Terrain-Based Vehicle Localization With Discrete Road Segments
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Solution Overview
Problem
Existing vehicle localization systems, such as GNSS, lack the accuracy and resolution needed for advanced vehicle features like active suspension and autonomous driving, and continuous terrain-based localization methods require substantial network bandwidth and computational resources.
Innovation Solution
Implement terrain-based localization using discrete road segments, combining sensor data with reference profiles to determine vehicle position intermittently, supplemented by GNSS, reducing computational and network demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous terrain-based localization is used to achieve accurate vehicle positioning, then measurement precision is improved, but use of energy and computational resources increases
Solution Approach 1:
The system performs terrain-based localization intermittently at discrete road segments rather than continuously. The vehicle controller compares sensor data with reference road profiles only at predetermined locations along the route, reducing computational and network bandwidth requirements while maintaining sufficient localization accuracy for advanced vehicle features.
Solution Approach 2:
The localization route is divided into discrete road segments with reference profiles stored in a database. The vehicle localizes by matching sensor data against these segmented reference profiles at specific locations, rather than processing continuous terrain data, thereby reducing the computational burden and energy consumption.
2Device complexity
If GNSS-based localization is used, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system combines GNSS-based localization with terrain-based localization methods. GNSS provides coarse location information and route guidance, while terrain-based localization at discrete segments provides fine-grained position correction and verification, achieving high precision without excessive system complexity.
Solution Approach 2:
Reference road profiles stored in a database serve as an intermediary between the vehicle sensors and the localization algorithm. These pre-stored profiles contain expected terrain characteristics that facilitate efficient matching and position determination, reducing the computational complexity of real-time localization while improving accuracy.
Data Source
AI summary
Systems and methods described herein include implementation of road surface-based localization techniques for advanced vehicle features and control methods including lane drift detection, passing guidance, bandwidth conservation and caching based on road data, vehicle speed correction, suspension and vehicle system performance tracking and control, road estimation calibration, and others.


