智慧駕駛模擬和世界模式(2025年)

1. 世界模型將徹底改變智慧駕駛模擬

面向 L3 及更高級別的自動駕駛，端到端技術的發展對高質量數據規模、多樣化場景的全面性、物理真實感的保障、多模態數據的同步生成、行為邏輯的合理性以及迭代效率的提升提出了更高的要求。

在高品質智慧駕駛的三大核心要素（數據、模型、算力）中，場景數據的品質和數量正成為智慧駕駛體驗的關鍵差異化因素。同時，訓練高階 ADAS（進階駕駛輔助系統）演算法模型需要數千萬級的影片片段和產生長序列的多模態駕駛場景。然而，從真實道路資料中可取得的長尾場景相對有限，無法滿足端到端演算法訓練對高品質資料的需求。

自動化模擬測試正在成為主機廠和供應商縮短開發週期、降低成本、提高效率、解決長尾場景覆蓋不足以及克服高風險駕駛工況復現課題的有力工具。同時，能夠理解真實環境物理特性和空間屬性的世界模型（World Model）正在被越來越多的主機廠和主要一級供應商採用。

目前，智慧駕駛訓練的場景資料主要來自以下幾種來源：

一是基於真實路測資料回放的模擬技術，其優勢在於場景真實性高，主要用於重現路測中的問題場景並驗證演算法修改的有效性。

二是人工定義的參數化場景（例如Open情勢格式），其特徵是測試標準化、邊界條件探索性強、場景可控性強。

第三是將真實世界測試資料（logsim）轉換為可泛化的虛擬模擬場景（Worldsim），以資料驅動的場景產生和泛化為核心功能，建構可靠的模擬場景庫，支援場景推導與自動化測試，進而提升場景覆蓋效率。

第四是世界模型（world model），利用人工智慧建構物理世界的內部表徵，實現預測環境狀態和反事實推理的智慧模型。其資料來源包括多模態資料（圖像、文字、物理規則）以及強化學習產生的資料。其優勢在於因果推理能力和對未知場景預測的支持。然而，世界模型需要大量的運算資源，其可解釋性有待提升，並且存在數據偏差的風險。

世界模型也在環境辨識與理解、未來情境發展預測、決策與規劃最佳化、增強資料生成與訓練、模擬與測試驗證、提升系統泛化能力等多個面向展現優勢。

2. 全鏈路安全驗證驅動模擬走向跨域整合

目前自動駕駛安全驗證正從單一功能測試轉變為全鏈路閉環驗證。模擬技術正在突破傳統界限，走向加速技術融合和工具鏈集成為核心的深度跨域協同。

隨著座艙駕駛整合和跨域整合應用的發展，模擬也正走向跨域整合。業界已具備面向汽車各領域的模擬測試解決方案，整合軟硬體工具/平台，積極推動跨域聯合測試。

本報告提供中國的汽車產業調查分析，提供智慧駕駛模擬技術的進步，世界模式的應用，國內外的供應商等資訊。

目錄

第1章 智慧駕駛模擬概要

• 智慧駕駛模擬技術進度分析
• 交通場景模擬分析
• 感測器仿真
• 車輛動力學模擬方案比較
• 模型在環 (MiL) 方案總結與比較
• 智慧駕駛模擬工具/平台總結
• 智慧座艙模擬測試工具/平台總結
• 智慧底盤模擬測試工具/平台總結
• 三大電氣（電池、馬達、電控）模擬測試工具/平台總結
• 汽車乙太網路測試工具/平台總結

第2章 模擬試驗情勢程式庫

• 智慧駕駛模擬標準法規綜述
• 智慧座艙模擬測試評估規範及參考標準
• ASAM OpenX系列標準更新比較分析
• ASAM OpenMATERIAL 3D標準分析
• OpenX系列標準在仿真平台中的應用範例
• 層次化場景模型綜述
• 仿真場景資料庫分類
• 3DGS高逼真度模擬場景重建技術及案例分析
• 4DGS技術在智慧駕駛的應用分析
• 智慧駕駛訓練資料來源分析
• 合成資料端對端演算法訓練的迫切需求

第3章 智慧駕駛的世界模式的應用

• 端對端自動駕駛的開放資料集
• 智慧駕駛相關公開資料集世界模型
• 其他開源模擬測試場景資料集
• 世界模型概述
• 世界模型總結
• 智慧駕駛領域世界模型分析
• 世界模型代表性應用案例

第4章 主機廠/Tier 1供應商智慧駕駛模擬及世界模型應用

• NIO
• XPeng Motors
• Xiaomi
• Li Auto
• Geely
• Zhuoyu Technology
• Horizon
• SenseAuto
• GigaAI

第5章 AI整合智慧駕駛模擬技術的調查

• 數位孿生與GNSS的應用 - 案例1
• 數位孿生與GIS技術在智慧駕駛中的整合應用分析
• AI與模擬的融合 - 案例1
• 人工智慧與模擬融合 - 案例2
• 人工智慧與模擬融合 - 案例3
• 人工智慧提升研發效率 - 案例1
• 人工智慧提升研發效率 - 案例2
• 人工智慧提升研發效率 - 案例3
• 智慧座艙系統自動化測試分析

第6章 中國的模擬平台和世界模式供應商

• 51WORLD
• IAE
• Zhejiang PanoSim
• Saimo Technology
• Synkrotron.ai
• PilotD Automotive
• Shengqi Technology
• Keymotek
• Tsing Standard
• Jingwei HiRain
• Dotrust Technologies
• Vehinfo
• Beijing Oriental Jicheng
• AUMO (ALINX)
• Kunyi Electronics
• KOTEI

第7章 國外的模擬平台和世界模式供應商

• NVIDIA
• UE
• Unity
• Wayve
• APPLE
• Foretellix
• Siemens
• Hexagon
• KISSsoft (Gleason)
• AVL
• VECTOR
• IPG Automotive
• dSPACE
• MathWorks
• LeddarTech
• VI-Grade
• NI (EMERSON)
• Ansys (Synopsys)

1. The world model brings innovation to intelligent driving simulation

In the advancement towards L3 and higher-level autonomous driving, the development of end-to-end technology has raised higher requirements for the scale of high-quality data, coverage of diverse scenarios, assurance of physical realism, synchronized generation of multimodal data, rationality of behavioral logic, and improvement of iteration efficiency.

Among the three core elements of high-quality intelligent driving (data, models, and computing power), the quality and quantity of scenario data are becoming key differentiators in the intelligent driving experience. Meanwhile, training high-level advanced driver-assistance system (ADAS) algorithm models requires tens of millions of video clips and the generation of long-sequence multimodal driving scenarios. However, the long-tail scenarios captured in real-world road data are relatively limited and cannot meet the demand for high-quality data to feed end-to-end algorithm training.

Automated simulation testing is becoming a powerful tool for OEMs and suppliers to shorten development cycles, reduce costs, improve efficiency, address insufficient coverage of long-tail scenarios, and overcome challenges in reproducing high-risk operating conditions. At the same time, world models, which can understand the physical characteristics and spatial attributes of the real-world environment, are being adopted by an increasing number of OEMs and leading Tier1 suppliers.

Currently, for intelligent driving training, scenario data mainly comes from the following sources:

One is simulation technology based on the replay of real road test data, with the advantage of high scenario authenticity, primarily used to reproduce road test problem scenarios and verify the effectiveness of algorithm fixes;

The second is artificially defined parametric scenarios (such as OpenScenario format), characterized by standardized testing, exploration of boundary conditions, and strong scenario controllability;

The third involves converting real road test data (logsim) into generalizable virtual simulation scenarios (Worldsim), with the core function being data-driven scenario generation and generalization, building a high-confidence simulation scenario library, supporting scenario derivation and automated testing, thereby improving scenario coverage efficiency.

The fourth is the World Model, which uses AI to construct an internal representation of the physical world, enabling intelligent models for environmental state prediction and counterfactual reasoning. Its data sources include multimodal data (images, text, physical rules) and reinforcement learning-generated data. Its advantages include causal reasoning capabilities and support for unknown scenario prediction. However, world models require significant computational resources, their interpretability needs improvement, and they also carry the risk of data bias.

World models also demonstrate advantages in multiple aspects, such as environmental perception and understanding, prediction of future scenario evolution, decision and planning optimization, data generation and training enhancement, simulation and test validation, and improvement of system generalization capabilities. The following table provides a glimpse of the innovation world models bring to intelligent driving training through case studies of typical OEMs and Tier1 suppliers applying world models.

2. Full-chain safety validation is driving simulation toward cross-domain integration

Current autonomous driving safety validation has shifted from single-function testing to full-chain closed-loop verification. Simulation technology is breaking through traditional boundaries and moving toward deep cross-domain collaboration, with core drivers including accelerated technological convergence and toolchain integration.

Specifically:

Accelerated Technological Convergence: AI-driven scenario generation is crucial for building high-quality training datasets. For example, DriveDreamer4D and OASIS SIM's generative AI technologies have improved long-tail scenario generation efficiency by 10 times (e.g., 51Sim generates 32,000 extreme scenarios per day). Meanwhile, multi-domain model collaboration is becoming more prominent, such as vehicle dynamics (PanoCar), sensors (physics-level radar modeling), traffic flow (SUMO/VISSIM), and cloud-based world models (e.g., Li Auto's MindGPT) working together to build a digital twin closed loop.

Toolchain Integration: Leading solution providers (e.g., Horizon's AIDI platform, Synkrotron.ai's OASIS) have achieved full-stack toolchain integration from "perception - planning - control - vehicle-road-cloud," supporting seamless transitions from MIL to VIL. For instance, Horizon's UniAD framework uses an end-to-end model to compress perception-planning latency to around 50ms and validates multi-vehicle gaming strategies in simulation.

Due to the development of cockpit-driving integration and cross-domain integration applications, simulation is also moving toward cross-domain integration. The industry has introduced simulation testing solutions for various automotive domains, integrating software and hardware tools/platforms to actively promote joint cross-domain testing. Overall, OEMs and suppliers are currently advancing cross-domain simulation, mainly focusing on: Intelligent cockpit + intelligent driving integration, Intelligent chassis + intelligent driving cross-domain integration, Three-electric systems (battery, motor, electronic control) + thermal management integration, IoV + intelligent driving integration, global digital twins.

Examples include:

Tsing Standard's active suspension HIL and Zhejiang PanoSim's PanoCar conducting suspension-planning co-simulation to address cross-domain control latency and improve stability in extreme conditions (reducing roll by >=15%).

AUMO (under Alinx Electronic) collaborated with BYD to develop a cockpit-driving domain integration testing solution, using the W50 platform to validate in-cabin vision systems (DMS/OMS) alongside autonomous driving algorithms, enabling data exchange between cockpit and driving domains to accelerate "cockpit-driving integration."

In Q1 2025, Mercedes-Benz partnered with VECTOR to conduct centralized electronic architecture virtualization validation, using SIL Kit middleware for distributed simulation testing of domain controllers (e.g., autonomous driving, body domains) to optimize cross-domain communication and functional integration efficiency.

In October 2024, Beijing Oriental Jicheng and Great Wall Motors collaborated on cross-domain joint testing for intelligent cockpit, intelligent driving, and vehicle connectivity, covering signal-level simulation to full-vehicle testing in a one-stop service.

Kunyi Electronics' cockpit HIL testing, based on Kunyi's high-real-time RTPC system and combined with its high-level autonomous driving data closed-loop testing solution, provides simulations for 360° surround view, driver monitoring, and streaming rearview mirrors, meeting high-performance testing needs for vehicle-cloud integration, cockpit-parking integration, and cockpit-driving integration.

3. Industry progress in enhancing simulation credibility

One of the biggest pain points in simulation testing is credibility. The industry needs to consider how to ensure high fidelity in scenario simulation, high accuracy in sensor models, high confidence in dynamics models, as well as challenges in real-time performance, data bandwidth, and stability of data interfaces.

In terms of improving simulation credibility, the following approaches are being adopted.

1. Application of AI Technology

AI technology is gradually being applied to simulation testing in engineering practice, significantly accelerating the automation efficiency of testing and validation, thereby improving automotive development efficiency. For example:

In February 2025, IAE partnered with VDBP to launch the industry's first AI scenario generation tool integrated with the DeepSeek R1 large model. It pioneered an end-to-end solution for "generating high-quality OpenDRIVE and OpenSCENARIO standard scenarios with text commands," supporting intelligent generation from simple ADAS tests to complex traffic rules and extreme working conditions. It covers full-scenario needs such as ADAS, urban NOA, and V2X, improving scenario construction efficiency by 300% and enabling seamless integration with mainstream simulation software like CARLA, VTD, and Prescan.

In December 2024, AVL released the AI simulation assistant ChatSDT to simplify and enhance user interaction with AVL simulation components. MathWorks also introduced the MATLAB Large Language Support Package, aiming to deeply integrate large language models (such as ChatGPT, Qwen, and DeepSeek) with MATLAB/Simulink to improve engineering development efficiency.

2. Open-Source Datasets

Additionally, organizations like the China Association of Automobile Manufacturers (CAAM) are actively promoting open-source data initiatives. Nearly 20 datasets have been released, including Coral Data, vehicle-road-cloud integrated simulation scenario open-source data, OEM-open-sourced end-to-end autonomous driving public datasets, and publicly available training datasets related to intelligent driving world models. The goal of open-sourcing is to facilitate efficient reuse of these high-quality scenario datasets and avoid redundant development within the industry.

In April 2025, the ASAM OpenMATERIAL 3D 1.0.0 standard was officially released. This standard specifies a standardized format for physical material properties and 3D object descriptions, precisely defining parameters such as refractive index, surface roughness, and permeability. By providing accurate and standardized 3D assets and material properties, the standard enhances the realism of perception sensor simulations, making the outputs of LiDAR, radar, and cameras more lifelike.

3. Simulation Tool Upgrades

Simulation testing companies have also updated and upgraded the functions of simulation software tools/platforms, such as PreScan software version 2503, HEXAGON VTD/MSC/ADAMS/KISSoft simulation software, CarMaker14.0, AURELION 24.3, MATLAB/Simulink R2025a, Ansys 2025R1, Oasis SIM 3.0, aiSim intelligent driving simulation software UE5.5 upgrade, Qianxing system V3.0 with 20+ new features, PanoCarV1.7 PanoSim V33 version, etc. (see the report for details).

Table of Contents

Terminology and Definitions

1 Overview of Intelligent Driving Simulation

• 1.1 Analysis of Intelligent Driving Simulation Technology Advancements
• 1.2 Traffic Scenario Simulation Analysis
• Typical Collaborations in Traffic Scenario Simulation
• Case 1
• Case 2
• 1.3 Sensor Simulation
• Comparison of Different Virtual Camera Modeling Techniques
• High-Fidelity Radar Simulation: Performance Comparison of Radar Modeling Technologies (1)
• High-Fidelity Radar Simulation: Performance Comparison of Radar Modeling Technologies (2)
• Case 1
• Case 2
• Comparison of Sensor Simulation Solutions
• 1.4 Vehicle Dynamics Simulation Solution Comparison
• Case 1
• 1.5 Summary and Comparison of Model-in-the-Loop (MiL) Solutions
• Summary and Comparison of Software-in-the-Loop (SiL) Solutions
• Summary and Comparison of Hardware-in-the-Loop (HiL) Solutions
• Summary and Comparison of Driver-in-the-Loop (DiL) Solutions
• Summary and Comparison of Vehicle-in-the-Loop (ViL) Solutions
• 1.6 Summary of Intelligent Driving Simulation Tools/Platforms
• 1.7 Summary of Intelligent Cockpit Simulation Testing Tools/Platforms
• 1.8 Summary of Intelligent Chassis Simulation Testing Tools/Platforms
• 1.9 Summary of Three-Electric (Battery, Motor, Electronic Control) Simulation Testing Tools/Platforms
• 1.10 Summary of Automotive Ethernet Testing Tools/Platforms

2 Simulation Test Scenario Libraries

• 2.1 Summary of Intelligent Driving Simulation Standards and Regulations
• 2.2 Evaluation Specifications and Reference Standards for Intelligent Cockpit Simulation Testing
• 2.3 Comparative Analysis of ASAM OpenX Series Standard Updates
• 2.4 Analysis of ASAM OpenMATERIAL 3D Standard
• 2.5 Application Cases of OpenX Series Standards in Simulation Platforms
• 2.6 Research on Scenario Model Layering
• Latest Dynamics in Scenario Model Layering
• Scenario Abstraction Levels
• Scenario Abstraction Classification
• Dynamic Scenario Analysis
• 2.7 Classification of Simulation Scenario Databases
• 2.8 3DGS High-Fidelity Simulation Scene Reconstruction Technology and Case Studies
• 2.9 Analysis of 4DGS Technology Applications in Intelligent Driving
• Comparative Analysis of 4D Reconstruction and Dynamic Modeling Algorithms for Intelligent Driving Scenarios (1)
• Comparative Analysis of 4D Reconstruction and Dynamic Modeling Algorithms for Intelligent Driving Scenarios (2)
• Comparative Analysis of 4D Reconstruction and Dynamic Modeling Algorithms for Intelligent Driving Scenarios (3)
• 2.10 Analysis of Training Data Sources for Intelligent Driving
• 2.11 Urgent Requirements of End-to-End Algorithm Training for Synthetic Data

3 Application of World Models in Intelligent Driving

• 3.1 Open Datasets for End-to-End Autonomous Driving
• 3.2 Public Datasets Related to Intelligent Driving World Models
• 3.3 Other Open-Source Simulation Test Scenario Datasets
• 3.4 Overview of World Models
• 3.5 Summary of World Models
• 3.6 Analysis of World Models in the Field of Intelligent Driving
• 3.7 Cases of Typical World Model Applications

4 Intelligent Driving Simulation and World Model Applications by OEMs/Tier1 Suppliers

• 4.1 NIO
• Autonomous Driving Technology System
• NWM World Model (1)
• NWM World Model (2)
• 4.2 XPeng Motors
• Simulation Toolchain Application (1)
• Simulation Toolchain Application (2)
• World Foundation Model (1)
• World Foundation Model (2)
• Cloud-based Model Factory
• 4.3 Xiaomi
• Intelligent Driving Simulation Toolchain and Technology System (1)
• Intelligent Driving Simulation Toolchain and Technology System (2)
• ORION Framework (1)
• ORION Framework (2)
• MiLA Framework (1)
• MiLA Framework (2)
• MiLA Framework (3)
• MiLA Framework (4)
• 4.4 Li Auto
• VLA and Simulation (1)
• VLA and Simulation (2)
• Simulation Toolchain Application
• Closed-loop Simulation System
• 4.5 Geely
• Simulation Toolchain (1)
• Simulation Toolchain (2)
• Collaboration of Simulation Toolchain and Technology System
• 4.6 Zhuoyu Technology
• End-to-End World Model (1)
• End-to-End World Model (2)
• Personalized Innovation of GenDrive Generative Autonomous Driving
• Implementation of End-to-End World Model and GenDrive System
• 4.7 Horizon
• (Simulation) Toolchain/Technology System (1)
• (Simulation) Toolchain/Technology System (2)
• Core Test Scenario
• Scenario Construction Strategy
• UMGen: Unified Framework for Multimodal Driving Scenario Generation (1)
• UMGen: Unified Framework for Multimodal Driving Scenario Generation (2)
• UniMM: Multi-agent Simulation
• TTOG Framework (1)
• TTOG Framework (2)
• 4.8 SenseAuto
• Simulation Toolchain
• Technology System
• Cost Reduction through Simulation Toolchain and Technological Innovation
• R-UniAD
• Progress in AI Domain Development
• Mass-Production E2E Solution Framework Diagram
• 4.9 GigaAI
• Profile
• ReconDreamer (1)
• ReconDreamer (2)
• ReconDreamer (3)
• DriveDreamer4D

5 Research on AI-Integrated Intelligent Driving Simulation Technologies

• 5.1 Digital Twin & GNSS Application - Case 1
• 5.2 Integrated Application Analysis of Digital Twin & GIS Technologies in Intelligent Driving
• 5.3 AI-Simulation Convergence - Case 1
• 5.4 AI-Simulation Convergence - Case 2
• 5.5 AI-Simulation Convergence - Case 3
• 5.6 AI-Driven R&D Efficiency - Case 1
• 5.7 AI-Driven R&D Efficiency - Case 2
• 5.8 AI-Driven R&D Efficiency - Case 3
• 5.9 Automated Testing Analysis for Intelligent Cockpit Systems
• Cockpit Testing - Case 1
• Cockpit Testing - Case 2

6 Chinese Simulation Platform and World Model Providers

• 6.1 51WORLD
• EC Master Plan
• Product Portfolio
• 51Sim Solutions
• 51Sim SimOne (1)
• 51Sim SimOne (2)
• 51Sim SimOne (3)
• 51Sim SimOne (4)
• 51Sim DataOne (1)
• 51Sim DataOne (2)
• New AI-driven TIM Platform
• TIM Platform Tunnel Simulation
• TIM TransAI Analysis (1)
• TIM TransAI Analysis (2)
• Customer Deployment Cases
• 6.2 IAE
• Technology Architecture (1)
• Technology Architecture (2)
• Technology Architecture (3)
• Technology Architecture (4)
• Technology Architecture (5)
• Technology Architecture (6)
• Shuimu Lingjing Scenario Factory (1)
• Shuimu Lingjing Scenario Factory (2)
• SCANeR Simulation Platform (1)
• SCANeR Simulation Platform (2)
• DeepOCEAN.AI Platform
• DeepOCEAN.AI: Crab Module (1)
• DeepOCEAN.AI: Crab Module (2)
• Full-element High-fidelity Simulation Analysis
• Coral-Data Open Source Initiative (1)
• Coral-Data Open Source Initiative (2)
• Ecosystem Partnerships
• 6.3 Zhejiang PanoSim
• PanoSimV33 Integrated Platform
• PanoCar Dynamics Software (1)
• PanoCar Dynamics Software (2)
• PanoCar V1.7
• OEM Adoption
• Cooperation Dynamics
• 6.4 Saimo Technology
• Toolchain Architecture & Key OEM Clients
• E2E Safety Validation Solution
• Scenario Application Analysis
• 6.5 Synkrotron.ai
• CARLA 0.10.0 Analysis (1)
• CARLA 0.10.0 Analysis (2)
• CARLA 0.10.0 Analysis (3)
• CARLA-based Development Toolchain
• SYNKROTRON(R) OASIS Data
• OASIS SIM V3.0 (1)
• OASIS SIM V3.0 (2)
• OASIS SIM V3.0 (3): Core Functional Architecture
• OASIS SIM V3.0 AI Traffic Flow Simulation (1)
• OASIS SIM V3.0 AI Traffic Flow Simulation (2)
• Advanced HIL Testing
• OASIS SIM V3.5.0 (1)
• OASIS SIM V3.5.0 (2)
• HIL Solutions (1)
• HIL Solutions (2)
• DIL&VIL Solutions
• BridgeGen Framework (1)
• BridgeGen Framework (2)
• 6.6 PilotD Automotive
• AI Simulation Technologies
• Simulation Testing Product Series (1)
• Simulation Testing Product Series (2)
• Model Library Platform
• 6.7 Shengqi Technology
• Qianxing System V3.0 (1)
• Qianxing System V3.0 (2)
• Intelligent Driving Development Test Platform
• Client Deployment
• 6.8 Keymotek
• Profile
• aiSim E2E Intelligent Driving Simulation Software (1)
• aiSim E2E Intelligent Driving Simulation Software (2)
• aiSim E2E Intelligent Driving Simulation Software (3)
• aiSim E2E Intelligent Driving Simulation Software (4)
• aiSim E2E Intelligent Driving Simulation Software (5)
• aiData Solution (1)
• aiData Solution (2)
• ADAS Spatiotemporal Data Collection Solution (1)
• ADAS Spatiotemporal Data Collection Solution (2)
• Anyverse AI In-Cabin Monitoring Platform (1)
• Anyverse AI In-Cabin Monitoring Platform (2)
• ADTF Framework (1)
• ADTF Framework (2)
• OEM Clients
• 6.9 Tsing Standard
• Profile
• Automotive Ethernet Testing Solutions: Jingling Products
• Automotive Ethernet Testing Solutions: Jingling Products
• Automotive Ethernet Testing Clients
• MW-level Charging Test Equipment
• MW-level Charging Test Equipment Clients
• VCU Test Systems
• VCU Test Systems Cooperative Projects
• Active Suspension Testing Solutions
• Active Suspension Testing Solutions Clients
• 6.10 Jingwei HiRain
• Independent Toolchain
• R&D Services & Solutions
• INTEWORK Series (1)
• INTEWORK Series (2)
• INTEWORK Series (3)
• INTEWORK Series (4): VBA New Version
• Ethernet Testing
• HIL Solutions
• ViL Lab Solution SYNO
• HIL Solution
• Next-gen HIL Platform
• TestBase Platform (1)
• TestBase Platform (2)
• 6.11 Dotrust Technologies
• Profile and Development History
• Testing Capabilities
• Desktop-level OTA Test Solutions
• Vehicle Network Testing
• Automotive V2X Network Test System Customer
• Automotive Ethernet AVB/TSN Development Test Solution
• Automotive Ethernet AVB/TSN Development Test Customer Analysis
• SIL Solution
• SIL Solution Customer Analysis
• Full Vehicle Testing
• Intelligent Driving Simulation Testing
• Intelligent Electronic Control Simulation Testing
• Intelligent Cockpit Simulation Testing
• Intelligent Cockpit Simulation Testing Solution Customer Analysis
• SusPIS Intelligent Cockpit HMI Automated Testing Solution
• Voice Interaction Automated Testing System
• Agent Products
• Typical Customers
• Partners
• 6.12 Vehinfo
• Profile
• Development Dynamics
• LABCAR Platform: Three-Electric Test Bench
• LABCAR Thermal Management HiL System Solution (1)
• LABCAR Thermal Management HiL System Solution (2)
• LABCAR Thermal Management HiL System Solution (3)
• LABCAR HIL Product Equipment Customer (1)
• LABCAR HIL Product Equipment Customer (2)
• YIES Intelligent Test Data Fusion Cloud Platform Solution (1)
• YIES Intelligent Test Data Fusion Cloud Platform Solution (2)
• YIES Customer
• 6.13 Beijing Oriental Jicheng
• New Energy Vehicle Testing Services: In-Loop Simulation & Intelligent Driving Testing
• New Energy Vehicle Testing Services: Intelligent Cockpit & Connectivity Testing
• Active Suspension Test System
• In-Loop Simulation Testing Customer
• Intelligent Driving Testing Customer
• Intelligent Cockpit & Connectivity Testing Customer
• Intelligent Chassis Testing Customer
• High Voltage System Testing Customer
• 6.14 AUMO (ALINX)
• Profile
• AUMO Brand Analysis
• In-Vehicle Simulation Test System AUSIM Customer
• Intelligent Driving HIL Platform AD Station W100
• W100 Customer
• HDMI Video Injection System W51
• HDMI Video Injection System W51/W50
• W51/W50 Customer
• Intelligent Driving Multi-Source Data Acquisition Platform BZ1001
• BZ1001 Customer
• GMSL Video Stream Analyzer VSA100 (1)
• GMSL Video Stream Analyzer VSA100 (2)
• 6.15 Kunyi Electronics
• Profile
• Product Matrix
• Cluster Simulation Test System CubeStack (1)
• Cluster Simulation Test System CubeStack (2)
• Advanced Intelligent Driving Closed-Loop Test Solution
• AD HIL Closed-Loop Test Case (1)
• AD HIL Closed-Loop Test Case (2)
• Cockpit HIL Testing (1): Bus
• Cockpit HIL Testing (2): HMI
• Cockpit HIL Testing (3): RF & Cockpit-Driving Integration
• Simulation Test Solution Customer
• 6.16 KOTEI
  • 6.16.1 Autonomous Driving Test Solution
  • 6.16.2 Intelligent Cockpit Solution
  • 6.16.3 Automotive Electronics Software Testing
  • 6.16.4 AI Simulation Training Platform

7 Foreign Simulation Platform and World Model Providers

• 7.1 NVIDIA
• Automotive Simulation Testing Solutions, Partner OEMs and Project Analysis
• Cosmos(TM) World Foundation Model (WFM) Upgrade (1)
• Cosmos(TM) World Foundation Model (WFM) Upgrade (2)
• Specific Applications of Cosmos Platform in Intelligent Driving (1)
• Specific Applications of Cosmos Platform in Intelligent Driving (2)
• Detailed Analysis of Cosmos Platform (1)
• Detailed Analysis of Cosmos Platform (2)
• Omniverse Blueprint Analysis
• 7.2 UE
• Unreal Engine 5.5 Core Functions
• Automotive Partners and Application Analysis
• Application Case: An Automotive SOC Manufacturer
• Application Case: A Foreign OEM (1)
• Application Case: A Foreign OEM (2)
• 7.3 Unity
• Intelligent Cockpit Solutions
• IVI Suite
• Automotive Customer (1)
• Automotive Customer (2)
• 7.4 Wayve
• Profile
• GAIA-2 (1)
• GAIA-2 (2)
• GAIA-2 Application Value
• GAIA-2 Enabled Customer
• 7.5 APPLE
• GIGAFLOW Analysis (1)
• GIGAFLOW Analysis (2)
• GIGAFLOW Analysis (3)
• GIGAFLOW Analysis (4)
• 7.6 Foretellix
• Main Business
• Data-Driven Intelligent Driving Development Validation Toolchain Foretify (1)
• Data-Driven Intelligent Driving Development Validation Toolchain Foretify (2)
• Data-Driven Intelligent Driving Development Validation Toolchain Foretify (3)
• High-Fidelity Sensor Simulation (1)
• High-Fidelity Sensor Simulation (2)
• Foretify Platform Automotive Customer
• 7.7 Siemens
• Simcenter PreScan Software Version 2503
• Simcenter PreScan Software Automotive Customer
• Simcenter Autonomy Data Solution
• Simcenter Autonomy Data Analysis Automotive Customer
• 7.8 Hexagon
• VTDx Solution
• VTD Simulation Software Analysis
• VTD Simulation Software Automotive Customer
• MSC
• MSC Simulation Product Array
• ADAMS Analysis (Multi-body Dynamics Simulation Software)
• ADAMS Automotive Customer
• ROMAX Simulation Software
• ROMAX Simulation Software Automotive Customer
• 7.9 KISSsoft (Gleason)
• Simulation Software Analysis
• Simulation Software Automotive Customer
• 7.10 AVL
• Profile
• 2024R2 New Version
• AI Simulation Assistant ChatSDT
• DevOps Pilot(TM)
• DevOps Pilot(TM) Automotive Customer
• Scenario Simulator(TM) Automotive Customer
• SCENIUS(TM) Toolchain Automotive Customer
• PreonLab Meshless Simulation Software
• PreonLab Meshless Simulation Software Automotive Customer
• EXCITE M
• EXCITE M Automotive Customer
• CRUISE(TM) M
• CRUISE(TM) M Automotive Customer
• FIRE
• FIRE Automotive Customer
• VSM
• VSM Automotive Customer
• 7.11 VECTOR
• Software Product Series (1)
• Software Product Series (2)
• Hardware Product Series (1)
• Hardware Product Series (2)
• Hardware Product Series (3)
• XiL Verification System
• SiL Application Analysis
• SiL Automotive Application Analysis
• SiL Latest Partner (1)
• SiL Latest Partner (2)
• SiL Latest Partner (3)
• SiL Latest Partner (4)
• CANoe Automotive Field Partnership
• DYNA4 Automotive Field Partnership
• vTESTstudio Automotive Field Partnership
• 7.12 IPG Automotive
• Profile
• CarMaker14.0 Version Feature Highlights
• CarMaker Partner (1)
• CarMaker Partner (2)
• Driving Simulator Platform Solution SEP Partner Customers
• Cloud Simulation Platform VIRTO Partner Customers
• Digital Twins Partner Customers
• AV HIL Partner Customers
• CarMaker Office Extended (1)
• CarMaker Office Extended (2)
• 7.13 dSPACE
• Profile
• AURELION New Version 24.3 (1)
• AURELION New Version 24.3 (2)
• PC-based VEOS Simulation Platform Analysis
• PC-based VEOS Accelerated Software Testing Cases
• Intelligent Driving Solutions: AURELION, DARTS & RADAR Testbench
• Intelligent Driving Solutions: AUTERA & RTMaps
• Intelligent Driving Solutions: Data Replay Solution
• Intelligent Driving Solutions: ADAS/AD SIL Solution
• Intelligent Driving Solutions: SIMPHERA
• SIL Testing Solution Customer
• ADAS/AD HIL Solution
• ADAS/AD HIL Solution Customer
• dSPACE HIL SCALEXIO Product Portfolio
• MicroAutoBox III (1)
• MicroAutoBox III (2)
• MicroAutoBox III Main Advantages and Functions
• Electric Drive Series Products and Solutions
• Electric Drive SIL Testing Customer
• Electric Drive HIL Solution
• Electric Drive HIL Solution Customer
• 7.14 MathWorks
• Profile
• MATLAB/Simulink R2025a Version Update (1)
• MATLAB/Simulink R2025a Version Update (2)
• MATLAB/Simulink & Polyspace New Version Comparative Analysis
• MATLAB/Simulink and Polyspace Automotive Customer
• MATLAB/Simulink and Polyspace Accelerating SDV Development
• MATLAB/Simulink Intelligent Chassis Virtualization Development and Validation
• MATLAB/Simulink Application Case 1
• MATLAB/Simulink Application Case 2
• MATLAB/Simulink Application Case 3
• MATLAB/Simulink Application Case 4
• MATLAB/Simulink Application Case 5
• Simscape
• Simscape Battery(TM)
• Simscape
• Simscape Automotive Customer
• 7.15 LeddarTech
• Profile
• LeddarSim(TM) New Generation Simulation Platform
• LeddarSim(TM) Customer
• LeddarVision Software Analysis (1)
• LeddarVision Software Analysis (2)
• LeddarVision Customer
• 7.16 VI-Grade
• VI-grade2025.1 Software Version Release (1)
• VI-grade2025.1 Software Version Release (2)
• VI-grade2025.1 Software Version Release (3)
• VI-CarRealTime 2024.2 Version
• VI-CarRealTime Customer
• VI-CarRealTime Partnership Case 1
• VI-CarRealTime Partnership Case 2
• Driving Simulator Matrix
• Driving Simulator Partnership Cases
• DiM FSS
• DiM FSS Customer
• DiM FSS Partnership Case 1
• DiM FSS Partnership Case 2
• AutoHawk Extreme & VPG
• Compact HMI Simulator
• Compact HMI Simulator Customer
• VR/MR Integration Accelerating HMI Development
• 7.17 NI (EMERSON)
• Profile
• Testing Software: LabVIEW (1)
• Testing Software: TestStand & G Web Development Software
• Testing Software: DIAdem & FlexLogger Software
• Testing Software: InstrumentStudio
• Testing Software Customer
• DAQ Hardware: mioDAQ
• DAQ Hardware: CompactDAQ
• PXI Testing System
• PXI DAQ
• DAQ Hardware Customer
• Powertrain Bench Automation Testing System (1)
• Powertrain Bench Automation Testing System (2)
• Powertrain Bench Automation Testing System Customer
• In-Vehicle Communication Testing Platform
• In-Vehicle Communication Testing Platform Customer
• Smart Camera Testing Solution (1)
• Smart Camera Testing Solution (2)
• Smart Camera Testing Solution Customer
• 7.18 Ansys (Synopsys)
• Profile
• Ansys 2025 R1 Version
• AVxcelerate Autonomy
• AVxcelerate Headlamp
• AVxcelerate Sensors
• TwinAI(TM) for Digital Twins Customer
• Speos Customer
• HFSS Software Customer
• LS-DYNA Software Customer
• medi analyze Software Customer
• Ansys Enabling EPS Efficient Development Case