Traffic Light Applicability Detection for Autonomous Vehicles
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Solution Overview
Problem
Autonomous vehicles face challenges in distinguishing between traffic lights that apply to them and those that do not, leading to potential false positives or negatives, which can be dangerous.
Innovation Solution
A method and system that analyze images of the vehicle's surroundings to determine the number, duration, and spatial position of traffic lights, using threshold values to differentiate between applicable and inapplicable traffic lights, thereby reducing false positives and negatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system identifies all traffic lights in the surrounding area, then the detection coverage is improved, but the false positive rate increases due to including non-applicable traffic lights
Solution Approach 1:
The patent segments the traffic light identification process into multiple evaluation stages: initial detection, count threshold evaluation, duration threshold evaluation, and spatial position evaluation. Each stage filters out non-applicable traffic lights, progressively reducing false positives while maintaining detection coverage.
Solution Approach 2:
The system performs preliminary evaluations (count threshold, duration threshold) before final traffic light applicability determination. These preliminary actions filter out obviously non-applicable traffic lights early in the process, preventing them from reaching the final decision stage and reducing false positives.
2Reliability
If the system uses multiple evaluation criteria (count, duration, position), then the false positive reduction is improved, but the system complexity increases
Solution Approach 1:
The patent divides the complex evaluation process into distinct modular stages: count threshold evaluation module, duration threshold evaluation module, and spatial position evaluation module. Each module handles a specific aspect of the evaluation, making the overall complex system manageable and maintainable through clear separation of concerns.
Solution Approach 2:
The system uses multiple parameters (count threshold, duration threshold, spatial position thresholds) to evaluate traffic light applicability. By changing and comparing multiple parameters rather than relying on a single criterion, the system achieves more accurate false positive reduction while organizing the complexity through parameter-based evaluation stages.
3Measurement precision
If the system evaluates spatial position and duration of traffic lights, then the applicability determination accuracy is improved, but the processing time increases
Solution Approach 1:
The system performs preliminary evaluations using count threshold and duration threshold before conducting more computationally intensive spatial position analysis. This preliminary action filters out non-applicable traffic lights early, reducing the number of objects that require detailed spatial evaluation and thus reducing overall processing time.
Solution Approach 2:
The patent segments the evaluation process into time-efficient preliminary stages (count and duration checks) and more intensive final stages (spatial position analysis). This segmentation allows the system to quickly eliminate obvious non-applicable traffic lights before investing more processing time in detailed analysis of potential candidates.
Data Source
AI summary
A method and system to determine whether a traffic light applies to a vehicle. Traffic light count, visibility duration and spatial position are analyzed to determine the applicability of a traffic light to a vehicle.