Intelligent Driving Simulation and World Model Research Report, 2025

Description

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).

Product Code: FZQ019

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