V2I Traffic Light Recognition via Infrastructure Mediator
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Solution Overview
Problem
Existing autonomous driving technologies, such as those using multi-function cameras, struggle to recognize traffic lights in adverse weather conditions or when obstructed by large vehicles, leading to ineffective signal state recognition and impaired autonomous driving capabilities.
Innovation Solution
A vehicle-to-infrastructure (V2I) communication-based system that allows vehicles to receive signal information directly from signal controllers, enabling accurate determination of driving behaviors and providing notifications or autonomous control when traffic lights cannot be recognized through cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a multi-function camera (MFC) is used to recognize traffic lights, then the system structure is simple and cost-effective, but the traffic light recognition fails under adverse weather conditions or when obstructed by large vehicles
Solution Approach 1:
The patent introduces an intermediary system consisting of infrastructure-based sensors (cameras, radars, lidars) and a server that mediates between the vehicle's MFC and the traffic light information. When the MFC cannot recognize traffic lights due to adverse conditions, the infrastructure-based system captures the traffic light state and transmits it to the vehicle through V2I communication, thereby resolving the recognition failure caused by environmental factors or obstructions
Solution Approach 2:
The patent creates a multi-functional traffic light recognition system that combines both direct camera recognition and infrastructure-based recognition. The system can switch between or combine multiple information sources (MFC direct detection, V2I communication data, sensor fusion) to achieve reliable traffic light state identification under various conditions, making the overall system universally applicable regardless of weather or obstruction
2Extent of automation
If autonomous driving relies solely on camera-based traffic light recognition, then the system complexity is low, but the autonomous driving capability is impaired under challenging conditions
Solution Approach 1:
The patent segments the traffic light recognition function into two independent subsystems: a vehicle-based MFC subsystem for direct recognition and an infrastructure-based sensor subsystem for alternative recognition. This segmentation allows each subsystem to operate independently and provides redundancy, enhancing autonomous driving capability without requiring a complete system redesign
Solution Approach 2:
The patent merges the vehicle-based camera recognition system with the infrastructure-based sensor system through V2I communication. The two systems combine their capabilities to provide comprehensive traffic light information, where the infrastructure system compensates for the vehicle system's limitations under adverse conditions, thereby enhancing autonomous driving capability
3Reliability
If V2I communication is implemented to receive signal information from signal controllers, then traffic light recognition reliability is improved, but the device complexity and communication infrastructure requirements increase
Solution Approach 1:
The patent uses V2I communication as an intermediary channel to transmit traffic light information from infrastructure sensors to the vehicle. This communication mechanism serves as a bridge that delivers reliable traffic light state data without requiring complex modifications to the vehicle's internal system architecture, thus improving recognition reliability while managing complexity
Data Source
AI summary
Disclosed are a driving guide system and method. The driving guide system includes an input unit configured to receive signal information from a signal controller, a memory in which a driving guide program using the signal information is embedded, and a processor configured to execute the program. When it is not possible to recognize a traffic light using a camera, the processor determines a driving behavior using the signal information and then performs autonomous driving according to the driving behavior or provides a notification to a driver.