Vehicle Rule Detection Using Sensor-History Comparison
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Solution Overview
Problem
Users of vehicles are often unaware of local map changes, such as newly established vehicle-related rules, leading to penalties like parking tickets due to hidden or atypically displayed signs, which existing systems fail to detect effectively.
Innovation Solution
An apparatus and method that utilize sensor data comparison with historical data to determine the likelihood of newly established vehicle-related rules, such as parking restrictions, by analyzing ticket issuance and parking orientations, and provide notifications to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional road signs are used to indicate vehicle-related rules, then the rules are officially communicated, but the signs are hidden or displayed in atypical locations making them undetectable to drivers
Solution Approach 1:
The patent introduces an intermediary detection system consisting of sensors, processors, and mapping systems that act as a mediator between the road signs and drivers. This intermediary system captures sensor data, processes it to identify new rules, and communicates the information to users through mobile devices, thereby resolving the detectability problem without changing the official sign placement
Solution Approach 2:
The patent replaces the mechanical/visual detection method (drivers physically seeing signs) with an electronic/digital detection system using sensors, image processing, and data analysis. The system uses sensors to capture visual information, processes images to detect sign changes, and uses digital communication to notify users, substituting the direct visual-mechanical detection chain with an electronic information processing chain
2Device complexity
If no detection system is implemented, then the system remains simple, but users receive penalties for unknown rule changes
Solution Approach 1:
The patent implements preliminary detection and notification actions before users are affected by new rules. The system proactively scans for rule changes using sensors, processes the data to identify new vehicle-related rules, and notifies users in advance through mobile devices, preventing penalties before they occur rather than reacting after violations happen
Solution Approach 2:
The patent establishes a feedback loop where sensor data is continuously collected, processed to detect rule changes, and then used to generate notifications to users. The system monitors the environment, compares current state with historical data, and provides feedback to users about detected changes, creating a closed-loop information system that reduces harmful penalties
3Measurement precision
If sensor data collection is implemented to detect rule changes, then new rules are detected, but data processing complexity increases
Solution Approach 1:
The patent extracts only the essential and relevant information from the collected sensor data for processing. Instead of analyzing all sensor data in detail, the system focuses on extracting specific features such as sign presence, text content, and location information that are directly relevant to detecting vehicle-related rules, thereby reducing processing complexity while maintaining detection accuracy
Solution Approach 2:
The patent segments the data processing task into distinct modular components: sensor data acquisition, image processing and analysis, rule change detection logic, and notification generation. Each component handles a specific aspect of the processing pipeline independently, making the overall complex system more manageable and maintainable through functional segmentation
Data Source
AI summary
An apparatus, method and computer program product are provided for determining a newly established vehicle-related rule within an area. In one example, the apparatus receives sensor data indicating attributes of an area for a first period. The attributes indicate a number of vehicle-related tickets issued within the area, a parking orientation of each vehicle within the area, or a combination thereof. The apparatus compares the sensor data to historical data associated with the area. The historical data indicate the attributes of the area for one or more second periods preceding the first period. Based on comparison of the sensor data and the historical data, the apparatus determines a likelihood of a vehicle-related rule established for the area, where the vehicle-related rule did not exist during the one or more second periods. The apparatus causes a notification indicating the likelihood at a user interface.