Driving Image Distance Measurement Using Vehicle Size Classification
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Solution Overview
Problem
Conventional methods for measuring inter-vehicle distance inaccurately treat vehicle widths as fixed values, leading to errors in risk judgment and interfering with safe driving by ADAS systems.
Innovation Solution
Calculate the ratio between the image width of a front vehicle and the lane width to determine the vehicle's size class, and use this to measure the inter-vehicle distance accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If vehicle width is treated as a predetermined constant value, then the measurement process is simple, but the inter-vehicle distance measurement accuracy deteriorates
Solution Approach 1:
The patent changes the parameter of vehicle width from a fixed constant to a variable value determined by image processing. The system calculates the actual vehicle width by detecting the vehicle's image width in pixels and converting it to real-world dimensions using the camera's field of view and focal length, thereby improving measurement accuracy while maintaining automated processing.
Solution Approach 2:
The patent replaces the mechanical assumption of fixed vehicle width with an optical measurement system. By using the camera's optical properties (focal length, field of view) and image processing algorithms, the system automatically determines vehicle width without requiring manual input or predetermined values, resolving the contradiction between simplicity and accuracy.
2Ease of operation
If a fixed vehicle width value is used for all vehicles, then the system operation is simple, but the risk judgment accuracy deteriorates
Solution Approach 1:
The system performs self-measurement of vehicle width by automatically processing the captured image. The algorithm detects the vehicle boundaries in the image, calculates the image width in pixels, and converts it to actual width using camera parameters. This self-service approach eliminates the need for manual vehicle width input while improving risk judgment accuracy for different vehicle types.
Solution Approach 2:
The patent dynamically changes the vehicle width parameter based on actual image measurement rather than using a fixed value. By calculating the ratio of image width to lane width and using camera focal length, the system adapts the vehicle width parameter to match the actual vehicle being measured, thereby improving reliability without complicating operation.
3Device complexity
If vehicle width is not considered, then the measurement process is simple, but the forward collision warning accuracy deteriorates
Solution Approach 1:
The patent creates a universal measurement system that handles different vehicle types (compact cars, midsize cars, full-sized cars) using the same image processing algorithm. The system universally applies the formula: actual width = (image width in pixels / focal length) × field of view, making the process adaptable to various vehicle sizes without requiring different measurement procedures, thus improving accuracy without significantly increasing complexity.
Data Source
AI summary
A method for measuring an inter-vehicle distance using a processor is provided. The method includes acquiring a driving image photographed by a photographing device of a first vehicle; detecting a second vehicle from the driving image and calculating a ratio between an image width of the detected second vehicle and an image width of a lane in which the second vehicle is located; determining a size class of the second vehicle among a plurality of size classes based on the calculated ratio; determining a width of the second vehicle based on the determined size class of the second vehicle; and calculating a distance from the photographing device to the second vehicle based on the determined width of the second vehicle, a focal length of the photographing device, and the image width of the second vehicle.