Road traffic detection control method based on vehicle-mounted camera module

Abstract

The invention discloses a road traffic detection control method based on a vehicle-mounted camera module, and belongs to the technical field of traffic detection, and the method specifically comprises the steps: collecting road image data in real time through the vehicle-mounted camera module; preprocessing the acquired road image data, and extracting a road area; performing edge extraction on the preprocessed road image data by using an edge detection algorithm to obtain road edge information; according to the road edge information, detecting straight-line segments in the road through Hough transform, and calculating an included angle between adjacent straight-line segments to determine the line type of the road; calculating the distance between the vehicle and the road boundary and the offset of the vehicle relative to the road center line according to the line type of the road in combination with the speed and position information of the vehicle; according to the distance between the vehicle and the road boundary and the offset of the vehicle relative to the road center line, the driving direction and speed of the vehicle are adjusted through a preset control strategy; according to the invention, real-time safety detection of the vehicle in the driving state is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic detection, and in particular to a road traffic detection control method based on a vehicle-mounted camera module. Background Art

[0002] With the rapid development of the automotive industry and increasingly busy road traffic, road safety has become a hot topic of global concern. Effectively detecting and controlling the distance between a vehicle and the road's edge, as well as its offset from the road's centerline, is crucial for improving road safety and reducing traffic accidents. However, in the face of complex road traffic, individual attention alone cannot fully observe all road conditions.

[0003] Traditional road traffic detection methods rely primarily on ground-based sensors, radar, lasers, and other equipment for data collection and processing. However, these methods suffer from high equipment costs, difficult installation and maintenance, and significant susceptibility to environmental factors. Furthermore, these methods often only provide partial road information and fail to fully and accurately reflect the entire road situation.

[0004] In recent years, with the development of computer vision technology, road traffic detection methods based on vehicle-mounted camera modules have gradually attracted attention. Based on this, the present invention provides a road traffic detection and control method based on a vehicle-mounted camera module. Summary of the Invention

[0005] The purpose of the present invention is to provide a road traffic detection and control method based on a vehicle-mounted camera module to solve the following technical problems: Traditional road traffic monitoring methods rely primarily on ground-based sensors, radar, lasers, and other equipment for data collection and processing. These methods suffer from high equipment costs, difficulty in installation and maintenance, and significant susceptibility to environmental factors. They often only provide partial road information and fail to fully and accurately reflect the overall road situation.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A road traffic detection and control method based on a vehicle-mounted camera module comprises the following steps: The vehicle-mounted camera module collects road image data in real time during vehicle driving; Preprocess the collected road image data, including denoising, enhancement and segmentation, and extract the road area; The edge detection algorithm is used to extract the edges of the preprocessed road image data to obtain road edge information. Based on the road edge information, the straight line segments in the road are detected through Hough transform, and the straight line segments are repaired. The angle between adjacent straight line segments is calculated to determine the road line shape. Based on the road line shape, combined with the vehicle's speed and position information, the distance between the vehicle and the road boundary and the vehicle's offset from the road centerline are calculated; The vehicle's direction and speed are adjusted according to the distance between the vehicle and the road boundary and the offset of the vehicle relative to the road centerline through a preset control strategy.

[0007] As a further solution of the present invention: the denoising process adopts a median filter or a Gaussian filter algorithm, the enhancement process adopts a histogram equalization or a contrast stretching algorithm, and the segmentation process adopts an Otsu method or a maximum inter-class variance method.

[0008] As a further solution of the present invention: the edge detection algorithm adopts the Canny operator, the Sobel operator or the Prewitt operator, applies the selected edge detection operator to calculate the gradient magnitude and direction of each pixel in the image, separates the edge from the background noise by applying a threshold to the gradient magnitude, and outputs a binary image in which the road edge is marked in white.

[0009] As a further solution of the present invention: the Hough transform adopts the standard Hough transform, and the angle calculation formula is: θ = arctan((y2 - y1) / (x2 - x1)), where (x1, y1) and (x2, y2) are the coordinates of the two endpoints of adjacent straight line segments, respectively.

[0010] As a further solution of the present invention: the process of repairing the straight line segment is: The remaining vehicles on the road are deleted, the vehicle images in the road image are replaced with the basic road image, the original landmark lines in the road image are detected, and the landmark lines are extended along the original directions so that the landmark lines pass through the basic road image and connect with each other, thereby obtaining a road image with pure landmark lines.

[0011] As a further solution of the present invention: the distance between the vehicle and the road boundary is calculated as follows: D = |k * x + b| / √(k^2 + 1), where k is the slope of the road linear fitting line, b is the intercept, and x is the horizontal coordinate of the vehicle's current position.

[0012] As a further solution of the present invention: the offset of the vehicle relative to the center line of the road is calculated as follows: Offset = (W / 2) - D, where W is the road width and D is the distance between the vehicle and the road boundary.

[0013] As a further solution of the present invention: the control strategy includes: when the distance and offset between the vehicle and the road boundary are both less than a preset threshold, reminding the driver; when only the distance to the road boundary is greater than or equal to the preset threshold, automatically reducing the vehicle speed to a safe speed; when only the offset is greater than the preset threshold, issuing a warning.

[0014] As a further solution of the present invention: real-time monitoring of the vehicle driving state, wherein the vehicle driving state includes the vehicle's speed, acceleration, heading angle and lateral offset, and judging whether the control strategy needs to be adjusted according to a preset threshold.

[0015] Beneficial effects of the present invention: This method collects and processes road image data in real time to accurately calculate the distance between the vehicle and the road boundary and its offset from the road centerline. Combined with the vehicle's speed and position information, it adjusts the vehicle's direction and speed using a pre-set control strategy, effectively improving road safety and driving comfort. This method boasts low equipment cost, simple installation and maintenance, strong stability, high reliability, and wide adaptability. It operates in a variety of environmental conditions, reducing traffic accidents while enhancing the driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below with reference to the accompanying drawings.

[0017] Figure 1 It is a schematic flow diagram of the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0019] See also Figure 1 As shown, the present invention is a road traffic detection and control method based on a vehicle-mounted camera module, comprising the following steps: The vehicle-mounted camera module collects road image data in real time during vehicle driving; Preprocess the collected road image data, including denoising, enhancement and segmentation, and extract the road area; The edge detection algorithm is used to extract the edges of the preprocessed road image data to obtain road edge information. Based on the road edge information, the straight line segments in the road are detected through Hough transform, and the straight line segments are repaired. The angle between adjacent straight line segments is calculated to determine the road line shape. Based on the road line shape, combined with the vehicle's speed and position information, the distance between the vehicle and the road boundary and the vehicle's offset from the road centerline are calculated; The vehicle's direction and speed are adjusted according to the distance between the vehicle and the road boundary and the offset of the vehicle relative to the road centerline through a preset control strategy.

[0020] In recent years, with the development of computer vision technology, road traffic detection methods based on vehicle-mounted camera modules have gradually attracted attention. Vehicle-mounted camera modules collect real-time road image data while vehicles are driving, and then process and analyze the image data to obtain road information. Compared with traditional methods, methods based on vehicle-mounted camera modules have the advantages of low cost, simple installation and maintenance, and less impact from environmental factors. The present invention uses an onboard camera module to capture real-time road image data. Combined with the vehicle's speed and position information, it accurately calculates the vehicle's distance from the road boundary and its offset from the road centerline. Pre-set control strategies can promptly adjust the vehicle's direction and speed, effectively preventing it from straying from its lane or colliding with roadside obstacles, thereby improving road safety.

[0021] Compared to traditional road traffic detection methods, this invention uses a vehicle-mounted camera module as a data acquisition device, offering advantages such as low cost and simple installation and maintenance. Furthermore, the method does not rely on ground-based sensors, radar, or other equipment, thus avoiding the additional costs and maintenance difficulties associated with these devices.

[0022] In another preferred embodiment of the present invention, the denoising process adopts a median filter or a Gaussian filter algorithm, the enhancement process adopts a histogram equalization or a contrast stretching algorithm, and the segmentation process adopts an Otsu method or a maximum inter-class variance method.

[0023] This method improves image quality by performing preprocessing operations such as denoising, enhancement, and segmentation on collected road image data, making subsequent edge extraction and straight line segment restoration more accurate and reliable. Furthermore, the method employs an improved Hough transform algorithm and angle calculation formula to further enhance the accuracy and robustness of road alignment detection.

[0024] In another preferred embodiment of the present invention, the edge detection algorithm uses a Canny operator, a Sobel operator, or a Prewitt operator. The selected edge detection operator is applied to calculate the gradient magnitude and direction of each pixel in the image. By applying a threshold to the gradient magnitude, the edge is separated from the background noise, and a binary image is output in which the road edge is marked in white.

[0025] In another preferred embodiment of the present invention, the Hough transform adopts the standard Hough transform, and the angle calculation formula is: θ = arctan((y2 - y1) / (x2 - x1)), where (x1, y1) and (x2, y2) are the coordinates of the two endpoints of adjacent straight line segments respectively.

[0026] In another preferred embodiment of the present invention, the process of repairing a straight line segment is as follows: The remaining vehicles on the road are deleted, the vehicle images in the road image are replaced with the basic road image, the original landmark lines in the road image are detected, and the landmark lines are extended along the original directions so that the landmark lines pass through the basic road image and connect with each other, thereby obtaining a road image with pure landmark lines.

[0027] In another preferred embodiment of the present invention, the distance between the vehicle and the road boundary is calculated as follows: D = |k* x + b| / √(k^2 + 1), where k is the slope of the road profile fitting line, b is the intercept, and x is the horizontal coordinate of the vehicle's current position.

[0028] In another preferred embodiment of the present invention, the calculation formula for the offset of the vehicle relative to the center line of the road is: Offset = (W / 2) - D, where W is the road width and D is the distance between the vehicle and the road boundary.

[0029] In another preferred embodiment of the present invention, the control strategy includes: when the distance and offset between the vehicle and the road boundary are both less than a preset threshold, reminding the driver; when only the distance to the road boundary is greater than or equal to the preset threshold, automatically reducing the vehicle speed to a safe speed; when only the offset is greater than the preset threshold, issuing a warning.

[0030] Improved driving comfort: This system adjusts the vehicle's direction and speed in real time, ensuring a safe and comfortable driving experience. This allows the driver to focus less on vehicle operation and more on observing traffic conditions and making decisions, improving driving comfort and convenience.

[0031] In another preferred embodiment of the present invention, the vehicle driving state is monitored in real time, and the vehicle driving state includes the vehicle's speed, acceleration, heading angle and lateral offset, and it is determined whether the control strategy needs to be adjusted based on a preset threshold.

[0032] The present invention can monitor vehicle driving conditions in real time, including speed, acceleration, heading angle, and lateral offset, and determine whether control strategies need to be adjusted based on preset thresholds. This allows for timely identification of potential hazards and implementation of appropriate measures, even in complex road conditions, to reduce the likelihood of traffic accidents.

[0033] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A road traffic detection and control method based on a vehicle-mounted camera module, characterized in that: The following steps are involved: The vehicle-mounted camera module collects road image data in real time during vehicle driving; Preprocess the collected road image data, including denoising, enhancement and segmentation, and extract the road area; The edge detection algorithm is used to extract the edges of the preprocessed road image data to obtain road edge information. Based on the road edge information, the straight line segments in the road are detected through Hough transform, and the straight line segments are repaired. The angle between adjacent straight line segments is calculated to determine the road line shape. Based on the road line shape, combined with the vehicle's speed and position information, the distance between the vehicle and the road boundary and the vehicle's offset from the road centerline are calculated; The vehicle's direction and speed are adjusted according to the distance between the vehicle and the road boundary and the offset of the vehicle relative to the road centerline through a preset control strategy.

2. A road traffic detection and control method based on a vehicle-mounted camera module according to claim 1, characterized in that: The denoising process adopts a median filter or a Gaussian filter algorithm, the enhancement process adopts a histogram equalization or a contrast stretching algorithm, and the segmentation process adopts an Otsu method or a maximum inter-class variance method.

3. The road traffic detection and control method based on a vehicle-mounted camera module according to claim 1, characterized in that: The edge detection algorithm uses the Canny operator, Sobel operator, or Prewitt operator. The selected edge detection operator is applied to calculate the gradient magnitude and direction of each pixel in the image. By applying a threshold to the gradient magnitude, the edge is separated from the background noise and a binary image is output in which the road edge is marked in white.

4. The road traffic detection and control method based on a vehicle-mounted camera module according to claim 1, characterized in that: The Hough transform adopts the standard Hough transform, and the angle calculation formula is: θ = arctan((y2 - y1) / (x2- x1)), where (x1, y1) and (x2, y2) are the coordinates of the two endpoints of adjacent straight line segments.

5. The road traffic detection and control method based on a vehicle-mounted camera module according to claim 1, characterized in that: The process of repairing a straight line segment is: The remaining vehicles on the road are deleted, the vehicle images in the road image are replaced with the basic road image, the original landmark lines in the road image are detected, and the landmark lines are extended along the original directions so that the landmark lines pass through the basic road image and connect with each other, thereby obtaining a road image with pure landmark lines.

6. The road traffic detection and control method based on a vehicle-mounted camera module according to claim 1, characterized in that: The distance between the vehicle and the road boundary is calculated as: D = |k * x + b| / √(k^2 + 1), where k is the slope of the road profile fitting line, b is the intercept, and x is the horizontal coordinate of the vehicle's current position.

7. The road traffic detection and control method based on a vehicle-mounted camera module according to claim 1, characterized in that: The formula for calculating the vehicle's offset relative to the road centerline is: Offset = (W / 2) - D, where W is the road width and D is the distance between the vehicle and the road edge.

8. The road traffic detection and control method based on a vehicle-mounted camera module according to claim 1, characterized in that: The control strategy includes: reminding the driver when both the distance and offset between the vehicle and the road boundary are less than a preset threshold; automatically reducing the vehicle speed to a safe speed when only the distance to the road boundary is greater than or equal to the preset threshold; and issuing a warning when only the offset is greater than the preset threshold.

9. The road traffic detection and control method based on a vehicle-mounted camera module according to claim 1, characterized in that: The vehicle's driving status is monitored in real time, including the vehicle's speed, acceleration, heading angle, and lateral offset, and a control strategy is determined based on preset thresholds to determine whether adjustments are needed.

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