Traffic Light Signal Determination Using Isolated Images and Map Data
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Solution Overview
Problem
Autonomous driving systems face challenges in accurately determining the signal state of traffic lights, which can lead to safety risks due to the complexity of identifying and interpreting traffic light information in real-time environments.
Innovation Solution
A method and electronic device that acquire an isolated image of a target traffic light using image processing, combine it with map data to determine the signal state, and utilize neural networks to identify the sequential position of illuminated lamps, thereby determining the traffic signal type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If deep learning technology is used to identify traffic lights in real-time environments, then the system can process visual information, but the accuracy and reliability of signal state determination deteriorates due to complexity in identifying and interpreting traffic light information
Solution Approach 1:
The patent segments the traffic light recognition task into distinct components: detecting candidate traffic lights, selecting the target traffic light based on map position, isolating the traffic light image, and determining signal state. This segmentation allows each component to be optimized independently, improving overall accuracy while maintaining real-time processing.
Solution Approach 2:
The patent introduces map data as an intermediary to bridge the gap between visual detection and signal state determination. The map provides prior information about traffic light positions and signal types, which serves as a mediator to guide the selection and interpretation of detected traffic lights, enhancing accuracy without sacrificing real-time performance.
2Adaptability or versatility
If the system processes all detected traffic lights equally, then comprehensive coverage is achieved, but the determination reliability worsens due to difficulty in identifying the relevant target traffic light
Solution Approach 1:
The patent performs preliminary actions by detecting multiple candidate traffic lights and using map data to predict which one is the target before final signal state determination. This preliminary filtering based on map position information increases reliability by identifying the relevant traffic light in advance, while still maintaining comprehensive coverage of all potential candidates.
3Measurement precision
If image processing is applied to isolate the target traffic light, then the signal state determination accuracy improves, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The patent extracts and isolates only the target traffic light image from the full scene using image processing techniques guided by map position information. This extraction approach improves accuracy by focusing computational resources on the relevant traffic light only, while the use of map data as a guide prevents excessive complexity by providing clear criteria for isolation.
Data Source
AI summary
A method of determining a signal state of a target traffic light includes: acquiring an isolated image of the target traffic light from an input image of the target traffic light, wherein the input image is captured when the vehicle is at a position, wherein the isolated image is acquired using image processing on the input image, the input image having been captured by a camera module of the vehicle; acquiring information about the target traffic light based on a map position in map data, the map position corresponding to the position of the vehicle when the input image is acquired; and determining the signal state of the target traffic light based on the isolated image of the target traffic light and based on the information about the target traffic light.