Traffic Sign Localization via Frame Synchronization
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Solution Overview
Problem
Current systems for autonomous vehicles (AVs) face inefficiencies in recognizing and localizing traffic signs, leading to potential unsafe driving behaviors due to time-consuming and inaccurate manual or sensor-based methods.
Innovation Solution
A system comprising sensors, processors, and memory that monitors a vehicle's location, detects signs frame-by-frame, synchronizes data with the vehicle's position, determines sign location before it disappears from view, and updates maps for navigation, enabling accurate sign recognition and driving actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual or sensor-based methods are used to determine traffic sign locations, then the system can obtain sign location data, but the process is time-consuming and inaccurate
Solution Approach 1:
The system performs preliminary actions by continuously capturing frame-by-frame data of traffic signs as the vehicle approaches them, synchronizing each frame with the vehicle's location. This preparation ensures that when a sign is detected, its location is already determined and ready for immediate use, eliminating time delays while maintaining high accuracy through pre-synchronized positional data.
Solution Approach 2:
The patent replaces manual determination methods with an automated sensor-based system that uses cameras and processors to detect and localize traffic signs. This substitution of mechanical/manual processes with electronic sensing and computational analysis dramatically reduces both time consumption and human error, achieving high precision automatically.
2Measurement precision
If the system captures frame-by-frame data to determine sign location, then measurement precision improves, but data processing complexity increases
Solution Approach 1:
The system segments the continuous video stream into individual frames and processes them sequentially, capturing only relevant frames where traffic signs are visible. By dividing the complex task of continuous analysis into discrete frame-level processing steps, the system achieves high measurement precision while managing computational complexity through structured, incremental analysis.
Solution Approach 2:
The system extracts only the essential information from each frame - specifically detecting whether a traffic sign is present and determining its location relative to the vehicle. By extracting only the critical data needed for navigation rather than processing all visual information, the system maintains high precision while reducing overall processing complexity.
Data Source
AI summary
Provided herein is a system and method of a vehicle. The system comprises one or more sensors, processors, maps, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: monitoring a location of the vehicle while driving; detecting a sign while the vehicle is driving; capturing, frame-by-frame, data of the sign until the sign disappears from a field of view of the sensor; synchronizing each frame of the data with the location of the vehicle; determining a location of the sign based on the frame-by-frame data; in response to determining, at a frame immediately before the sign disappears from the field of view of the sensor, that the vehicle is driving towards the sign, uploading the detected sign and the location of the sign onto the one or more maps; and implementing a driving action based on the sign.