Vehicle Location Estimation via Roadside Width Change Detection
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Solution Overview
Problem
Existing vehicle location estimation technologies face inaccuracies due to signal reception issues and multipath propagation, especially when roadside structures change width, leading to errors in estimating vehicle location within the road width direction.
Innovation Solution
A location estimation device that uses satellite positioning, autonomous navigation, and in-vehicle sensors to calculate and correct vehicle location by detecting width changes in roadside structures, employing cameras and LIDAR units to obtain shape information and correct the estimated location based on width deviations and positional accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the published technology calculates distance to roadside structure and estimates map-based location, then location estimation is achieved, but accuracy deteriorates when roadside structure width changes
Solution Approach 1:
The roadside structure is segmented into multiple parts along the traveling direction based on width changes. The change detection unit divides the structure at width change points, creating distinct segments (e.g., first roadside-structure part and second roadside-structure part). This segmentation allows the system to select appropriate distance calculation methods for each segment, improving overall location estimation accuracy when the structure width varies.
Solution Approach 2:
The system dynamically adapts its distance calculation approach based on detected width changes. When a width change point is detected, the system switches from treating the roadside structure as a single continuous element to using分段 (segmented) distance calculations. This dynamic adjustment allows the published technology to maintain accuracy across structures with varying width configurations.
2Productivity
If satellite positioning and autonomous navigation are used for location estimation, then location calculation is achieved, but errors accumulate due to signal issues and repeated updates
Solution Approach 1:
The system uses map-based location estimation as a feedback mechanism to correct errors from satellite positioning and autonomous navigation. By continuously comparing estimated location with map-based location derived from roadside structure distances, the system compensates for signal reception errors and accumulated navigation errors, maintaining accurate location estimation.
Solution Approach 2:
The map-based location estimation acts as an intermediary that bridges satellite positioning and autonomous navigation data. It provides an independent reference frame that helps correct errors from both sources, particularly when roadside structures are reliably detectable, thereby improving overall location accuracy.
Data Source
AI summary
In a location estimation device, a change detection unit detects a point of change in the width of a roadside structure as a width change point. A width correction unit calculates a width deviation between a first relative location of the roadside structure on a map data segment and a second relative location of the roadside structure obtained based on shape information of the roadside structure in the width direction of a vehicle. The width correction unit corrects, as a function of the width deviation and a positional accuracy of the vehicle in the travelling direction, an estimated location of the vehicle in the width direction when it is determined that there is the point of change in the width of the roadside structure in the travelling direction of the vehicle.