Driving Support System Visual Recognition Position Data
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Solution Overview
Problem
Existing driving support systems face challenges in accurately predicting the visual recognizability of traffic lights, especially in complex road conditions, leading to difficulties in notifying drivers when a traffic light is not visually recognizable.
Innovation Solution
A driving support system and server device that acquire and recognize visual-recognition position information using image acquisition and traffic-light recognition, notifying drivers when a traffic light is not recognized, and transmitting corrected information based on vehicle type, to ensure accurate notification of traffic light visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If visual recognizability is calculated only based on the height of the traffic light, then the calculation is simple, but the prediction accuracy is insufficient
Solution Approach 1:
The system changes from using a single parameter (traffic light height) to multiple parameters including vehicle position, road gradient, curve radius, and traffic light position to comprehensively determine visual recognizability. This multi-parameter approach resolves the contradiction by maintaining reasonable computational complexity while significantly improving prediction accuracy.
2Reliability
If the system notifies drivers frequently about traffic light visibility, then driver awareness is improved, but notification accuracy deteriorates due to false warnings
Solution Approach 1:
The system uses feedback from multiple sensors (camera, GPS, accelerometer, gyroscope) to continuously monitor actual vehicle position and road conditions, comparing them against predicted visibility conditions. This feedback mechanism enables the system to provide accurate notifications only when truly necessary, improving both driver awareness and notification accuracy by reducing false warnings.
3Measurement precision
If the system collects visual-recognition position information from multiple vehicles, then data accuracy is improved, but system complexity increases
Solution Approach 1:
The system merges visual-recognition position information from multiple vehicles through a server that aggregates and processes data from various sources. By combining data from multiple vehicles and merging it with map information and traffic light position data, the system achieves high data accuracy while managing complexity through centralized processing and data fusion techniques.
Data Source
AI summary
A driving support system includes: an acquisition portion configured to acquire visual-recognition position information on a position where a driver of a vehicle visually recognizes a traffic light; an image acquisition portion configured to acquire a forward image ahead of the vehicle; a traffic-light recognition portion configured to recognize a traffic light included in a forward image; and a notification portion configured to notify the driver of warning when the traffic light is not recognized from the forward image, in a case where the vehicle is present at a position based on the visual-recognition position information.