DUBLIN, April 29, 2021 /PRNewswire/ — The “Autonomous Driving Simulation Industry Chain Report, 2020-2021 (I)” report has been added to ResearchAndMarkets.com’s offering.
Autonomous Driving Simulation Research: Foreign giants build closed-loop simulation platforms, while domestic companies focus on the construction of scenario library
In the development of high-level autonomous driving, the importance of simulation testing becomes more and more apparent. From 2020 to 2021, both foreign and domestic companies stepped up the layout in the field of autonomous driving simulation.
Foreign simulation giants are committed to building closed-loop simulation platforms for setting up industrial barriers
In the transition from industrial simulation to autonomous driving simulation, giants such as Ansys and Siemens have established various modules of autonomous driving simulation through continuous acquisition, cooperation and technological development, strengthened the closed-loop of the simulation platform, and built industrial barriers. At present, the layout of foreign leading companies has covered more than 80% of the simulation sector, and which is continuously updated.
From 2020 to 2021, top foreign simulation companies updated and optimized the following sectors
At present, Chinese companies such as Tencent, CATARC, CAERI, Baidu, 51World have established their own autonomous driving simulation scenario libraries.
Tencent: More than 99% of autonomous vehicle simulation scenarios can be covered
Based on powerful game engine capabilities, Tencent’s autonomous driving simulation platform TAD Sim performs excellently in the reality and accuracy of scenarios. Its scenario generation system can derive 20 million virtual scenarios based on 2,000 types of logic scenarios, covering more than 99% of automated vehicle simulation scenarios.
In June 2020, Tencent released TAD Sim 2.0, the new generation of its autonomous driving simulation platform, to improve the development and testing efficiency of autonomous driving. Compared with the previous generation, TAD Sim 2.0 fills the gap between road test data and virtual scenarios. With higher resolution in 3D scenario reconstruction and sensor simulation, the platform can make the simulation closer to reality. A huge variety of environments, weather conditions and even extreme traffic conditions can be generated by combining road test data and virtual scenarios to fulfill the needs of autonomous driving testing in TAD Sim 2.0.
However, Tencent will not stop at autonomous driving. Its further layout is to further explore its own capabilities, build virtual twin cities, and facilitate smart cities and smart transportation. Specifically, it will integrate its game technology, cloud technology, and simulation technology to create a virtual twin platform so as to realize the mapping between the real world and the virtual world, and self-learn and update in the virtual world. In the future, it will achieve iteration, prediction, decision-making and other capabilities.
CATARC: AD Scenario Generator debuts, and the built-in scenario library covers 4,000 Scenarios
CATARC’s self-developed simulation platform AD Chauffeur has a built-in scenario library covering natural driving scenarios, standard and regulatory scenarios, CIDAS dangerous accident scenarios and experience restructuring scenarios, etc.
The AD Chauffeur 2.0 released by CATARC in September 2020 adds the AD Scenario Generator, which enables scenario construction, the conversion of multi-source data formats OpenSCENARIO, logical scenario splicing and reorganization to support scenario generation. At the same time, it expands the built-in scenario library to cover 4,000 scenarios, which is convenient for clients.
CAERI: typical accident scenarios, autonomous driving accident scenarios, and expected functional safety scenarios are added
In December 2020, CAERI released the “”i-VISTA China Typical Driving Scenario Library V3.0″”. Based on the natural driving scenarios, standard and regulatory scenarios, experience scenarios and a small number of accident scenarios in the previous version, CAERI added typical accident scenarios, autonomous driving accident scenarios, and expected functional safety scenarios. It supports autonomous driving simulation test and evaluation, and application to simulation systems such as MIL, SIL, and HIL.
In addition to the above-mentioned companies, Baidu exploits Apollo technology to establish a simulation scenario library. 51World’s “”Urban All-Element Scenario Automation Platform (AES2021)”” has improved the coverage and accuracy of scenarios.
Generally speaking, Chinese companies are still fighting their own way in the construction of scenario libraries, facing problems such as inconsistent data on scenarios, difficulty in establishing an evaluation and certification system of autonomous driving simulation & test. Therefore, the establishment of scenario library standards has become one of the current concerns in the field of simulation.
Key Topics Covered:
1. Introduction to Autonomous Driving Simulation
1.1 Overview of Simulation Technology
1.2 Significance of Simulation Testing to Autonomous Driving R&D
1.3 Types of Autonomous Driving Simulation Technology
1.4 Composition of Autonomous Driving Simulation Software
1.5 International Autonomous Driving Simulation Standardization Organization
1.5.1 Introduction to ASAM
1.5.2 Dynamic of ASAM
1.5.3 C-ASAM Working Group
1.5.4 Standards and Roadmap of ASAM
1.5.5 ASAM’s OpenX Series Standards
1.5.6 ASAM’s New Standards for Advanced Autonomous Driving
1.6 Status Quo of China’s Autonomous Driving Simulation Test Standards
1.6.1 National Autonomous Driving Road Test Standards
1.6.2 Provincial and Municipal Autonomous Driving Road Test Standards
1.7 Status Quo of China’s Participation in the Development of International Standards for Autonomous Driving Test Scenarios
1.8 Autonomous Driving Simulation Layout of OEMs
2. Autonomous Driving Simulation Platforms and Companies
2.1 Typical Components of Integrated Simulation Platform
2.2 Overview of Simulation Software System
2.3 Comparison of Key Foreign Companies
2.4 Comparison of Key Domestic Enterprises
2.5 ANSYS
2.5.1 Profile
2.5.2 Product Distribution
2.5.3 Simulation Capabilities Enhanced by Investment and Acquisition
2.5.4 Investment and Acquisition
2.5.5 Autonomous Driving Simulation Tool Chain
2.5.6 ANSYS SCADE
2.5.7 ANSYS SCADE Suite
2.5.8 ANSYS VRXPERIENCE
2.5.9 Update of ANSYS 2021 R1
2.5.10 Partners
2.5.11 Cooperation
2.5.12 Planning – 5G on Autonomous Vehicles
2.6 Siemens
2.6.1 Profile
2.6.2 Autonomous Vehicle Solutions
2.6.3 Expansion in ADAS and Autonomous Driving Simulation – Acquisition of Tass
2.6.4 PreScan
2.6.5 Sensor Model of Prescan
2.6.6 Sensor Types and Some Scenarios Supported by PreScan
2.6.7 PreScan Autonomous Driving Simulation and Detailed Functions
2.6.8 Update of PreScan in 2020
2.6.9 PreScan Autonomous Driving Simulation and Detailed Functions– Applications
2.6.10 PAVE360
2.6.11 Customers
2.6.12 Cooperation
2.7 NVIDIA
2.7.1 Profile
2.7.2 Simulation Solution: DRIVE Constellation
2.7.3 Drive Sim Software
2.7.4 Computing Module: DRIVE AGX Pegasus
2.7.5 NVIDIA DRIVE PX Pegasus AI Computing Platform
2.7.6 Cooperation
2.8 CARLA
2.8.1 Profile
2.8.2 Basic Structure
2.8.3 Product Features
2.8.4 Carla 0.9.11
2.8.5 Update in 2020
2.9 AVSimulation
2.9.1 Profile
2.9.2 Simulation Software: SCANeR
2.9.3 SCANeR studio 1.9
2.9.4 SCANeR studio 2021.1
2.9.5 Cooperation
2.10 LGSVL
2.10.1 Open-source Simulation Solution: LGSVL
2.10.2 LGSVL 2020.06
2.11 Panosim
2.11.1 Profile
2.11.2 Simulation Solution: PanoSim
2.12 AirSim
2.12.1 Open-source Simulation Solution: AirSim
2.12.2 Update of AirSim in 2020
2.13 51World
2.13.1 Profile
2.13.2 51Sim-One1.3
2.13.3 Update of 51Sim-One 2.0
2.13.4 Cooperation
2.14 Huawei
2.14.1 Profile
2.14.2 Autonomous Driving Simulation Platform: Octopus
2.14.3 Octopus — Combination of cloud + AI + software and hardware + chips
2.14.4 Ascend 910 AI Chip
2.15 Baidu
2.15.1 Apollo Simulation Platform
2.15.2 Apollo Scenario Library
2.15.3 AADS
2.15.4 Cooperation
2.16 Tencent
2.16.1 Autonomous Driving Layout
2.16.2 TAD Sim Simulation Platform — Comprehensive Combination of Game Technology and Autonomous Driving Simulation
2.16.3 TAD Sim Environment Simulation
2.16.4 TAD Sim Sensor Simulation
2.16.5 TAD Sim2.0
2.16.6 Autonomous Driving Simulation Derivation — Urban Simulation Platform
2.16.7 Cooperation
2.17 Alibaba
2.17.1 Autonomous Driving Layout
2.17.2 AutoDrive Platform
2.17.3 Hybrid Simulation Test Platform
2.18 BATH Simulation Business Comparison
2.19 China Automotive Technology & Research Center (CATARC)
2.19.1 Profile
2.19.2 Driving Scenario Simulation Platform
2.19.3 Autonomous Driving Simulation Cloud Platform: AD Chauffeur2.0
2.20 China Automotive Engineering Research Institute Co., Ltd. (CAERI)
2.20.1 Profile
2.20.2 Integrated Solutions of Scenario Library and Simulation system
2.20.3 Virtual Simulation Scenario Library: i-Scenario
2.20.4 i-VISTA Typical Driving Scenario Library in China
2.20.5 Self-developed Software Toolchain — Smart Driving Scenario Generate Software, Smart Driving Test and Evaluation Software
2.20.6 i-STAR Data Processing Cloud Platform
2.20.7 Data Collection: i-Collector
2.20.8 Cooperation
2.21 Saimo
2.21.1 Profile
2.21.2 Simulation Test Platform Construction
3. Vehicle Dynamics Simulation
3.1 Vehicle Dynamics Simulation
3.2 Vehicle Dynamics Enterprises
3.3 IPG Carmaker
3.3.1 IPG Automotive
3.3.2 CarMaker
3.3.3 Application of CarMaker in ADAS Development
3.3.4 Customers of CarMaker
3.3.5 CarMaker 9.0
3.3.6 Cooperation
3.4 Carsim
3.4.1 Kinetics Simulation Software: CarSim
3.4.2 Update of CarSim
3.5 AVL
3.5.1 Profile
3.5.2 AVL CRUISE
3.5.3 AVL Smart ADAS Analyzer
3.5.4 Cooperation
3.6 Simpack
3.6.1 Products
3.6.2 Automotive Application
3.6.3 Update of SIMPACK 2021X
3.7 TESIS DYNAware
3.7.1 TESIS and Products
3.7.2 TESIS DYNAware
3.7.3 Application Scenarios of DYNA4
3.7.4 Update of DYNA4 4.0
3.8 MATLAB/Simulink
3.8.1 Products
3.8.2 Automotive Solutions
3.8.3 Vehicle Dynamics Blockset
3.8.4 Automated Driving Toolbox
3.9 VI-Grade
3.9.1 Profile
3.9.2 VI-CarRealTime
3.9.3 DiM DYNAMIC Simulator
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