Traffic Sign Relevance via Pan and Tilt Angles
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Solution Overview
Problem
Current advanced driver assistance systems (ADAS) and automated driving systems (ADS) struggle to correctly interpret traffic signs due to varying placements, heights, and orientations, which affects their functionality and occupant awareness.
Innovation Solution
A system and method utilizing a vehicle camera and controller to capture images, identify traffic signs, determine pan and tilt angles, and assess relevance by comparing these angles to thresholds, without requiring additional sensor systems like LiDAR or radar, using deep learning models for segmentation and edge detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional sensor systems like LiDAR or radar are used to improve traffic sign detection accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The vehicle camera system is designed to perform multiple functions: capturing images for traffic sign detection, determining pan and tilt angles through image analysis, and providing occupancy awareness. By making the camera system multi-functional, the patent eliminates the need for additional specialized sensors like LiDAR or radar, thereby maintaining measurement precision while reducing device complexity
Solution Approach 2:
The system uses visual information from camera images to create a digital representation of traffic signs and their spatial characteristics. By extracting pan and tilt angles from image data rather than using dedicated angular sensors, the patent achieves accurate measurement without adding physical sensor complexity
2Reliability
If multiple sensors are deployed to handle varying traffic sign placements and orientations, then reliability is improved, but device complexity increases
Solution Approach 1:
The system handles varying traffic sign placements and orientations by changing the parameters extracted from images (pan angle, tilt angle, position coordinates) rather than adding sensors. The algorithm adapts to different sign characteristics by adjusting these measured parameters, maintaining reliability without increasing device complexity
Solution Approach 2:
The patent addresses the variability in traffic sign characteristics by adding angular dimensions (pan and tilt angles) to the detection framework. This allows the system to reliably interpret signs at various orientations and placements by measuring their spatial parameters in multiple dimensions, rather than requiring multiple physical sensors
Data Source
AI summary
A system for determining a relevance of a traffic sign for a vehicle includes at least one vehicle camera configured to provide a view of an environment surrounding the vehicle and a vehicle controller in electrical communication with the at least one vehicle camera. The vehicle controller is programmed to capture an image using the at least one vehicle camera. The vehicle controller is further programmed to identify the traffic sign in the image. The vehicle controller is further programmed to determine a pan angle and a tilt angle of the traffic sign based at least in part on the image. The vehicle controller is further programmed to determine the relevance of the traffic sign based at least in part on the pan angle and the tilt angle of the traffic sign.