Vehicle Localization Using Image Classification and Sensor Fusion
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Solution Overview
Problem
Conventional autonomous driving systems (ADS) face challenges in providing meaningful and actionable information to drivers about nearby vehicles, as they often display vehicles as moving rectangles or blobs, making it difficult for drivers to correlate sensory input with actual vehicles on the road, limiting the system's utility.
Innovation Solution
An ego vehicle equipped with image sensors, processors, and memory that obtain images of target vehicles, classify them, and determine their position information relative to the ego vehicle, using vehicle characteristics such as dimensions, color, and license plate information, to enhance localization and identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional ranging sensors (radar/lidar) are used to detect nearby vehicles, then vehicle presence detection is achieved, but the information is difficult to correlate with actual vehicles on the roadway
Solution Approach 1:
The patent creates a visual copy of the detected vehicle by capturing an image with an image sensor and displaying it on the display device. This allows the driver to see the actual visual appearance of the vehicle (including color, shape, and features) rather than just abstract sensor data, making it easy to correlate the displayed information with the actual vehicle on the roadway.
Solution Approach 2:
The patent merges multiple information sources including image sensor data, ranging sensor data, and display output into a unified presentation. The vehicle image is combined with position information and other characteristics, creating a comprehensive visual representation that preserves identification information while maintaining ease of driver interpretation.
2Measurement precision
If vehicle images are captured and processed to determine position information, then vehicle identification accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the vehicle detection and tracking system into distinct functional modules: an image sensor for capturing vehicle images, a processor for analyzing images and determining position information, and a display device for presenting the information. This segmentation allows each component to perform its specific function efficiently while maintaining overall system manageability.
Solution Approach 2:
The processor performs multiple functions including image processing, position calculation, and data integration. By making the processor multi-functional, the patent reduces the need for separate dedicated components for each task, thereby improving measurement precision without proportionally increasing system complexity.
Data Source
AI summary
Disclosed embodiments pertain to a method for determining position information of a target vehicle relative to an ego vehicle. The method may comprise: obtaining, by at least one image sensor, first images of one or more target vehicles and classifying at least one target vehicle from the one or more target vehicles based on the one or more first images. Further, vehicle characteristics corresponding to the least one target vehicle may be obtained based on the classification of the least one target vehicle. Position information of the at least one target vehicle relative to the ego vehicle may be determined based on the vehicle characteristics.