Lane-Level Map Positioning Using GPS Error Variation Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods struggle to accurately determine the absolute position of a mobile object on a map due to low-cost GPS inaccuracies and the impracticality of placing numerous landmarks for correction, which is costly and inefficient.
Innovation Solution
An information processing device that combines GPS data with road information and camera images to estimate the position at the lane level, using offline processing to calculate a second absolute position by minimizing error variations through a combination of correction positions and relative positions, reducing the need for frequent environmental adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If landmarks are placed frequently to correct GPS position, then positional accuracy is improved, but cost and user effort increase
Solution Approach 1:
The system uses the mobile object's own movement information (odometer, gyro sensor) to self-correct GPS position errors without requiring external landmarks. The self-position estimation unit calculates correction amounts based on accumulated movement data and applies them to GPS coordinates, enabling the system to serve itself rather than relying on externally placed landmarks.
Solution Approach 2:
The patent introduces movement information (odometer readings, gyro sensor data) as an intermediary to bridge the gap between GPS positions. This intermediary data serves as a reference to calculate position correction amounts, replacing the need for direct landmark-based correction while maintaining accuracy.
2Ease of operation
If GPS is used to determine absolute position, then ease of operation is improved, but measurement precision deteriorates due to low-cost GPS inaccuracies
Solution Approach 1:
The system merges GPS positioning with movement information-based positioning. The self-position estimation unit combines GPS coordinates with correction amounts derived from odometer and gyro sensor data, creating a hybrid positioning system that maintains the simplicity of GPS while achieving higher accuracy through computational correction.
Solution Approach 2:
The system implements feedback by continuously calculating position correction amounts based on accumulated movement information and applying these corrections to GPS positions. The correction amount calculation unit constantly adjusts the position estimate based on the difference between expected position (from movement data) and actual GPS position, creating a closed-loop correction system.
Data Source
AI summary
According to one embodiment, an information processing device includes a hardware processor. The processor calculates an error variation indicating a variation in error between a first absolute position of a mobile object and a relative position of the mobile object. The first absolute position is based on a global positioning system (GPS). The relative position is based on information other than the GPS. The processor calculates at least one section on a map in which the error variation is equal to or less than a first threshold value. The processor calculates a second absolute position on the map such that a constant difference loss becomes smaller. The constant difference loss is used for causing a difference between the first absolute position and the second absolute position to be constant for each of the sections.