Terrain-Based Vehicle Localization with Discrete Road Profile Matching
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Solution Overview
Problem
Existing localization systems, such as GNSS, lack the accuracy and resolution needed for advanced vehicle features like active suspension and autonomous driving, and continuous pattern matching between measured and reference road profiles requires substantial network bandwidth and computational resources, making it commercially unfeasible.
Innovation Solution
Implementing terrain-based localization using discretized road segments, where vehicle location is determined intermittently at predetermined intervals through comparisons of measured and reference road profiles, supplemented by dead reckoning or GNSS, reducing computational and network demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous pattern matching between measured and reference road profiles is implemented, then localization accuracy is improved, but network bandwidth and computational resources are excessively consumed
Solution Approach 1:
The road is divided into discrete road segments with predetermined endpoints. Instead of continuous pattern matching, the system only performs comparisons at segment endpoints, significantly reducing computational load while maintaining localization accuracy through the discretized approach.
Solution Approach 2:
The system performs localization comparisons periodically at predetermined intervals (road segment endpoints) rather than continuously. This periodic action reduces network bandwidth consumption and computational resources while still providing accurate localization updates at critical points.
2Measurement precision
If continuous pattern matching between measured and reference road profiles is implemented, then localization accuracy is improved, but network bandwidth consumption increases
Solution Approach 1:
By segmenting the road into discrete sections with predetermined endpoints, the system reduces the frequency of data transmissions. Only endpoint comparisons require network communication, dramatically reducing bandwidth consumption compared to continuous profile matching.
Solution Approach 2:
The system implements periodic localization updates at road segment endpoints rather than continuous updates. This periodic approach minimizes network bandwidth consumption by transmitting and comparing data only at necessary intervals while maintaining accurate localization.
3Productivity
If discretized road segments with intermittent localization are used, then computational resources are reduced, but localization frequency decreases
Solution Approach 1:
Road segments are pre-defined with predetermined endpoints and reference profiles stored in advance. This preliminary structuring allows the system to perform quick endpoint comparisons without requiring complex real-time continuous analysis, balancing computational efficiency with localization frequency.
Solution Approach 2:
The system uses dead reckoning or GNSS as intermediary localization methods between discrete road segment endpoint comparisons. These intermediaries provide continuous localization estimates without requiring intensive computational pattern matching, maintaining localization frequency while preserving computational efficiency.
Data Source
AI summary
A method of terrain-based localization of a vehicle is provided. The method may include determining the vehicle is within a threshold distance of a road segment end point and comparing a measured road profile to a reference road profile associated with the road segment. A method of identifying a track (e.g., a lane) of a road segment road profile is provided. The method may include determining if a number of stored road profiles exceeds a threshold number of road profiles and identifying one or more clusters in the stored road profiles if the threshold number is exceeded.