GPS Bias Detection and Reduction for Autonomous Vehicles
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Solution Overview
Problem
Current vehicle GPS navigation systems face inaccuracies due to GPS noise and bias, which can lead to deviations from the true vehicle location, affecting autonomous and self-driven vehicle operations.
Innovation Solution
A GPS-bias detection and reduction system that utilizes a GPS-bias model created from statistical data collected from thousands of vehicles. This system calculates GPS-bias, compares new data points to reduce bias, and updates the model to improve vehicle position determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If crowd sourced GPS data is used to determine vehicle location, then data availability increases, but GPS-bias causes mean location deviation from ground-truth location
Solution Approach 1:
The patent introduces an intermediary processing system that mediates between raw crowd-sourced GPS data and the final location determination. This system applies statistical analysis and bias correction algorithms to eliminate GPS-bias effects, allowing the system to utilize abundant crowd-sourced data while maintaining location accuracy comparable to ground-truth measurements.
Solution Approach 2:
The patent transforms the GPS data by changing its statistical parameters through bias correction. By identifying and removing systematic bias components from the GPS measurements, the system converts biased GPS readings into corrected location estimates that maintain the advantages of crowd-sourced data availability while achieving measurement precision suitable for navigation applications.
2Measurement precision
If GPS statistical data from thousands of vehicles is collected and processed, then GPS-bias can be reduced, but system complexity increases
Solution Approach 1:
The patent segments the complex task of GPS-bias correction into distinct functional modules: data collection from multiple vehicles, statistical analysis to identify bias patterns, bias calculation algorithms, and application of corrections to individual vehicle locations. This segmentation allows each module to be optimized independently and simplifies the overall system architecture despite handling large volumes of data.
Solution Approach 2:
The system implements self-service through automated statistical analysis and bias detection algorithms that process crowd-sourced data without requiring manual intervention. The system automatically identifies GPS-bias patterns from aggregated vehicle data and generates correction parameters, reducing operational complexity while maintaining high measurement precision.
Data Source
AI summary
A global positioning system (GPS)-bias detection and reduction system including a GPS-bias model having GPS statistical data creating a database representing data collected from a vehicle group having thousands or multiple thousands of vehicles saved in a database. At least one newly collected vehicle GPS data point is compared to the GPS statistical data to reduce negative effects of GPS-bias and to update the vehicle GPS-bias correction based on a previous GPS-bias model. A selected road node and a segment of a roadway have a map matching performed using a nearest service from a collection location of the GPS statistical data. A GPS-bias is calculated using a look-up of the database. An estimated horizontal position error (EHPE) defining a quality indicator is applied to distinguish a good quality GPS statistical data from a poor quality GPS statistical data.