Global and China L4 Autonomous Driving and Start-ups Report, 2022

Search by Type

Report DataBase News

Abstract

Selected Charts

Related Reports

Related Companies

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

L3/L4 autonomous driving enjoys much greater policy support.

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

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

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

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

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

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

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

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

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

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

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

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

L4 -1_副本.png

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

Compared with Super Cruise, Ultra Cruise has added some new autonomous driving functions:
?Follow the internal navigation route and keep moving forward;
?Observe the speed limit
?Support automatic and on-demand lane change
?Support automatic left and right turns
?Support close object avoidance

L4 -2_副本.png

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

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

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

L4 -3_副本.png

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

L4 -4_副本.png

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

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

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

L4 -5_副本.png

Global and China L4 Autonomous Driving and Start-ups Report, 2022 highlights the following:
L4 autonomous driving (policies, standards, regulations, etc.);
L4 autonomous driving market (size, competitive landscape, etc.);
Key technologies (algorithm, HD map and positioning, data closed-loop, vehicle-road-cloud cooperation, redundancy, etc.) of L4 autonomous driving (major suppliers, technical solutions, etc.);
Application scenarios (Robotaxi, autonomous shuttle, autonomous delivery, autonomous truck, etc.) of L4 autonomous driving (major suppliers, technical solutions, operation, etc.);
OEMs’ layout and planning of L4 autonomous driving solutions;
Major L4 technology suppliers (technical solution iterations, application and layout of L4 products, etc.).

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

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

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

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

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

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

Auto Shanghai 2025 Summary Report

The post-show summary report of 2025 Shanghai Auto Show, which mainly includes three parts: the exhibition introduction, OEM, and suppliers. Among them, OEM includes the introduction of models a...

Automotive Operating System and AIOS Integration Research Report, 2025

Research on automotive AI operating system (AIOS): from AI application and AI-driven to AI-native Automotive Operating System and AIOS Integration Research Report, 2025, released by ResearchInChina, ...

Software-Defined Vehicles in 2025: OEM Software Development and Supply Chain Deployment Strategy Research Report

SDV Research: OEM software development and supply chain deployment strategies from 48 dimensions The overall framework of software-defined vehicles: (1) Application software layer: cockpit software, ...

Research Report on Automotive Memory Chip Industry and Its Impact on Foundation Models, 2025

Research on automotive memory chips: driven by foundation models, performance requirements and costs of automotive memory chips are greatly improved. From 2D+CNN small models to BEV+Transformer found...

48V Low-voltage Power Distribution Network (PDN) Architecture and Supply Chain Panorama Research Report, 2025

For a long time, the 48V low-voltage PDN architecture has been dominated by 48V mild hybrids. The electrical topology of 48V mild hybrids is relatively outdated, and Chinese OEMs have not given it suf...

Research Report on Overseas Cockpit Configuration and Supply Chain of Key Models, 2025

Overseas Cockpit Research: Tariffs stir up the global automotive market, and intelligent cockpits promote automobile exports ResearchInChina has released the Research Report on Overseas Cockpit Co...

Automotive Display, Center Console and Cluster Industry Report, 2025

In addition to cockpit interaction, automotive display is another important carrier of the intelligent cockpit. In recent years, the intelligence level of cockpits has continued to improve, and automo...

Vehicle Functional Safety and Safety Of The Intended Functionality (SOTIF) Research Report, 2025

Functional safety research: under the "equal rights for intelligent driving", safety of the intended functionality (SOTIF) design is crucial As Chinese new energy vehicle manufacturers propose "Equal...

Chinese OEMs’ AI-Defined Vehicle Strategy Research Report, 2025

AI-Defined Vehicle Report: How AI Reshapes Vehicle Intelligence? Chinese OEMs’ AI-Defined Vehicle Strategy Research Report, 2025, released by ResearchInChina, studies, analyzes, and summarizes the c...

Automotive Digital Key (UWB, NearLink, and BLE 6.0) Industry Trend Report, 2025

Digital key research: which will dominate digital keys, growing UWB, emerging NearLink or promising Bluetooth 6.0?ResearchInChina has analyzed and predicted the digital key market, communication techn...

Integrated Battery (CTP, CTB, CTC, and CTV) and Battery Innovation Technology Report, 2025

Power battery research: 17 vehicle models use integrated batteries, and 34 battery innovation technologies are released ResearchInChina released Integrated Battery (CTP, CTB, CTC, and CTV)and Battery...

AI/AR Glasses Industry Research Report, 2025

ResearchInChina released the " AI/AR Glasses Industry Research Report, 2025", which deeply explores the field of AI smart glasses, sorts out product R&D and ecological layout of leading domestic a...

Global and China Passenger Car T-Box Market Report 2025

T-Box Research: T-Box will achieve functional upgrades given the demand from CVIS and end-to-end autonomous driving ResearchInChina released the "Global and China Passenger Car T-Box Market Report 20...

Automotive Microcontroller Unit (MCU) Industry Report, 2025

Research on automotive MCUs: the independent, controllable supply chain for automotive MCUs is rapidly maturing Mid-to-high-end MCUs for intelligent vehicle control are a key focus of domestic produc...

Automotive LiDAR Industry Report, 2024-2025

In early 2025, BYD's "Eye of God" Intelligent Driving and Changan Automobile's Tianshu Intelligent Driving sparked a wave of mass intelligent driving, making the democratization of intelligent driving...

Software-Defined Vehicles in 2025: SOA and Middleware Industry Research Report

Research on automotive SOA and middleware: Development towards global SOA, cross-domain communication middleware, AI middleware, etc. With the implementation of centrally integrated EEAs, OEM softwar...

Global and Chinese OEMs’ Modular and Common Technology Platform Research Report, 2025

Modular platforms and common technology platforms of OEMs are at the core of current technological innovation in automotive industry, aiming to enhance R&D efficiency, reduce costs, and accelerate...

Research Report on the Application of AI in Automotive Cockpits, 2025

Cockpit AI Application Research: From "Usable" to "User-Friendly," from "Deep Interaction" to "Self-Evolution" From the early 2000s, when voice recognition and facial monitoring functions were first ...

Abstract

Table of Contents

Selected Charts

Related Reports

Related Companies