Vehicle Vision System Lane-Specific Speed Limit Validation
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Solution Overview
Problem
Existing traffic sign recognition systems fail to accurately determine the validity of speed limits for the correct lane, especially when adjacent lanes have different speed limits, and struggle with blockages or exit lanes, often displaying incorrect speed limits to drivers due to incomplete or outdated navigation map data and inability to distinguish valid signs from exit lanes.
Innovation Solution
A vehicle vision system using one or more cameras processes image data to identify and validate speed limit signs by recognizing lane-specific indicators and integrating navigation data, AI algorithms, and vehicle-to-infrastructure communication to determine the correct speed limit based on the vehicle's lane and position, ignoring invalid or exit lane signs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system uses basic camera-based traffic sign detection, then it can detect traffic signs, but it cannot accurately determine which lane the sign applies to when multiple lanes have different speed limits
Solution Approach 1:
The system transitions from two-dimensional image processing to three-dimensional spatial reasoning by integrating navigation map data with camera imagery. This allows the system to determine not only what signs are visible but also which lanes they apply to by correlating sign positions with lane geometries and vehicle navigation data, thereby recovering the lost lane-specific validity information.
Solution Approach 2:
The patent introduces navigation map data as an intermediary between the camera detection system and the final speed limit determination. This intermediary layer provides contextual information about lane configurations and sign placements, enabling the system to resolve ambiguities about which lanes specific signs apply to, thus improving measurement precision without losing lane-specific information.
2Productivity
If the system displays speed limits from all detected signs, then it captures all possible speed limit information, but it displays incorrect speed limits when the vehicle is in exit lanes or when signs are blocked
Solution Approach 1:
The system performs preliminary validation of detected signs by checking multiple conditions before displaying speed limits. It pre-determines whether the vehicle is in an exit lane by comparing current position with navigation route data, checks for blockages by analyzing image quality metrics, and validates sign relevance to the current lane. This preliminary filtering ensures that only reliable speed limit information is displayed, maintaining high reliability while preserving efficient information processing.
Solution Approach 2:
The system implements feedback mechanisms where detected signs are validated against multiple data sources (navigation data, lane detection, image quality metrics) before being displayed. If validation fails or confidence is low, the system adjusts its behavior by selecting alternative speed limit sources or marking the sign as invalid, thereby maintaining display accuracy without sacrificing processing throughput.
3Device complexity
If the system relies on outdated navigation map data, then it can provide basic navigation context, but it cannot accurately determine current lane positions and valid signs
Solution Approach 1:
The patent merges multiple data sources including camera imagery, real-time navigation data, lane detection algorithms, and map data into a unified processing framework. This combination allows the system to compensate for outdated or incomplete navigation map data by using real-time visual and positional information to accurately determine current lane positions and validate which signs apply to the vehicle's current lane, thereby maintaining measurement precision without significantly increasing system complexity.
Data Source
AI summary
A vision system for a vehicle includes a camera and a control. The control determines information on traffic signs and determines whether an indicated speed limit is for the lane being traveled by the vehicle. The vision system determines whether the indicated speed limit is for the lane being traveled by the vehicle responsive to a determination that the sign is at the left side of the lane and has an indicator representative of the right side of the lane and leaves the field of view at its left side, determination that the sign is at the right side of the lane and has an indicator representative of the left side of the lane and leaves the field of view at its right side, or determination of a speed limit sign at both sides of the road being traveled by the vehicle with both signs indicating the same speed limit.