Local Map Generation Using GPS Doppler Velocity Vectors
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Solution Overview
Problem
Conventional road surface markings map generating methods are limited by requiring highly accurate vehicle positions and loci, which are not feasible for general vehicles, and suffer from positioning errors in GPS navigation, especially in cities and suburban areas, leading to inaccurate alignment of road surface marks.
Innovation Solution
A local map generating device that acquires environment information using a moving body, computes velocity vectors from GPS satellite data, and integrates this information to create a local map, allowing for accurate recording of environment details along the vehicle's path, even with lower GPS accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional GPS positioning is used for general vehicles, then the system is simple and applicable to general vehicles, but the positioning accuracy deteriorates with errors of several meters to tens of meters in cities
Solution Approach 1:
The patent introduces road surface mark images as an intermediary reference system. Instead of relying solely on GPS coordinates, the system captures images of road surface marks and uses their positions in the images as reference points to calculate vehicle position and orientation, thereby achieving high accuracy without requiring specialized measurement vehicles
Solution Approach 2:
The patent replaces the mechanical/GPS-based positioning system with an optical/image-based system. By using cameras to capture road surface marks and processing these images to determine vehicle position and orientation, the system achieves higher accuracy than conventional GPS while remaining applicable to general vehicles
2Manufacturing precision
If reference path alignment is used to improve accuracy, then the map alignment accuracy improves, but the method cannot be applied to general vehicles without highly accurate reference paths
Solution Approach 1:
The patent inverts the conventional approach by not trying to align the vehicle position to a reference path, but rather using road surface mark images captured by the vehicle itself as the reference. This allows general vehicles to generate accurate local maps without requiring pre-existing highly accurate reference paths
Solution Approach 2:
The system uses the vehicle's own camera-captured images of road surface marks as the reference data for positioning and mapping. Each vehicle serves as its own reference source, eliminating the need for external highly accurate reference paths that would require specialized measurement vehicles
3Measurement precision
If velocity information from GPS satellites is integrated, then the locus computation accuracy improves, but the system complexity increases
Solution Approach 1:
The patent uses GPS satellite information for multiple purposes: both for obtaining velocity vectors through Doppler shift measurement and for backup positioning. This multi-functional use of the GPS receiver justifies the system complexity by providing both high-accuracy velocity data and position data from a single device
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the generation of highly accurate local and global maps by integrating velocity information and motion states, providing precise environment information for each point on the map, even with lower GPS accuracy, and merging local maps into an absolute coordinate system.
Implementation Method 1
acquires satellite information that includes information relating to respective positions of a plurality of GPS satellites that are transmitted from the respective GPS satellites, and information relating to distances between the respective GPS satellites and the moving body, and information relating to relative velocities of the moving body with respect to the respective GPS satellites
Implementation Method 2
computes a velocity vector that includes a traveling direction of the moving body, or velocity information that expresses a velocity of the moving body and the traveling direction of the moving body
Data Source
AI summary
An image pickup device picks-up forward images, and a GPS information acquiring section acquires satellite information that includes Doppler frequencies. A position/velocity vector computing section computes a velocity vector by using the Doppler frequencies. A locus computing section computes a locus of positions of ones own vehicle. A projected image generating section generates, from the forward images, projected images that are projected onto a road surface. A local map generating section records road surface images, that are obtained for respective points on the locus of ones own vehicle, at respective regions of a local map that is determined on the basis of a traveling direction of a moving body at each point on the locus and a set position and a posture of the image pickup device. Due thereto, a local map generating device can, by a simple structure, generate a highly accurate map.