Dublin, March 20, 2019 (GLOBE NEWSWIRE) -- The "Autonomous Driving High-Precision Positioning Industry Report, 2018-2019" report has been added to ResearchAndMarkets.com's offering.
Solving the problem of establishing where a vehicle is (initial position) and where it is going (target position) is key to autonomous driving. Autonomous driving at a high level demands centimeter-level positioning technology. High-precision positioning technology, therefore, plays a vital role in autonomous driving above L3.
High-precision positioning technology for autonomous driving is classified by positioning method into the three types as follows:
- Signal-based positioning technology such as global navigation satellite system (GNSS), UWB and 5G;
- Dead reckoning, an IMU-based technology that reckons the current position and direction of a vehicle after learning where it was;
- Environmental feature matching, or LiDAR and vision sensor-based positioning, that is, matching features observed with those stored in a database to know where the vehicle is and what it looks like.
Among signal-based positioning methods, GNSS and 4G/5G are often used for outdoor positioning and UWB for indoor positioning.
After comparing different positioning technologies, 5G and vehicle body sensor fusion (combining radar, camera, LiDAR, and map) emerge as the two optimal solutions for L4/L5 autonomous driving in densely populated areas.
Satellite positioning, however, is more suited to sparsely populated places where it is impossible to build 5G base stations on a large scale.
GNSS with meter-level positioning accuracy falls far short of autonomous driving. Centimeter-level satellite positioning is required to correct GNSS positioning errors caused by the ionosphere, which is often done by real-time kinematic (RTK), a technology which has evolved from a conventional 1+1 or 1+2 system to a wide area differential one. The continuous operational reference stations (CORS) which have been built in some cities improve RTK measurement range significantly.
Correcting satellite positioning errors by multiple stationary CORS on the ground is also called ground-based augmentation. Qianxun SI has constructed over 2,400 ground-based augmentation stations across China and its Beidou-based positioning system has served a total of 190 million users.
Ground-based augmentation systems (GBAS) offer limited coverage albeit with high accuracy. The system only works with targets in the coverage area of its communication signals, which makes it hard to reach high altitudes, seas, deserts, and mountains - so it misses a large area. To meet the needs of high-precision positioning on a larger scale, correction parameters collected from CORS are sent to satellites for broadcast, so that the end-user can be free of inadequate communication capacity. Such a correction method is referred to as satellite-based augmentation.
Ground-based augmentation systems (GBAS) have many technical defects from limited communication capacity and non-uniform architecture to heavy concurrent load and high maintenance costs, such that GBAS is bound to be replaced by satellite-based augmentation system (SBAS) over time.
Autonomous vehicles need not only to carry sensors like LiDAR but be capable of centimeter-level positioning for self-driving in any case. SBAS will be the best choice for L5 autonomous driving because of its unique ability to provide rapid global coverage for billions of users at the same time and at a very low cost.
Satellite navigation and positioning systems are trending towards an integration between SBAS and GBAS, between communication and navigation.
The autonomous driving industry is advancing gradually, and its makeup after 2023 is worth forecasting.
Key Topics Covered
1 Concept and Technology of High-precision Positioning for Autonomous Driving
1.1 Positioning Technology
1.1 High-precision positioning of Autonomous Driving
1.2 Classification of High-precision Positioning Technology
1.3 Signal-based Positioning
1.3.1 Satellite-based Positioning
1.3.2 UWB-based Positioning
1.3.3 5G-based Positioning
1.3.4 Positioning System Integrating Communications with GNSS
1.3.5 Communication-Navigation Integration and Starlink
1.4 Positioning Based on Dead Reckoning - Inertial Navigation System
1.4.1 Gyroscope
1.4.2 Accelerometer
1.5 Positioning Based on Environmental Feature Matching
1.5.1 Lidar-based Positioning
1.5.2 Vision Technology-based Positioning
1.6 Integrated Positioning
1.6.1 Combination of GNSS and IMU
1.6.2 Baidu multi-sensor Positioning Technology Solution
1.6.3 Lane-level Positioning Based on Vision and Radar
2 Positioning Chips, Modules and Related Companies
2.1 u-blox
2.1.1 Development History
2.1.2 Global Operations
2.1.3 Business and Product Technology Roadmap
2.1.4 GNSS Positioning Platform Products
2.1.5 ZED-F9P GNSS Positioning Modules
2.1.6 Global GNSS Correction Services
2.2 STMicroelectronics
2.2.1 Automotive Business
2.2.2 Automotive Business and Core Technology
2.2.3 High-precision Positioning Chip
2.2.4 Teseco APP
2.2.5 ST ASM330LHH
2.3 ADI
2.3.1 Inertial Navigation Products
2.3.2 ADIS16490
2.4 Decawave
2.5 InvenSens
2.6 Bosch
3 Inertial Navigation Positioning Technologies and Companies
3.1 Development trend
3.2 Market size
3.3 DAISCH
3.3.1 Automotive Inertial Navigation System
3.3.2 Key Features and Commercialization of Products
3.4 eCHIEV
3.4.1 GEMINI OpenPilot Platform
3.4.2 EC-MU101 Combined Positioning Units
3.5 Xilang Technology
3.6 StarNeto
3.7 Navtech
4 Signal-based Positioning Technologies and Companies
4.1 Satellite-based High-precision Positioning Technology
4.1.1 Overview of SBAS
4.1.2 Trimble SBAS
4.2 5G-based Positioning Technology
4.2.1 Strengths and Challenges of 5G Positioning
4.3 UWB-based Positioning
4.4 Qianxun SI
4.4.1 Autonomous Driving High-precision Positioning Solution
4.4.2 Telematics High-precision Positioning Solution
4.4.3 Time-Space City Brain Project
4.4.4 Create OEM High-precision Positioning Modules with Quectel
4.4.5 Huawei Vehicle Terminal Integrates Positioning Services of Qianxun SI
4.4.6 Development Trends
4.5 Sapcorda
4.6 Mitsubishi Electric
4.6.1 CLAS Services
4.7 Hi-Target
4.7.1 Positioning Technology Development History
4.7.2 Layout in Autonomous Driving
4.7.3 Hi-RTP Global Positioning Service Technology Solution
4.7.4 Hi-RTP Global Positioning Service Construction Planning and Product Mass Production Solution
4.8 BroadGNSS Technology
4.9 South Survey
4.10 Swift Navigation
4.10.1 Piksi Multi and Duro GPS Receiver
4.10.2 Swift Starling Positioning Engine
4.11 Unistrong
4.11.1 Beidou Navigation Agricultural Machinery Autonomous Driving System
4.12 Kunchen
4.12.1 Hawkeye Ultra-Wideband Positioning System Architecture
4.12.2 Industrial Customers and High-precision Positioning Solution
4.12.3 AVP Application Solution Based on UWB Positioning Technology
4.12.4 Application Cases
4.13 Jingwei Technology
5 Integrated Positioning Technology Solution and Companies
5.1 Integrated Positioning Technology
5.2 Novatel
5.2.1 Product Line
5.2.2 SPAN Inertial Navigation System Configuration and Level 1 System
5.2.3 SPAN Inertial Navigation Level 2/3 System
5.2.4 Inertial Navigation System Application
5.3 Trimble Navigation
5.3.1 Trimble RTX Positioning Technology
5.3.2 Trimble Offers High-precision Positioning for Cadillac
5.4 BDStar Navigation
5.5 CTI
5.6 Starcart
5.7 Baidu
5.7.1 Baidu's Multi-sensor Fusion Positioning System Architecture
5.7.2 Point Cloud Positioning Algorithm Architecture
5.7.3 RTK Positioning
5.7.4 Inertial Navigation Solution
5.7.5 Multi-module Fusion
5.7.6 Multi-sensor Fusion Positioning Hardware Architecture
5.8 Wayz.ai
5.8.1 Business Layout
5.8.2 Three Services
5.9 AutoNavi (amap.com)
5.9.1 Camera-based Positioning Solution
5.9.2 Integrated Solution Based on HD Map and High-precision Positioning
5.9.3 Technology Roadmap
Companies Mentioned
- ADI
- AutoNavi (amap.com)
- Baidu
- BDStar Navigation
- Bosch
- BroadGNSS Technology
- CTI
- DAISCH
- Decawave
- eCHIEV
- Hi-Target
- Integrated Positioning Technology
- InvenSens
- Jingwei Technology
- Kunchen
- Mitsubishi Electric
- Navtech
- Novatel
- Qianxun SI
- Sapcorda
- South Survey
- Starcart
- StarNeto
- STMicroelectronics
- Swift Navigation
- Trimble Navigation
- u-blox
- Unistrong
- UWB-based Positioning
- Wayz.ai
- Xilang Technology
For more information about this report visit https://www.researchandmarkets.com/research/8jnvhd/autonomous?w=12
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