Target Vehicle Road Positioning From Tracked Trajectories
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating effectively due to the vast amounts of data they need to process and store, particularly with traditional mapping technologies, which can limit their ability to accurately identify locations, obstacles, and navigate through complex environments.
Innovation Solution
The use of cameras and processing devices to analyze images, determine vehicle location, and calculate navigational actions based on elevation and lane width information, allowing for real-time navigation decisions without relying on extensive data storage or updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping technology is used for autonomous vehicle navigation, then comprehensive map data can be obtained, but the data storage requirements and processing complexity increase significantly
Solution Approach 1:
The patent extracts only the essential navigation elements (road geometry, lane markings, traffic signals) from comprehensive map data, storing them in a simplified format that maintains navigation accuracy while significantly reducing data storage requirements. The system takes out only what is necessary for safe autonomous operation rather than storing complete traditional maps.
Solution Approach 2:
The navigation system segments the environment into discrete, manageable components such as road segments, lane markings, and traffic signal locations. Each segment is processed and stored independently, allowing efficient data management and reducing overall data volume while maintaining comprehensive navigation coverage.
2Measurement precision
If comprehensive environmental data is processed in real-time, then navigation accuracy improves, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary processing of map data during off-line operations, pre-identifying road geometries, lane configurations, and traffic signal locations. This preliminary action allows real-time processing to focus only on matching sensor data with pre-processed reference information, significantly reducing computational load and processing time while maintaining high location identification accuracy.
3Reliability
If extensive map data is stored and updated, then navigation reliability improves, but system complexity and update requirements increase
Solution Approach 1:
Instead of maintaining complex, continuously updated traditional map databases, the system uses simplified, static road geometry data that does not require frequent updates. The system is designed to operate reliably with this simpler data structure, treating the mapping system as more disposable and less complex while maintaining navigation reliability through robust real-time sensor processing.
Data Source
AI summary
Systems and methods are provided for navigating a host vehicle. In an embodiment, a processing device may be configured to receive a plurality of images captured by an image capture device, the plurality of images being representative of an environment of the host vehicle; analyze at least one of the plurality of images to identify a target vehicle in the environment of the host vehicle; receive map information associated with an environment of the host vehicle; determine a trajectory of the target vehicle over a time period based on analysis of the plurality of images; determine, based on the determined trajectory of the target vehicle and the map information, a position of the target vehicle relative to a road in the environment of the host vehicle; and determine a navigational action for the host vehicle based on the determined position of the target vehicle.