Road Surface Localization Using Vertical Wheel Motion
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Solution Overview
Problem
Current localization systems, such as GPS, fail to provide sufficient accuracy or resolution for advanced vehicle systems like active suspension and autonomous driving, especially in environments with signal blockage or overlapping coordinates.
Innovation Solution
Utilizing vertical motion data from a vehicle's wheels, transformed into the space domain, to match with reference road surface characteristics for precise localization, combined with other localization systems to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS-based localization systems are used, then the system is simple and provides broad coverage, but the localization accuracy and resolution are insufficient for advanced vehicle systems
Solution Approach 1:
The patent combines GPS localization with road surface-based localization by merging data from multiple sensors (accelerometers, gyroscopes) with GPS coordinates. The system integrates satellite-based positioning with inertial measurement unit (IMU) data to achieve high-resolution localization that overcomes GPS limitations while maintaining system feasibility through coordinated use of multiple existing technologies
Solution Approach 2:
The patent introduces road surface characteristics as an intermediary element between the vehicle and localization systems. By measuring vertical wheel motions and comparing them to stored road profiles, the system creates an intermediate reference framework that enhances GPS accuracy without requiring direct modification of satellite infrastructure or complex onboard processing
2Reliability
If GPS signals are used for localization, then the system operates over large areas, but accuracy deteriorates in environments with signal blockage or overlapping coordinates
Solution Approach 1:
The patent performs preliminary actions by pre-storing road surface profile data in a database before the vehicle reaches those locations. During operation, the system queries and compares real-time wheel motion measurements against these pre-stored profiles, enabling reliable localization even when GPS signals are blocked, as the comparison-based method does not depend on satellite visibility
Solution Approach 2:
The system implements feedback by continuously comparing measured vertical wheel motions with expected motions from stored road profiles. This closed-loop comparison provides real-time verification of localization accuracy and allows the system to maintain reliability by detecting and correcting deviations, ensuring consistent performance regardless of GPS signal conditions
3Measurement precision
If vertical motion data from multiple wheels is sensed and processed, then localization precision is improved, but the complexity of data processing and system configuration increases
Solution Approach 1:
The patent segments the localization problem by treating each wheel's vertical motion independently, measuring and processing data from individual wheels separately. This segmentation allows the system to build up high-resolution localization information incrementally from multiple independent measurement sources, improving precision while managing complexity through modular data processing
Solution Approach 2:
The system achieves universality by using the same accelerometer-based measurement and comparison methodology for all wheels. The same processing algorithm applies regardless of which wheel is being measured, creating a scalable framework that can accommodate any number of sensors without proportionally increasing system complexity, as the approach is universally applicable across different vehicle configurations
Data Source
AI summary
Systems and methods for determining the location of a vehicle are disclosed. In one embodiment, a method for localizing a vehicle includes driving over a first road segment, identifying by a first localization system a set of candidate road segments, obtaining vertical motion data while driving over the first road segment, comparing the obtained vertical motion data to reference vertical motion data associated with at least one candidate road segment, and identifying, based on the comparison, a location of the vehicle. The use of such localization methods and systems in coordination with various advanced vehicle systems such as, for example, active suspension systems or autonomous driving features, is contemplated.