Parking Assistance ROI Classification for Special Slot Detection
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Solution Overview
Problem
Existing parking assistance systems struggle to differentiate between various types of special purpose parking slots and no-parking areas, requiring drivers to understand complex and region-specific symbols, leading to potential violations.
Innovation Solution
A method that utilizes a vehicle's camera to detect ground markings and symbols, classifies them into specific parking slot types, and determines potential parking spots based on user-defined criteria, integrating artificial intelligence for symbol recognition and pre-defined patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If parking assistance systems detect and analyze lines painted on the ground to detect parking slots, then parking slot detection capability is improved, but the system cannot differentiate special purpose parking slots and no-parking areas
Solution Approach 1:
The system segments the detection process into two stages: first detecting basic parking slot boundaries using line detection, then performing symbol recognition within detected regions. This segmentation allows the system to first identify all potential parking areas and then differentiate special purpose slots through additional symbol analysis, resolving the contradiction between basic detection and specialized classification.
Solution Approach 2:
The system performs preliminary line detection to identify all parking slot boundaries before attempting symbol recognition. By first establishing the basic parking area boundaries and then subsequently analyzing symbols within those boundaries, the system ensures that no parking slots are missed while also capturing special purpose information.
2Reliability
If drivers manually understand and interpret various region-specific symbols to avoid parking violations, then parking compliance is improved, but driver burden and complexity increase
Solution Approach 1:
The parking assistance system performs self-service by automatically detecting, recognizing, and interpreting parking symbols without requiring driver intervention. The system autonomously analyzes symbols within detected parking regions, determines their meaning, and provides compliance information to the driver, thereby ensuring parking compliance while eliminating the complexity of manual symbol interpretation.
Solution Approach 2:
The system introduces an intermediary processing layer that translates complex visual symbols into simple, actionable information for the driver. Instead of requiring drivers to directly interpret region-specific symbols, the system acts as a mediator that recognizes symbols and presents simplified compliance guidance, reducing cognitive burden while maintaining reliability.
3Loss of information
If the parking assistance system analyzes all detected lines and symbols in the environment, then comprehensive parking information is obtained, but processing time and computational load increase
Solution Approach 1:
The system extracts only the relevant symbols from the entire environmental image by first detecting parking slot boundaries and then limiting symbol recognition to regions within those boundaries. This extraction approach prevents the system from unnecessarily processing unrelated lines and symbols outside parking areas, reducing computational load while maintaining information completeness within parking regions.
Solution Approach 2:
The system applies different processing quality levels to different regions: full symbol recognition and analysis is applied only within detected parking slot regions, while areas outside parking slots receive minimal or no processing. This local quality approach ensures comprehensive information extraction from relevant areas while minimizing processing time for the entire environment.
Data Source
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AI summary
(Method for operating a parking assistance system for a vehicle, computer program product, parking assistance system, vehicle and system) A method for operating a parking assistance system (110) for a vehicle (100) is suggested. The method comprises: a) receiving (S1) an optical image (IMG) of an environment of the vehicle (100) and a digital environment map (MAP) representing the environment of the vehicle (100), the digital environment map (MAP) including at least one designated parking area (P1 - P7), b) selecting (S2), for each of the at least one designated parking areas (P1 - P7), a region of interest (ROI1 - ROI7) in the received optical image (IMG) corresponding to the respective designated parking area (P1 - P7), c) detecting (S3), in each selected region of interest (ROI1 - ROI7), lines (PAT) and/or symbols (SYM1 - SYM3) provided on the ground, d) assigning (S4) one of a plurality of parking slot classes (CLS) to each selected region of interest (ROI1 - ROI7) based on the detected lines (PAT) and/or symbols (SYM1 - SYM3), and e) determining (S5), for each of the at least one designated parking areas (P1 - P7), if the respective designated parking area (P1 - P7) corresponding to the selected region of interest (ROI1 - ROI7) is a potential parking slot based on the parking slot class (CLS) as¬ signed to the corresponding region of interest (ROI1 - ROI7).