Multi-Sensor Lane Recognition with Road Boundary Filtering
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Solution Overview
Problem
Current autonomous driving technologies face inaccuracies in road boundary detection due to weather conditions, obstacles, and sensor characteristics, and are costly, making them unsuitable for mass production.
Innovation Solution
An apparatus and method utilizing a low-cost GPS system combined with multiple environment recognition sensors and a precision map to detect road boundaries and recognize driving lanes, involving sensors for road, obstacle, and vehicle movement information, with a controller to extract and validate candidate location data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive GNSS/INS is used for autonomous driving, then position recognition accuracy is improved, but production cost increases
Solution Approach 1:
The patent replaces expensive GNSS/INS with low-cost sensors (camera, radar, ultrasonic sensor) that can be affordably deployed in mass-produced vehicles. The system uses multiple inexpensive sensors working together to achieve positioning accuracy comparable to expensive single-point solutions, making autonomous driving economically viable for mass production
Solution Approach 2:
The patent combines data from multiple different low-cost sensors (camera for visual recognition, radar for distance measurement, ultrasonic sensor for close-range detection) to achieve accurate position recognition. By merging the capabilities of these inexpensive sensors, the system reaches the performance level of expensive GNSS/INS without the high cost
2Ease of operation
If road boundary detection is performed using traditional sensors, then driving lane recognition is enabled, but detection accuracy decreases due to weather and obstacles
Solution Approach 1:
The patent employs feedback mechanisms where the system continuously monitors detection confidence levels and adjusts sensor activation and data processing accordingly. When detection accuracy is compromised by weather or obstacles, the system receives feedback about degraded conditions and compensates by integrating additional sensor data or adjusting processing algorithms to maintain accurate road boundary detection
Solution Approach 2:
The patent creates a composite sensing system that combines multiple sensor types (camera, radar, ultrasonic sensor) to detect road boundaries. This composite approach is analogous to composite materials in engineering, where combining different materials with complementary properties creates a system that overcomes the limitations of individual components, enabling accurate road boundary detection under various weather and obstacle conditions
Data Source
AI summary
An apparatus for recognizing a driving lane based on multiple sensors is provided. The apparatus includes a first sensor configured to calculate road information, a second sensor configured to calculate moving obstacle information, a third sensor configured to calculate movement information of a vehicle, and a controller configured to remove the moving obstacle information from the road information to extract only road boundary data, accumulate the road boundary data to calculate a plurality of candidate location information on the vehicle based on the movement information, and select final candidate location information from the plurality of candidate location information.