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中国の独立系OEMのADAS・自律走行（2023年）

Chinese Independent OEMs ADAS and Autonomous Driving Report, 2023
出版日: | 発行: ResearchInChina | ページ情報: 英文 420 Pages | 納期: 即日から翌営業日

価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=155.13円
中国の独立系OEMのADAS・自律走行（2023年）
出版日: 2023年10月07日
発行: ResearchInChina
ページ情報: 英文 420 Pages
納期: 即日から翌営業日
  • 全表示
  • 概要
  • 目次
概要

1.NOAの普及が始まり、現地ブランドがシェアを獲得します。

2023年1月～8月のL2.5以上のシステム搭載数に占める合弁ブランドの割合は3.0%で、主にTeslaが牽引しました。独立系ブランドの割合は3.7%で、2022年の1.9%から1.8ポイント上昇しました。2023年1月～8月のL2.9システムの搭載数に占める独立系ブランドの割合は1.9%で、2022年比で1ポイント上昇しました。都市NOAは主にLi Auto、NIO、Avatr、AITO、Xpengで利用可能です。

自動車メーカーが発表したモデルや計画によると、独立系ブランドはNOAの展開に取り組んでおり、価格を下げ、構成を改善し始めています。

2. オールシナリオ都市NOAの困難さを考慮し、多くのOEMは通勤NOAから始めています。

Li Autoは、簡単なルートであれば1週間で訓練でき、複雑なルートでは2～3週間かかることを明らかにしました。

3. 従来の独立系OEMは、インテリジェントドライビングチームの技術力を高めるため、人材獲得競争を繰り広げています。

L2インテリジェントドライビングからL3インテリジェントドライビングにアップグレードする過程で、従来の独立系OEMのオリジナルインテリジェントドライビングチームの技術力は業界の技術開発動向に追いつけません。そのため、各自動車メーカーは、業界の先駆者や技術企業、新興自動車メーカーから技術専門家を引き抜き、自社のインテリジェントドライビングチームの技術レベルを向上させています。

4. 産業チェーンの上流と下流が共同で最適な性能とコストのソリューションを推進します。

HDマップは都市カバー率が低く、収集コストが高く、更新頻度が不安定であり、これは業界にとって解決不可能な問題であるため、主要OEMは「軽量マップ」ソリューションで業界のコンセンサスを得ました。

さらに、Tier 1サプライヤーは、センサーソリューションのコストを削減するために、新しいソリューションを積極的に導入しています。

全体として、NOA市場の"内巻"は、競争力を高めるため、OEMがハイレベルな運転支援を迅速に導入するよう促しました。しかし、ハイレベルなインテリジェントドライビング技術は非常に複雑です。短いウィンドウピリオドでは、自社開発能力が不十分なOEMは、十分な量産経験と先進の成熟した技術を持つHuaweiやDJIのような主要Tier 1サプライヤーを好むと見られます。

当レポートでは、中国の自動車産業について調査分析し、独立系OEMのADAS・自動運転の搭載数、導入計画、開発動向などの情報を提供しています。

目次

ADASのレーティング

ADAS機能の定義

第1章 中国の独立系ブランドのADAS市場の現状

  • ADASの搭載数と搭載率：機能レベル別
  • 中国の独立系ブランドの構造：ADASレベル別
  • 中国の独立系ブランドのADASの搭載数と搭載率：機能別
  • L2/L2+ADASの搭載数と搭載率：全体の状況
    • L2/L2+ADASの搭載数と搭載率：ブランド別
    • L2/L2+ADASの搭載率：ブランド別
  • L2/L2.5/L2.9 ADASの搭載数：ブランド別
  • L2/L2.5/L2.9 ADASの搭載数：モデル別
  • L2/L2+/L2.5/L2.9 ADASの搭載数：価格帯別
  • L2/L2+/L2.5/L2.9 ADASの搭載率：価格帯別
  • L2.5/L2.9 ADASの搭載数：価格帯別、モデル別（2022年）
  • L2.5/L2.9 ADASの搭載数：価格帯別、モデル別（2023年）
  • L2.5/L2.9 ADASの搭載数と搭載率：価格帯別

第2章 ADASと自動運転に関する中国の独立系ブランドのレイアウト

  • 中国の独立系ブランドのADAS/AD導入計画
  • 中国の独立系新興ブランドのADAS/AD導入計画
  • L2/L2.5/L2.9 ADASソリューションの比較
  • 中国の独立系OEMのパートナーキャンプ（1）
  • 中国の独立系OEMのパートナーキャンプ（2）
  • 中国の独立系新興ブランドのパートナーキャンプ
  • 独立系ブランドの自動運転レイアウトの開発動向
  • 独立系ブランドのインテリジェントドライビング技術のアップグレード
  • 独立系ブランドのインテリジェントドライビングシステムのアップグレード
  • 独立系新興ブランドの自動運転の開発動向

第3章 中国の独立系ブランドのADAS・自動運転に関する調査

  • Changan Automobile
  • Great Wall Motor
  • BYD
  • FAW
  • Geely
  • GAC
  • BAIC
  • SAIC
  • Chery
  • Dongfeng

第4章 中国の独立系新興ブランドのADAS・自動運転に関する調査

  • NIO
  • XPeng
  • LI Auto
  • Neta
  • Leapmotor
  • インテリジェントドライビングの自己開発
目次
Product Code: WWJ008

1. Wide adoption of NOA begins, and local brands grab market share.

According to ResearchInChina, from January to August 2023, joint venture brands accounted for 3.0% of installations of L2.5 and higher-level systems, mainly driven by Tesla; the proportion of independent brands was 3.7%, up 1.8 percentage points from 1.9% in 2022. From January to August 2023, independent brands took up 1.9% of installations of L2.9 systems, up 1 percentage point from that in 2022. Urban NOA is mainly available to Li Auto, NIO, Avatr, AITO and Xpeng.

As per the models and plans released by automakers, independent brands are working to deploy NOA, and they are beginning to reduce the price and improve the configuration, which means they intend to occupy the market ahead of others, by virtue of "cost performance".

For example, the new AITO M7, launched in September 2023, is priced at RMB249,800-329,800 (the price of the old model is RMB319,800-379,800). The new M7, equipped with 27 sensors including a roof LiDAR, 3 radars, 11 high-definition cameras and 12 ultrasonic radars, supports Huawei ADS 2.0 and enables high-level intelligent driving on highways and in urban areas without HD maps. Up to now, AITO has realized the commercialization of NOA in six cities without using maps, which is expected to available to up to 45 cities in the fourth quarter.

In October 2023, IM LS6 (including four editions) was launched on market. Equipped with the IM AD intelligent driving system, it is priced at RMB229,900-291,900 (limited-time offer: RMB214,900-276,900). The IM AD system valued at RMB36,800 (NVIDIA OrinX, a LiDAR, 3 radars, 11 cameras and 12 ultrasonic radars) features highway NOA and urban NOA (some functions are realized via OTA updates).

According to IM's plan, the urban NOA on IM LS6 will be tested on public roads at the end of 2023, or will be launched before the 2024 Spring Festival, first available in Shanghai. In mid-2024, "non-map" urban NOA may be implemented; within 2024, the commuting mode will cover 100 key cities across China.

2. In view of the difficulty of all-scenario urban NOA, many OEMs start with commute NOA.

Commute NOA, also known as urban memory driving, tailors the "urban driving assistance" route according to users' mobility habits. Compared with urban NOA, commute NOA can be trained on a single vehicle. It can achieve the vision of 99% autonomous driving on fixed routes based on the user's driving routes and memorized trajectories. Li Auto revealed that simple routes can be trained in one week, and complicated routes take 2-3 weeks.

3. Independent conventional OEMs compete for talents to enhance the technical capabilities of their intelligent driving teams.

In the process of upgrading from L2 to L3 intelligent driving, the technical capabilities of the original intelligent driving teams of independent conventional OEMs can't keep up with the development trend of industrial technologies. Therefore they have poached technical experts from bellwethers, technology companies, and emerging carmakers to improve the technology level of their intelligent driving teams.

For example, in August 2023, BYD invited Liao Jie, the former Intelligent Driving R&D Director of Horizon Robotics, to serve as the head of BYD's intelligent driving team in Shanghai. In September 2023, Tao Ji, the former CEO of Autra.tech, a L4 truck company, joined Changan Automobile to take in charge of intelligent driving technology. Tao Ji used to work with Baidu as the general manager of the autonomous driving division of Intelligent Driving Group (IDG) and the general manager of intelligent transportation product research and development. He participated in the entire founding process of Baidu's autonomous driving project team from 0 to 1.

4. The upstream and downstream of the industry chain jointly promote solutions with optimal performance and cost.

HD maps have low city coverage, high collection cost and unstable update frequency, which are insoluble problems for the industry, so major OEMs have reached an industry consensus on "low-weight map" solutions.

In August 2023, IM Motors and Momenta released a solution based on Data Driven Landmark Detection (DDLD) technology without using HD maps. The DDLD model can replace HD maps, construct maps in real time during driving, integrate the road features recognized in multiple mappings to generate road topology, and predict road network information that is difficult to observe with conventional perception algorithms. The solution was first mounted on IM LS6, and used for NOA public beta in September 2023 without HD maps.

In addition, Tier 1 suppliers are actively introducing new solutions to reduce the cost of sensor solutions.

In April 2023, DJI released a thousand-yuan intelligent driving solution which uses 7V/9V vision-only configuration to achieve L2+ intelligent driving functions, including urban memory driving (32TOPS)/urban NOA (80TOPS) through "strong visual online real-time perception", without relying on HD maps or LiDAR". In September 2023. The 7V solution was launched on market with the Linxi Edition of Baojun Yunduo 460 Pro priced at RMB125,800. Thus high-level intelligent driving functions are popularized to mainstream RMB100,000 family cars. After several years of low-profile development, DJI's designated projects surged in 2023. It is estimated that more than 20 cars models will carry intelligent driving products from DJI by the end of 2024.

In October 2023, Haomo.AI released three "cost-effective" driving-parking integrated products - HP170 (5TOPS), HP370 (32TOPS) and HP570 (72TOPS or 100TOPS), which enable non-map highway NOH, city memory driving, and all-scenario non-map urban NOH, with the price of RMB3,000, RMB5,000 and RMB8,000 respectively.

In general, the "involution" in the NOA market has stimulated OEMs to quickly implement high-level driving assistance for greater competitive edges. However, the high-level intelligent driving technology is highly complex. In a short window period, OEMs with insufficient self-development capabilities will prefer large Tier 1 suppliers like Huawei and DJI, which have enough mass production experience, and advanced and mature technologies.

Table of Contents

ADAS Rating

ADAS Function Definition

1 Status Quo of Chinese Independent Brands' ADAS Market

  • 1.1 ADAS Installations and Installation Rate: By Function Level
  • 1.2 Structure of Chinese Independent Brands by ADAS Level
  • 1.3 ADAS Installations and Installation Rate of Chinese Independent Brands: By Function
  • 1.4 L2/L2+ ADAS Installations and Installation Rate: Overall Situation
    • 1.4.1 L2/L2+ ADAS Installations and Installation Rate: By Brand
    • 1.4.2 L2/L2+ ADAS Installation Rate: By Brand
  • 1.5 L2/L2.5/L2.9 ADAS Installations: By Brand
  • 1.6 L2/L2.5/L2.9 ADAS Installations: By Model
  • 1.7 L2/L2+/L2.5/L2.9 ADAS Installations: By Price Range
  • 1.8 L2/L2+/L2.5/L2.9 ADAS Installation Rate: By Price Range
  • 1.9 L2.5/L2.9 ADAS Installations: By Price Range + Model (2022)
  • 1.10 L2.5/L2.9 ADAS Installations: By Price Range + Model (2023)
  • 1.11 L2.5/L2.9 ADAS Installations and Installation Rate: By Price Range

2 ADAS and Autonomous Driving Layout of Chinese Independent Brands

  • 2.1 ADAS/AD Implementation Plan of Chinese Independent Brands
  • 2.2 ADAS/AD Implementation Plan of Chinese Independent Emerging Brands
  • 2.3 Comparison of L2/L2.5/L2.9 ADAS Solutions
  • 2.4 Partner Camps of Chinese Independent OEMs (1)
  • 2.4 Partner Camps of Chinese Independent OEMs (2)
  • 2.5 Partner Camps of Chinese Independent Emerging Brands
  • 2.6 Development Trends of Autonomous Driving Layout for Independent Brands
    • 2.6.1 Trend 1
    • 2.6.2 Trend 2
    • 2.6.3 Trend 3
    • 2.6.4 Trend 4
  • 2.7 Upgrade of Intelligent Driving Technology for Independent Brands
    • 2.7.1 Upgrade of Intelligent Driving Technology: EE Architecture
    • 2.7.2 Upgrade of Intelligent Driving Technology (2)
    • 2.7.3 Upgrade of Intelligent Driving Technology (3)
    • 2.7.4 Upgrade of Intelligent Driving Technology (4)
  • 2.8 Upgrade of Intelligent Driving System for Independent Brands
    • 2.8.1 Upgrade of Intelligent Driving System (1)
    • 2.8.2 Upgrade of Intelligent Driving System (2)
    • 2.8.3 Upgrade of Intelligent Driving System (3)
  • 2.9 Development Trends of Autonomous Driving for Independent Emerging Brands
    • 2.9.1 Trend 1
    • 2.9.1 Trend 1
    • 2.9.2 Trend 2
    • 2.9.3 Trend 3
    • 2.9.4 Trend 4
    • 2.9.5 Trend 5
    • 2.9.6 Trend 6

3 Research on ADAS/Autonomous Driving of Chinese Independent Brands

  • 3.1 Changan Automobile
    • 3.1.1 Changan's ADAS Strategic Planning
    • 3.1.2 ADAS/AD Strategy: "Beidou Tianshu" strategy (August 2018)
    • 3.1.2 ADAS/AD Strategy: 123 Strategy (August 2021)- Business Model
    • 3.1.2 ADAS/AD Strategy: 123 Strategy (August 2021) - Ark Architecture
    • 3.1.2 ADAS/AD Strategy: 123 Strategy (August 2021) - SDA
    • 3.1.2 ADAS Strategy: 123 Strategy - SDA - L3
    • 3.1.2 ADAS Strategy: 123 Strategy - SDA - L4
    • 3.1.2 ADAS Strategy: 123 Strategy - SDA - L4 Layout
    • 3.1.2 ADAS Strategy: 123 Strategy - SDA - L5
    • 3.1.2 ADAS Strategy: 123 Strategy - SDA - L6
    • 3.1.2 ADAS Strategy: 123 Strategy - SDA - L5/L6 Layout
    • 3.1.2 ADAS Strategy: 123 Strategy - SDA Architecture - Zhuge Intelligence (Aug 2022)
    • 3.1.2 ADAS Strategy: 123 Strategy - SDA Landing
    • 3.1.2 ADAS strategy: 123 Strategy - Electric Vehicle Platform
    • 3.1.3 Development History of ADAS Functions
    • 3.1.4 ADAS Roadmap
    • 3.1.5 Typical ADAS/AD Functions
    • 3.1.6 Typical ADAS Models: L2.9 Deepal SL03 & Avatr 011
    • 3.1.7 L4 Autonomous Vehicles
    • 3.1.8 Changan's Autonomous Driving Tests
    • 3.1.9 Investment and Cooperation in ADAS
    • 3.1.10 Overseas Layout
  • 3.2 Great Wall Motor
    • 3.2.1 Overall ADAS Layout
    • 3.2.2 ADAS/AD Strategy
    • 3.2.3 Development History of ADAS
    • 3.2.4 ADAS: HPilot
    • 3.2.4 ADAS: HPilot 3.0
    • 3.2.5 Typical ADAS Function
    • 3.2.6 Typical Models with ADAS: L2.9 WEY Lanshan & Tank 500
    • 3.2.7 ADAS Technology Layout: EEA (1)
    • 3.2.7 ADAS Technology Layout: EEA (2)
    • 3.2.8 ADAS Technology Layout of Haomo.AI
    • 3.2.9 Autonomous Driving Chip Layout
    • 3.2.10 Dynamic ADAS Layout - Intelligence Crowd Creativity Platform
    • 3.2.10 Dynamic ADAS Layout
    • 3.2.11 Overseas Layout
  • 3.3 BYD
    • 3.3.1 Development History of ADAS
    • 3.3.2 Overall ADAS Layout
    • 3.3.3 ADAS Responsible Team
    • 3.3.4 ADAS Roadmap
    • 3.3.5 ADAS: DiPilot & DNP
    • 3.3.5 ADAS: Eyes of the God
    • 3.3.6 Typical ADAS-enabled Vehicle: Denza N7
    • 3.3.7 ADAS Hardware Layout
    • 3.3.8 ADAS Software Layout
    • 3.3.9 ADAS Algorithm Layout
    • 3.3.9 ADAS Algorithm Layout: Planning & Decision Algorithm
    • 3.3.10 Autonomous Driving Tests
    • 3.3.11 ADAS Cooperative Ecosystem Layout
    • 3.3.12 Overseas Layout
  • 3.4 FAW
    • 3.4.1 ADAS Path Planning
    • 3.4.2 ADAS Development Strategy
    • 3.4.3 ADAS R&D Layout
    • 3.4.4 ADAS Technology Layout
    • 3.4.5 Typical ADAS/AD-Enabled Models: L2 - Hongqi HS7 and Besturn E01
    • 3.4.5 Typical ADAS/AD-Enabled Models: L2.5 - Hongqi E-HS9
    • 3.4.5 Typical ADAS/AD-Enabled Models: L4 - Robotaxi
    • 3.4.5 Typical ADAS/AD-Enabled Models: L4 - Hongqi Electric Minibus
    • 3.4.6 ADAS/AD Road Tests: Demonstration Bases
    • 3.4.6 ADAS Road Test: Public Road
    • 3.4.7 Intelligent Driving Simulation Test
    • 3.4.8 ADAS Investment and Cooperation
    • 3.4.9 Overseas Layout
  • 3.5 Geely
    • 3.5.1 ADAS Strategic Planning
    • 3.5.2 ADAS/AD Strategic Plan: Smart Geely 2025 Strategy
    • 3.5.3 ADAS Self-development Path
    • 3.5.4 ADAS Technology Layout
    • 3.5.5 ADAS Roadmap: Autonomous Driving & Automated Parking
    • 3.5.6 ADAS Technology Route
    • 3.5.7 Typical ADAS/AD Technologies
    • 3.5.8 Typical ADAS/AD-Enabled Models:L2 - Geely Xingyue L and Lynk & Co 03
    • 3.5.8 Typical ADAS/AD-Enabled Models:L2.5 - Lynk & Co 01/05
    • 3.5.8 Typical ADAS-Enabled Models: L2.9 - Zeekr 001 and Boyue L
    • 3.5.9 Autonomous Driving Test
    • 3.5.10 Commercial Vehicle Intelligent Driving Layout
    • 3.5.11 ADAS Partners
    • 3.5.12 ADAS Investment and Cooperation
    • 3.5.13 Layout Dynamics in ADAS/AD
    • 3.5.14 Overseas Layout
  • 3.6 GAC
    • 3.6.1 ADAS Roadmap
    • 3.6.2 ADAS/AD Strategy Plan: "1615" Strategy (Nov.2020)
    • 3.6.3 ADAS Team
    • 3.6.4 ADAS/AD Technology Layout
    • 3.6.5 Evaluation Roadmap of ADAS/AD Solution: ADiGO
    • 3.6.6 ADAS/AD Systems: ADiGO
    • 3.6.6 ADAS/AD Systems: ADiGO 3.0
    • 3.6.6 ADAS/AD Systems: ADiGO 4.0
    • 3.6.7 L4/L5 Autonomous Driving Layout
    • 3.6.8 L4/L5 Autonomous Driving Commercialization Progress
    • 3.6.9 Autonomous Driving Tests
    • 3.6.10 Investment and Cooperation in ADAS/AD
    • 3.6.11 Overseas Layout
  • 3.7 BAIC
    • 3.7.1 Development Course of Autonomous Driving
    • 3.7.2 ADAS/AD Strategy
    • 3.7.3 ADAS/AD Technology Layout
    • 3.7.4 ADAS/AD Roadmap
    • 3.7.5 Typical ADAS/AD-Enabled Models:L2.5,ARCFOX αT
    • 3.7.5 Typical ADAS/AD-Enabled Models: L2.9, ARCFOX αS New HI Edition
    • 3.7.6 Autonomous Driving Tests
    • 3.7.7 Autonomous Driving Cooperation Layout
    • 3.7.8 Dynamic Deployments in ADAS/AD
  • 3.8 SAIC
    • 3.8.1 Development Course of Intelligent Driving Self-developed Team
    • 3.8.2 Autonomous Driving Planning
    • 3.8.3 ADAS/AD Technology Layout
    • 3.8.4 Development Course of Autonomous Driving
    • 3.8.5 ADAS/AD Roadmap
    • 3.8.6 Typical ADAS/AD-Enabled Models: L2, Rising MARVEL-R and MG ONE
    • 3.8.6 Typical ADAS/AD-Enabled Models:L2.5, Roewe Whale and 3rd Gen Roewe RX5
    • 3.8.6 Typical ADAS/AD-Enabled Models: L2.9, IM L7 and Rising R7
    • 3.8.7 Advanced Intelligent Driving Solution
    • 3.8.8 Advanced Intelligent Driving Solution: PP-CEM
    • 3.8.9 Rising Auto Advanced Intelligent Driving System: RISING PILOT
    • 3.8.10 IM: Advanced Intelligent Driving System: IM AD
    • 3.8.11 Technical Advantage of IM AD
    • 3.8.12 Data Performance of IM Intelligent Driving
    • 3.8.13 Cooperation between IM Momenta on Intelligent Driving
    • 3.8.14 Autonomous Driving Road Tests
    • 3.8.15 L4 Autonomous Driving Operation Platform: Xiangdao Robotaxi
    • 3.8.16 Autonomous Driving Commercial Vehicle: UTOPILOT
    • 3.8.17 ADAS/AD Partners
    • 3.8.18 Dynamic Deployments in ADAS/AD
    • 3.8.19 Overseas Layout
  • 3.9 Chery
    • 3.9.1 Development Course of Autonomous Driving
    • 3.9.2 Intelligence Strategy: LION (Apr.2018)
    • 3.9.2 Intelligence Strategy: Yaoguang 2025 Strategy
    • 3.9.3 ADAS/AD Technology Self-developed Layout
    • 3.9.4 ADAS Cooperation Layout
    • 3.9.5 ADAS/AD Roadmap
    • 3.9.6 Typical ADAS/AD-Enabled Models: L2.9, Tiggo 9 & EXEED Stellar
    • 3.9.7 Dynamic Deployments in ADAS/AD
    • 3.9.8 Overseas Layout
  • 3.10 Dongfeng
    • 3.10.1 Brand Strategy
    • 3.10.2 Strategy: 14th Five-year Plan
    • 3.10.3 ADAS Layout/ Technology Plan: Realizing L3+ City Navigation Assisted Driving Implementation Application by 2025
    • 3.10.4 ADAS/AD Roadmap
    • 3.10.5 Typical ADAS/AD-Enabled Models: L2.5, Aeolus Yixuan MAX and Voyah FREE
    • 3.10.6 L4 Business Introduction: Self-developed "Two Systems and One Platform" Technology Products
      • 3.10.6.1 L4 Business Introduction: Autonomous Driving Pilot Project
      • 3.10.6.2 L4 Business Introduction: Autonomous Driving Pilot System R&D
      • 3.10.6.3 Typical ADAS/AD-Enabled Models: L4,RoboTaxi
      • 3.10.6.4 Typical ADAS/AD-Enabled Models: L4, Autonomous Minibus Sharing-VAN Iteration
      • 3.10.6.5 Typical ADAS/AD-Enabled Models: L4, Autonomous Minibus Sharing-VAN 1.0 Plus
      • 3.10.6.6 Typical ADAS/AD-Enabled Models: L4, Autonomous Minibus Sharing-VAN 2.0
      • 3.10.6.7 L4 Business Introduction: Seamless Mobility Services
      • 3.10.6.8 L4 Business Introduction: Feed L4 Technology back into L2 and L3 Autonomous Driving Mass Production Technology
      • 3.10.6.9 L4 Business Introduction: Smart Logistics
    • 3.10.7 Cooperation in AD Field
      • 3.10.7.1 Autonomous Driving Layout: Invested in Black Sesame Technologies to Build Driving-Parking Integrated Domain Control Platform
    • 3.10.8 Autonomous Driving Partners
    • 3.10.9 EEA Technology Layout: Overall Roadmap
      • 3.10.9.1 EEA Technology Layout: SOA-based EEA 4.0 Platform
      • 3.10.9.2 EEA Technology Layout: Network Topology of EEA 4.0
      • 3.10.9.3 EEA solution: Hardware Architecture
      • 3.10.9.4 EEA solution: Software Architecture
      • 3.10.9.5 EEA solution: Software Hierarchical Decomposition
      • 3.10.9.6 EEA solution: End - Cloud Cooperation
      • 3.10.9.7 Centralized SOA EEA Case: Dongfeng Quantum Architecture Supports L3+ Autonomous Driving
    • 3.10.10 Software Technology: AI Application
      • 3.10.10.1 Software Technology: Fusion Perception and Positioning Technology of AI Application
      • 3.10.10.2 Software Technology: Fusion Perception of AI Application
      • 3.10.10.3 Software Technology: BSW Development Model and Development Process of AUTOSAR Application
      • 3.10.10.4 Software Technology: AUTOSAR-based Controller Developed for AUTOSAR Applications

4. Research on ADAS/Autonomous Driving of Chinese Independent Emerging Brands

  • 4.1 NIO
    • 4.1.1 ADAS/Autonomous Driving Team
    • 4.1.2 ADAS/Autonomous Driving Roadmap
    • 4.1.3 ADAS/Autonomous Driving Function Evolution
    • 4.1.4 NIO Pilot Function of 1st Gen ADAS System
    • 4.1.5 NIO NAD Function of 2nd Gen ADAS System
    • 4.1.6 Comparision of NIO PILOT NAD Hardware Configuration
    • 4.1.7 NOP+
    • 4.1.8 Core Functions and Iteration Path of NOP+beta
    • 4.1.9 NOP+ was formally Launched
    • 4.1.10 Comparison between NOP and NOP+
    • 4.1.11 NOP Function Evolution
    • 4.1.12 Development Path of Automated Parking
    • 4.1.13 Update of Latest Parking System
    • 4.1.14 Automated Parking Function Evolution
    • 4.1.15 Technology Layout 1
    • 4.1.16 Technology Layout 2
    • 4.1.17 Technology Layout 3
    • 4.1.18 Technology Layout 4
    • 4.1.19 ADAS/Autonomous Driving Cooperation Model and Dynamics
    • 4.1.20 Investment
    • 4.1.21 ADAS/Autonomous Driving Related Suppliers
    • 4.1.22 Truck Autonomous Driving Layout
  • 4.2 XPeng
    • 4.2.1 ADAS/Autonomous Driving Team
    • 4.2.2 XPILOT Development Roadmap
    • 4.2.3 NGP
    • 4.2.4 XNGP
    • 4.2.5 NGP Function Evolution
    • 4.2.6 Development Path of Automated Parking
    • 4.2.7 VPA
    • 4.2.8 VPA-L
    • 4.2.9 VPA Function Evolution
    • 4.2.10 Technology Layout 1
    • 4.2.11 Technology Layout 2
    • 4.2.12 Technology Layout 3
    • 4.2.13 Technology Layout 4
    • 4.2.14 Technology Layout 5
    • 4.2.15 Autonomous Driving Hardware Configuration and Related Suppliers
    • 4.2.16 Autonomous Driving Dynamics
    • 4.2.17 Cooperation
  • 4.3 LI Auto
    • 4.3.1 ADAS/Autonomous Driving Team and Product Development Mode
    • 4.3.2 ADAS/Autonomous Driving Development Route
    • 4.3.3 AD System and Typical Models
    • 4.3.4 AD MAX System
    • 4.3.5 AD Pro System
    • 4.3.6 ADAS Typical Functions
    • 4.3.7 ADAS System Software Iteration
    • 4.3.8 Development Roadmap of Automated Parking
    • 4.3.9 Intelligent Parking and Summon
    • 4.3.10 Function Evolution of Automated Parking
    • 4.3.11 ADAS System Hardware Iteration and Related Suppliers
    • 4.3.12 Technology Layout 1
    • 4.3.13 Technology Layout 2
    • 4.3.14 Technology Layout 3
    • 4.3.15 Technology Layout 4
    • 4.3.16 Technology Layout 5
    • 4.3.17 Technology Layout 6
    • 4.3.18 Recent Planning and Cooperation
  • 4.4 Neta
    • 4.4.1 Intelligent Driving Team
    • 4.4.2 Development Course of Intelligent Driving
    • 4.4.3 Autonomous Driving Strategy
    • 4.4.4 Haozhi Super-computing Platform
    • 4.4.5 EEA
    • 4.4.6 Development Course of Intelligent Driving System
    • 4.4.7 Scenarios Covered by Intelligent Driving System
    • 4.4.8 NETA PILOT 3.0/4.0
    • 4.4.9 Advanced Function Release Plan of NETA PILOT 3.0/4.0
    • 4.4.10 Parking Functions (1)
    • 4.4.11 Parking Functions (2)
    • 4.4.12 Intelligent Driving Full-Stack Self-development Solution
    • 4.4.13 Intelligent Driving Parts Suppliers
    • 4.4.14 Intelligent Driving Cooperation Dynamics
  • 4.5 Leapmotor
    • 4.5.1 Development Course
    • 4.5.2 Full-domain Self-development
    • 4.5.3 Self-developed Achievement
    • 4.5.4 R&D Team
    • 4.5.5 Vehicle Platform
    • 4.5.6 EEA
    • 4.5.7 Clover EEA
  • 4.5.8Intelligent Driving Self-Development
    • 4.5.9 Intelligent Driving System --Leap Pilot
    • 4.5.10 Technology Layout
    • 4.5.11 Suppliers