Automated Parking Zone Detection Using Satellite Imagery
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Solution Overview
Problem
Existing methods for detecting parking zones on streets are inefficient, requiring manual counts and vehicle-based surveys, which are time-consuming, incomplete, and dependent on lighting and vehicle positioning, and often only cover one side of the road.
Innovation Solution
A system using a computing unit that reads in panorama images and road data to analyze vehicles and signs, determining parking and no-stopping zones by fusing vehicle and sign information, and visualizing the results on a terminal, allowing for automated detection and mapping of parking zones across entire regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle-based methods are used to detect parking zones, then parking spot detection can be performed, but the method is time-consuming and requires traveling along every road at different rates
Solution Approach 1:
The patent uses satellite images as a copy or representation of the actual street scene to detect parking zones. Instead of physically traveling along roads with vehicles, the system processes satellite imagery that captures the entire region simultaneously, dramatically reducing detection time while maintaining accuracy through image analysis algorithms
Solution Approach 2:
The patent transitions from ground-level vehicle-based detection to aerial satellite-based detection. This dimensional change allows simultaneous observation of entire regions from above, eliminating the need to traverse each road sequentially and enabling parallel processing of multiple areas
2Quantity of substance
If vehicle-based camera systems are used, then parking spots can be surveyed, but complete coverage is not influenceable and lengthy
Solution Approach 1:
Satellite images provide a comprehensive copy of the entire region including all streets and parking zones simultaneously. This allows complete coverage of the survey area in a single data capture event, eliminating the lengthy sequential traversal required by vehicle-based systems
Solution Approach 2:
The patent merges multiple data sources including satellite images, map databases, and vehicle detection algorithms into a unified system. This integration allows simultaneous processing of multiple regions and aspects of parking zone detection, achieving complete coverage efficiently
3Extent of automation
If vehicle internal camera images are used, then automatic parking detection is possible, but the method is computation time intensive
Solution Approach 1:
The patent processes satellite images which are pre-captured representations of the scene, rather than processing continuous video streams from vehicle cameras. This reduces the computational burden by working with static, lower-frequency data that still provides complete automated detection capability
Solution Approach 2:
The system extracts only the essential features needed for parking zone detection from satellite images, such as road boundaries, parking spot patterns, and signage. This selective extraction reduces computational requirements compared to processing complete vehicle camera feeds with all their details
4Measurement precision
If vehicle-based camera systems are used, then parking spots can be detected, but results are highly dependent on vehicle position and lighting conditions
Solution Approach 1:
By moving from ground-level vehicle cameras to aerial satellite imaging, the system eliminates dependency on vehicle position relative to the curb and reduces lighting dependency through consistent overhead illumination. This dimensional shift provides a stable, consistent viewing angle for all locations
Solution Approach 2:
Satellite images provide a universal viewing platform that works consistently across all locations and lighting conditions. The overhead perspective and standardized imaging protocol make the detection system adaptable to diverse environments without being constrained by local vehicle positioning or lighting variations
Data Source
AI summary
A method automatically detects parking zones in at least one residential street, wherein a) a computing unit is provided; b) information in the form of panoramic images of the at least one residential street is inputted from an external data store; c) information in the form of street data of the at least one residential street is inputted from a map database; d) an internal database is generated, which persists the panoramic images; e) the inputted panoramic images are analyzed for the presence of vehicles; f) the inputted panoramic images are analyzed for the presence of street signs and traffic signs; g) from the analyses of the presence of vehicles and the presence of street signs and traffic signs for at least one selected residential street, expected existing no-parking/no-stopping zones are determined; h) a data set that contains the detected information regarding identified vehicles, street signs, and the markings of no-parking/no-stopping zones and parking zones is generated, and i) the information contained in the data set is visualized on a terminal unit.