Road Arrow Orientation Detection for Lightweight Vehicle Navigation
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating due to the sheer volume of data required for processing and storing information from various sources, such as cameras, GPS, and sensors, which can limit their navigation capabilities and increase complexity.
Innovation Solution
The use of cameras and processors to analyze images and update autonomous vehicle road navigation models, including lane marks, directional arrows, traffic lights, and free spaces, allowing for real-time navigation and data distribution among vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping technology is used to navigate, then navigation coverage is comprehensive, but data storage requirements and system complexity increase significantly
Solution Approach 1:
The patent extracts only the essential navigation elements (lane marks, directional arrows, traffic lights, free spaces) from the complete traditional map data, storing only these critical features rather than comprehensive geographic information. This reduces data storage requirements while maintaining navigation accuracy by focusing on road geometry and traffic control elements.
Solution Approach 2:
The navigation model is segmented into discrete, independently detectable road features (lane marks, arrows, traffic lights, free spaces) rather than storing continuous map data. Each feature type is detected and stored separately, allowing the system to process and store only relevant navigation information without the overhead of complete traditional mapping data.
2Loss of information
If comprehensive sensor data is collected from multiple sources, then navigation information is complete, but processing time and computational load increase
Solution Approach 1:
The system extracts only the essential navigation features (lane marks, directional arrows, traffic lights, free spaces) from sensor data, ignoring redundant information. This selective extraction maintains information completeness for navigation purposes while significantly reducing processing time by focusing computational resources on critical features only.
Solution Approach 2:
The patent applies partial action by detecting and processing only the specific road features necessary for navigation (lane marks, arrows, traffic lights, free spaces) rather than analyzing all possible sensor data. This partial processing approach provides sufficient navigation information without the computational burden of complete data analysis.
3Reliability
If real-time map updates are performed for all vehicles, then navigation accuracy is maintained, but data transmission and processing overhead increase
Solution Approach 1:
The system transmits only the extracted essential navigation features (lane mark positions, arrow orientations, traffic light states, free space locations) rather than complete map updates. This selective data transmission maintains navigation model accuracy across the fleet while minimizing communication overhead and energy consumption.
Solution Approach 2:
Each vehicle maintains a local copy of the navigation model with essential features, updating it with transmitted feature data rather than receiving complete map updates. This copying approach allows vehicles to operate independently with minimal data exchange while maintaining synchronized navigation information.
Data Source
AI summary
A system for vehicle navigation is provided. The system includes at least one processing circuitry programmed to receive via a data interface one or more images captured by one or more cameras representative of an environment of a vehicle, identify, based on analysis of the one or more images, at least one direction of at least one directional arrow on a road surface in the one or more images, determine a direction of travel for the vehicle based on the at least one direction of the at least one directional arrow on the road surface, determine at least one navigational action for the vehicle based on the determined direction of travel for the vehicle, and cause one or more actuator systems of the vehicle to implement the determined at least one navigational action for the vehicle.