Target Vehicle Trajectory Matching for Lane-Level Road Positioning
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating due to the sheer volume of data from sensors and traditional mapping technologies, which can limit navigation accuracy and efficiency.
Innovation Solution
The use of cameras and processing devices to analyze images for object identification, location determination, and navigational actions, incorporating elevation and lane width information, and determining distances to objects for navigational decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping technology is used for autonomous navigation, then navigation functionality is provided, but the sheer volume of data needed to store and update the map poses daunting challenges and limits navigation accuracy and efficiency
Solution Approach 1:
The patent extracts only the essential navigational elements (lane markings, road geometry, elevation data) from complete map data, storing minimal sufficient information for navigation decisions while eliminating redundant data that does not contribute to navigation accuracy
Solution Approach 2:
Instead of using traditional approaches that store complete map data and then query it, the patent inverts the approach by using camera images directly with minimal stored reference data, querying the map system only for essential updates rather than storing comprehensive map information
2Reliability
If vast volumes of sensor data are collected and analyzed for autonomous navigation, then navigation decisions can be made, but the sheer quantity of data to analyze, access, and store poses challenges that limit navigation efficiency
Solution Approach 1:
The system extracts only critical navigational information from camera images (lane markings, road boundaries, elevation changes) rather than processing complete image datasets, eliminating redundant data processing while maintaining navigation decision accuracy
Solution Approach 2:
The patent replaces traditional mechanical sensor systems (multiple cameras, LIDAR, radar) with a simplified camera-based system that uses computational methods to achieve the same navigational functions with less data processing overhead
3Measurement precision
If complete map data is stored and updated continuously, then accurate navigation is possible, but the data storage and update requirements become unmanageably large
Solution Approach 1:
The patent stores map data with local quality by maintaining high precision only for locally relevant navigational features (current lane markings, immediate road geometry) while using lower precision or cached data for distant or less critical areas, reducing overall storage requirements while maintaining positioning accuracy where needed
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 images captured over a time period; analyze images to identify a target vehicle; receive map information associated including a plurality of target trajectories; determine, based on a size of a representation of the target vehicle in the plurality of images, first and second estimated positions of the target vehicle within the time period, determine, based on the first and second estimated positions, a trajectory of the target vehicle over the time period; compare the determined trajectory to the plurality of target trajectories to identify a target trajectory traversed by the target vehicle; determine, based on the identified target trajectory, a position of the target vehicle; and determine a navigational action for the host vehicle based on the determined position.