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表紙：世界と中国のL4自動運転とスタートアップの分析 (2022年版)
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世界と中国のL4自動運転とスタートアップの分析 (2022年版)

Global and China L4 Autonomous Driving and Start-ups Report, 2022
出版日: | 発行: ResearchInChina | ページ情報: 英文 360 Pages | 納期: 即日から翌営業日

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世界と中国のL4自動運転とスタートアップの分析 (2022年版)
出版日: 2022年11月13日
発行: ResearchInChina
ページ情報: 英文 360 Pages
納期: 即日から翌営業日
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  • 概要
  • 目次
概要

L4自動運転の分析：業界は「寸法縮小＋コスト削減」という新たな開発段階に入ります。

L3/L4自律走行は、より大きな政策的支援を享受します。

L3/L4自律走行の発展には、政策と技術の両方のサポートが必要です。2022年以降、中国はハイレベルな自律走行に対してはるかに大きな政策的支援を与えています。

ノックアウトが始まると、L4自律走行サプライヤーは「コスト削減＋寸法縮小」を模索し、業界は大規模な実用化の段階に入ります。

現在、自動車への自律走行機能の搭載率は上昇傾向にあり、L2/L2+自律走行技術も比較的成熟しています。一方で市場の競争は白熱し、OEMや自律走行ソリューションプロバイダーはより高い競争力を得るため、より高度な自律走行のトラックに参入しようと競い合っています。

「寸法縮小」アプリケーション

QCraftやCruiseでは、技術開発と普及適用を継続的に進め、死角の解消や冗長性の確保などに取り組んでいます。

「コスト削減」アプリケーション

L4自律走行製品の実現には、コストの高さも大きな障害となります。特に、コストに敏感な乗用車にとって、一般的に数十万元もするL4自律走行は正当化できないことは明らかです。そのため、各サプライヤーは精力的に「コスト削減」に着手しています。

当レポートでは、世界と中国のL4自動運転技術の最新動向や将来展望、スタートアップの動静について分析し、L4自動運転技術の関連政策や市場規模・競合情勢、L4自動運転の主要技術の概略と主力サプライヤー・ソリューション、各種分野でのL4自動運転のアプリケーションシナリオ、OEM各社のL4自動運転ソリューションの展開状況と開発計画、L4自動運転技術の主要サプライヤーのプロファイルと主力技術、といった情報を取りまとめてお届けいたします。

目次

第1章 L4自動運転の制作・規制・基準

  • L3/L4自動運転の分類と標準化
    • 運転自動化のSAEレベル
    • 中国の自動運転車分類法 (GB/T 40429-2021) の導入
    • 中国の自動車自動運転の分類：技術要件
    • 中国の自動車自動運転の分類：L3/L4の定義
    • 中国の自動車自動運転の分類：中国規格はL3安全要件を強化
    • 世界の自動運転標準化団体
    • ISO TC22/SC33 WG9：自動運転システムワーキンググループのテストシナリオ
    • ISO TC22 ADAGワーキンググループ
    • ISO TC22/SC32/WG8ワーキンググループ
    • ISO WP29 国連車両規制調和世界フォーラム
    • ISO 22737：ISO初のL4自動運転システムの国際安全規格
    • ISO 22737：L4 LSAD (低速自動運転) システムアーキテクチャ
  • 中国国内のL3/L4自動運転の政策と規制
    • 中国国内のL3/L4自動運転規制：まとめ
    • 中国国内のL3/L4自動運転規制：インテリジェント・コネクテッド・ビークルの参入と走行の試験運用に関する通知 (意見募集案)
    • 中国国内のL3/L4自動運転規制：深セン市がL3自動運転車の事故の責任範囲を初めて明確化
    • 中国国内のL3/L4自動運転規制：北京市がインテリジェントコネクテッド自動運転シャトルの管理規則を発表
    • 中国国内のL3/L4自動運転規制：インテリジェントコネクテッドビークルのイノベーション主導の開発を加速するための上海市の実施計画
  • L3/L4自動運転に関する世界各国の政策と規制
    • 世界の自動運転業界が実質的な政策支援を先導
    • 世界のL3/L4自動運転規制：まとめ
    • 世界のL3/L4自動運転規制：韓国が「Mobility Innovation Roadmap」を発表
    • 世界のL3/L4自動運転規制：米国NHTSAが、運転制御のない車両の乗員保護安全基準を発表
    • 世界のL3/L4自動運転規制：欧州連合が高度自動化車両の型式承認規制を発表
    • 世界のL3/L4自動運転規制：日本がL4自動運転車の路上走行を許可するよう提案

第2章 L4自動運転の市場動向

  • L4自動運転の市場規模
    • 世界のL4自動運転車の市場規模
    • 中国のL4自動運転乗用車の市場規模 (OEM)
    • 中国のL4自動運転商用車の市場規模 (OEM+AM)
  • L4自動運転の競合情勢
    • 世界のL4自動運転市場の主要企業

第3章 L4自動運転のサブシナリオのアプリケーション

  • ビジネスモデル
    • L4自動運転の商用化に向けた限られたシナリオ
    • L4自動運転の標準操作 (SOP) のタイムライン
    • L4サプライヤーの商品化モデル (I)：マルチシナリオレイアウト
    • L4サプライヤの製品化モデル (II)：寸法縮小アプリケーション
  • L4のアプリケーションシナリオ：ロボタクシー
    • ロボタクシー市場の参入企業：従来のロボタクシー企業が作成する鉄の三角形のパターン
    • ロボタクシー市場の参入企業：新興自動車メーカーが市場に参入
    • 外資系ロボタクシー事業者の統計データ
    • 国内系ロボタクシー事業者の統計データ
    • ロボタクシーの比較：Apollo Go、Pony.ai、SAIC Mobility
    • 中国におけるロボタクシーの規模展開
    • 中国のロボタクシーの市場規模
  • L4のアプリケーションシナリオ：自動運転シャトル
    • 都市運営における自動運転シャトルの役割
    • 中国の自動運転・低速シャトルのサプライヤー
    • 自動運転シャトルの市場規模
    • 自動運転シャトルの主要サプライヤーのレイアウト
  • L4のアプリケーションシナリオ：自動配送
    • 自動配送の産業チェーン
    • 大手ユーザーによる自動配送車の営業運転の展開
    • 自動配送車製品を展開する主要ユーザー：Meituan
    • 自動配送車製品を展開する主要ユーザー：JD
    • 自動配送車製品を展開する主要ユーザー：Haomo.ai
    • 自動配送車製品を展開する主要ユーザー：Neolix
    • 自動配送車製品を展開する主要ユーザー：White Rhino
    • 中国の屋外用自動配送車の市場規模
    • 中国の自動配送の市場パターン
    • 自動配送のビジネスモデル
  • L4のアプリケーションシナリオ：自動運転トラック
    • L3+/L4自動運転トラックシステム・サプライヤーの競合情勢環境
    • 自動運転トラックの開発技術ルート
    • 自動運転トラックの運用モデル：鉱山シナリオ
    • 海外の自動運転トラック市場のプレーヤー
    • 中国の自動運転トラック市場のプレーヤー (I)：自動運転大型トラックのソリューションプロバイダー
    • 中国の自動運転トラック市場のプレーヤー (II)：従来の大型トラック企業
    • 主要なL4自動運転トラック・サプライヤーの比較
    • クローズドシナリオでの自動運転事例
    • 中国の自動運転トラック市場の現状：セグメント別
    • 中国の自動運転トラック市場規模

第4章 L4自動運転の量産化に向けた主要技術

  • L4自動運転の主要技術：アルゴリズム
    • L4自動運転技術を支えるアルゴリズム
    • 自動運転ソフトウェアのアルゴリズムの事例
  • L4自動運転の主要技術：データクローズドループ
    • L4自動運転におけるデータクローズドループの重要性
    • 自動運転のためのデータクローズドループ技術
    • 自動運転データクローズドループのプロバイダー
    • 自動運転データクローズドループの事例
  • L4自動運転の主要技術：車両・道路・クラウド連携
    • 車両・道路・クラウド連携：高度自動運転への主要経路の1つ
    • 車両・道路・クラウド連携による自動運転の実現方法
    • 車両・道路・クラウド連携ソリューションプロバイダー
    • 車両・道路・クラウド連携連携によるL4自動運転の事例
  • L4自動運転の主要技術：HDマップとポジショニング
    • HDマップ向けL4自動運転の要件
    • 高精度ポジショニング技術のためのL4自動運転の要件
    • L4自動運転用HDマップのプロバイダー：乗用車
    • L4自動運転用HDマップのプロバイダー：商用車
    • L4自動運転用HDマップ・ポジショニングの量産事例
  • L4自動運転の主要技術：冗長化
    • 自動運転冗長システムのサプライヤー
    • 自動運転冗長化の事例
    • Great Wall Motor の自動運転冗長化ソリューション

第５章 OEM各社のL3/L4自動運転ソリューション

  • OEM各社のL3/L4自動運転のレイアウト
    • 主要OEMのL4自動運転車の製品・アプリケーション企画
    • OEMのL3/L4自動運転の計画とレイアウト
    • L4自動運転ソリューション：OEM間の比較
    • OEMの一般的なL4ソリューション構成
  • Jidu Auto
  • Xpeng Motors
  • Great Wall Motor
  • Tesla
  • Toyota
  • Volvo
  • その他の自動車メーカー
    • Weltmeister
    • Hongqi
    • Yutong Bus

第6章 ティア1サプライヤーとスタートアップのL4自動運転ソリューション

  • 国内系・外資系のL4サプライヤーの技術開発
    • 国内系の乗用車向けL4自動運転ソリューション
    • 国内系の乗用車向けL4自動運転ソリューション：Pony.ai
    • 国内系の乗用車向けL4自動運転ソリューション：Baidu
    • 国内系の乗用車向けL4自動運転ソリューション：Idriverplus
    • 国内系の乗用車向けL4自動運転ソリューション：WeRide
    • 国内系の乗用車向けL4自動運転ソリューション：AutoX
    • 国内系の乗用車向けL4自動運転ソリューション：Momenta
    • 国内系の乗用車向けL4自動運転ソリューション：Deeproute.ai
    • 外資系の乗用車向けL4自動運転ソリューション
    • 外資系の乗用車向けL4自動運転ソリューション：Waymo
    • 外資系の乗用車向けL4自動運転ソリューション：Cruise
    • 主要技術プロバイダーのL4自動運転ソリューション：商用車
    • 主な商用車向けL4自動運転ソリューション：QCraft
    • 主な商用車向けL4自動運転ソリューション：Inceptio Technology
    • 主要技術プロバイダーのL4自動運転ソリューション：自動配送
  • Waymo
  • Cruise
  • Aurora
  • Navya
  • Mobileye
  • Valeo
  • Baidu Apollo
  • Pony.ai
  • WeRide
  • AutoX
  • Momenta
  • Deeproute.ai
  • Huawei
  • Haomo.ai
  • DeepBlue Technology
  • Allride.ai
  • UISEE Technology
  • Idriverplus
  • QCraft
  • TuSimple
  • Plus.ai
  • Inceptio Technology
  • CiDi
目次
Product Code: ZHP125

L4 autonomous driving research: the industry enters a new development phase, "dimension reduction + cost reduction".

L3/L4 autonomous driving enjoys much greater policy support.

The development of L3/L4 autonomous driving needs both policy and technology support. Since 2022, China has given far greater policy support to high-level autonomous driving.

The Development Plan for New Energy Vehicle Industry (2021-2035) issued by the State Council indicates that "by 2025, L4 vehicles will be commercialized in limited areas and specific scenarios, and by 2035, L4 vehicles will find massive application."

On March 1, 2022, the national recommended standard GB/T 40429-2021 Taxonomy of Driving Automation for Vehicles came into force. In November 2022, the Ministry of Industry and Information Technology together with the Ministry of Public Security organized the drafting of Notice on Piloting Entry and Road Travel of Intelligent Connected Vehicles (Draft for Comments), suggesting piloting the entry of production-ready intelligent connected vehicles with autonomous driving functions (L3 and L4 in the GB/T 40429-2021 standard).

As concerns local governments, the Administrative Rules of Beijing Municipality for Autonomous Shuttles in the Pilot Areas Carrying out Intelligent Connected Vehicle Policies (Road Test and Demonstration Application) released in November 2022, is China's first policy to give the corresponding right of way in the form of coding to autonomous shuttles. In August 2022, the Regulation on the Administration of Intelligent Connected Vehicles in Shenzhen Special Economic Zone came into effect. It is China's first L3 autonomous driving regulation that highlights the first clear identification of accident responsibilities.

As the knockout starts, L4 autonomous driving suppliers seek "cost reduction + dimension reduction", and the industry enters the phase of large-scale commercial application.

At present, the installation rate of autonomous driving functions in vehicles is on the rise, and L2/L2+ autonomous driving technology has been relatively mature. The competition in the market is white hot. To gain more competitive edges, OEMs and autonomous driving solution providers compete to enter the track of higher-level autonomous driving.

Yet high-level autonomous driving consumes more capital, and is unlikely to build a full commercial closed-loop in the short term. In October 2022, Argo AI, a star start-up specializing in L4 autonomous driving, declared bankruptcy due to the capital chain rupture, a result of the inability to attract further investments, as its backers Ford and Volkswagen decided to stop investing in it.

Despite ceasing to invest in Argo AI and turning the focus on L2+/L3 that is easier to implement, Ford is still optimistic about L4 autonomous driving, but chooses not to develop on its own. It would team up with L4 autonomous driving solution providers in the future.

The case of Argo AI shows the challenges faced by L4 autonomous driving suppliers in current stage. If they do not try to develop real commercial solutions, they may eventually be weeded out by the market under capital pressure. To run farther on L4 autonomous driving track, all major suppliers aim at the mass production OEM market of passenger cars and embark on "dimension reduction" application, while working hard on L4 technology.

(1) "Dimension reduction" application

QCraft: propose the dual engine strategy. On one hand, based on public road L4 autonomous driving software and hardware solutions, it makes continuous efforts to improve its technical competence; on the other hand, based on the mass production and large-scale application of autonomous driving for OEM market, it keeps expanding application scenarios.

In May 2022, QCraft introduced DBQ V4, an autonomous driving solution for passenger car OEM market. Supporting 1 to 5 LiDARs, 0 to 4 blind spot radars, 6 radars and 12 perception cameras, it enables 360-degree perception without missing blind spots and dead corners, and allows mutual redundancy between left and right. It also packs a customized traffic light recognition camera. The solution is expected to be mass produced and mounted on vehicles during 2023-2024.

DBQ V4 offers standard and high configuration versions. The high configuration version has all L4 autonomous driving functions. Compared with high configuration version, the standard version features a slightly lower configuration, but it can still enable 99% L4 autonomous driving capabilities. The DBQ V4 autonomous driving solution integrates full-stack autonomous driving software and hardware technologies independently developed by QCraft. The standard version with a reduced LiDAR configuration carries a computing platform with lower computing power, cutting down the mass production cost to about RMB10,000. The mass-produced solution for the OEM market also enables driving and parking integrated functions.

Cruise: since 2021, it has worked to build Ultra Cruise intelligent driving system for GM. This solution is mainly mounted on the high-end vehicle models of GM and complements the Super Cruise system, helping GM to apply driving assistance technologies to all of its models.

Compared with Super Cruise, Ultra Cruise has added some new autonomous driving functions:

  • Follow the internal navigation route and keep moving forward;
  • Observe the speed limit
  • Support automatic and on-demand lane change
  • Support automatic left and right turns
  • Support close object avoidance

"Cost reduction" application

In addition, the high cost is also a major obstacle to the implementation of L4 autonomous driving products. In particular, for cost-sensitive passenger cars, it is obvious that L4 autonomous driving that generally costs hundreds of thousands of yuan doesn't justify it. All suppliers therefore have begun to vigorously "cut down cost".

Deeproute.ai: in June 2022, Deeproute.ai launched DeepRoute-Driver 2.0, a low-cost L4 autonomous driving system worth USD10,000 (about RMB64,000). This solution carries 2 to 5 solid-state LiDARs and 8 cameras, Nvidia Orin high computing power automotive chip, integrated navigation and HD map, enabling high-level autonomous driving.

Deeproute.ai says that in the future the cost of L4 autonomous driving could be lowered to less than RMB20,000 by cooperating with conventional OEMs for mass production and purchasing hardware equipment uniformly.

Haomo.ai: in April 2022, Haomo.ai launched Little Magic Camel 2.0, a product priced RMB128,800 for a single vehicle. Haomo.ai can build RMB100,000 autonomous distribution vehicles, mainly because its autonomous distribution vehicles reuse its passenger car autonomous driving technologies, and cost less by virtue of passenger car supply chain advantages. In terms of hardware, Little Magic Camel 2.0 that bears an automotive perception kit and ICU 3.0, a computing platform with high computing power can cover all medium- and low-speed road scenarios and all road conditions on urban public roads.

Technology reuse helps to expand multiple application scenarios for L4 autonomous driving systems.

Affected by technology maturity and regulatory restrictions, L4 autonomous driving is available to relatively limited application scenarios in the short run. The main application scenarios include Robotaxi, autonomous delivery, autonomous shuttle, and autonomous logistics in (semi) closed scenarios.

For L4 autonomous driving is being piloted in application fields, the deployment scale is not large, and just with tweaks, L4 autonomous driving technology can be reused in different types of vehicles, so L4 suppliers rarely follow a single business line, and generally make multi-scenario deployments.

“Global and China L4 Autonomous Driving and Start-ups Report, 2022” highlights the following:

  • L4 autonomous driving (policies, standards, regulations, etc.);
  • L4 autonomous driving market (size, competitive landscape, etc.);
  • Key technologies (algorithm, HD map and positioning, data closed-loop, vehicle-road-cloud cooperation, redundancy, etc.) of L4 autonomous driving (major suppliers, technical solutions, etc.);
  • Application scenarios (Robotaxi, autonomous shuttle, autonomous delivery, autonomous truck, etc.) of L4 autonomous driving (major suppliers, technical solutions, operation, etc.);
  • OEMs' layout and planning of L4 autonomous driving solutions;
  • Major L4 technology suppliers (technical solution iterations, application and layout of L4 products, etc.).

Table of Contents

1 Policies, Regulations and Standards for L4 Autonomous Driving

  • 1.1 Taxonomy and Standardization of L3/L4 Autonomous Driving
    • 1.1.1 SAE Levels of Driving Automation (1)
    • 1.1.2 SAE Levels of Driving Automation (2)
    • 1.1.3 China's Taxonomy of Driving Automation for Vehicles (GB/T 40429-2021) Has Been Implemented
    • 1.1.4 China's Taxonomy of Driving Automation for Vehicles: Technical Requirements (1)
    • 1.1.5 China's Taxonomy of Driving Automation for Vehicles: Technical Requirements (2)
    • 1.1.6 China's Taxonomy of Driving Automation for Vehicles: Definition of L3/L4
    • 1.1.7 China's Automotive Driving Automation Classification: The Chinese Standard Enhances L3 Safety Requirements
    • 1.1.8 Global Autonomous Driving Standards Organizations
    • 1.1.9 ISO TC22/SC33 WG9 - Test Scenarios of Automated Driving Systems Working Group
    • 1.1.10 ISO TC22 ADAG Working Group
    • 1.1.11 ISO TC22/SC32/WG8 Working Group
    • 1.1.12 ISO WP29 United Nations World Forum for Harmonization of Vehicle Regulations
    • 1.1.13 ISO's First International Safety Standard for L4 Automated Driving Systems: ISO 22737
    • 1.1.14 ISO 22737: L4 LSAD (Low Speed Automated Driving) System Architecture
  • 1.2 Policies and Regulations for L3/L4 Autonomous Driving in China
    • 1.2.1 L3/L4 Autonomous Driving Regulations in China: Summary
    • 1.2.2 L3/L4 Autonomous Driving Regulations in China: Notice on Piloting the Entry and Road Travel of Intelligent Connected Vehicles (Draft for Comments) (1)
    • 1.2.3 L3/L4 Autonomous Driving Regulations in China: Notice on Piloting the Entry and Road Travel of Intelligent Connected Vehicles (Draft for Comments) (2)
    • 1.2.4 L3/L4 Autonomous Driving Regulations in China: Shenzhen Clarified the Identification of Responsibilities for L3 Autonomous Vehicle Accidents for the First Time
    • 1.2.5 L3/L4 Autonomous Driving Regulations in China: Beijing Released the Administrative Rules for Intelligent Connected Autonomous Shuttles
    • 1.2.6 L3/L4 Autonomous Driving Regulations in China: The Implementation Plan of Shanghai Municipality for Accelerating the Innovation-driven Development of Intelligent Connected Vehicles
  • 1.3 Global Policies and Regulations for L3/L4 Autonomous Driving
    • 1.3.1 The Global Autonomous Driving Industry Ushers in Substantial Policy Support
    • 1.3.2 Global L3/L4 Autonomous Driving Regulations: Summary
    • 1.3.3 Global L3/L4 Autonomous Driving Regulations: South Korea Announced "Mobility Innovation Roadmap"
    • 1.3.4 Global L3/L4 Autonomous Driving Regulations: US NHTSA Announced the Occupant Protection Safety Standards for Vehicles Without Driving Controls
    • 1.3.5 Global L3/L4 Autonomous Driving Regulations: The European Union Released the Type-approval Regulation for Highly Automated Vehicles
    • 1.3.6 Global L3/L4 Autonomous Driving Regulations: Japan Proposed to Allow L4 Autonomous Vehicles to Travel on Roads

2 L4 Autonomous Driving Market Trends

  • 2.1 L4 Autonomous Driving Market Size
    • 2.1.1 Global L4 Autonomous Vehicle Market Size
    • 2.1.2 China's L4 Autonomous Passenger Car OEM Market Size
    • 2.1.3 China's Commercial L4 Autonomous Driving Market Size (OEM + AM)
  • 2.2 Competitive Landscape of L4 Autonomous Driving
    • 2.2.1 Major Players in Global L4 Autonomous Driving Market (1)
    • 2.2.2 Major Players in Global L4 Autonomous Driving Market (2)

3 Application Sub-scenarios of L4 Autonomous Driving

  • 3.1 Business Models
    • 3.1.1 Limited Scenarios for Commercial Application of L4 Autonomous Driving
    • 3.1.2 L4 Autonomous Driving SOP Timeline
    • 3.1.3 Commercialization Models of L4 Suppliers (I): Multi-Scenario Layout (1)
    • 3.1.4 Commercialization Models of L4 Suppliers (I): Multi-Scenario Layout (2)
    • 3.1.5 Commercialization Models of L4 Suppliers (I): Multi-Scenario Layout (3)
    • 3.1.6 Commercialization Models of L4 Suppliers (I): Multi-Scenario Layout (4)
    • 3.1.7 Commercialization Models of L4 Suppliers (II): Dimension Reduction Application (1)
    • 3.1.8 Commercialization Models of L4 Suppliers (II): Dimension Reduction Application (2)
  • 3.2 L4 Application Scenarios - Robotaxi
    • 3.2.1 Players in Robotaxi Market (I): Conventional Robotaxi Companies Create an Iron Triangle Pattern (1)
    • 3.2.2 Players in Robotaxi Market (I): Conventional Robotaxi Companies Create an Iron Triangle Pattern (2)
    • 3.2.3 Players in Robotaxi Market (I): Conventional Robotaxi Companies Create an Iron Triangle Pattern (3)
    • 3.2.4 Players in Robotaxi Market (I): Conventional Robotaxi Companies Create an Iron Triangle Pattern (4)
    • 3.2.5 Players in Robotaxi Market (II): Emerging Carmakers Enter the Market
    • 3.2.6 Statistics of Foreign Robotaxi Operators
    • 3.2.7 Statistics of Chinese Robotaxi Operators (1)
    • 3.2.8 Statistics of Chinese Robotaxi Operators (2)
    • 3.2.9 Robotaxi Comparison between Apollo Go, Pony.ai and SAIC Mobility (1)
    • 3.2.10 Robotaxi Comparison between Apollo Go, Pony.ai and SAIC Mobility (2)
    • 3.2.11 Robotaxi Comparison between Apollo Go, Pony.ai and SAIC Mobility (3)
    • 3.2.12 Scale Development of Robotaxi in China
    • 3.2.13 China's Robotaxi Market Size
  • 3.3 L4 Application Scenarios - Autonomous Shuttle
    • 3.3.1 The Role of Autonomous Shuttles in City Operation
    • 3.3.2 Low-speed Autonomous Shuttle Suppliers in China (1)
    • 3.3.3 Low-speed Autonomous Shuttle Suppliers in China (2)
    • 3.3.4 Autonomous Shuttle Market Size
    • 3.3.5 Layout of Some Autonomous Shuttle Suppliers
  • 3.4 L4 Application Scenarios - Autonomous Delivery
    • 3.4.1 Autonomous Delivery Industry Chain
    • 3.4.2 Commercial Operation of Autonomous Delivery Vehicles Deployed by Major Users (1)
    • 3.4.3 Commercial Operation of Autonomous Delivery Vehicles Deployed by Major Users (2)
    • 3.4.4 Major Users That Deploy Autonomous Delivery Vehicle Products: Meituan
    • 3.4.5 Major Users That Deploy Autonomous Delivery Vehicle Products: JD
    • 3.4.6 Major Users That Deploy Autonomous Delivery Vehicle Products: Haomo.ai
    • 3.4.7 Major Users That Deploy Autonomous Delivery Vehicle Products: Neolix
    • 3.4.8 Major Users That Deploy Autonomous Delivery Vehicle Products: White Rhino
    • 3.4.9 China's Outdoor Autonomous Delivery Vehicle Market Size
    • 3.4.10 China's Autonomous Delivery Market Pattern
    • 3.4.11 Autonomous Delivery Business Models
  • 3.5 L4 Application Scenarios - Autonomous Truck
    • 3.5.1 Competitive Landscape of L3+/L4 Autonomous Truck System Suppliers
    • 3.5.2 Technical Route for the Development of Autonomous Trucks
    • 3.5.3 Operating Model of Autonomous Trucks: Mine Scenario
    • 3.5.4 Players in Foreign Autonomous Truck Market
    • 3.5.5 Players in China's Autonomous Truck Market (I): Autonomous Heavy Truck Solution Providers
    • 3.5.6 Players in China's Autonomous Truck Market (II): Conventional Heavy Truck Companies
    • 3.5.7 Comparison between Major L4 Autonomous Truck Suppliers
    • 3.5.8 Autonomous Driving Cases in Closed Scenarios
    • 3.5.9 Status Quo of Autonomous Truck Market Segments in China
    • 3.5.10 China's Autonomous Truck Market Size

4 Key Technologies for Mass Production of L4 Autonomous Driving

  • 4.1 Key Technologies of L4 Autonomous Driving: Algorithm
    • 4.1.1 Algorithm is the Support for L4 Autonomous Driving Technology (1)
    • 4.1.2 Algorithm is the Support for L4 Autonomous Driving Technology (2)
    • 4.1.3 L4 Autonomous Driving Algorithm Providers (1)
    • 4.1.4 L4 Autonomous Driving Algorithm Providers (2)
    • 4.1.5 L4 Autonomous Driving Algorithm Providers (3)
    • 4.1.6 L4 Autonomous Driving Algorithm Providers (4)
    • 4.1.7 L4 Autonomous Driving Algorithm Providers (5)
    • 4.1.8 L4 Autonomous Driving Algorithm Providers (6)
    • 4.1.9 Autonomous Driving Software Algorithm Cases (I)
    • 4.1.10 Autonomous Driving Software Algorithm Cases (II)
    • 4.1.11 Autonomous Driving Software Algorithm Cases (III)
  • 4.2 Key Technologies of L4 Autonomous Driving: Data Closed Loop
    • 4.2.1 The Importance of Data Closed Loop to L4 Autonomous Driving
    • 4.2.2 Data Closed Loop Technology for Autonomous Driving (I)
    • 4.2.3 Data Closed Loop Technology for Autonomous Driving (II)
    • 4.2.4 Autonomous Driving Data Closed Loop Providers (2)
    • 4.2.5 Autonomous Driving Data Closed Loop Providers (2)
    • 4.2.6 Autonomous Driving Data Closed Loop Providers (3)
    • 4.2.7 Autonomous Driving Data Closed Loop Cases (I)
    • 4.2.8 Autonomous Driving Data Closed Loop Cases (II)
    • 4.2.9 Autonomous Driving Data Closed Loop Cases (III)
    • 4.2.10 Autonomous Driving Data Closed Loop Cases (IV)
    • 4.2.11 Autonomous Driving Data Closed Loop Cases (V)
    • 4.2.12 Autonomous Driving Data Closed Loop Cases (VI)
    • 4.2.13 Autonomous Driving Data Closed Loop Cases (VII)
    • 4.2.14 Autonomous Driving Data Closed Loop Cases (VIII)
    • 4.2.15 Autonomous Driving Data Closed Loop Cases (IX)
  • 4.3 Key Technologies of L4 Autonomous Driving: Vehicle-Road-Cloud Cooperation
    • 4.3.1 Vehicle-Road-Cloud Cooperation Will Become One of the Mainstream Paths to High-Level Autonomous Driving
    • 4.3.2 Ways How Vehicle-Road-Cloud Cooperation Enables Autonomous Driving
    • 4.3.3 Vehicle-Road-Cloud Cooperation Solution Providers (1)
    • 4.3.4 Vehicle-Road-Cloud Cooperation Solution Providers (2)
    • 4.3.5 Vehicle-Road-Cloud Cooperation Solution Providers (3)
    • 4.3.6 L4 Autonomous Driving Cases Based on Vehicle-Road-Cloud Cooperation (I): Nansha Smart Bus
    • 4.3.7 L4 Autonomous Driving Cases Based on Vehicle-Road-Cloud Cooperation (II): Yangshan Port Autonomous Driving
  • 4.4 Key Technologies of L4 Autonomous Driving: HD Map and Positioning
    • 4.4.1 Requirements of L4 Autonomous Driving for HD Maps (1)
    • 4.4.2 Requirements of L4 Autonomous Driving for HD Maps (2)
    • 4.4.3 Requirements of L4 Autonomous Driving for High-precision Positioning Technology
    • 4.4.4 Providers of HD Maps for L4 Autonomous Driving: Passenger Car (1)
    • 4.4.5 Providers of HD Maps for L4 Autonomous Driving: Passenger Car (2)
    • 4.4.6 Providers of HD Maps for L4 Autonomous Driving: Commercial Vehicle (1)
    • 4.4.7 Providers of HD Maps for L4 Autonomous Driving: Commercial Vehicle (2)
    • 4.4.8 Mass Production Cases of HD Map and Positioning for L4 Autonomous Driving (I)
    • 4.4.9 Mass Production Cases of HD Map and Positioning for L4 Autonomous Driving (II)
  • 4.5 Key Technologies of L4 Autonomous Driving: Redundancy
    • 4.5.1 Suppliers of Autonomous Driving Redundant Systems: Brake Redundancy
    • 4.5.2 Suppliers of Autonomous Driving Redundant Systems: Sensing Redundancy
    • 4.5.3 Suppliers of Autonomous Driving Redundant Systems: Computing Redundancy
    • 4.5.4 Autonomous Driving Redundancy Cases (I)
    • 4.5.5 Autonomous Driving Redundancy Cases (II)
    • 4.5.6 Autonomous Driving Redundancy Cases (III)
    • 4.5.7 Autonomous Driving Redundant Solutions of Great Wall Motor (1)
    • 4.5.8 Autonomous Driving Redundant Solutions of Great Wall Motor (2)

5 L3/L4 Autonomous Driving Solutions of OEMs

  • 5.1 L3/L4 Autonomous Driving Layout of OEMs
    • 5.1.1 L4 Autonomous Vehicle Products and Application Planning of Main OEMs
    • 5.1.2 L3/L4 Autonomous Driving Planning and Layout of OEMs (1)
    • 5.1.3 L3/L4 Autonomous Driving Planning and Layout of OEMs (2)
    • 5.1.4 Comparison of L4 Autonomous Driving Solutions between OEMs (1)
    • 5.1.5 Comparison of L4 Autonomous Driving Solutions between OEMs (2)
    • 5.1.6 Typical L4 Solution Configurations of OEMs
  • 5.2 Jidu Auto
    • 5.2.1 L4 Autonomous Driving SOP Planning
    • 5.2.2 L4 Autonomous Driving Technology
    • 5.2.3 LiDAR-based Autonomous Driving Solution
  • 5.3 Xpeng Motors
    • 5.3.1 L4 Autonomous Driving Planning
    • 5.3.2 Autonomous Driving System
    • 5.3.3 Autonomous Driving Technologies (I): Perception
    • 5.3.4 Autonomous Driving Technologies (II): Data Closed Loop
  • 5.4 Great Wall Motor
    • 5.4.1 Evolution of L3/L4 Autonomous Driving Solutions
    • 5.4.2 Hpilot Autonomous Driving Product Roadmap of Great Wall Motor (Haomo.ai)
  • 5.5 Tesla
    • 5.5.1 New Autopilot Layout
    • 5.5.2 FSD Beta v 10.69 System (1)
    • 5.5.3 FSD Beta v 10.69 System (2)
  • 5.6 Toyota
    • 5.6.1 L4 Autonomous Driving Solutions (1)
    • 5.6.2 L4 Autonomous Driving Solutions (2)
  • 5.7 Volvo
    • 5.7.1 L4 Autonomous Driving Solutions
    • 5.7.2 L4 Autonomous Driving Technologies (1)
    • 5.7.3 L4 Autonomous Driving Technologies (2)
  • 5.8 Other Automakers
    • 5.8.1 L4 Autonomous Driving Solution of Weltmeister
    • 5.8.2 L4 Autonomous Driving Solution of Hongqi
    • 5.8.3 L4 Autonomous Driving Solution of Yutong Bus

6 L4 Autonomous Driving Solutions of Tier 1 Suppliers and Startups

  • 6.1 L4 Technology Development of Chinese and Foreign Suppliers
    • 6.1.1 Chinese L4 Autonomous Driving Solutions for Passenger Cars (1)
    • 6.1.2 Chinese L4 Autonomous Driving Solutions for Passenger Cars (2)
    • 6.1.3 Chinese L4 Autonomous Driving Solutions for Passenger Cars (3)
    • 6.1.4 Chinese L4 Autonomous Driving Solutions for Passenger Cars: Pony.ai (1)
    • 6.1.5 Chinese L4 Autonomous Driving Solutions for Passenger Cars: Pony.ai (2)
    • 6.1.6 Chinese L4 Autonomous Driving Solutions for Passenger Cars: Baidu (1)
    • 6.1.7 Chinese L4 Autonomous Driving Solutions for Passenger Cars: Baidu (2)
    • 6.1.8 Chinese L4 Autonomous Driving Solutions for Passenger Cars: Baidu (3)
    • 6.1.9 Chinese L4 Autonomous Driving Solutions for Passenger Cars: Idriverplus
    • 6.1.10 Chinese L4 Autonomous Driving Solutions for Passenger Cars: WeRide (1)
    • 6.1.11 Chinese L4 Autonomous Driving Solutions for Passenger Cars WeRide (1)
    • 6.1.12 Chinese L4 Autonomous Driving Solutions for Passenger Cars: AutoX
    • 6.1.13 Chinese L4 Autonomous Driving Solutions for Passenger Cars: Momenta
    • 6.1.14 Chinese L4 Autonomous Driving Solutions for Passenger Cars: Deeproute.ai
    • 6.1.15 Foreign L4 Autonomous Driving Solutions for Passenger Cars
    • 6.1.16 Foreign L4 Autonomous Driving Solutions for Passenger Cars: Waymo
    • 6.1.17 Foreign L4 Autonomous Driving Solutions for Passenger Cars: Cruise
    • 6.1.18 L4 Autonomous Driving Solutions of Major Technology Providers: Commercial Vehicle (1)
    • 6.1.19 L4 Autonomous Driving Solutions of Major Technology Providers: Commercial Vehicle (2)
    • 6.1.20 L4 Autonomous Driving Solutions of Major Technology Providers: Commercial Vehicle (3)
    • 6.1.21 Main L4 Autonomous Driving Solutions for Commercial Vehicles: QCraft (1)
    • 6.1.22 Main L4 Autonomous Driving Solutions for Commercial Vehicles: QCraft (2)
    • 6.1.23 Main L4 Autonomous Driving Solutions for Commercial Vehicles: Inceptio Technology (1)
    • 6.1.24 Main L4 Autonomous Driving Solutions for Commercial Vehicles: Inceptio Technology (2)
    • 6.1.25 L4 Autonomous Driving Solutions of Major Technology Providers: Autonomous Delivery
  • 6.2 Waymo
    • 6.2.1 Profile
    • 6.2.2 Layout of Autonomous Driving Business
    • 6.2.3 L4 Autonomous Driving System: Waymo Driver
    • 6.2.4 L4 Autonomous Driving Technologies (I): Perception
    • 6.2.5 L4 Autonomous Driving Technologies (II): Architecture
    • 6.2.6 L4 Autonomous Driving Technologies (III): Data Model and Architecture
    • 6.2.7 L4 Autonomous Driving Technologies (IV): Simulation
    • 6.2.8 L4 Autonomous Driving Technologies (V): Planning
    • 6.2.9 L4 Autonomous Driving Technologies (VI): Computing Platform
    • 6.2.10 L4 Products (I): Waymo One (1)
    • 6.2.11 L4 Products (I): Waymo One (2)
    • 6.2.12 L4 Products (II): Waymo Via
  • 6.3 Cruise
    • 6.3.1 Profile
    • 6.3.2 Autonomous Vehicle: Hardware
    • 6.3.3 Autonomous Vehicle: Software Algorithms and Chips (1)
    • 6.3.4 Autonomous Vehicle: Software Algorithms and Chips (2)
    • 6.3.5 Autonomous Driving Technologies (I)
    • 6.3.6 Autonomous Driving Technologies (II)
    • 6.3.7 Autonomous Driving Technologies (III)
    • 6.3.8 L4 Products (I)
    • 6.3.9 L4 Products (II)
    • 6.3.10 L4 Products (III)
  • 6.4 Aurora
    • 6.4.1 Profile
    • 6.4.2 Autonomous Driving System: Aurora Driver Platform (1)
    • 6.4.3 Autonomous Driving System: Aurora Driver Platform (2)
    • 6.4.4 Autonomous Driving Technology: Perception and Decision
    • 6.4.5 Layout of L4 Autonomous Driving
  • 6.5 Navya
    • 6.5.1 Cooperated with Valeo to Deploy L4 Autonomous Driving
    • 6.5.2 Autonomous Shuttle Business
  • 6.6 Mobileye
    • 6.6.1 L4 Autonomous Driving Service: Mobileye Drive
    • 6.6.2 L4 Autonomous Driving Service: System Design Architecture of Mobileye Drive
    • 6.6.3 Mobileye Plans to Enable the Popularization of Low-cost L4 Autonomous Driving by Independently Developing 4D Imaging Radars
    • 6.6.4 Application Layout of L4 Autonomous Driving
  • 6.7 Valeo
    • 6.7.1 L3 and L3+ Autonomous Driving Solutions
    • 6.7.2 Allocation of Safety Levels of Main ECU and Backup ECU in L3+ Autonomous Driving
  • 6.8 Baidu Apollo
    • 6.8.1 Autonomous Driving Layout
    • 6.8.2 L4 Technologies (I): Security Redundancy
    • 6.8.3 L4 Technologies (II): Computing Platform
    • 6.8.4 L4 Autonomous Driving Systems (I): Apollo Air (1)
    • 6.8.5 L4 Autonomous Driving Systems (I): Apollo Air (2)
    • 6.8.6 L4 Autonomous Driving Systems (II): Apollo Lite
    • 6.8.7 L4 Autonomous Driving Systems (III): Multi-sensor Fusion Autonomous Driving Solution
    • 6.8.8 L3/L4 Synergy
    • 6.8.9 L4 Products (I): Apollo Go (1)
    • 6.8.10 L4 Products (I): Apollo Go (2)
    • 6.8.11 L4 Products (I): Apollo Go (3)
    • 6.8.12 L4 Products (I): Apollo Go (4)
    • 6.8.13 L4 Products (I): Apollo Go (5)
    • 6.8.14 L4 Products (I): Apollo Go (6)
    • 6.8.15 L4 Products (II): 5G Cloud Valeting
    • 6.8.16 L4 Products (III): Autonomous Truck
    • 6.8.17 L4 Products (IV): Automated Valet Parking (AVP)
  • 6.9 Pony.ai
    • 6.9.1 Profile
    • 6.9.2 Persist in Simultaneous R&D of Software and Hardware
    • 6.9.3 Released the New-generation L4 Autonomous Driving System
    • 6.9.4 L4 Autonomous Driving System: Hardware Architecture (1)
    • 6.9.5 L4 Autonomous Driving System: Hardware Architecture (2)
    • 6.9.6 L4 Autonomous Driving System: Computing Unit (1)
    • 6.9.7 L4 Autonomous Driving System: Computing Unit (2)
    • 6.9.8 L4 Autonomous Driving System: Computing Unit (3)
    • 6.9.9 L4 Autonomous Driving System: Data Closed Loop Capability
    • 6.9.10 Cooperation on Application of L4 Autonomous Driving System: SAIC AI LAB
    • 6.9.11 Commercial Application Achievements of L4 Autonomous Driving (1)
    • 6.9.12 Commercial Application Achievements of L4 Autonomous Driving (2)
    • 6.9.13 Implemented Business Model of L4 Autonomous Driving
  • 6.10 WeRide
    • 6.10.1 Profile
    • 6.10.2 Development History of Autonomous Driving Business
    • 6.10.3 Autonomous Driving Platform
    • 6.10.4 To Create A New-generation Autonomous Driving Platform
    • 6.10.5 Core Technology of Autonomous Driving
    • 6.10.6 Autonomous Driving Technologies (I): Data Closed Loop
    • 6.10.7 Autonomous Driving Technologies (II): Redundancy
    • 6.10.8 Autonomous Driving Technologies (III): Algorithm
    • 6.10.9 L4 Products (I): Robotaxi (1)
    • 6.10.10 L4 Products (I): Robotaxi (2)
    • 6.10.11 L4 Products (I): Robotaxi (3)
    • 6.10.12 L4 Products (II): Robobus
    • 6.10.13 L4 Products (III): Robovan
    • 6.10.14 L4 Products (IV): Robo Street Sweeper
  • 6.11 AutoX
    • 6.11.1 Profile
    • 6.11.2 Autonomous Driving Capabilities
    • 6.11.3 Autonomous Driving System: AutoX Gen5
    • 6.11.4 Autonomous Driving Technology: Panoramic Fusion Perception System - xFusion
    • 6.11.5 L4 Product: Robotaxi
  • 6.12 Momenta
    • 6.12.1 Profile
    • 6.12.2 Autonomous Driving Technology Layout
    • 6.12.3 Autonomous Driving Solutions
    • 6.12.4 Autonomous Driving Solutions: Mpilot
    • 6.12.5 Autonomous Driving Solutions: L4 Solution
    • 6.12.6 Strategic Planning of L4 Autonomous Driving
    • 6.12.7 L4 Product: Robotaxi
  • 6.13 Deeproute.ai
    • 6.13.1 Profile
    • 6.13.2 L4 Autonomous Driving Solution
    • 6.13.3 L4 Autonomous Driving Technologies: Multi-sensor Fusion
    • 6.13.4 L4 Autonomous Driving Technologies: Self-developed Reasoning Engine
    • 6.13.5 L4 Products (I): Robotaxi
    • 6.13.6 L4 Products (II): Autonomous Container Truck
  • 6.14 Huawei
    • 6.14.1 Advanced Autonomous Driving System: ADS (1)
    • 6.14.2 Advanced Autonomous Driving System: ADS (2)
    • 6.14.3 L4 Autonomous Driving Technology: Computing Platform
  • 6.15 Haomo.ai
    • 6.15.1 Profile
    • 6.15.2 Passenger Car Autonomous Driving System
    • 6.15.3 Autonomous Vehicle Technologies (I): Data Closed Loop (1)
    • 6.15.4 Autonomous Vehicle Technologies (I): Data Closed Loop (2)
    • 6.15.5 Autonomous Vehicle Technologies (II): Algorithm
    • 6.15.6 Autonomous Vehicle Technologies (III): Computing Platform
    • 6.15.7 L3/L4 Autonomous Driving Planning
    • 6.15.8 L4 Products (I): Autonomous Delivery Vehicle (1)
    • 6.15.9 L4 Products (I): Autonomous Delivery Vehicle (2)
    • 6.15.10 L3/L4 Products (II): Passenger Car
  • 6.16 DeepBlue Technology
    • 6.16.1 Main Products
    • 6.16.2 L4 Product: Panda AI Bus (1)
    • 6.16.3 L4 Product: Panda AI Bus (2)
  • 6.17 Allride.ai
    • 6.17.1 Profile
    • 6.17.2 L4 Autonomous Driving System for Roadside Sensing Only
    • 6.17.3 L4 Products (I): Robotaxi
    • 6.17.4 L4 Products (II): Robobus
  • 6.18 UISEE Technology
    • 6.18.1 Profile
    • 6.18.2 Main Autonomous Driving Products and Solutions
    • 6.18.3 L4 Autonomous Driving Platform: U-Drive
    • 6.18.4 L4 Products (I): Robotaxi
    • 6.18.5 L4 Products (II): Autonomous Logistics
    • 6.18.6 L4 Products (III): Autonomous Delivery (1)
    • 6.18.7 L4 Products (III): Autonomous Delivery (2)
    • 6.18.8 L4 Products (IV): Autonomous Minibus
  • 6.19 Idriverplus
    • 6.19.1 L4 Autonomous Driving Technologies
    • 6.19.2 L4 Autonomous Driving Technology: Data Closed Loop
    • 6.19.3 L4 Products (I): Robotaxi (1)
    • 6.19.4 L4 Products (I): Robotaxi (2)
    • 6.19.5 L4 Products (II): Robobus
  • 6.20 QCraft
    • 6.20.1 Development Strategy for L4 Autonomous Driving
    • 6.20.2 4th-Generation L4 Autonomous Driving Mass Production Solution: DBQ V4
    • 6.20.3 L4 Autonomous Driving Technology Layout
    • 6.20.4 L4 Autonomous Driving Technologies (I): Algorithm (1)
    • 6.20.5 L4 Autonomous Driving Technologies (I): Algorithm (2)
    • 6.20.6 L4 Autonomous Driving Technologies (II): QCraft Matrix
    • 6.20.7 L4 Autonomous Driving Technologies (III): Perception
    • 6.20.8 L4 Products (I): Autonomous Commercial Vehicle
    • 6.20.9 L4 Products (II): Robotaxi
  • 6.21 TuSimple
    • 6.21.1 Profile
    • 6.21.2 Layout of L4 Autonomous Driving Business
    • 6.21.3 Autonomous Driving Technology Providers
    • 6.21.4 Completed Unmanned Tests of L4 Heavy Truck
    • 6.21.5 Autonomous Driving Business Model
  • 6.22 Plus.ai
    • 6.22.1 L4 Autonomous Driving Layout
    • 6.22.2 L4 Autonomous Driving Planning
    • 6.22.3 L4 Autonomous Driving Demonstration
    • 6.22.4 L4 Autonomous Driving System: PlusDrive
  • 6.23 Inceptio Technology
    • 6.23.1 Completed L4 Autonomous Heavy Truck Road Tests
    • 6.23.2 Evolution of Autonomous Driving System
    • 6.23.3 Self-developed Autonomous Driving Technologies (I): Regulation and Control Integration
    • 6.23.4 Self-developed Autonomous Driving Technologies (II): Fuel-saving Algorithm
    • 6.23.5 Self-developed Autonomous Driving Technologies (III): Data Closed Loop
  • 6.24 CiDi
    • 6.24.1 L4 Products (I): Autonomous Mining Truck
    • 6.24.2 L4 Products (II): Non-cabin Autonomous Commercial Vehicle