Vehicle Visibility Detection Using Maps and Onboard Images
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Solution Overview
Problem
Conventional safety systems for vehicles are limited in detecting low visibility conditions beyond 200 meters, necessitating a need for determining low visibility closer to the vehicle to enable effective counter-measures.
Innovation Solution
An apparatus and method using a processor, image capture sensors, and a map database to determine visibility information by identifying road segments and objects, applying machine learning models, and outputting visibility information for vehicle control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional safety systems are used to detect low visibility conditions, then the detection range is limited to 200 meters, but this limitation prevents effective counter-measures in areas with dense fog or heavy rainfall where visibility drops below 200 meters
Solution Approach 1:
The patent combines multiple data sources including image capture sensors, map databases, and machine learning models to create a comprehensive visibility detection system that overcomes the 200-meter limitation of conventional systems by integrating diverse information streams for enhanced detection capability
Solution Approach 2:
The patent introduces map databases as an intermediary layer that provides contextual road segment information and attributes, enabling the system to determine visibility conditions indirectly through environmental context rather than relying solely on direct sensor detection range
2Reliability
If the visibility detection range is extended beyond 200 meters, then more counter-measures can be implemented, but the system complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing and storing road segment attributes and environmental data in map databases before visibility detection is needed, allowing the runtime system to query pre-prepared information rather than computing everything in real-time, thus reducing operational complexity
Solution Approach 2:
The patent segments the visibility detection task into distinct functional modules: image capture, map database querying, machine learning analysis, and counter-measure determination. This modular segmentation allows each component to be developed and optimized independently while maintaining overall system effectiveness
Data Source
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AI summary
An apparatus for determining low visibility of an environment around a vehicle is disclosed. The apparatus obtains location information indicating a location of the vehicle. The apparatus further detects, by using a map database, a road segment satisfying a road attribute requirement proximate to the location based on the location information. The apparatus further obtains, from the map database, at least one attribute associated with the road segment. The apparatus further determines a position of the vehicle with respect to the road segment based on the at least one road attribute. The apparatus further acquires at least one image via at least one image capture sensor equipped by the vehicle based on the position. The apparatus further determines visibility information indicative of visibility of the environment of the vehicle based on the at least one image. The apparatus further outputs the visibility information.