Camera Distance Calculation Using Lane Width Estimation
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Solution Overview
Problem
Existing vehicle driving support technologies face challenges in accurately detecting the distance to a front vehicle due to environmental factors such as buildings and changes in road terrain, which can hinder the detection of the horizon in camera image data.
Innovation Solution
A driving support apparatus and method that includes a detection unit for identifying a front vehicle and driving lane using camera image data, a first calculation unit to estimate the width of the front vehicle based on detected and preset lane information, and a second calculation unit to calculate the distance from the front vehicle using the camera's focal length and estimated widths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If horizon detection technology is used to detect distance from object, then measurement precision is improved, but reliability deteriorates when horizon cannot be detected due to environmental factors
Solution Approach 1:
The patent introduces a lane marking as an intermediary reference object to calculate distance when horizon detection fails. Instead of directly detecting horizon, the system uses detectable lane markings on the road surface as a mediator to infer distance information, thereby maintaining reliability in environments where horizon is not visible.
Solution Approach 2:
The patent changes the reference parameter for distance calculation from horizon position to lane marking position. When horizon detection is not feasible, the system switches to using lane marking detection parameters (position, width, perspective) to calculate distance, adapting the measurement parameters according to environmental conditions.
2Ease of operation
If camera-based detection is used to detect front vehicle and lane, then ease of operation is improved, but measurement precision deteriorates due to environmental factors
Solution Approach 1:
The patent implements a feedback mechanism where the detected lane width and position information is used to verify and refine the distance calculation. The system continuously compares the detected lane markings with expected geometric relationships to validate the measured distance, improving precision while maintaining the simplicity of camera-based operation.
Solution Approach 2:
The patent transitions from two-dimensional image plane detection to three-dimensional spatial calculation by incorporating perspective geometry. By analyzing the convergence of lane markings and their position in the image plane, the system derives accurate distance information, adding a dimensional transformation layer that enhances precision without complicating operation.
Data Source
AI summary
Disclosed relates to a driving support apparatus including at least: a detection unit that detects a driving lane on which a user's vehicle and a front vehicle located in front of the user's vehicle are driving based on image data output from a camera; a first calculation unit that calculates a second front vehicle width for the front vehicle based on a first front vehicle width for the front vehicle measured on the image data, a first driving lane width for the driving lane measured on the image data, and a second driving lane width predetermined according to a characteristic of the driving lane; and a second calculation unit that calculates a distance from the front vehicle based on a focal length of the camera, the first front vehicle width, and the second front vehicle width, thereby precisely measuring the distance from the front vehicle based on camera image data.