Vehicular Navigation Using Real-Time Sensor Data
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Solution Overview
Problem
Vehicle navigation systems face difficulties when high-definition map data is unavailable, particularly for manually driven, ADAS-equipped, and autonomous vehicles, as they struggle to navigate sections of roadway without prior map data.
Innovation Solution
A system utilizing sensors to generate segmented sensor data, applying graphical models to identify lane boundaries and determine travel directions, and creating an objective map in real-time to assist vehicles in navigating unknown roadway sections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-definition map data is used for navigation, then navigation accuracy is improved, but the system cannot navigate sections of roadway for which no prior map data is available
Solution Approach 1:
The system performs preliminary actions by collecting and storing sensor data (images, LIDAR, radar) from multiple vehicles as they traverse roadway sections. This pre-collected data is stored in a database and can be retrieved when a vehicle needs to navigate an unknown section, eliminating the need for real-time map data while maintaining navigation accuracy.
Solution Approach 2:
The patent introduces an intermediary mechanism - a centralized database system that mediates between vehicles and roadway information. Instead of relying on pre-existing map data, the system uses an intermediary database that stores sensor data from multiple vehicles, which then serves as the reference for navigation decisions in unknown areas.
2Reliability
If real-time sensor data processing is performed to generate objective maps, then navigation reliability in unknown areas is improved, but computational complexity and processing time increase
Solution Approach 1:
The system performs data collection and initial processing in advance as vehicles traverse roadway sections. Sensor data is captured, stored, and organized in a database before it is needed for navigation, shifting the computational burden from real-time processing to pre-processing operations.
Solution Approach 2:
The patent creates a universal database system that serves multiple vehicles and multiple navigation scenarios. The same database infrastructure supports navigation for different vehicle types (manually driven, ADAS-equipped, autonomous) and different roadway conditions, reducing the need for vehicle-specific processing complexity.
3Measurement precision
If sensor data from multiple vehicles is collected and processed, then map accuracy for unknown sections is improved, but data processing time and computational resources increase
Solution Approach 1:
The system collects and processes sensor data from multiple vehicles in advance, storing it in a database before it is needed for navigation. This preliminary data collection and storage eliminates the need for time-consuming real-time processing when a vehicle needs to navigate an unknown section.
Solution Approach 2:
The patent merges data from multiple vehicles by collecting sensor data from various sources (different vehicle positions, angles, and sensor types) and combining them into a unified database entry for each roadway section. This merging process creates comprehensive and accurate maps while distributing the data collection burden across multiple vehicles.
Data Source
AI summary
Systems and methods for vehicular navigation are disclosed herein. One embodiment receives, from one or more sensors, sensor data pertaining to a roadway section that is proximate to a vehicle; generates segmented sensor data to identify, in the roadway section, one or more boundary lines of one or more lanes; determines, from the sensor data, a direction of travel associated with at least one of the one or more lanes; applies a graphical model to the segmented sensor data to generate an output that includes a set of discrete points corresponding to the one or more boundary lines; generates an objective map of the roadway section from the set of discrete points; and uses the objective map to assist the vehicle in navigating the roadway section.