Road Curve Detection Using Attached Structure Identification
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Solution Overview
Problem
Existing methods for detecting the starting position of slopes or curves on roads are inefficient due to the extensive time and labor required to accurately map road structures, making it difficult to incorporate all accurate positions and structures into maps.
Innovation Solution
A road information detection device with a curve-starting-position identification part that identifies the starting position of transition curves based on detected attached structures on the road, using image information capture and processing to calculate distances and notify drivers of upcoming slopes or curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map information is used to detect the starting position of slopes or curves, then the position can be identified, but it requires enormous time and labor to include all accurate positions and structures of slopes or curves into maps
Solution Approach 1:
The system performs preliminary detection of attached structures (signposts, guardrails, etc.) and pre-calculates the starting positions of transition curves based on these structures. By preparing this information in advance through automated detection rather than manual mapping, the system achieves accurate starting position identification without requiring enormous time and labor for comprehensive map updates.
2Measurement precision
If comprehensive road structure mapping is performed to accurately identify all slope and curve positions, then detection accuracy improves, but the complexity and cost of the mapping system increases
Solution Approach 1:
The system extracts only the essential attached structures (signposts, guardrails, kilometer posts) that serve as reliable indicators for transition curve starting positions, rather than attempting to map all road structures comprehensively. This selective extraction approach maintains detection accuracy while significantly reducing system complexity by focusing on key reference objects that can be automatically detected.
Solution Approach 2:
The system uses attached structures on the road as intermediary objects that indirectly indicate the starting positions of transition curves. Instead of directly detecting complex road geometries, the system detects these simpler intermediary structures (signposts, guardrails) and calculates transition curve positions based on their locations, thereby simplifying the detection system while maintaining accuracy.
3Reliability
If real-time detection of transition curve starting positions is implemented, then driving safety improves, but the computational processing requirements increase
Solution Approach 1:
The system pre-calculates and stores the relationship between detected attached structures and transition curve starting positions during the detection phase. This preliminary processing allows the system to provide real-time safety information by simply retrieving pre-computed data rather than performing complex calculations in real-time, thereby reducing computational energy requirements while maintaining driving safety.
Data Source
AI summary
A road information detection device includes a curve-starting-position identification part configured to identify the starting position of a transition curve according to a road structure upon detecting an attached structure on a road. It further includes an image information capture part configured to capture an image, an attached-structure detection part configured to detect the identification of an attached structure reflected in the image, and a storage media configured to store the position of an attached structure. The curve-starting-position identification part may identify the starting position based on the detected identification of an attached structure, the stored position of an attached structure, and a distance from the attached structure to the starting position of a transition curve.