The Large-Scale Application Of L4-Above AD Requires that Communication Networks Should Transfer from C-V2X to 5G-V2X and Satellite Positioning Should Shift from Large-Scale Ground-Based Augmentation to Large-Scale Satellite-Based Augmentation
Positioning technology currently comprises outdoor and indoor positioning. Outdoor positioning technology involves traditional satellite positioning, radar positioning, inertial measurement unit (IMU) positioning and cellular mobile network positioning. Indoor positioning technology includes WLAN positioning, Zigbee positioning, Bluetooth positioning, ultra-wideband (UWB) positioning, infrared positioning, computer vision positioning, and ultrasonic positioning.
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.
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Table of Contents
Samples
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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
Methodology
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