Anonymized Road Segment Mapping for Autonomous Navigation
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating due to the vast amounts of data they need to process and store, particularly with traditional mapping technologies, which can limit their ability to efficiently analyze and update maps in real-time.
Innovation Solution
The system employs cameras to collect and analyze environmental data, using a processor to determine motion representations and road characteristics, and transmits this information to a server for constructing an autonomous vehicle road navigation model, allowing for efficient data management and navigation without storing extensive map data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping technology is used to navigate, then navigation accuracy is maintained, but data storage requirements and processing complexity increase significantly
Solution Approach 1:
The patent extracts only the essential navigation elements from complete map data by using sparse map representation. Instead of storing and processing entire map datasets, the system identifies and stores only critical features such as lane markings, intersections, and navigable paths, thereby reducing data storage requirements while maintaining navigation accuracy.
Solution Approach 2:
The patent segments the map data into discrete, manageable components representing only the necessary navigation information. By dividing the continuous map into segmented features like road segments, intersections, and waypoints, the system reduces overall data volume while preserving essential navigation functionality.
2Reliability
If complete map data is stored and updated in real-time, then navigation reliability is improved, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential navigation features from complete map data, storing and processing only critical elements such as lane markings, intersections, and navigable paths. This extraction approach maintains navigation reliability by preserving essential information while reducing processing time through minimized data volume.
3Measurement precision
If vast volumes of navigation data are collected and analyzed, then navigation accuracy is improved, but system complexity and data management challenges increase
Solution Approach 1:
The patent applies extraction by identifying and retaining only the essential navigation features from vast volumes of collected data. By filtering out redundant information and storing only critical elements like lane markings, intersections, and navigable paths, the system maintains measurement precision while significantly reducing system complexity and data management burden.
Data Source
AI summary
Systems and methods are provided for collecting anonymized drive information. A processing device may be configured to receive outputs from one or more sensors; determine at least one motion representation for the host vehicle based on the outputs; receive at least one image representative of an environment of the host vehicle; analyze the at least one image to determine at least one road characteristic associated with a road section; assemble first road segment information relative to a first portion of the road section, wherein the first portion of the road section is separated from a starting point associated with a route traveled by the host vehicle; assemble second road segment information relative to a second portion of the road section; and cause transmission of the first road segment information and the second road segment information to a server for assembly of an autonomous vehicle road navigation model.