Traffic Light State Detection for Low-Map Autonomous Navigation
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating due to the vast amount of data they need to process and store, including image data, map data, and sensor data, which can limit their navigation capabilities and rely heavily on traditional mapping technology that requires significant data storage and updates.
Innovation Solution
The use of cameras to monitor the vehicle's environment, analyze traffic lights, and implement navigational actions based on their state, combined with crowd-sourced maps that link drivable paths to logical traffic light groups, allowing vehicles to make informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping technology is used to navigate, then navigation capability is provided, but the volume of data needed to store and update the map becomes excessively large
Solution Approach 1:
The patent extracts only the essential navigational elements (traffic lights, signs, road geometry) from complete map data, storing merely the information needed for navigation decisions rather than full map replicas, thereby reducing data storage requirements while maintaining navigation capability
Solution Approach 2:
The patent segments map data into discrete, localized features (individual traffic lights, signs, road segments) that can be independently identified and stored, allowing the system to process and store only relevant portions of environmental data rather than complete maps
2Measurement precision
If vast volumes of visual information are processed, then navigation accuracy is improved, but the complexity of data processing and storage increases
Solution Approach 1:
The patent applies local quality by focusing processing power on identifying and analyzing specific critical features (traffic lights, signs, lane markings) in the vehicle's immediate environment rather than processing all visual data uniformly, thereby maintaining navigation accuracy while reducing overall processing complexity
Solution Approach 2:
The patent performs preliminary identification and classification of relevant environmental features before detailed analysis, pre-filtering visual data to identify only those elements that will impact navigation decisions, thus reducing the complexity of subsequent processing while preserving navigation accuracy
3Loss of information
If complete map data is stored for all road segments, then comprehensive navigation information is available, but storage and update demands become unmanageable
Solution Approach 1:
The patent extracts only the essential navigational elements (traffic lights, signs, road geometry) from complete map data, storing merely the information needed for navigation decisions rather than full map replicas, thereby reducing data storage requirements while maintaining navigation capability
Solution Approach 2:
The patent inverts the traditional approach by not storing complete map data and then querying it, but instead identifying and storing only the specific features relevant to the vehicle's current navigation needs, achieving information completeness with minimal storage
Data Source
AI summary
Systems and methods are provided for vehicle navigation. In one implementation, a system for navigating a vehicle may include at least one processor configured to receive a first image frame; detect in the first image frame a representation of a traffic light and determine a color state associated with lamps included on the traffic light. The at least one processor may receive an additional image frame includes a representation of the at least one traffic light; and determine, based on a comparison of the first image frame and the additional image frame, whether the at least one traffic light includes a blinking lamp. If the at least one traffic light includes a blinking lamp, the processor may cause the vehicle to implement a navigational action relative the traffic light in accordance with the determination and also based on a detected color state for the blinking lamp.