[시장보고서]중국의 L3 및 L4 자율주행과 스타트업(2025년)

중국의 L3 및 L4 자율주행과 스타트업(2025년)

L3/L4 Autonomous Driving and Startups Research Report, 2025

상품코드 : 1652116

리서치사 : ResearchInChina

발행일 : 2025년 02월

페이지 정보 : 영문 495 Pages

라이선스 & 가격 (부가세 별도)

한글목차

샘플 요청 목록에 추가

로보택시는 2026-2030년 규모 확대로 L3 개인용 자동차가 새로운 상업화 기회를 열 것

2023-2024년에 로보택시 시장의 통합이 가속된 후, 주요 로보택시 기업은 무인 실증운전에서 상업운전으로 서서히 이행하고 있습니다. 많은 기업들은 2026년을 로보택시의 대규모 개발의 원년으로 자리매김하고 대규모의 전개를 계획하고 있습니다. 베이징과 우한이 2025년에 L3 자율주행 자가용차의 발매를 정식으로 발표해 중국 인텔리전트 드라이빙 산업의 최초의 벤치마크를 설정하여, 대기업 자동차 제조업체는 레이아웃을 가속하고 있어, 2025-2027년을 L3 자율주행 운전차의 양산을 향한 중요한 단계로 하고 있습니다. 그 중 Li Auto는 2025년까지 감리된 L3 지능형 운전을 실현할 계획입니다.

L3-L4 자율주행 응용 시나리오 1: 로보택시 시장

로보택시의 동향 1: 2023-2024년은 로보택시 산업발전의 조정기이다.

Google이 2009년에 자율주행차 프로젝트를 시작한 이래로 자율주행 기술은 점차 세계의 주목을 끌게 되어 세계의 주목과 투자를 촉발시키고 있습니다. 캘리포니아 DMV의 최신 데이터에 따르면 2024년 캘리포니아에서 자율주행차의 시험 주행 거리는 450만 마일로 2023년부터 50% 감소했습니다. 인간의 안전 드라이버에 의한 테스트 허가는 크게 감소하고 31개 기업만이 허가를 가지고 있지만, 2024년에 실제로 공도 테스트를 실시한 것은 11개 기업만으로, 9개 기업은 테스트를 중지하고 프로그램에서 철수하고 있습니다. 무인 테스트의 경우 AutoX, WeRide, Waymo, Zoox, Nuro의 6개 기업만이 허가를 받았습니다. 이 변화는 10년 이상에 걸친 기술 개발, 비즈니스 모델 모색, 시장 시행착오를 거쳐 로보택시 산업이 2023-2024년에 중요한 조정기에 들어간 것을 반영하고 있습니다. 이 단계는 기술과 시장의 성숙도가 시험될 뿐만 아니라 산업 내 적자 생존의 분수령이기도 합니다.

2023년부터 2024년까지 일부 L4 자율주행 기업은 재무적 압력으로 인해 철수 또는 전략적 조정을 강요했습니다. 이러한 기업들은 기술적 혁신에 주력하면서도 비즈니스 모델이 불분명하거나 시장 확대가 잘못되었기 때문에 자립을 이루지 못했던 시장에 대한 초기 진출기업이 대부분이었습니다. 2024년에 Cruise가 해산을 발표했고, 2024년 2월에는 Tier 1 거대 기업 Aptiv이 자율주행 기업 Motional에 대한 투자 비율을 낮추어 레이아웃을 최적화하고 자체 핵심 강점에 집중했습니다.

산업 조정 기간 동안 로보택시 부문은 복잡한 양상을 보였습니다. 자본시장은 보다 신중해지고, L4 기술에서 명확한 이점을 가지고 있으며, 초기 비즈니스 모델의 루프를 형성한 자율주행 기업에 점차 자금이 집중되었습니다.

2024년 7월, Waymo는 50억 달러의 전략적 투자를 받았으며 로보택시 분야에서 주도적 지위를 더욱 강화했습니다. 한편, WeRide와 Pony.ai는 NASDAQ 상장에 성공하여 산업의 중진이 되고 있습니다. 이러한 상장은 각 회사에 자금 지원을 가져왔을 뿐만 아니라 산업 전체에 새로운 활력을 주입하고 로보택시 부문이 조정기를 거쳐 서서히 성숙한 개발 단계로 이행하고 있음을 보여줍니다.

로보택시 동향 2: 기술 주도 자율주행 기업이 추진속도, 운행범위, 차량 전개규모 등 로보택시 사업을 선도하고 있다.

로보택시 부문에는 주로 세 가지 유형의 기업이 있습니다.

1: SAIC와 GAC와 같은 전통적인 자동차 제조 업체와 Tesla와 XPeng 같은 새로운 자동차 제조 업체.

2: Ruqi와 Caocao와 같은 이동성 플랫폼.

3: Waymo, Zoox, Baidu Apollo, Pony.ai, WeRide, AutoX 등 L4 자율주행 솔루션 제공업체 및 로보택시 사업자.

로보택시의 상업화에서는 Waymo, Baidu Apollo, Pony.ai, WeRide 등 기술 주도형의 자동 운전기업(제3유형의 기업)이, 기존 자동차 제조업체(제1유형)나 모빌리티 플랫폼(제2유형)과 비교해, 상업화 스피드, 운용 범위, 차량 전개 규모와 같은 부분에서 주요 기업보다 앞서나가고 있습니다.

이 보고서는 중국 자동차 산업에 대한 조사 분석을 통해 L3/L4 자율주행 정책 및 규제, 응용 시나리오, 주요 기술 및 각 회사의 솔루션에 대한 정보를 제공합니다.

영문목차

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.

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

한글목차

목차

제1장 L3/L4 자율주행 정책, 규제, 표준

제2장 L3/L4 자율주행의 응용 시나리오

제3장 레벨 4 자율주행의 양산을 위한 주요 기술

제4장 OEM L3/L4 자율주행 솔루션

제5장 Tier 1과 스타트업 L4 자율주행 솔루션