Autonomous Driving Simulation Industry Chain Report, 2019-2020 (I)
  • Mar.2020
  • Hard Copy
  • USD $3,400
  • Pages:160
  • Single User License
    (PDF Unprintable)       
  • USD $3,200
  • Code: THC001
  • Enterprise-wide License
    (PDF Printable & Editable)       
  • USD $4,800
  • Hard Copy + Single User License
  • USD $3,600
      

Autonomous driving (AD) simulation: a market impossible to be ruled by IT giants

After the pioneers Baidu and Tencent in the AD simulation market, Huawei Technologies Co., Ltd follows suit and forays into it, getting small- and medium-sized players cornered.

In this report, conclusions are drawn from our insights into AD simulation.

As manufacturing is growing digital and transferring to a software-enabled industry, industrial software becomes the heart of digital manufacturing, so does for the automotive sector. Industrial software tends to be a platform facilitating industrial digitalization, networking and intelligent transformation and where small applications will run.

Industrial software segments feature complex processes, rather high thresholds and long cycles. For the IT giants, they have neither first-mover advantage nor much late-developing advantage. AD simulation software is also subject to industrial software, into which IT firms set foot and will find their incompetence, while the traditional simulation tycoons not only excel in simulation of auto parts but spare no effort in AD simulation.

It is mentioned in our study a year ago that: traditional simulation leaders keep expanding through mergers and acquisitions, boasting dozens to hundreds of product varieties that have been found in dozens of industries. For instance, ANSYS leads the pack in the CFD market, develops embedded codes, beefs up chip packaging design, and enriches internal combustion engine (ICE) simulation products through more than ten acquisitions of peers in the industry.

In 2019, ANSYS acquired British Granta Design, and American Utah-based 3DSIM, a developer of additive manufacturing (3D printing) simulation technologies. 3DSIM brings ANSYS the sole complete additive manufacturing (AM) process inside the industry. Granta Design helps to have the product portfolios of ANSYS applied to key fields. Granta Design provides customers with all kinds of important material data and enables them to visit Granta’s material intelligent database system. Granta Design has products including Granta MI, a system used for enterprise material information management, and CES Slector that allows the user to grope for influence of different materials on its product behavior. Granta Design has a broad range of clients such as Airbus, General Motors, Emerson, Lockheed Martin, NASA, Saudi Aramco, and Rolls-Royce.

Traditional simulation giants builds up autonomous driving simulation technologies

Just like automakers striving to be mobility providers and recruiting software engineers aggressively, the traditional simulation companies are also improving their weaknesses. ANSYS purchased Optics in 2018 and strengthened sensor (LiDAR, camera, radar, etc.) simulation technologies, becoming a real blockbuster in the AD simulation market.

Automated Driving Toolbox of MathWorks R2019b version is added with 3D simulation support and fulfills the integrated simulation of Simulink model with the camera, LiDAR or radar sensor model in Unreal Engine, rapidly partitioning the 3D point cloud data from LiDAR.

In February 2019, Vector acquired TESIS GmbH. TESIS DYNA4 starts to be fully integrated with Vector’s product lineup. The latest version of TESIS DYNA4 is added with single vertical scanning LiDAR model, supportive for the geo-reference road network of World Geodetic System WGS84, and used for simulation of GPS receiving and V2X.

In May 2019, IPG unveiled CarMaker 8.0 and rolled out sensor model LiDAR RSI, Camera RSI camera model additional with “to gain semantic segmentation image data” feature, allowing introduction and use of road network from the OpenDrive format.

The most professional Chinese testing institutions team up with overseas simulation companies to build AD simulation laboratories and provide services to domestic customers by leveraging world’s state-of-the-art technologies. In February 2019, China Automotive Technology & Research Center Co., Ltd (CATARC) collaborated with IPG on building driving scenario simulation joint laboratory. In November 2019, China Automotive Engineering Research Institute Co., Ltd. (CAERI) partnered with Hexagon, NI and Konrad Technologies to jointly set up i-VISTA intelligent connected vehicle joint simulation and test laboratory.

Why can’t IT giants rule the autonomous driving simulation market?

Although they are competitive in simulation software development, distributed computing, scene building, chip research and development, etc., IT giants have shortcomings as follows:

(1) As far as autonomous driving hardware is concerned, Chinese IT giants are left at least ten years behind foreign leading companies. As for autonomous driving software technology, there is a narrow gap between Chinese and foreign brands, but a wide gap of more than a decade particularly in chassis and chip. The absence of rich data about core components of vehicle and technical accumulation make it impossible to control the vehicle accurately.
(2) With regard to automotive simulation technology, Chinese IT giants are left dozens of years behind foreign leading companies. Automotive simulation is a fusion of technologies about computer graphics, multimedia, sensors, optics & display, materials, electronic semiconductors, kinetics, to name a few. Most Chinese IT firms are only familiar with a few disciplines.
(3) Foreign simulation leaders has decades of rich experience in developing customers. Once an automotive simulation client selects a certain simulation technology, it is hard to change. With loyal clientele, the traditional simulation vendors keep abreast of the real demand in real time and convert it into products and services swiftly.
(4) Autonomous driving simulation is in essence the upgrade of traditional automotive simulation. Figuratively, traditional automotive simulation has already built a 100-storey building, and only 10 storeys needing building can make it in autonomous driving simulation. Chinese IT giants can build the 101st-110th storeys but must build them on the already 100-storey, and they are enslaved. Wishing for a new building, they have to start from scratch.

So, it is useless for Chinese IT giants (except Huawei) to rebuild a simulation technology system. Even if it succeeds in building its own simulation software system, Huawei will apply the system in specific field rather than dominate the market.

Where are the opportunities for Chinese AD simulation competitors?

The aforementioned big platform and small application are the trend of industrial software (incl. simulation software). Baidu and Tencent seem to be competent enough to make big platform, but they are impossible to make a fresh start and have no choice but to join the existing simulation technology system. Tencent and Baidu with superiorities in cloud platform and HD map are improving traditional simulation technologies and products through all-round cooperation with traditional simulation technology providers on the one hand and using the newest AI and cloud computing technologies on the other hand.

For example, Baidu is improving its weakness in dynamics simulation amid introducing AADS system as concerns the ‘realness’ of simulation.

In July 2019, Apollo was souped up to 5.0 edition with the addition of vehicle dynamics models. Apollo 5.0 has the vehicle dynamics modeling approach (constraints in the model’s complexity, precision, transferability and scalability, etc.) upgraded to the machine learning based Apollo dynamics model (high complexity, high accuracy, etc.). It is said by Baidu that the errors take a nosedive of 80% compared with the traditional modeling outcome.

The most advanced method of simulation system is to create driving scenes by using games engine. However, the CG (Computer Graphics) from the games engine rendering differs from the real scene shooting in richness and truth, degrading the performance of CG-trained autonomous driving algorithms in real scene. The AADS system, jointly developed by the University of Maryland, Baidu Research Institute and the University of Hong Kong, not only cuts the testing costs of simulation system considerably but undergoes a substantive leap in realness and scalability.

Except IT tycoons, small and medium simulation tech firms are supposed to give up big platform poise and transfer to focus on small application as an integral of the platform, in a bid to get the platform enriched and flexible use.

Beyond simulation platform, there are the AD simulation segments such as road environment simulation, traffic scene simulation, weather simulation, sensor simulation and facsimile system interface, to all of which the small and medium players can access. The opportunities here will be seen in our to-be-soon research report – Autonomous Driving Simulation Industry Chain Report, 2019-2020 (II). 

1. Autonomous Driving (AD) Simulation
1.1 Simulation Technology
1.1.1 Overview
1.1.2 Drivers for Automotive Simulation
1.2 AD Simulation and Test
1.2.1 AD Simulation Test and Methods
1.2.2 AD Test Needs Computer Simulation
1.2.3 Classification of AD Simulation Software
1.2.4 Scenario-based ADAS/AD Test and Verification Tool Chain
1.2.5 Structure of AD Simulation Industry Chain
1.2.6 Contents of AD Simulation
1.2.7 AD System Simulation Model
1.2.8 Composition of Simulation Test System
1.2.9 Renault AD Simulation Tool Chain
1.2.10 Challenges to AD Simulation
1.3 Segmentation of AD Simulation
1.3.1 Road and Weather Simulation
1.3.2 Traffic Scene Simulation (Traffic Flow Simulation)
1.3.3 Sensor Simulation
1.3.4 Vehicle Dynamics Simulation
1.3.5 Simulation System Interfaces
1.3.6 Distributed Simulation Platform
 
2. Integrated Simulation Platform and Company Study
2.1 Introduction to Simulation Platform
2.1.1 Typical Composition of Simulation Platform
2.1.2 Competition in Simulation Platform between IT Firms and Traditional Simulation Companies
2.2 ANSYS
2.2.1 Profile
2.2.2 ANSYS’ Acquisition of OPTIS
2.2.3 ANSYS’ Cross-industry Acquisitions to Improve Simulation Industry Chain
2.2.4 Background of the Acquired Companies by ANSYS
2.2.5 ANSYS’ More Input in Operation and R&D
2.2.6 AD Solutions and Products of ANSYS
2.2.7 Significance of ANSYS’ Acquisition of OPTIS
2.2.8 ANSYS 2019 R3
2.2.9 ANSYS SCADE
2.2.10 Partners of ANSYS
2.2.11 Dynamics in ANSYS’ Collaborations
2.3 Siemens
2.3.1 AD Simulation Layout
2.3.2 Major Products
2.3.3 Siemens’ Acquisition of TASS
2.3.4 Functional Features of PreScan
2.3.5 AD Simulation Use of PreScan
2.3.6 Running Process of PreScan
2.3.7 Sensor Types and Some Scenarios Enabled by PreScan
2.3.8 External Tools and Software Favored by Prescan
2.3.9 Scenario Sources Favored by Prescan
2.4 NVIDIA Simulation Platform
2.4.1 NVIDIA Drive Constellation
2.4.2 Attributes of NVIDIA Drive Constellation
2.4.3 Data Exchange between Drive Constellation and Target Vehicle
2.4.4 DRIVE Constellation and DRIVE Sim
2.4.5 NVIDIA Simulation Platform Composition
2.4.6 Broad Partnership
2.5 Gazebo
2.5.1 Open Simulation Platform -- Gazebo
2.5.2 Functionality and Use of Gazebo
2.5.3 Merits of Gazebo
2.6 Carla
2.6.1 Introduction to Carla
2.6.2 Carla Building of Different Scenarios
2.6.3 Latest Version of Carla
2.6.4 Functional Highlights of Carla
2.7 China Automotive Technology and Research Center Co., Ltd. (CATARC)
2.7.1 Profile of CATARC
2.7.2 CATARC Simulation Platform
2.7.3 CATARC Scene Platform
2.7.4 Collaboration between CATARC and IPG on Building a Driving Scene Simulation Job Lab
2.8 China Automotive Engineering Research Institute Co., Ltd. (CAERI)
2.8.1 CAERI Layout in Simulation Test Platform Tool Chain
2.8.2 i-Collector
2.8.3 i-Transfomer and i-Creator
2.8.4 ADAS HIL Integration and Test Services
2.8.5 Building AD Simulation Data Crowdsourcing & Testing Service Cloud Platform
2.9 Baidu Apollo Distributed Simulation Platform
2.9.1 Apollo Simulation Platform
2.9.2 Apollo Simulation Engine
2.9.3 ApolloScape
2.9.4 Apollo Control-in-the-loop
2.9.5 Apollo Vehicle Dynamics Model Simulation
2.9.6 AADS System
2.9.7 Two Superiorities of AADS
2.9.8 Collaborations with Apollo Simulation Platform
2.10 Tencent TAD Sim
2.10.1 Autonomous Driving Layout of Tencent
2.10.2 TAD Sim Simulation Platform
2.10.3 Characteristics of TAD Sim Simulation Platform
2.10.4 High-fidelity Scenarios of TAD Sim
2.10.5 Sensor Simulation of TAD Sim Simulation Platform
2.10.6 Simulation of Complex Road Conditions
2.10.7 Cloud Acceleration Simulation, CIVS (Cooperative Vehicle Infrastructure System) Simulation, 3D City Rebuilding
2.10.8 Application of TAD Sim Simulation Platform
2.11 Panosim
2.11.1 Profile
2.11.2 Major Products
2.11.3 Key Customers
2.11.4 PanoSim Based on Physical Model and Numerical Simulation
2.11.5 PanoSim Interface and Functions
2.11.6 PanoSim Used to Create Simulation Experiment Flow
2.11.7 PanoSim 3.0 Added with Radar Model and GPS Physical Model
2.11.8 PanoSim 3.0 - V2X and True Value Sensor Function Upgrade
2.11.9 PanoSim3.0 Optimized Simulink Model
2.12 AirSim
2.12.1 Open Simulation Platform -- AirSim
2.12.2 AirSim on Unity
2.12.3 Features of AirSim Simulator
2.13 51World
2.13.1 Profile of 51WORLD
2.13.2 51Sim-One
2.13.3 In-built Vehicle Dynamics System
2.13.4 Application of 51Sim-One
2.13.5 AD Simulation Partners
2.13.6 51WORLD EC (Earth Clone)
 ........

3. Vehicle Dynamics Simulation
3.1 Introduction to Vehicle Dynamics Simulation
3.2 MATLAB/Simulink
3.2.1 Introduction to Mathworks and Simulink
3.2.2 Product Packets
3.2.3 Simulink-based AEB and FCW System
3.2.4 ADST
3.2.5 Various Models of Simulink
3.2.6 Driving Scenario Designer
3.2.7 Vehicle Dynamics Blockset
3.2.8 Key Modules of Vehicle Dynamics Blockset
3.2.9 Cases of Use for Close-loop Simulation Test
3.2.10 Use in Voyage
3.2.11 New Features
3.3 Simpack
3.3.1 Introduction to Simpack
3.3.2 Simpack Real-time Simulation Tools
3.3.3 Simpack Automotive
3.3.4 Simpack Automotive Modeling Features
3.3.5 Simpack Use in ADAS
3.3.6 New Functions
3.4 TESIS DYNAware
3.4.1 Profile of TESIS
3.4.2 TESIS DYNAware
3.4.3 veDYNA Real-time Simulation of Vehicle Dynamics
3.4.4 ve-DYNA Model
3.4.5 DYNA4 Software
3.4.6 DYNA4 Software Functionality
3.4.7 DYNA4 Simulation Scene
3.4.8 Latest Trends of DYNA4
3.4.9 New Functions of DYNA4
3.5 IPG Carmaker
3.5.1 Profile of IPG Carmaker
3.5.2 Products Backed by IPG Carmaker
3.5.3 Characteristics of IPG Carmaker
3.5.4 Roll-out of IPG Carmaker 8.0
3.5.5 Latest News about IPG
3.6 AVL
3.6.1 Profile
3.6.2 AVL CRUISE
3.6.3 AVL Automotive Test Simulation Platform
3.6.4 AVL model.Connect
3.6.5 Features and Application of AVL model.Connect
3.6.6 AVL DRIVINGCUBE
3.6.7 AVL Autonomous Driving Simulation Developments
 

Global and China Automotive Gateway Industry Report, 2019-2020

Automotive Gateway Industry Research: Tenfold Improvement in Gateway Performance Breaks the Bottleneck of Software-defined Vehicles. Automotive gateway chip is actually a field with scarcely ever cha...

Automotive Vision Industry Chain Report (II) Binocular and Others

Visual Perception Algorithms Become Crucial Automotive cameras are divided into perception cameras and video cameras, according to Sunny Optical. Perception camera, used for active safety (generally...

Global and China Tire Pressure Monitoring System (TPMS) Industry Report, 2020-2026

TPMS OEM prevails across the world, with its market size reaching 59.2 million units and the installation rate at 64.5% (an increase of 4.9 points from a year ago) in 2019 as TMPS needs to be installe...

Automotive High-precision Positioning Research Report, 2019-2020

High-precision Positioning Research: Competition from Chips, Terminals to Ground-based Augmentation Stations Autonomous driving prompts the use of high-precision positioning technology in the realm o...

Shared Mobility Industry Research--Autonomous Driving Leads Shared Mobility 3.0

The global shared mobility industry is experiencing a hard time. It is since 2019 that shared mobility enterprises have been exposed to financial fragility and have closed down one after another amid ...

Automotive Vision Industry Chain Report 2019-2020 (I): Monocular Vision

Automotive Vision Industry Chain Report 2019-2020 (I): The front-view monocular camera market soared 95.6% year-on-year in 2019 About 23 million cameras were pre-installed in new passenger cars in Ch...

China Automotive Financial Leasing Industry Report, 2020-2026

After ceaseless decline in 2018 and 2019, the Chinese automobile industry ushers in a period of recovery when the consumers are more prudent to buy cars and automobile consumer finance draws more atte...

Autonomous Driving Simulation Industry Chain Report, 2019-2020 (II)

Autonomous Driving Simulation (II): It Turns Out to Be a Battlefield of GiantsAlibaba DAMO Academy unveiled in early 2019 the "Top Ten Technology Trends of 2019", most of which are still credible toda...

Automotive Radar Dismantling and Cost Analysis, 2019-2020

It is in this report that over a dozen of millimeter-wave radar types are studied on design, supply chain and cost, including Continental’s ARS4A, ARS4B, ARS408 and ARS410, Bosch’s LRR4, FR5CP, MRR1PL...

Global and China L4 Autonomous Driving Industry Report, 2019-2020

Giants gain high finance.Progress of L4 autonomous driving is greatly hampered over the recent two years, causing OEMs’ and Tier 1 suppliers’ delay in L4 launches. Yet, the top L4 companies still rais...

Automotive Domain Control Unit (DCU) Industry Report, 2019-2020

Domain control unit shipments will boom in 2021. When the one-to-one correspondence between the growing number of sensors and electronic control units (ECU) leads to underperforming vehicles and adds...

Global and China Automotive Millimeter-wave (MMW) Radar Industry Report, 2019-2020

Millimeter wave radar installations soared by 44.37% year-on-year in 2019 and were available in more scenarios, encroaching on Lidar and ultrasonic. Automotive radar wins popularity and gets increasi...

ADAS and Autonomous Driving Tier 1 Suppliers Report, 2019-2020

Tier 1 suppliers for autonomous driving: Chinese Tier 1 suppliers have not embarked on the actuation layer, and L3 will spread after 2022 Amid the controversy in L3, some media believe that Audi will...

Global and China Automotive Operating System (OS) Industry Report, 2019-2020

With advances in smart cockpit and intelligent driving, and enormous strides of Tesla, OEMs care more about automotive operating system (OS). Yet, it is by no means easy for both new carmakers and tra...

Global and China Low Speed Autonomous Driving Industry Report, 2019-2020

In 2019, low speed autonomous driving market tended to calm down, with more regular pilots but on small scale. In 2020, the COVID-19 pandemic brings new opportunities to low speed autonomous delivery ...

Special Vehicle Autonomous Driving Industry Report, 2019-2020

Autonomous mining vehicle and autonomous sanitation vehicle markets take off. This report highlights progress of autonomous working vehicles in four fields: sanitation, airport, agriculture and minin...

Automated/Autonomous Parking Industry Report, 2019-2020

Why is the installation rate of automated parking not high? Automated parking was found in 7.7 percent of passenger cars in China in 2019, according to the data from ResearchInChina. As shown in t...

Global and China Li-ion Power Battery Industry Report, 2019-2025

Amid the thriving development of new energy vehicles, a total of 2,209,831 electric vehicles were sold globally in 2019, a year-on-year spurt of 14.5% and as a percentage of 2.5% in total automobile s...

2005- www.researchinchina.com All Rights Reserved 京ICP备05069564号-1 京公网安备1101054484号