Table of Content

1 Overview of Autonomous Driving Data Closed Loop
1.1 Three Cornerstones for Development of Autonomous Driving Technology
1.2 What Is Data Closed Loop
1.2.1 Data Collection
1.2.1.1 Real Scene Data Collection
1.2.1.2 Simulation Scene Data Collection
1.2.2 Data Compliance
1.2.2.1 Regulatory Requirements for Data Processing Security
1.2.2.2 Automotive Data Security Technology and Protection System
1.2.3 Automated Data Processing
1.2.4 Algorithms
1.2.4.1 AD Algorithm Trends
1.2.5 Data Annotation and Development
1.2.5.1 TOP 10 Autonomous Driving Data Annotation Providers, 2023
1.2.5.2 Examples of Automatic Annotation System - DataOcean AI
1.2.5.3 Examples of Automatic Annotation System - Tesla
1.2.5.4 3D Point Cloud Technology
1.2.5.5 3D Point Cloud Image Annotation
1.2.5.6 2D/3D Fusion Annotation
1.2.5.7 3D Point Cloud Semantic Segmentation Annotation
1.2.5.8 3D Point Cloud Continuous Frame Annotation


2 Application of Foundation Model in Autonomous Driving Data Closed Loop
2.1 Foundation Model Based on Neural Network
2.2 Post-fusion, Feature-level Fusion and Pre-fusion
2.3 BEV+Transformer Has Become the Mainstream Solution at Present
2.3.1 BEV+Transformer Significantly Improves the Feature-level Fusion Effect
2.3.2 BEV+Transformer Helps City NOA to Get Rid of Maps
2.3.3 Light Map Data Closed Loop Solution Example 1
2.3.3 Light Map Data Closed Loop Solution Example 2
2.3.4 BEV Is Upgraded to Network Occupation (Vision + Radar) to Be Free from LiDAR
2.3.5 Multi-sensor Fusion Route: Necessity of LiDAR
2.3.6 Software 2.0 Drives Autonomous Driving Algorithms to Head in the End-to-End Direction
2.4 Overview of Foundation Models Enabling Autonomous Driving
2.4.1 Foundation Models Facilitate Data Mining and Automatic Annotation
2.4.2 Foundation Model + Small Model
2.5 Foundation Model Capability Building and Tool Chain
2.5.1 Examples of Foundation Model Capability Output – Microsoft
2.5.2 Examples of Foundation Model Capability Output – Nvidia
2.6 Overview of Foundation Model Layout in Automotive Industry
2.7 AI Foundation Model Accelerates Automotive GPT
2.8 AI Foundation Model Accelerates Implementation of City NOA


3 Application of Cloud Platform in Autonomous Driving Data Closed Loop
3.1 Roles of Cloud Platform in Data Closed Loop (1)
3.2 Roles of Cloud Platform in Data Closed Loop (2)
3.3 Roles of Cloud Platform in Data Closed Loop (3)
3.4 List of Autonomous Driving Cloud Supercomputing Centers in China
3.5 Typical: AWS Cloud Platform Data Closed Loop
3.6 Typical: Volcengine Data Closed Loop Cloud Service Platform
3.7 Typical: Alibaba Cloud Data Closed Loop


4 Typical Simulation Companies in Autonomous Driving Data Closed Loop
4.1 The International Organization for the Standardization of Autonomous Driving Simulation
4.2 The Localization of ASAM Standards in China
4.3 Domains of ASAM Standards
4.4 Foreign Vehicle Dynamics Benchmarking Companies
4.5 Foreign Traffic Scene Simulation Benchmarking Companies
4.6 Foreign Virtual Scene Simulation Benchmarking Companies
4.7 Foreign Sensor Simulation Benchmarking Companies
4.8 Foreign Hardware-in-the-Loop Simulation Benchmarking Companies
4.9 Dynamics of Autonomous Driving Simulation Platforms in China
4.10 Typical Company: IAE
4.10.1 Profile
4.10.2 X-IN-LOOP? Simulation Test Technology System
4.10.3 Vision
4.11 Typical Company: PanoSim
4.11.1 Profile
4.11.2 Autonomous Driving Simulation Test Platform
4.11.2 Product Composition and Function
4.11.2 Products and Features
4.11.3 Application Scenarios of xPilot
4.12 Typical Company: 51WORLD
4.12.1 Profile
4.12.2 Simulation Platform 51Sim-One
4.12.3 Simulation Platform 51Sim-One: Cloud Simulation
4.13 Typical Company: Cognata
4.13.1 Profile
4.13.2 Overview of Autonomous Driving Simulation
4.14 Typical Company: VI-grade
4.14.1 Profile
4.14.2 Simulator Series
4.14.3 AutoHawk Platform
4.14.4 Simulator Third-party Software Tools/Interfaces
4.14.5 Customers
4.14.5.1 Customer Cases


5 Data Closed Loop Layout of Typical OEMs
5.1 BYD
5.1.1 Data Closed Loop System Construction
5.1.2 Big Data Accumulation
5.1.3 Data-driven Foundation Model R&D Route
5.1.4 R&D of Data-driven Perception Model
5.1.5 Multi-camera BEV Object Perception Model
5.1.6 Transformer-based Multi-sensor Multi-task Fusion Perception
5.1.7 Truth-value System Based on Foundation Model
5.1.8 Vehicle Computing Platform
5.1.9 R&D of Decision and Planning Foundation Models
5.2 SAIC
5.2.1 SAIC’s "157X" Technology Innovation System
5.2.2 SAIC’s Data Closed Loop Solution
5.2.3 Z-ONE Galaxy Intelligent Driving Full-stack Solution
5.2.4 Z-ONE Galaxy Intelligent Driving Computing Platform
5.2.5 Z-ONE Galaxy Intelligent Driving Computing Platform - Cloud-Pipe-Terminal Data Closed Loop
5.2.6 Rising Auto/IM Motors - PP-CEM Intelligent Driving System
5.2.7 Rising Auto/IM Motors - Autonomous Driving Data Closed Loop
5.2.8 Rising Auto/IM Motors - Autonomous Driving Data Mining & Processing
5.2.9 Rising Auto’s Fully Integrated Advanced Intelligent Driving System
5.2.10 IM Motors’ D.L.P. Artificial Intelligence Model
5.2.11 NOA Performance of IM Motors
5.3 Changan Automobile
5.3.1 New Technology Architecture
5.3.2 New Technology Architecture – Cloud Platform
5.3.3 New Technology Architecture – Data Closed Loop
5.4 Geely
5.4.1 Xingrui Intelligent Computing Center
5.4.2 Intelligent Driving Cloud Data Factory
5.4.3 Intelligent Driving Closed Loop System
5.4.4 ROBO Galaxy Toolchain Process Solution
5.4.5 Data Production Modes
5.4.6 Underlying Software Abstraction of Self-developed Algorithms
5.4.7 Intelligent driving Design Based on Self-developed SOA
5.4.8 Fully Self-developed Cockpit Operating System
5.4.9 Global Platform Operation System
5.5 Xpeng
5.5.1 Fuyao Intelligent Computing Center
5.5.2 XNet Deep Visual Neural Network
5.5.3 All-scenario Intelligent Driving Assistance System - XNGP
5.5.4 Closed Loop Data Iteration System of XNGP
5.5.5 SEPA2.0 Fuyao Architecture
5.6 Li Auto
5.6.1 Progress in Intelligent Computing Center
5.6.2 AD MAX3.0 Algorithm Training
5.6.3 Vehicle Model Planning
5.7 Tesla
5.7.1 Progress in Dojo Supercomputer Platform
5.7.2 Autonomous Driving Data Closed Loop System
5.7.3 Data Engine Data Center
5.7.4 Data Annotation
5.7.5 Iteration History of Autonomous Driving Algorithms
5.7.6 Intelligent Driving AP/EAP/FSD
5.7.7 4D Radar


6 Data Closed Loop Layout of Typical Autonomous Driving Providers
6.1 Baidu
6.1.1 Autonomous Driving Data Closed Loop Solution
6.1.2 Road Data Collection Service
6.1.3 Autonomous Driving Data Processing Compliance Service
6.1.4 Data Annotation Service
6.1.5 Intelligent Driving Data Management Platform
6.1.6 Simulation Test Service
6.1.7 Autonomous Driving Toolchain
6.1.8 ERNIE Bot Foundation Model
6.2 Huawei
6.2.1 "1+3+M+N" Solution
6.2.2 Huawei Cloud ModelArts Platform
6.2.3 "Octopus" Platform
6.2.4 ADS 2.0 Algorithm
6.2.5 Progress in ADS 2.0
6.2.6 Released the "Cloud-Edge-Terminal" Automatic Data Closed Loop System
6.2.7 Huawei Cloud Empowers Automakers
6.3 Freetech
6.3.1 ODIN Digital Intelligence Base
6.3.2 Data Closed Loop System
6.3.3 Autonomous Driving Software Platform - FAS
6.3.4 Development Route of Advanced Autonomous Driving Solutions
6.3.5 Advanced Domain Controller Solution
6.3.6 Upgraded Data Storage Platform
6.4 MAXIEYE
6.4.1 Profile and Development History
6.4.2 MonoToGo Solution
6.4.3 Data Closed Loop System
6.4.4 MAXIPILOT? Intelligent Driving Platform Solution
6.4.5 MAXIPILOT? 1.0/2.0/3.0
6.4.6 Major Customers and Partners
6.5 Nullmax
6.5.1 Profile and Development History
6.5.2 Self-developed Full-stack Autonomous Driving Brain - Max
6.5.3 Data Closed Loop
6.5.4 BEV-AI Architecture
6.5.5 BEV 3D Object Detection Algorithm
6.5.6 Driving-parking Integrated Solution - MaxDrive
6.5.7 Driving-parking Integrated Low-compute Platform Solution 4.0
6.5.8 Driving-parking Integrated Mid-to-high-compute Platform Solution 4.0
6.5.9 Partners
6.6 Pony.ai
6.6.1 Progress in Unmanned Autonomous Driving
6.6.2 Passenger Car Intelligent Driving Business
6.6.3 Intelligent Driving Solution - Shitu
6.6.4 Shitu’s New Planning and Control Algorithm Architecture - NLPP
6.6.5 Self-developed Domain Controller - Fangzai
6.6.6 Data Closed Loop Toolchain – Cangqiong
6.7 Momenta
6.7.1 Profile
6.7.2 Core Technologies
6.7.3 Autonomous Driving Solutions
6.7.4 Data Closed Loop Automation
6.7.5 “Mapless” Intelligent Driving Algorithm Solution
6.7.6 Mpilot Pro Medium-configured Solution for Mass Production
6.7.7 Software-hardware Integration Layout
6.7.8 Partners


7 Typical Data Closed Loop Solution Providers
7.1 Haomo.ai
7.1.1 Progress
7.1.2 MANA OASIS
7.1.3 MANA OASIS Upgrade
7.1.4 Introduction to DriveGPT
7.1.5 DriveGPT Training
7.1.6 HPilot 3.0 & City NOH
7.1.7 Ecosystem Partners
7.2 SenseTime
7.2.1 SenseAuto - Cockpit-driving-cloud System
7.2.2 SenseAuto - Data Closed Loop Capability
7.2.3 SenseAuto - Perception-decision Integration
7.2.4 Foundation Model R&D Capabilities
7.2.5 SenseNova Foundation Model System
7.2.6 General Foundation Model - "INTERN 2.5"
7.2.7 Data Filtering Engine
7.2.8 Automatic Annotation of Ultra Large Models
7.2.9 Production Process of Vehicle Small Models
7.3 EXCEEDDATA
7.3.1 Profile
7.3.2 Data Base
7.3.3 Full-stack Data-driven Capabilities
7.3.4 Vehicle-cloud Data Driven Panorama
7.3.5 Vehicle-cloud Isomorphic Computing
7.3.6 Intelligent Driving Data Collection Tool
7.3.7 Intelligent Driving Data Transmission
7.3.8 Shadow Mode Solution
7.4 LiangDao Intelligence
7.4.1 Profile
7.4.2 Development History
7.4.3 Products and Services (1)
7.4.4 Products and Services (2)
7.4.5 Smart City Solutions
7.4.6 Data Closed Loop
7.4.7 Data Factory Solution
7.4.8 Data Collection Service Co-developed with ZhongOu Intelligent Technology
7.4.9 Partners
7.5 JueFX Technology
7.5.1 "Perception-Decision-Data" Closed Loop Capability
7.5.2 Perception Foundation Model Algorithm Architecture
7.5.3 High-precision Fusion Positioning Architecture
7.5.4 City NOA Intelligent Driving Solution
7.5.5 Highway NOA Map & Positioning Solution for Mass Production
7.5.6 Dynamics in Cooperation
7.6 Rhino
7.6.1 Profile
7.6.2 Data Closed Loop System
7.7 Horizon Robotics
7.7.1 Journey 2/3/5
7.7.2 Highlights of Journey? 5
7.7.3 BEV Time-space Fusion Architecture on Journey? 5
7.7.4 BPU Intelligent Computing Architecture
7.7.5 Intelligent Computing Development Tools
7.7.6 AIDI? Development Cloud Infrastructure
7.7.7 Ecosystem Cooperation
7.8 Black Sesame Technologies
7.8.1 Data Closed Loop Solution
7.8.2 BEV Framework
7.8.3 Data Collection System
7.8.4 Automatic Annotation of 3D Data
7.8.5 Latest Cooperation Cases
7.9 Kunyi Electronics
7.9.1 Profile
7.9.2 Products and Solutions
7.9.3 Autonomous Driving Data Processing Workstation
7.9.3 Remote Data Collection Recording and Analysis Solution
7.9.4 Intelligent Driving Data Reinjection System
7.9.4 Road Collection and Reinjection Function
7.9.5 Hardware-in-the-loop (HIL) Test System
7.9.6 VGATE Series Vehicle Bus Recorder
7.9.7 Automotive Ethernet Module
7.9.8 Controller Analysis and Calibration Software - VCAR MCD
7.9.8 Bus Simulation Analysis Software - VCAR DAS
7.9.9 Distribution of Customers