Projecting Vehicle Network Data for Intersection Navigation
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Solution Overview
Problem
Vehicle transportation network information is often missing, incomplete, or inaccurate, which hinders effective navigation and routing in vehicle transportation systems.
Innovation Solution
A method generates projected vehicle transportation network information by processing remote vehicle messages containing geospatial and kinematic state information from multiple vehicles, allowing for the identification of intersections and routing even when defined network information is unavailable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicle transportation network information is used for navigation, then routing capability is improved, but the information may be missing, incomplete, or inaccurate
Solution Approach 1:
The patent uses remote vehicles as intermediary sources to provide transportation network information. Instead of relying solely on centralized map data that may be incomplete, the system extracts network information from multiple remote vehicles' trajectory data, using them as mediators to fill information gaps and improve routing reliability
Solution Approach 2:
The system enables vehicles to self-generate transportation network information by processing their own and other vehicles' trajectory data. Each vehicle contributes to and benefits from the collective network information, allowing the system to serve itself without requiring complete external map data
2Measurement precision
If projected network information is generated from remote vehicle data, then navigation accuracy in unknown sections is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the transportation network into discrete elements (intersections, road segments) that can be independently identified and processed from vehicle trajectory data. This segmentation allows the system to handle complex data processing in manageable units, extracting network information piece by piece from remote vehicle positions and paths
Solution Approach 2:
The system processes trajectory data from multiple remote vehicles to generate network information, using more data than strictly necessary to achieve accurate navigation. This excessive data collection from multiple sources improves navigation precision in unknown sections while distributing the processing complexity across multiple input streams
Data Source
AI summary
A method and apparatus for generating projected vehicle transportation network information representing an intersection for use in traversing a vehicle transportation network may include receiving a remote vehicle message including remote vehicle information indicating remote vehicle geospatial state information and remote vehicle kinematic state information, identifying host vehicle information including host vehicle geospatial state information and host vehicle kinematic state information, generating projected vehicle transportation network information representing a portion of the vehicle transportation network including an intersection based on the remote vehicle information and the host vehicle information, and traversing the intersection represented by the projected vehicle transportation network information using the projected vehicle transportation network information.