CHC Navigation examines the global automotive industry and its current position on the cusp of a transformation, driven by the rapid advancement of autonomous driving technology. Read more >>
By 2026, the market for autonomous vehicles (AVs) is projected to reach $557 billion, reflecting its immense potential. More than 500 companies worldwide are actively developing AV technology, with key players based in the United States, China, and Germany. The number of AVs on the road is expected to rise from 8.5 million in 2019 to over 20 million by 2030.
A crucial step in this evolution is the introduction of Level 3 (L3) autonomous driving — hands-off operation under specific conditions. By 2024, leading automakers plan to roll out L3 capabilities in flagship models, while regulatory frameworks across North America, Europe, and Asia are adapting to accommodate these advances.
As AV technology matures, precise positioning and navigation systems, particularly GNSS+INS solutions, are becoming indispensable.
The Evolution of Autonomous Driving and the Need for Precision
Autonomous vehicles rely on a complex interplay of computing, artificial intelligence, and sensor technology to navigate safely. The Society of Automotive Engineers (SAE) defines six levels of automation, ranging from Level 0 (no automation) to Level 5 (full automation).
Currently, most AVs operate at Level 2 (L2), where systems such as Advanced Driver Assistance Systems (ADAS) support lane-keeping and adaptive cruise control. These features enhance highway driving but require constant driver supervision. L3 automation, however, marks a shift toward conditional autonomy, where vehicles can execute most driving tasks independently, significantly reducing the driver’s workload.
Achieving higher levels of automation demands robust environmental perception and ultra-precise positioning. This is where GNSS and inertial navigation systems (INS) play a critical role, providing the foundational data required for reliable autonomous navigation.
GNSS and INS: A Dual Approach to Autonomous Navigation
Autonomous vehicles depend on a network of sensors to perceive their surroundings and determine their exact position. This ecosystem includes:
- Situational Awareness Sensors:
- RGB Cameras: Capturing visual data for object recognition
- LiDAR: Generating detailed 3D maps of the environment
- Millimeter-Wave Radar: Detecting object speed and distance
- Ultrasonic Sensors: Aiding in short-range obstacle detection
- Positioning and Navigation:
- GNSS/INS Systems: Delivering precise location and timing data essential for autonomous decision-making
The GNSS+INS combination is particularly crucial, ensuring continuous positioning even in challenging conditions such as urban environments, tunnels, and underpasses. GNSS provides absolute positioning using satellite signals, while INS utilizes accelerometers and gyroscopes to track movement, filling in data gaps when GNSS signals are weak or obstructed.
Overcoming Challenges: The Role of Tightly Coupled GNSS+INS Systems
Unlike standard GNSS receivers used in surveying applications, those designed for autonomous vehicles must meet stringent requirements:
- Centimeter-Level Accuracy: Precise lane positioning is critical. However, urban environments can cause GNSS signal blockage and multipath interference, reducing accuracy.
- Environmental Adaptability: AVs operate in varying conditions, requiring GNSS receivers to withstand vibration, temperature fluctuations, and signal disruptions.
- Real-Time Processing: Autonomous navigation demands continuous, low-latency positioning updates, even in GNSS-degraded environments.
Tightly coupled GNSS+INS systems address these challenges by integrating raw GNSS and INS data at an early processing stage, rather than merging outputs separately. This enables the system to maintain accuracy even during GNSS outages, as the INS component continues to provide reliable navigation data.
CHCNAV’s Advanced GNSS+INS Solutions for Autonomous Vehicles
CHCNAV has developed a range of high-precision GNSS+INS sensors designed to enhance autonomous vehicle navigation. The CGI-610 GNSS/INS sensor, for instance, delivers:
- Centimeter-Level Accuracy: Ensuring precise localization for AV operation
- Multi-Constellation Support: Improving reliability in urban environments
- Advanced Algorithms: Enabling rapid initialization and re-convergence
- Robust Durability: Designed to perform in extreme conditions, including high-vibration scenarios
Field Testing: Proving Performance in Real-World Conditions
To validate the CGI-610’s performance, CHCNAV conducted extensive field tests in complex urban environments in Japan. Mounted on a light truck and connected to an external antenna and GNSS RTK correction network, the system was tested under varied conditions:
- Urban Business Districts: Maintained RMS positioning accuracy within 0.7m, with heading accuracy around 0.1°
- Open Roads: Achieved sub-0.1m RMS accuracy, ideal for AV lane positioning
- Dense Urban Areas: Maintained positioning accuracy within 0.5-1m RMS despite signal interference
- Tunnels: Positioning errors remained within 1.5%° of tunnel length, with RMS values under 0.5m
These results confirm that the CGI-610 delivers reliable positioning and heading accuracy, even in environments with significant GNSS signal challenges.
The Road Ahead: Pushing GNSS+INS Technology Further
As the autonomous driving industry advances, the demand for highly accurate GNSS+INS solutions will continue to grow. Future innovations may integrate AI-based sensor fusion, enhanced real-time corrections, and improved power efficiency to extend operational longevity.
CHCNAV is at the forefront of these developments, with next-generation receivers like the CGI-830 and CGI-230 building on the success of the CGI-610. These systems offer enhanced INS accuracy and improved positioning performance, ensuring that autonomous vehicles operate with the precision required for safe and efficient navigation.
By refining GNSS+INS technology, CHCNAV is helping pave the way for the widespread adoption of autonomous vehicles, ensuring that precision navigation remains a cornerstone of the industry’s future.
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