중국의 L3 및 L4 자율주행과 스타트업(2025년)

Robotaxi steps towards scaling during 2026-2030, L3 Personal Vehicles Open New Commercial Opportunities

ResearchInChina categorizes L3-L4 autonomous driving into seven application scenarios based on the operational environment from "closed -> semi-closed -> open" and the driving speed of autonomous vehicles: Robotaxi, L3-L4 personal vehicles, unmanned delivery, unmanned shuttles, port autonomous driving, mining autonomous driving, and long-haul logistics autonomous driving. This report will focus on the Robotaxi and L3-L4 personal vehicle scenarios.

After the accelerated consolidation of Robotaxi market in 2023-2024, leading Robotaxi players are gradually transitioning from unmanned demonstration operations to commercial operations. Many companies view 2026 as the first year of large-scale development for Robotaxi, with plans for mass deployment. With Beijing and Wuhan officially announcing the launch of L3 autonomous private cars in 2025, setting the first benchmark for the domestic intelligent driving industry, major automakers are accelerating their layouts, targeting 2025-2027 as the critical phase for mass production of L3 autonomous vehicles. Among them, Li Auto plans to achieve supervised L3 intelligent driving by 2025.

L3-L4 Autonomous Driving Application Scenario 1: Robotaxi Market

Robotaxi Trend 1: The year of 2023-2024 is the Adjustment Period for Robotaxi Industry Development

Since Google launched its autonomous vehicle project in 2009, autonomous driving technology has gradually entered the public eye, sparking widespread global attention and investment. According to the latest data from the California DMV, the total test mileage of autonomous vehicles in California in 2024 was 4.5 million miles, a 50% decrease from 2023. The number of test permits with human safety drivers has significantly decreased, with only 31 companies holding such permits, but only 11 actually conducted public road tests in 2024, and 9 have stopped testing and exited the program. In terms of unmanned testing, only 6 companies have obtained permits, including AutoX, WeRide, Waymo, Zoox, and Nuro. This change reflects that after more than a decade of technological development, business model exploration, and market trial and error, the Robotaxi industry has entered a critical adjustment period in 2023-2024. This phase is not only a test of technological and market maturity but also a watershed for the survival of the fittest within the industry.

In 2023-2024, some L4 autonomous driving companies were forced to exit or make strategic adjustments due to financial pressures. These companies were mostly early entrants in the market, focusing on technological breakthroughs but failing to achieve self-sufficiency due to unclear business models or poor market expansion. In 2024, Cruise announced its dissolution, and in February 2024, Tier 1 giant Aptiv optimized its layout by reducing its stake in the autonomous driving company Motional, focusing on its core strengths.

During the industry adjustment period, Robotaxi sector presented a mixed picture. Capital markets became more cautious, with funds gradually concentrating on autonomous driving companies that have clear advantages in L4 technology and have formed initial business model loops.

In July 2024, Waymo secured a $5 billion strategic investment, further solidifying its leading position in the Robotaxi field. Meanwhile, WeRide and Pony.ai successfully listed on NASDAQ, becoming heavyweight players in the industry. These listings not only brought more financial support to the companies themselves but also injected new vitality into the entire industry, signaling that the Robotaxi sector is gradually moving towards a mature development stage after the adjustment period.

Robotaxi Trend 2: Tech-Driven Autonomous Driving Companies Lead in Robotaxi Operations including promotion speed, operation coverage and vehicle deployment scale

There are three main types of players in the Robotaxi sector:

1) Traditional automakers like SAIC and GAC, and new carmakers like Tesla and XPeng. Automakers are entering the Robotaxi space to seize the future opportunity of unmanned mobility.

2) Mobility platforms like Ruqi and Caocao. These platforms enter the Robotaxi market through two approaches: one focuses on platform construction and operations, collaborating with automakers and autonomous driving algorithm providers to jointly advance autonomous driving services. They use a "mixed operations" model for dispatching, creating an open mobility platform. The other is a "full-stack" development model, where the platform independently develops autonomous vehicles, platform technology, and algorithm systems, handling all aspects of operations. This approach gives the platform full control over R&D, deployment, and maintenance, allowing for better resource integration, system optimization, and rapid iteration.

3) L4 autonomous driving solution providers and Robotaxi operators like Waymo, Zoox, Baidu Apollo, Pony.ai, WeRide, and AutoX. Facing commercialization challenges, these companies face technical, cost, and policy constraints in scaling up, resulting in insufficient data and limited cost reductions, so adopting strategies like "downgrading to L2++" for mass production and "scenario progression" to accumulate commercialization experience, alleviate financial pressure, and reuse more road data.

In the commercialization of Robotaxi, tech-driven autonomous driving companies (the third type of player) like Waymo, Baidu Apollo, Pony.ai, and WeRide are leading in terms of commercialization speed, operational coverage, and vehicle deployment scale compared to traditional automakers (the first type) and mobility platforms (the second type).

Japanese automakers are taking a different approach by partnering with strong L4 autonomous driving system providers to accelerate their Robotaxi layout, especially in the promising Chinese market. For example, Nissan has partnered with L4 autonomous driving system provider WeRide in China, focusing on Suzhou High-Speed Rail New City Intelligent Connected Vehicle Demonstration Zone. This project has successfully entered the commercialization pilot phase, starting charging services in December 2024.

In contrast, German automakers are currently focusing on R&D and market promotion of L3/L4 personal passenger car autonomous driving systems, showing less enthusiasm for Robotaxi. Markus Verge, CTO of Mercedes-Benz, stated that the company's core focus is not on entering the Robotaxi field but on L3/L4 autonomous driving system R&D and promotion.

Among Chinese domestic brands, SAIC, Changan, and Chery have entered the Robotaxi demonstration operation phase, with deployment scales not exceeding 100 vehicles. SAIC launched its Robotaxi business in 2021 and was approved for unmanned demonstration applications in 2024. Currently in the demonstration application phase, it does not charge users, with nearly 100 Robotaxi vehicles deployed.

Robotaxi Trend 3: in 2026-2030, Robotaxi will enter the large-scale commercial development phase, with 2026 as the first year of scaling

Zhang Ning, Vice President of Pony.ai, estimates that deploying thousands of Robotaxi vehicles is necessary to achieve operational breakeven. Pony.ai plans to deploy a thousand Robotaxi vehicles in 2025 and double that number in 2026. Additionally, Pony.ai is accelerating the global landing of its L4 business through strategic partnerships with automakers, mobility platforms, and autonomous driving technology companies, having already entered markets in South Korea, Luxembourg, and Singapore. WeRide plans to achieve large-scale Robotaxi commercialization by 2026, aiming to significantly reduce per-kilometer mobility costs through scale operations, making them lower than traditional taxis.

Tesla will launch Cybercab in 2026, priced under $30,000, equipped with an "end-to-end" large model algorithm, and committed to a mapless solution, with operations expected to start in the second half of 2026. XPeng Motors announced it will launch a new generation of competitive Robotaxi in 2026.

In addition to new carmakers, traditional domestic brands like Geely are focusing on building an open operational platform in the domestic market, integrating Robotaxi from various brands through its Caocao Mobility platform, and plans to launch a customized Geely-branded Robotaxi model in 2026. In the international market, its Zeekr brand has partnered with Waymo, planning to deploy related products in the U.S. market by 2025. GAC plans to deploy a thousand Robotaxi vehicles with Pony.ai by 2025, while its joint venture with Didi, Andi Technology, is also planning to start production in 2025.

Robotaxi Trend 4: China and the U.S. Lead in Robotaxi, with Leading Companies Moving Towards Fully Unmanned Robotaxi Demonstration Applications

For Robotaxi companies, removing safety drivers is a key step towards profitability. The salaries, benefits, and training costs of safety drivers are significant components of Robotaxi operational costs. In first-tier cities, an experienced safety driver's annual salary can range from 100,000 to 200,000 yuan. For a Robotaxi fleet with hundreds or even thousands of vehicles, the annual human cost can reach tens or even hundreds of millions of yuan. Removing safety drivers can significantly reduce these costs, improving the company's profitability. Additionally, removing safety drivers can increase the actual operational time and utilization rate of vehicles. To accelerate Robotaxi development, cities like Beijing, Guangzhou, Shenzhen, Wuhan, and Chongqing have successively released policies for unmanned commercial pilot programs.

L4 Autonomous Driving Application Scenario 2: L3-L4 Personal Passenger Car Market

Trend 1: The First Year of L3 Autonomous Driving Commercialization Begins, with Multiple Local Governments Introducing Supportive Policies to Boost Industry Development

In December 2024, Beijing released "Beijing Autonomous Vehicle Regulations," clarifying expansion of autonomous driving applications to "personal vehicles" and set to take effect on April 1, 2025. This regulation provides a clear legal basis for the application of L3 autonomous driving technology in personal vehicles, eliminating legal and regulatory uncertainties, offering a stable policy environment for automakers and related companies. In the same month, Wuhan released the "Wuhan Autonomous Vehicle Regulations," supporting the demonstration and commercial pilot applications of intelligent connected vehicles in smart passenger cars, meaning consumers will have more opportunities to experience the convenience of L3 and above autonomous driving technologies.

L3 Autonomous Driving Technology Enters a New Phase, with Legal Support as a Key Driving Force

Trend 2: 2025 Marks the First Year of L3 Autonomous Driving Commercialization, with Automakers Preparing for L3 Autonomous Driving, Targeting 2025-2027 as the Key Phase for Mass Production

L3 Autonomous Driving Technology is About to Enter a Market Explosion, with Major Automakers Layout to Seize Market Opportunities

XPeng has set 2025 as the key milestone for mass production of L3 autonomous driving in personal vehicles. Li Auto also aims to achieve L3 autonomous driving mass production by 2025. Tesla, as a global leader in autonomous driving technology, plans to accelerate the landing of its FSD unsupervised version in 2025, potentially triggering new changes in the L3 market.

SAIC's IM Motors and GAC both view 2025 as a critical year for L3 autonomous driving mass production. GAC further plans to achieve L3+ autonomous driving mass production by 2026 and move towards L4 by 2027. Geely, through its Zeekr brand, obtained L3 pilot qualifications in Shanghai and Hangzhou in 2023, achieving L3 in large-scale urban scenarios. Nissan plans to launch ProPILOT 3.0 with L3 functionality by 2027 and ProPILOT 4.0 with L4 functionality by 2030. BMW obtained L3 test licenses for Shanghai's elevated roads in 2023 and has already delivered L3-capable vehicles in Germany, laying a solid foundation for its subsequent mass production plans.

Table of Contents

1 L3/L4 Autonomous Driving Policies, Regulations, and Standards

• 1.1 Autonomous Driving Classification and Standardization
• SAE Autonomous Driving Classification Standards (1)
• SAE Autonomous Driving Classification Standards (2)
• China's "Automotive Driving Automation Classification" (GB/T 40429-2021) Implemented
• China's "Automotive Driving Automation Classification": L3/L4 Definitions
• China's "Automotive Driving Automation Classification": Chinese Standards Strengthen L3 Safety Requirements
• ISO TC22 ADAG Working Group
• ISO TC22/SC32/WG8 Working Group
• ISO WP29 United Nations World Forum for Harmonization of Vehicle Regulations
• ISO's First L4 Autonomous Driving System International Safety Standard: ISO 22737
• ISO 22737: L4 LSAD (Low-Speed Autonomous Driving) System Architecture
• 1.2 China's Autonomous Driving Policies and Regulations
• China's L3/L4 Autonomous Driving Regulations: Summary
• China's L3/L4 Autonomous Driving Regulations: "Notice from Four Ministries on Conducting Pilot Programs for Intelligent Connected Vehicle Access and Road Travel"
• China's L3/L4 Autonomous Driving Regulations: Ministry of Transport Issues "Autonomous Vehicle Transport Safety Service Guidelines (Trial)"
• 1.3 Global Autonomous Driving Policies and Regulations
• Global Autonomous Driving Industry Sees Substantial Policy Promotion
• Global L3/L4 Autonomous Driving Regulations: Summary
• Global L3/L4 Autonomous Driving Regulations: Japan's "Road Traffic Law" Allows L4 Autonomous Vehicles and Robots on Roads
• Global L3/L4 Autonomous Driving Regulations: Japan's Autonomous Driving Environment Construction Measures
• Global L3/L4 Autonomous Driving Regulations: Japan's Autonomous Driving Development Goals
• Global L3/L4 Autonomous Driving Regulations: Japan's RoAD to the L4 Project
• U. S. Plans to Ban Chinese Software in Autonomous Vehicles

2 L3/L4 Autonomous Driving Application Scenarios

• 2.1 L3/L4 Autonomous Driving Business Model Analysis
• Commercial Value of L3/L4 High-Level Autonomous Driving
• Social Value of L3/L4 High-Level Autonomous Driving
• Seven Major Application Scenarios for L3/L4 High-Level Autonomous Vehicles
• L4 Autonomous Driving Commercialization in Limited Scenarios and Related Companies
• Application Timeline and Market Size of L4 Autonomous Driving Major Scenarios Commercial Scale
• L2-L5 Autonomous Driving Penetration Rate in China and Global Markets, 2025-2035E
• China Robotaxi Market Size,2025-2035E
• L4 Commercialization Landing Model 1: L4 Multi-Scenario Layout
• L4 Commercialization Landing Model 2: L4 and L2++ Dual-Track Development
• L4 Commercialization Landing Model 3: Technology Downgrading from L4 to L2++, Startups Accelerating L2++ Mass Production Landing
• 2.2 L4 Application Scenario - Robotaxi
• Robotaxi Trend 1
• Robotaxi Trend 2
• Robotaxi Trend 3
• Three Types of Players in the Robotaxi Industry
• Robotaxi 2024: Summary of Global Automakers' "Unmanned Driving" Layout Progress
• Three Operational Models Adopted by Global Automakers in Robotaxi Layout
• Global Major Automakers' Robotaxi Layout in 2024: Layout Methods, Operational Models, Development Stages, and Vehicle Configurations Comparison (1)
• Global Major Automakers' Robotaxi Layout in 2024: Layout Methods, Operational Models, Development Stages, and Vehicle Configurations Comparison (2)
• Foreign Leading Robotaxi Operators' Layout in 2024: Layout Methods, Operational Models, Development Stages, and Vehicle Configurations Comparison
• Domestic Leading Robotaxi Operators' Layout in 2024: Layout Methods, Operational Models, Development Stages, and Vehicle Configurations Comparison
• Current Development Stage Analysis of China's Robotaxi Market
• Licenses and Qualifications Required for China's Robotaxi Market to Transition from Technical Routine Testing to Commercial Model Verification
• Domestic Policy Pilot Zones Land In-Vehicle Unmanned Commercial Pilot Policies
• Main "Iron Triangle" Model Adopted by China's Robotaxi Market Players
• Summary of "Iron Triangle" Model Players in the Robotaxi Market (1)
• Summary of "Iron Triangle" Model Players in the Robotaxi Market (2)
• China Robotaxi Ownership, 2024-2027E
• Single Vehicle Profit Model: Achieving Single Vehicle Profit Breakeven by 2027
• Expert Opinions on Robotaxi Scaled Landing
• 2.3 L3/L4 Personal Passenger Car Market
• The First Year of L3 Autonomous Driving Commercialization Begins, with Three Local Governments Introducing Supportive Policies to Boost Industry Development
• Multiple Automakers Preparing for L3 Autonomous Driving, Targeting 2025-2027 as the Key Phase for Mass Production
• Domestic Automakers with L3 Autonomous Driving Road Test Licenses
• End-to-End Large Model Mass Production Landing: L3-L4 Autonomous Driving Will Accelerate
• Starting from 2024, Multiple Automakers Accelerate AI Layput, Officially Entering a New Era of AI Deep Empowerment in Automotive Industry
• Comparison of L3/L4 Autonomous Driving Product Planning of New Car Makers
• Comparison of L3/L4 Autonomous Driving Product Planning of Domestic Leading Automakers
• Comparison of L3/L4 Autonomous Driving Product Planning of German and Japanese Leading Automakers
• 2.4 L4 Application Scenario - Unmanned Shuttles
• The Commercial Value of Unmanned Shuttles and Five Typical Application Scenarios

2024 Sees 20 Vehicle-Road-Cloud Integration Pilot Cities, Accelerating Unmanned Shuttle Demonstration Applications

• Targeted Policy Regulations Release Further Accelerate Unmanned Shuttle Landing
• Key Players in Domestic Low-Speed Unmanned Shuttle Scenarios 1: L4 Autonomous Driving System Providers (1)
• Key Players in Domestic Low-Speed Unmanned Shuttle Scenarios 1: L4 Autonomous Driving System Providers (2)
• Key Players in Domestic Low-Speed Unmanned Shuttle Scenarios 2: OEMs
• Unmanned Shuttle Products: WeRide Autonomous Minibus
• Unmanned Shuttle Products: PIX Robobus 2.0
• Unmanned Shuttle Products: Qcraft Dragon Boat Series
• Commercial Operation of RoboBus: WeRide officially Launched Commercial Charging Operation in Guangzhou
• Unmanned Shuttle Market Size Forecast
• Layout of Some Unmanned Shuttle Players
• 2.5 L4 Application Scenario - Unmanned Delivery
• "Last Mile" Transformation: Rise of Unmanned Delivery
• National Policies Encourage the Development of Unmanned Delivery Vehicles to Effectively Reduce Social Logistics Costs
• Development Trend 1: Local Administrative Rules Are Released Intensively, Opening the "Access" Door for On-road Use of Unmanned Delivery
• Trend 2: Innovation Cities Show Significant Leader Agglomeration Effects, and Multiple Industries Actively Expand into Lower-Tier Markets
• Experts' Opinions on the Development of the L4 Unmanned Delivery Vehicle Market
• Chinese Outdoor Unmanned Delivery Vehicle Market Size Forecast
• Status Quo and Industry Chain of Unmanned Delivery
• Major Players Deploying Unmanned Delivery Vehicle Products (1): Meituan
• Major Players Deploying Unmanned Delivery Vehicle Products (2): Cainiao
• Major Players Deploying Unmanned Delivery Vehicle Products (3): Haomo.ai
• Major Players Deploying Unmanned Delivery Vehicle Products (4): Neolix
• Major Players Deploying Unmanned Delivery Vehicle Products (5): Rino.ai
• Major Players Deploying Unmanned Delivery Vehicle Products (6): Profile of ZELOS
• Major Players Deploying Unmanned Delivery Vehicle Products (6): Product Matrix and Parameters of ZELOS
• Major Players Deploying Unmanned Delivery Vehicle Products (7): Go Further.AI
• Key Player 1: Comparison of Commercial Operation Progress between Suppliers of L4 Autonomous Driving Systems for Unmanned Delivery
• Key Player 2: Comparison of Unmanned Delivery Vehicle Commercial Operation Progress between Internet Scenario Players
• Key Player 3: Comparison of Unmanned Delivery Vehicle Commercial Operation Progress between Logistics and Courier Scenario Players
• Unmanned Delivery Business Models
• Focus of Unmanned Delivery Commercialization (1)
• Focus of Unmanned Delivery Commercialization (2)
• 2.6 L4 Application Scenario - Autonomous Trucks
• Autonomous Trucks Face Development Bottlenecks
• Competitive Landscape of L3+/L4 Autonomous Truck System Suppliers
• Technology Routes for Autonomous Truck Development
• Autonomous Truck Business Models: Mine Scenario
• Autonomous Truck Business Models: Port Scenario
• Commercial Application Solutions for Autonomous Trucks
• Key Players in the Foreign Autonomous Truck Market
• Player 1 in Chinese Autonomous Truck Market: Autonomous Truck Solution Providers (1)
• Player 1 in Chinese Autonomous Truck Market: Autonomous Truck Solution Providers (2)
• Player 2 in Chinese Autonomous Truck Market: Traditional Heavy Truck Companies
• Player 3 in Chinese Autonomous Truck Market: Emerging Truck Manufacturers
• Comparison between Major L4 Autonomous Truck Suppliers
• RoboTruck Solutions
• RoboTruck Closed Scenario Application Cases
• Status Quo of China's Autonomous Truck Market Segments - Port
• Status Quo of China's Autonomous Truck Market Segments - Mine
• Status Quo of China's Autonomous Truck Market Segments - Park Logistics
• China's Autonomous Truck Market Size Forecast

3 Key Technologies for Mass Production of L4 Autonomous Driving

• 3.1 Key Technologies for L4 Autonomous Driving: Algorithms
• L4 Autonomous Driving Requires Higher Computing Power (1)
• L4 Autonomous Driving Requires Higher Computing Power (2)
• Evolution of Autonomous Driving Algorithms
• Autonomous Driving Algorithms: Modular Algorithms
• Autonomous Driving Algorithms: End-to-End Foundation Model Algorithms
• Evolution of Foundation Model Algorithms for Autonomous Driving
• Application of Foundation Models Accelerates the Implementation of L3/L4 Autonomous Driving
• Comparison of End-to-End System Solution Layout between ADAS Tier1s (1)
• Comparison of End-to-End System Solution Layout between ADAS Tier1s (2)
• Comparison of End-to-End System Solution Layout between Other Autonomous Driving Companies
• Comparison of End-to-End System Solution Layout between OEMs (1)
• Comparison of End-to-End System Solution Layout between OEMs (2)
• 3.2 Key Technologies for L4 Autonomous Driving: Data Loop
• High-Level Autonomous Driving Evolves Towards Data-Centric Approach
• Importance of Data Loop for L4 Autonomous Driving
• Autonomous Driving Data Loop Technology 1: Data-Driven Models for Autonomous Driving
• Autonomous Driving Data Loop Technology 2: Cloud Computing Infrastructure and Big Data Processing Technologies
• Suppliers with Autonomous Driving Data Loop Capabilities
• Autonomous Driving Data Loop Suppliers (1)
• Autonomous Driving Data Loop Suppliers (2)
• Autonomous Driving Data Loop Suppliers (3)
• Autonomous Driving Data Loop Case 1: Tesla (1)
• Autonomous Driving Data Loop Case 1: Tesla (2)
• Autonomous Driving Data Loop Case 2: Momenta
• Autonomous Driving Data Loop Case 3
• Autonomous Driving Data Loop Case 4
• Autonomous Driving Data Loop Case 5
• Autonomous Driving Data Loop Case 6
• 3.3 Key Technologies for L4 Autonomous Driving: Redundancy
• Autonomous Driving Redundant System Suppliers: Braking Redundancy
• Autonomous Driving Redundant System Suppliers: Sensor Redundancy
• Autonomous Driving Redundant System Suppliers: Computing Redundancy
• Autonomous Driving Redundant System Cases (1): BMW L4/L5 Autonomous Driving Redundant System
• Autonomous Driving Redundant System Cases (2): Baidu Sensor Redundancy
• 3.4 Key Technologies for L4 Autonomous Driving: Vehicle-Road-Cloud Cooperation
• Vehicle-Road Cooperation Enables Smart Autonomous Mobility
• Release of the Cooperative Architecture Design of Collaborative Automated Driving System (1)
• Release of the Cooperative Architecture Design of Collaborative Automated Driving System (2)
• China Established Its First Vehicle-Road-Cloud Integrated Research Center
• AI Foundation Models Enable Vehicle-Road-Cloud Integration, Accelerating Autonomous Driving Implementation
• China's First L4 Autonomous Driving Highway with Vehicle-Road-Cloud Cooperation Was Officially Opened
• Vehicle-Road-Cloud Cooperation Solution Suppliers (1)
• Vehicle-Road-Cloud Cooperation Solution Suppliers (2)
• Vehicle-Road-Cloud Cooperation Solution Suppliers (3)
• Vehicle-Road-Cloud Integrated Solution: MOGO Package 2.0 by Mogo.ai
• L4 Autonomous Driving Case Based on Vehicle-Road-Cloud Cooperation: Yangshan Port Autonomous Driving
• 3.5 Key Technologies for L4 Autonomous Driving: HD Maps and Positioning
• Requirements of L4 Autonomous Driving for HD Maps (1)
• Requirements of L4 Autonomous Driving for HD Maps (2)
• Requirements of L4 Autonomous Driving for High-precision Positioning Technology
• L3/L4 Autonomous Driving HD Map Providers: Traditional Map Providers (1)
• L3/L4 Autonomous Driving HD Map Providers: Traditional Map Providers (2)
• L3/L4 Autonomous Driving HD Map Providers: Commercial Vehicles (1)
• L3/L4 Autonomous Driving HD Map Providers: Commercial Vehicles (2)
• L3/L4 Autonomous Driving HD Maps and Positioning Cases

4 L3/L4 Autonomous Driving Solutions of OEMs

• 4.1 XPeng
• AI-Defined Automotive Transformation Layout
• Autonomous Driving Plan: Parallel Development of L2 and L4
• Autonomous Driving System Evolution Path
• L4 Autonomous Driving Plan: XPeng ROBOTAXI (1)
• L4 Autonomous Driving Plan: XPeng ROBOTAXI (2)
• The Ultimate Form Before XPeng Achieves L4 Autonomous Driving: XPeng Navigation Guided Pilot (XNGP) (1)
• The Ultimate Form Before XPeng Achieves L4 Autonomous Driving: XPeng Navigation Guided Pilot (XNGP) (2)
• All-Scenario Intelligent Driving Architecture - XBrain
• Intelligent Driving Technology Bases (1): Perception Architecture - XNet 1.0
• Intelligent Driving Technology Bases (1): Perception Architecture - XNet 2.0
• Intelligent Driving Technology Bases (2): Planning and Control Architecture - XPlanner
• End-to-end System (1): Architecture
• End-to-end System (2): Intelligent Driving Model
• End-to-end System (2): Intelligent Driving Model
• End-to-end System (3): AI+XNGP
• End-to-end System (4): Organizational Change
• Key to the Next Generation of Mid- and back-end Capabilities: Data Processing Efficiency
• AI Technology Bases for the Second Half of Intelligent Driving (1): Data Collection
• AI Technology Bases for the Second Half of Intelligent Driving (2): Data Labeling - Fully Automatic Labeling System
• AI Technology Bases for the Second Half of Intelligent Driving (3): Data Training - Autonomous Driving Computing Platform "Fuyao"
• AI Technology Bases for the Second Half of Intelligent Driving (4): Data Deployment
• 4.2 Li Auto
• Autonomous Driving System Evolution Path
• Accelerate L3/L4 Deployment and Further Extend Towards AGI in the Future
• Algorithm Architecture of Intelligent Driving 3.0 - End-to-End Algorithm Architecture Based on Foundation Models
• Hardware Foundation & Algorithm Models in the Era of Intelligent Driving 3.0
• End-to-End Solutions (1): Iterative Evolution of System 1
• End-to-End Solutions (2): System 1 (End-to-End Model) + System 2 (VLM)
• End-to-End Solutions (3): Next-Generation Autonomous Driving Technology Architecture
• Underlying Technologies of Intelligent Driving End-to-End Algorithm: BEV Model + NPN Feature Extraction + TIN Model (1)
• Underlying Technologies of Intelligent Driving End-to-End Algorithm: BEV Model + NPN Feature Extraction + TIN Model (2)
• Perception Algorithm: BEV+Transformer+OCC
• Control and Planning Algorithm: Spatiotemporal Joint Planning + MPC model
• Autonomous Driving Training Platform: Poseidon Training Platform
• L4 Autonomous Driving Planning: Plan to Enter the Field of Intelligent Driving Logistics
• L4 Autonomous Driving Technology Base: Data-driven - Data Closed Loop (1)
• Autonomous Driving Technology Base: Data-driven - Data Closed Loop (2)
• Autonomous Driving Technology Base: Data-driven - Data Closed Loop (3)
• 4.3 Chery
• Profile of ZDRIVE.AI (1)
• ZDRIVE.AI Develops both ADAS and L4 High-level Autonomous Driving Products
• End-to-end System Development Plan
• L4 Autonomous Driving Plan (1)
• L4 Autonomous Driving Plan (2): Robotaxi 1.0
• L4 Autonomous Driving Plan (3): Robotaxi 2.0
• L4 Autonomous Driving Technology Base: Drive 2.0
• Humanoid Robot Layout
• 4.4 GAC
• L3/L4 Autonomous Driving Product Layout Plan and Implementation Timetable
• Robotaxi Layout: Independent Operation + External Cooperation
• Robotaxi Layout: Ecosystem Partners and Production Models
• Release of the First Large-scale Intelligent Driving Platform for Commercial Vehicles
• L4 Autonomous Driving Technology Analysis: GAC Aion Robotaxi
• GAC Aion and Wuxi Communications Industry Group: Establish L4 Autonomous Driving Demonstration Area
• 4.5 Great Wall Motor
• Great Wall Motor's L3/L4 Autonomous Driving Planning Route
• Haomo.ai's Hpilot Autonomous Driving Product Roadmap
• Haomo.ai's Technology Bases in Era of Autonomous Driving 3.0 (1): MANA Data Intelligence System
• Haomo.ai's Technology Bases in Era of Autonomous Driving 3.0 (2): Autonomous Driving Generative AI Model Drive GPT (1)
• Haomo.ai's Technology Bases in Era of Autonomous Driving 3.0 (2): Autonomous Driving Generative AI Model Drive GPT (2)
• Haomo.ai's Technology Bases in Era of Autonomous Driving 3.0 (3): Intelligent Computing Center MANA OASIS
• 4.6 Tesla
• The National Highway Traffic Safety Administration (NHTSA) under U.S. Department of Transportation Proposes A National Framework AV-STEP
• Tesla Accelerates the Robotaxi Plan
• L4 Product Portfolio
• AD Algorithm Development History
• End-to-end Process Overview, 2023-2024
• AD Algorithm Development History: FSD V12
• "End-to-end" Algorithm
• Core Elements of the Perception and Decision Full-Stack Integrated Model
• Tesla Semi: Weakening Autonomous Driving Features (1)
• Tesla Semi: Weakening Autonomous Driving Features (2)
• Tesla Semi: Weakening Autonomous Driving Features (3)
• 4.7 Toyota
• Toyota ADAS/AD Development Path
• Toyota L3 Guardian
• Toyota L4 Autonomous Driving Solutions: bZ4X Robotaxi (1)
• Toyota L4 Autonomous Driving Solutions: bZ4X Robotaxi (2)
• Toyota L4 Autonomous Driving Solutions: Autonomous Driving System Redundancy Design
• Toyota L4/L5 System: e-Palette Platform
• Toyota End-to-end Autonomous Driving Layout
• Nissan ADAS/AD Development Path
• Nissan ADAS: Iteration Process
• Nissan Shared Mobility Development Process (1)
• Japanese Government Accelerated Industrial Implementation of L4 Autonomous Driving in 2024
• Nissan Shared Mobility Development Process (2)
• Nissan's Robotaxi Progress in Japanese and Chinese Markets in 2024
• Nissan Robotaxi Business
• Nissan Launches Robotaxi Demonstration Operation in Suzhou
• Nissan China's Layout in China: Conduct Robotaxi Tests in Suzhou
• 4.8 Volvo
• Autonomous Driving Technology Route
• Autonomous Driving - L3 Ride Pilot
• Global - L4 System: Highway Pilot
• L4 Autonomous Driving Solution
• L4 Autonomous Driving Technology 1: Dual Computing Platforms + Execution Redundancy
• L4 Autonomous Driving Technology 2: Data-driven Software
• 4.9 Mercedes-Benz
• Mercedes-Benz Is Committed to Developing and Upgrading L3 Autonomous Driving Technology
• L3 Autonomous Driving Solutions (1): Drive Pilot
• L3 Autonomous Driving Solutions (2): Redundant Design (1)
• L3 Autonomous Driving Solutions (2): Redundant Design (2)
• Mercedes-Benz Has Formed A Multi-line Intelligent Driving Path for L2, L3, and L4
• L4 Autonomous Driving Solution: Driverless Parking System
• 4.10 BMW
• On-road Use of L3 Autonomous Driving Accelerates
• L3 Autonomous Driving Solution: Personal Pilot
• 4.11 Volkswagen
• Volkswagen Adjusts Its Autonomous Driving Business to Accelerate the Implementation of L4 Commercial Vehicles
• Volkswagen's L4 Autonomous Driving Solution: ID. Buzz AD (2)
• SAIC Volkswagen's L4 Autonomous Driving Planning
• SAIC Volkswagen's L4 Autonomous Driving Platform Sensor Solution
• 4.12 SAIC
• Policies Protect IM Motors to Accelerate L3/L4 Layout
• Profile of SAIC Intelligent Technology
• SAIC Intelligent Technology's Robotaxi Commercialization Progress
• SAIC Intelligent Technology's Robotaxi3.0
• SAIC AI LAB's L4 Autonomous Driving Technologies (1): Advanced Autonomous Driving Technology Architecture 2.0
• SAIC AI LAB's L4 Autonomous Driving Technologies (2): Fully Unmanned Technology Solution
• SAIC AI LAB's L4 Autonomous Driving Technologies (3): Vehicle-cloud-road Integration
• SAIC's L4 Autonomous Driving Layout
• 4.13 Geely
• Geely Accelerates L3/L4 Layout: Dual Wheel Drives of independent R&D and Strategic Ecosystem Cooperation
• Geely Released "Intelligent Vehicle Full-domain AI" Technology System
• L3 End-to-End Technology: End-to-End Plus Introduces Digital Precognition Network Based on Multimodal Large Language Models
• L3 End-to-End Technology: Analysis of End-to-End Plus System
• Geely's ADAS Technology Layout: Geely Xingrui Intelligent Data Center
• Xingrui AI Foundation Model
• Geely's L4 Application Solution: Vehicle Intelligence + 5G V2X
• 4.14 Changan
• ADAS Strategic Planning
• ADAS Strategy: Dubhe Strategy
• L4 Robotaxi Development History (1)
• L4 Robotaxi Development History (2)
• End-to-end System: BEV+LLM+GoT
• Production Model with End-to-end System: Changan NEVO E07
• 4.15 Other OEMs
• Hongqi's L4 Autonomous Driving Technology Solution
• Yutong's L4 Autonomous Driving Technology Solution

5 L4 Autonomous Driving Solutions of Tier1s and Startups

• 5.1 Waymo
• Profile
• Robotaxi Commercialization Progress
• L4 Product: Waymo One
• Comparison of Hardware Configurations Across Generations of Vehicle Models (First to Sixth Generation)
• L4 Strategic Partners and Cooperation Model
• Strategic OEM Partners (1)
• Strategic OEM Partners (2)
• Strategic Partners (3)
• L4 Autonomous Driving System: Waymo Driver
• L4 Autonomous Driving Technology 1: Perception
• L4 Autonomous Driving Technology 2: Architecture
• L4 Autonomous Driving Technology 3: Data Model and Architecture
• L4 Autonomous Driving Technology 4: Simulation
• L4 Autonomous Driving Technology 4: Open Source Simulator
• L4 Autonomous Driving Technology 5: Planning
• L4 Autonomous Driving Technology 6: Computing Platform
• Waymo Postponed Autonomous Truck Business Waymo Via
• Waymo Released End-to-end Multimodal Model for Autonomous Driving (EMMA)
• Limitations of EMMA
• 5.2 Aurora
• Aurora and Continental Cooperated to Build the Aurora Driver Autonomous Trucking System
• Autonomous Driving System: Aurora Driver Platform (1)
• Autonomous Driving System: Aurora Driver Platform (2)
• Autonomous Driving Technology: Perception and Decision
• L4 Autonomous Driving Layout
• 5.3 Baidu Apollo
• Profile of Baidu Apollo
• Core Robotaxi Service Operators' Exploration of Business Models
• Robotaxi Development Plan
• Apollo's Robotaxi Development Progress in 2024
• Sixth Generation Robotaxi Models
• The New-generation Robotaxi Introduces Two-Model End-to-end: Adopting A Strategy of First Segmentation and Then Joint Training
• Robotaxi Commercialization Progress
• Cost Reduction Logic of Six Generation Robotaxi Models and Analysis on Wuhan Autonomous Vehicle Commercial Demonstration Area
• Robotaxi Operation and Cost in the Shanghai Jiading Intelligent Connection Demonstration Operation Area
• L4 Technology 1: Safety Redundancy
• L4 Technology 2: Computing Platform
• L4 Product 1: Apollo Go (6)
• L4 Product 2: 5G Cloud Valeting
• L4 Product 3: Strategic Investment in Autonomous Trucks
• L4 Product 4: AVP
• 5.4 Pony.ai
• Profile
• Three Major Business Lines
• Robotaxi Business Model (1)
• Robotaxi Business Model (2)
• Robotaxi Business Model (3)
• Global Robotaxi Strategy
• Strategic Cooperation Ecosystem
• Operation
• Robotaxi Commercialization Progress
• Sixth Generation Robotaxi
• Sixth Generation L4 Autonomous Driving System
• Commitment to Integrated Hardware and Software Co-Development
• Hardware Architecture of L4 Autonomous Driving System (1)
• Hardware Architecture of L4 Autonomous Driving System (2)
• Computing Unit of L4 Autonomous Driving System (1)
• Computing Unit of L4 Autonomous Driving System (2)
• Data Closed-loop Capability of L4 Autonomous Driving System
• Autonomous Freight Enters the Inter-provincial Stage
• Obtain Inter-provincial Heavy Autonomous Truck License
• Recent Dynamics in Cooperation
• 5.5 WeRide
• Profile (1)
• Profile (2)
• Business Layout (1)
• Business Layout (2)
• Exploration of Business Models for Multi-Scenario Applications of L4 Autonomous Driving Technology
• Overview of L4 Autonomous Driving Product Robotaxi
• Robotaxi Commercialization Progress
• Global Robotaxi Strategy
• Autonomous Driving Technology: Sensor Suite (1)
• Autonomous Driving Technology: Sensor Suite (2)
• Core Technologies of Autonomous Driving
• Application of Autonomous Driving Technology: Providing Technical Support to Nissan
• Autonomous Driving Technology 1: Data Closed Loop
• Autonomous Driving Technology 2: Redundancy
• Autonomous Driving Technology 3: Algorithm
• L4 Product 1: Robotaxi (1)
• L4 Product 1: Robotaxi (2)
• The Latest Progress in L4 Autonomous Driving Products
• L4 Product 2: Robobus (1)
• L4 Product 2: Robobus (2)
• L4 Product 3: Robsweeper
• 5.6 AutoX
• Profile
• Commercialization Progress
• Autonomous Driving System: Gen5
• Autonomous Driving Technology: Panoramic Fusion Perception System xFusion
• L4 Product: Robotaxi
• L4 Product: Operation of Robotaxi
• Determined to Follow the L4 Route
• 5.7 Momenta
• Profile
• Autonomous Driving Strategy
• Strategic Focus L2++: Intelligent Driving Solution
• Mass Production and Introduction of End-to-end Foundation Models in Vehicles: One-Model End-to-end Solution (1)
• Mass Production and Introduction of End-to-end Foundation Models in Vehicles: One-Model End-to-end Solution (2)
• L4 Large-scale Application Outlook: Surpassing Moore's Law of Software (1)
• L4 Large-scale Application Outlook: Surpassing Moore's Law of Software (2)
• 5.8 DeepRoute.ai
• Product Layout and Strategic Deployment
• End-to-end VLA Model
• L4 Autonomous Driving Solution
• L4 Autonomous Driving Technology: Multi-sensor Fusion
• L4 Autonomous Driving Technology: Self-developed Reasoning Engine
• L4 Product 1: Robotaxi
• L4 Product 2: Autonomous Container Truck
• Overseas Layout
• 5.9 Chenqi Technology
• Profile (1)
• Profile (2)
• Robotaxi Commercialization Progress
• Three Major Business Deployments
• Robotaxi Business Model
• 5.10 Huawei
• In 2025 Huawei Will Promote Commercialization of Highway L3 Autonomous Driving
• L4 Autonomous Driving Technology: Computing Platform
• 5.11 Haomo.ai
• Passenger Car Autonomous Driving System
• Autonomous Vehicle Technology 1: Data Closed Loop (1)
• Autonomous Vehicle Technology 1: Data Closed Loop (2)
• Autonomous Vehicle Technology 2: Algorithm
• Autonomous Vehicle Technology 3: Computing Platform (1)
• Autonomous Vehicle Technology 3: Computing Platform (2)
• L4 Product 1: Unmanned Delivery Vehicle
• L4 Product 1: Unmanned Delivery Vehicles Open 9 Major Operating Scenarios
• L3/L4 Product 2: Passenger Car
• 5.12 UISEE Technology
• Profile
• Main Autonomous Driving Product Solutions
• L4 Autonomous Driving Platform: U-Drive
• L4 Product 1: Robotaxi
• L4 Product 2: Unmanned Logistics
• L4 Product 3: Unmanned Delivery (1)
• L4 Product 3: Unmanned Delivery (2)
• L4 Product 4: Robobus
• 5.13 IDRIVERPLUS
• L4 Autonomous Driving Technology
• L4 Autonomous Driving Technology: Data Closed Loop
• L4 Product 1: Robotaxi
• L4 Product 2: Robobus
• L4 Product 3: Autonomous Logistics Vehicle
• L4 Technology Application: Designated by M-Hero
• 5.14 QCraft
• L4 Autonomous Driving Development Strategy
• L4 Autonomous Driving Technology Layout
• L4 Autonomous Driving Technology 1: Algorithm
• L4 Autonomous Driving Technology 2: QMatrix
• L4 Autonomous Driving Technology 3: Perception
• L4 Product 1: Robobus Product Matrix
• L4 Product 1: Robobus Sensor Solution
• L4 Product 1: Robobus Operation Progress
• L4 Product 2: Robotaxi
• 5.15 PlusAI
• L4 Autonomous Driving Layout
• L4 Autonomous Driving Planning
• L4 Autonomous Driving System: PlusDrive
• Business Model: Logistics Company + OEM + Autonomous Driving Company
• L4 Autonomous Driving Application: ANE (Cayman) Inc.
• L4 Autonomous Driving Application: Dongfeng Liuzhou Motor
• 5.16 Inceptio Technology
• Evolution of Autonomous Driving System
• Self-developed Autonomous Driving Technology 1: Planning and Control Integration
• Self-developed Autonomous Driving Technology 2: Algorithm
• Self-developed Autonomous Driving Technology 3: Data Closed Loop
• 5.17 CiDi
• L4 Product 1: Autonomous Mining Truck
• L4 Product 2: Autonomous Logistics
• 5.18 Deepway
• Delivered New Intelligent Driving Vehicles
• Obtained Road Test License