Road Debris Detection Using Vehicle Camera and Map Updates
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Solution Overview
Problem
Current vehicle sensors lack the capability to effectively detect and predict road debris indicators, which limits the provision of accurate route guidance and automated vehicle control, especially in scenarios where road conditions are hazardous.
Innovation Solution
A method and apparatus that utilize image data from vehicle cameras to identify and predict road debris indicators, associating them with navigable links in a geographic database, and provide alerts and route guidance to avoid potential hazards, leveraging machine learning models for accurate classification and prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional vehicle sensors are used for navigation and control, then basic location and environmental data can be obtained, but the capability to detect and predict road debris indicators is insufficient
Solution Approach 1:
The existing vehicle camera system is repurposed to perform multiple functions: original functions (capturing images for navigation and environmental perception) plus the new function of detecting road debris indicators. This allows the system to gain road debris detection capability without adding dedicated specialized sensors, thereby improving reliability while avoiding increased device complexity.
Solution Approach 2:
The system uses the vehicle's own existing camera infrastructure to detect road debris, making the vehicle self-sufficient for this detection task without requiring external specialized equipment. The camera system serves both its original navigation purpose and the additional road debris detection purpose simultaneously.
2Loss of information
If image data analysis is added to detect road debris, then road debris classification information can be provided, but the complexity of data processing increases
Solution Approach 1:
The system performs preliminary analysis of image data to identify potential road debris indicators before making final determinations. By pre-processing the image data to highlight relevant features and patterns, the system reduces the complexity of subsequent analysis while ensuring comprehensive road debris information is captured and classified.
3Measurement precision
If real-time road debris detection is implemented, then route guidance accuracy improves, but the processing time and computational resources increase
Solution Approach 1:
The system applies partial action by focusing image analysis only on specific regions or features that are most indicative of road debris, rather than analyzing the entire image in detail. This selective approach maintains high measurement precision for route guidance while reducing overall processing time and computational resource requirements.
Data Source
AI summary
A method, apparatus, and user interface for road debris detection comprising, in some embodiments, obtaining image data of at least one navigable link and/or road debris, determining a road debris indicator based on the obtained image data, wherein the road debris indicator includes road debris classification data, and associating the determined road debris indicator with one or more navigable links to update a map layer of a geographic database.