X9 and GX carry Qualcomm SA8295.

Four Turing chips are used for XPeng's robotaxi, and a separate one is added to serve as an autonomous driving redundant system. This move can increase the shipments of Turing chips as much as possible, dilute the chip R&D and NRE costs, and also simplify the hardware system design, multiplex the R&D results, and reduce R&D costs.

As the first supported vehicle model, Xpeng G7 Ultra is equipped with 3 Turing AI chips, with an effective computing power of 2200+TOPS and 216GB memory, boasting the industry's first L3 computing platform. Debut of local VLA+VLM: VLA-OL adds a "motion cerebrum" to autonomous driving for the first time, and the upper limit of autonomous driving capabilities is 10+ times higher than that of MAX vehicle models in the industry. VLM is an AI cerebrum for vehicles to understand the world, and the next-generation OS entry point for human-vehicle dialogue and control, which will become a standard feature of the next generation of AIDVs;

VLA-OL runs entirely locally, has stronger capabilities, does not require networking, and can be quickly deployed globally; it also has high frame rate, low latency, and long-sequence characteristics. Through 4D video stream perception fusion and 360° all-round perception, it improves environmental recognition capabilities in complex scenarios such as dark light, backlighting, rain and snow, etc., and helps autonomous driving respond to road conditions more accurately. In the future, this model will empower three major scenarios: ambulance recognition and giving way, reasonable lane changes in congested road sections, and pavement collapse avoidance.

According to information from XPeng's financial report conference call on March 20, 2026, the cumulative shipments of XPeng Turing chips had exceeded 200,000 units. It is expected to all vehicle models (including Max) will adopt Turing from the second quarter of 2026, and the annual shipments will be close to 1 million units. The large-scale production of the automotive business has reduced the manufacturing cost of a single Turing chip to RMB2,500-3,000.

In XPeng G7, XCCP looks like a box, but actually consists of two boxes (upper and lower) fixed together. There is a Turing chip on the board, equipped with 64GB storage. The LPDDR5 is speculated to be Micron D8CWL, and the UFS is Micron SH021, with a capacity of 256GB. XPeng G7's XCCP uses two MCUs (Infineon TC397); the cockpit uses Renesas U2A16, which is probably also responsible for gateways. The QSPI NorFlash equipped with U2A16 comes from Macronix. As a U2A16-specific ASIL-D PMIC, Renesas RAA271084 ensures that the system reaches ASIL-D.

Based on the MTK MT8676, Fibocom AN762S-CN is the next-generation multi-mode intelligent 5G Sub-6 communication module with built-in Android. AN762S-CN adopts a 60*60*5.0mm (TBD) SiP package to facilitate customers to flexibly develop terminals. It is compatible with 5G Sub-6, LTE, WCDMA, GSM and other network standards, and supports WiFi 6E, BT5.3 and multi-constellation GNSS. AN762S-CN has been certified by AEC-Q104. The CPU computing power is 170K DMIPS, the GPU computing power is 1.8TFLOPS, and the NPU computing power is 20TOPS.

For interconnection, the design leverages state-of-the-art 10G Ethernet to link multiple Turing chips. Broadcom BCM89890 (10G Ethernet PHY chip) is deployed. The Ethernet switch is Infineon 88Q6113, supporting two 10G ports. The 3-Turing and 4-Turing configurations may adopt Infineon MVQ6223, which features eight 10G ports and delivers a non-blocking switching capacity of 90G - the highest level in the automotive industry today.

In May 2026, BYD launched China's first 4nm autonomous driving chip - Xuanji A3. It has been mass-produced and supports L3 and L4 autonomous driving. The efficient collaboration of three chips can achieve a total computing power of over 2100TOPS, while taking into account power consumption control and computing power utilization.

BYD plans to launch DiPilot (L3/L4), which has ten layers of redundancy in the platform architecture. Besides, from sensor redundancy at the perception layer, to SoC and MCU redundancy at the computing layer, to algorithm and power supply redundancy at the control layer, as well as steering, braking, unlocking, communication, and parking redundancy at the execution layer, it realizes multiple backups for all aspects of the autonomous driving system. In addition, it is the first in the world to feature over-thousand-channel LiDAR, 1000fps global shutter cameras, dual long-wave IR cameras. The over-thousand-channel LiDAR has 4K image-level detection capabilities and an ultra-long detection range of 600 meters. The global shutter cameras have an ultra-high frame rate of 1000fps and an ultra-low latency of less than 1ms, ensuring the redundancy of L3 functions.

Summary 1: High-level ADCU & CCU and Chip Selection

Summary 2: Mid-level ADCU & CCU and Chip Selection (1)

Summary 2: Mid-level ADCU & CCU and Chip Selection (2)

Summary 3: Low-level ADCU & CCU and Chip Selection

1 ADCU and CCU Market

1.1 China's Passenger Car EEA and Computing Platform Deployment Method
China's Local Passenger Car EEA Penetration Rate, 2023-2030E
Attached Table: China's Local Passenger Car EEA Penetration Rate, 2023-2030E
1.2 China's Passenger Car Autonomous Driving System Installations and Penetration Rate
China's Local Passenger Car Autonomous Driving System Installations (L0~L4), 2023-2030E
Attached Table: China's Local Passenger Car Autonomous Driving System Installation Rate, 2023-2030E
1.3 China's Passenger Car ADCU Market Size and Penetration Rate
China's Local Passenger Car ADCU Shipments (10,000 Units), 2023-2030E
China's Local Passenger Car ADCU Market Size (RMB100 Million), 2023-2030E
Attached Table: China's Local Passenger Car ADCU Shipments and Market Size, 2023-2030E
China's Local Passenger Car ADCU Development Trend: Central Computing Platform Integration
Attached Table: Penetration Rate of Computing Platforms in Local Passenger Cars in China by Integration Form, 2023-2030E
China's Local Passenger Car Central Computing Platform (One Box One Chip) Penetration Rate, 2025-2030E
China's Local Passenger Car ADCU - Typical One-Chip Solution (1)
China's Local Passenger Car ADCU - Typical One-Chip Solution (2)
China's Local Passenger Car ADCU - Typical One-Chip Solution (3)
1.4 China's Passenger Car ADCU Suppliers and Their SoC Market Share
Shipments of China's Local Passenger Car ADCU Suppliers (10,000 Units), 2023-H1 2026 (1)
Shipments of China's Local Passenger Car ADCU Suppliers (10,000 Units), 2023-H1 2026 (2)
China's Local Passenger Car ADCU SoC Installations (Vehicles), 2023-H1 2026 (1)
China's Local Passenger Car ADCU SoC Installations (Vehicles), 2023-H1 2026 (2)
Breakdown of China's Local Passenger Car ADCU SoC Installations (Vehicles), H1 2026
Breakdown of China's Local Passenger Car ADCU SoC Installations (Vehicles), 2025
Breakdown of China's Local Passenger Car ADCU SoC Installations (Vehicles), 2024
China's Local Passenger Car ADCU SoC Shipments (Units), 2023-H1 2026 (1)
China's Local Passenger Car ADCU SoC Shipments (Units), 2023-H1 2026 (2)
1.5 Market Share of China's Passenger Car ADCU and SoC Vendors by Price Range
China's Local Passenger Car Sales Volume (by Price Range/Autonomous Driving Level), 2023-H1 2026 (1)
China's Local Passenger Car Sales Volume (by Price Range/Autonomous Driving Level), 2023-H1 2026 (2)
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (>RMB500,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (>RMB500,000), 2023-H1 2026
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (RMB400,000-500,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (RMB400,000-500,000), 2023-H1 2026
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (RMB350,000-400,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (RMB350,000-400,000), 2023-H1 2026
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (RMB300,000-350,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (RMB300,000-350,000), 2023-H1 2026
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (RMB250,000-300,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (RMB250,000-300,000), 2023-H1 2026
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (RMB200,000-250,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (RMB200,000-250,000), 2023-H1 2026
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (RMB150,000-200,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (RMB150,000-200,000), 2023-H1 2026
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (RMB100,000-150,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (RMB100,000-150,000), 2023-H1 2026
Installation Structure of Autonomous Driving Hardware in China's Local Passenger Cars (RMB0-100,000), 2023-H1 2026
Market Share of Autonomous Driving Domain Controller Hardware and Master SoCs in China's Local Passenger Cars (RMB0-100,000), 2023-H1 2026
1.6 Cost of Main ADCUs and SoCs
Cost of Main ADCUs and SoCs (1)
Cost of Main ADCUs and SoCs (2)
Cost of Main ADCUs and SoCs (5)
Hardware BOM Cost Estimation 1: Qualcomm SA8775P-Based Cockpit-Driving Integration Domain Controller
Hardware BOM Cost Estimation 2: NVIDIA Orin-N-Based Domain Controller
Hardware BOM Cost Estimation 3: NVIDIA DRIVE Thor-Based ADCU

2 High, Mid and Low-Level Autonomous Driving Chip Platforms and ADCU Solutions

2.1 High-Level (L2.9/L3) Autonomous Driving Chip Platforms and ADCU Solutions
2.1.1 NVIDIA Thor-U/X
NVIDIA Thor Installations and Major Customers, 2025-Jun 2026
NVIDIA Thor-Based ADCU Solution (1)
NVIDIA Thor-Based ADCU Solution (2)
NVIDIA Thor-Based ADCU Solution (3)
NVIDIA's Autonomous Driving Solution (1)
NVIDIA's Autonomous Driving Solution (2)
NVIDIA's Autonomous Driving Solution (3)
NVIDIA's Autonomous Driving Solution (4)
NVIDIA DRIVE Thor-Based DCU Solution 1 (1)
NVIDIA DRIVE Thor-Based DCU Solution 1 (2)
NVIDIA DRIVE Thor-Based DCU Solution 1 (3)
NVIDIA DRIVE Thor-Based DCU Solution 2 (1)
NVIDIA DRIVE Thor-Based DCU Solution 2 (5)
2.1.2 Qualcomm Snapdragon 8797
Qualcomm Snapdragon 8797 Installations and Major Customers, 2025-Jun 2026
Qualcomm Snapdragon 8797-Based ADCU Solution
Qualcomm Snapdragon 8797-Based DCU Solution 1 (1)
Qualcomm Snapdragon 8797-Based DCU Solution 1 (2)
Qualcomm Snapdragon 8797-Based DCU Solution 1 (3)
Qualcomm Snapdragon 8797-Based DCU Solution 2 (1)
Qualcomm Snapdragon 8797-Based DCU Solution 2 (2)
Qualcomm Snapdragon 8797-Based DCU Solution 2 (3)
Qualcomm Snapdragon 8797-Based DCU Solution 2 (4)
2.1.3 Horizon Robotics Starry
Horizon Robotics Starry-Based ADCU Solution
Horizon Robotics Cockpit-Driving Integration SoC (1)
Horizon Robotics Cockpit-Driving Integration SoC (2)
Horizon Robotics Cockpit-Driving Integration SoC (3)
Horizon Robotics Cockpit-Driving Integration SoC (4)
Horizon Robotics Cockpit-Driving Integration SoC-Based Computing Platform Solution
2.1.4 Horizon Robotics Journey 6P (J6P)
Horizon Robotics Journey 6P (J6P) Installations and Major Customers, 2025-Jun 2026
Horizon Robotics J6P-Based ADCU Solution
Horizon Robotics Journey 6P (1)
Horizon Robotics Journey 6P (2)
Horizon Robotics Autonomous Driving System Solution
Horizon Robotics Computing Platform Solution
2.1.5 Huawei MDC
Huawei MDC Installations and Major Customers, 2025-Jun 2026
Huawei Ascend-Based ADCU Solution
Huawei Ascend-Based DCU Solution 1 (1)
Huawei Ascend-Based DCU Solution 1 (2)
Huawei Ascend-Based DCU Solution 1 (3)
Huawei Ascend-Based DCU Solution 1 (4)
Huawei Ascend-Based DCU Solution 2 (1)
Huawei Ascend-Based DCU Solution 2 (5)
Huawei Ascend-Based DCU Solution 3 (1)
Huawei Ascend-Based DCU Solution 3 (5)
2.2 Mid-Level (L2/L2.5) Autonomous Driving Chip Platforms and ADCU Solutions
2.2.1 NVIDIA Orin-X/Y/N
NVIDIA Orin-X/Y/N Installations and Major Customers, 2025-Jun 2026
NVIDIA Orin-X-Based ADCU Solution (1)
NVIDIA Orin-X-Based ADCU Solution (2)
NVIDIA Orin-X-Based ADCU Solution (3)
NVIDIA Orin-Y/N-Based ADCU Solution
NVIDIA Orin-X-Based DCU Solution 1
NVIDIA Orin-X-Based DCU Solution 2
NVIDIA Orin-X-Based DCU Solution 3
NVIDIA Orin-X-Based DCU Solution 4 (1)
NVIDIA Orin-X-Based DCU Solution 4 (2)
NVIDIA Orin-X-Based DCU Solution 4 (3)
NVIDIA Orin-X-Based DCU Solution 4 (4)
NVIDIA Orin-N-Based DCU Solution 1 (1)
NVIDIA Orin-N-Based DCU Solution 5 (1)
2.2.2 Qualcomm Snapdragon 8775/8650
Qualcomm Snapdragon 8775/8650 Installations and Major Customers, 2025-Jun 2026
Qualcomm Snapdragon 8775-Based ADCU Solution
Qualcomm Snapdragon 8650-Based ADCU Solution
2.2.3 Mobileye EyeQ6/EyeQ5
Mobileye EyeQ6/EyeQ5 Installations and Major Customers, 2025-Jun 2026
Mobileye EyeQ6-Based ADCU Solution
Mobileye EyeQ5-Based ADCU Solution (1)
Mobileye EyeQ5-Based ADCU Solution (2)
Mobileye's Autonomous Driving Planning
Mobileye's Autonomous Driving Solution (1)
Mobileye's Autonomous Driving Solution (2)
Mobileye's Autonomous Driving Solution (3)
Mobileye's Autonomous Driving Solution (4)
Mobileye EyeQ6-Based DCU Solution
Mobileye's Autonomous Driving SoC Solution 1
Mobileye's Autonomous Driving SoC Solution 2
2.2.4 Horizon Robotics Journey 6E/6M (J6E/J6M)
Horizon Robotics Journey 6E/6M (J6E/J6M) Installations and Major Customers, 2025-Jun 2026
Horizon Robotics J6E-Based ADCU Solution (1)
Horizon Robotics J6E-Based ADCU Solution (2)
Horizon Robotics J6M-Based ADCU Solution (1)
Horizon Robotics J6M-Based ADCU Solution (2)
2.2.5 Horizon Robotics Journey 5 (J5)
Horizon Robotics Journey 5 (J5) Installations and Major Customers, 2025-Jun 2026
Horizon Robotics J5-Based ADCU Solution (1)
Horizon Robotics J5-Based ADCU Solution (2)
2.2.6 Xinxin Hangtu BMC X7
Xinxin Hangtu BMC X7 Installations and Major Customers, 2025-Jun 2026
Xinxin Hangtu BMC X7-Based ADCU Solution
Xinxin Hangtu Autonomous Driving SoC (1)
Xinxin Hangtu Autonomous Driving SoC (2)
Xinxin Hangtu Autonomous Driving SoC (3)
Xinxin Hangtu Autonomous Driving SoC Solution
2.2.7 Black Sesame Huashan A1000/A2000
Black Sesame Huashan A1000 Installations and Major Customers, 2025-Jun 2026
Black Sesame Huashan A1000-Based ADCU Solution
Black Sesame Huashan A2000-Based ADCU Solution
Black Sesame Autonomous Driving SoC (1)
Black Sesame Autonomous Driving SoC (2)
Black Sesame Autonomous Driving SoC (3)
Black Sesame Autonomous Driving SoC (4)
Black Sesame Huashan A2000 Solution
2.2.8 Black Sesame Wu-Tang C1000
Black Sesame Wudang C1000-Based ADCU Solution
Black Sesame Cockpit-Driving Integration SoC-Based Autonomous Driving Solution (1)
Black Sesame Cockpit-Driving Integration SoC-Based Autonomous Driving Solution (2)
Cockpit-Driving Integration SoC-Based Autonomous Driving Computing Platform: Secure & Intelligent Foundation (1)
Cockpit-Driving Integration SoC-Based Autonomous Driving Computing Platform: Secure & Intelligent Foundation (2)
2.2.9 SiEngine SE1000/AD1000
SiEngine SE1000/AD1000-Based ADCU Solution
SiEngine Cockpit-Driving Integration SoC
SiEngine Autonomous Driving SoC (1)
SiEngine Autonomous Driving SoC (2)
SiEngine Autonomous Driving Ecosystem Platform
2.2.10 Renesas R-Car X5
Renesas R-Car X5-Based ADCU Solution
Renesas Multi-Domain Fusion SoC (1)
Renesas Multi-Domain Fusion SoC (2)
2.3 Low-Level (below L2) Autonomous Driving Chip Platforms and ADCU Solutions
2.3.1 Horizon Robotics Journey 6B (J6B)
Horizon Robotics journey 6B (J6B) Installations and Major Customers, 2025-Jun 2026
Horizon Robotics J6B-Based ADCU Solution
2.3.2 TI TDA4
TI TDA4 Installations and Major Customers, 2025-Jun 2026
TI TDA4-Based ADCU Solution (1)
TI TDA4-Based ADCU Solution (5)
2.3.3 Renesas R-Car V3H/V4H
Renesas R-Car V3H/V4H Installations and Major Customers, 2025-Jun 2026
Renesas R-Car V3H/V4H-Based ADCU Solution
2.3.4 AXERA M
AXERA M Installations and Major Customers, 2025-Jun 2026
AXERA "Axera Auto"-Based ADCU Solution
AXERA High-Level Autonomous Driving Chip (1)
AXERA High-Level Autonomous Driving Chip (2)
AXERA "Axera Auto" (1)
AXERA "Axera Auto" (2)
2.3.5 ORITEK Longquan 560
ORITEK Longquan 560-Based ADCU Solution
ORITEK Autonomous Driving SoC (1)
ORITEK Autonomous Driving SoC (2)
2.4 Summary of ADCUs and System Solutions of Tier1 Suppliers
Summary of ADCU Product Lines of Tier1 Suppliers (1)
Summary of ADCU Product Lines of Tier1 Suppliers (4)
Summary of ADCU Product Lines of Tier1 Suppliers (5)
2.5 ADCUs and System Solutions of OEMs
Autonomous Driving Solutions and SoC Selection Strategy of BYD System (BYD) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of BYD System (Yangwang, Fangchengbao, Denza) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Leapmotor, AITO, and MAEXTRO (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Li Auto (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of NIO (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Xpeng (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Xiaomi and Zeekr (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Geely System (Geely) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Geely System (Geely) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Chery System (EXEED, JETOUR, iCAR) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Chery System (Fulwin, Chery, LUXEED) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of GAC Group (Aion, Trumpchi, Hyptec, AISTALAND) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of GAC Group (Aion, Trumpchi, Hyptec) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of SAIC Group (Roewe, MG, Rising Auto, SAIC (Shangjie)) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of SAIC Group (IM Motors) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of BAIC Group (ARCFOX, BAIC) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Changan Automobile (Avatr, Nevo, Deepal) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Great Wall Motor (Haval, WEY, Tank) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Dongfeng Motor (Dongfeng, EPICLAND) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Voyah and FAW Hongqi (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of BMW (China), Tesla and Mercedes-Benz (China) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Volkswagen (China) (Including Ongoing Projects)
Autonomous Driving Solutions and SoC Selection Strategy of Audi (China), Toyota (China) and Honda (China) (Including Ongoing Projects)