Lane line positioning system based on magnetic marks

Abstract

The invention discloses a lane line positioning system based on magnetic marks, and particularly relates to the field of lane line positioning, and the system comprises sensor configuration: a vehicle is equipped with magnetic sensors which are usually located at the front part and / or the bottom of the vehicle, and the sensors can detect the magnetic field change generated by the magnetic marks; and data processing: when the vehicle passes through the road section with the magnetic mark, the magnetic field data captured by the sensor is sent to a central processing unit of the vehicle, and the central processing unit analyzes the data. According to the method, the visibility of the lane line is remarkably improved by combining the magnetic mark and the sensor on the vehicle, under the condition that a visual system (such as a camera) is limited, the magnetic sensor provides a reliable alternative scheme, it is ensured that the vehicle can accurately recognize and follow the lane, and in addition, the driving safety of the vehicle is improved. The system can also be integrated with a navigation and automatic driving system of a vehicle, and more accurate lane keeping and vehicle positioning functions are provided, so that the overall road safety is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of lane line positioning, and more specifically, to a lane line positioning system based on magnetic markers. Background Art

[0002] With the rapid development of autonomous driving technology, accurate lane line recognition has become a key factor in ensuring road safety. Traditionally, lane line recognition relies on visual systems such as cameras and image processing technology, which is effective in most cases. However, when encountering adverse weather conditions such as rain and snow, the performance of the visual system drops significantly. In addition, conventional road markings, especially lane lines, are easily worn out due to environmental influences and daily use, requiring frequent maintenance and repainting.

[0003] Existing technologies have obvious shortcomings in dealing with these problems: for example, although enhancing the recognition ability of cameras or improving image processing algorithms has improved the recognition accuracy to a certain extent, it is still difficult to cope with low visibility and wear and tear conditions. In addition, these methods usually require expensive equipment and complex maintenance, increasing the cost and complexity of the overall system. Therefore, a new solution is needed that can improve the recognition accuracy of lane markings while reducing maintenance costs and complexity, especially in severe weather and wear conditions. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a lane line positioning system based on magnetic markers, which is set to be a special road marking material containing magnetic elements that can be detected by specific sensors. These markers are usually embedded or attached to the road surface in the form of strips, especially at the location of the lane line. Unlike traditional road markings, magnetic markers can maintain a high degree of detectability even in adverse weather conditions (such as rain, snow, and fog). In addition, due to the high wear resistance of magnetic elements, the service life of these markers is longer than that of ordinary road markings, reducing the need and cost of maintenance. In order to detect these magnetic markers, the vehicle is equipped with special magnetic sensors. These sensors are able to sense the changes in the magnetic field generated by the magnetic strips embedded in the road surface. When the vehicle is driving, the sensor continuously monitors these changes to determine the position and direction of the lane. This detection method is insensitive to environmental conditions and can therefore work effectively even in low visibility conditions.

[0005] To achieve the above object, the present invention provides the following technical solution: a lane line positioning system based on magnetic marking, comprising: Sensor configuration: The vehicle is equipped with magnetic sensors, usually located on the front and / or bottom of the vehicle, which are able to detect the changes in the magnetic field generated by the magnetic marker; Data processing: When a vehicle passes through a road section with magnetic markings, the magnetic field data captured by the sensor is sent to the vehicle's central processing unit, which analyzes the data to determine the vehicle's position relative to the lane markings; Real-time feedback: The system processes magnetic field data in real time and feeds the vehicle's position information back to the driver assistance system or autonomous driving system, so that the vehicle can accurately stay in the center of the lane under different road conditions or change lanes as needed; The magnetic lines of force generated by the passive magnets under the road surface will actively trigger the Hall sensor inside the magnetic sensor wirelessly through the magnetic lines of force when a vehicle equipped with magnetic sensor lines approaches. After the MCU inside the magnetic sensor detects the corresponding Hall sensor trigger signal, the MCU will automatically control the opening of the corresponding RFID field energy switch and activate the RFID chip in the tag to exchange data with the magnetic sensor.

[0006] Furthermore, the magnetic marker setting includes magnetic marker unit encoding and magnetic marker unit laying.

[0007] Furthermore, the magnetic marking unit encodes lane lines into dotted lines and solid lines. The dotted lines and solid lines are set to distinguish different road conditions. The specific magnetic lane label used for longitudinal marking is modeled as a tuple {?, ?}, where ? is the polarity, i.e. "N" or "S", and ? is the polarity direction.

[0008] Furthermore, the laying of the magnetic marker units includes embedding magnetic tags in the road surface and arranging them in the center of the road. Compared with arranging them on lane lines, the above arrangement is conducive to saving magnetic tags through reasonable distribution and can achieve the same accuracy.

[0009] Furthermore, the interval between the magnetic markers depends on the required positioning accuracy and the road structure. The shorter the interval between the magnetic markers, the more accurate the vehicle positioning.

[0010] Furthermore, the laying of the magnetic marker unit includes: Assume road structure 1: left and right turning road ends, curvature 12m, installation interval 1m or 2m; Assume road structure 2: curved section, curvature 30m, installation interval 1m, 2m or 8m; Assume road structure three: straight road, installation interval 2m, 8m or 16m.

[0011] Furthermore, the magnet detection algorithm: Step 1: Preprocessing, first apply Gaussian kernel smoother to denoise the real-time magnetometer data; Step 2: Derivation,After data preprocessing, the first-order derivative of the smoothed data is,calculated using the Savitzky-Golay (SG) filter, which can effectively eliminate,most of the unwanted zero-crossings and high-frequency noise.

[0012] Step 3: Peak / Valley Detection. Peaks / valleys can be reliably detected by searching for downward / upward zero crossings in the first-order derivative data. In order to eliminate false zero crossings caused by random noise, the slope data of the derivative data is introduced and a threshold-based detection algorithm is implemented. The slope caused by noise is smaller than the slope caused by the magnet. Therefore, the slope of each zero crossing pair is first calculated, and then the slope threshold reflecting the influence of the surrounding environment is initialized. Finally, the slope exceeding the threshold means the presence of a candidate magnet. In order to further eliminate false alarms, an amplitude threshold is introduced for each candidate zero crossing point. Specifically, the original candidate data point is compared with the amplitude difference between the magnet-based preset value and the threshold.

[0013] Technical effects and advantages of the present invention: The system significantly improves the "visibility" of lane markings by combining magnetic markers with sensors on the vehicle. In situations where visual systems (such as cameras) are limited, magnetic sensors provide a reliable alternative to ensure that the vehicle can accurately identify and follow the lane. In addition, this system can also be integrated with the vehicle's navigation and autonomous driving systems to provide more accurate lane keeping and vehicle positioning functions, thereby enhancing overall road safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The ground magnetic tag placement method of the present invention is applied to the solid lane line state diagram.

[0015] Figure 2 The ground magnetic tag placement method of the present invention is applied to the dashed lane line status diagram.

[0016] Figure 3 The magnetic label arrangement of the present invention is Figure 1 .

[0017] Figure 4 The magnetic label arrangement of the present invention is Figure 2 .

[0018] Figure 5 The magnetic label arrangement of the present invention is Figure 3 .

[0019] Figure 6 This is a coordinate display diagram of the magnet detection algorithm of the present invention.

[0020] Figure 7 This is a diagram of the placement of the magnetic sensor of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0022] according to Figure 1-7 A lane positioning system based on magnetic markers is shown, comprising a sensor configuration: a vehicle is equipped with magnetic sensors, usually located at the front and / or bottom of the vehicle, and these sensors are capable of detecting changes in the magnetic field generated by the magnetic markers; Data processing: When a vehicle passes through a road section with magnetic markings, the magnetic field data captured by the sensor is sent to the vehicle's central processing unit, which analyzes the data to determine the vehicle's position relative to the lane markings; Real-time feedback: The system processes magnetic field data in real time and feeds the vehicle's position information back to the driver assistance system or autonomous driving system, so that the vehicle can accurately stay in the center of the lane under different road conditions or change lanes as needed; The magnetic lines of force generated by the passive magnets under the road surface will actively trigger the Hall sensor inside the magnetic sensor wirelessly through the magnetic lines of force when a vehicle equipped with magnetic sensor lines approaches. After the MCU inside the magnetic sensor detects the corresponding Hall sensor trigger signal, the MCU will automatically control the opening of the corresponding RFID field energy switch and activate the RFID chip in the tag to exchange data with the magnetic sensor.

[0023] Furthermore, the magnetic marker setting includes magnetic marker unit encoding and magnetic marker unit laying.

[0024] Furthermore, the magnetic marker unit encodes lane lines into dotted lines and solid lines. The dotted lines and solid lines are set to distinguish different road conditions. The specific magnetic lane labels used for longitudinal marking are modeled as tuples {?,?}, where? is the polarity, i.e. "N" or "S", and? is the polarity direction. The direction is determined by analyzing the magnetic field distribution of the passive magnet. Specifically, the strongest magnetic field of the passive magnet is located at its N / S due to the highest magnetic flux density. When the pole of the magnet points to the sensor, the magnetometer is more likely to detect the magnet.

[0025] The magnets are set to N / S polarity up, i.e. ? = 90°, as shown in Figure 1-2, for these more safety-critical markings. To this end, a series of {"?", 90°} configured magnets can be solid lines. Similarly, we use a series of {"?", 90°} magnets to draw dashed lines. This design allows the driver or the car system to react in a timely manner, by detecting different magnetic pole directions through magnetic sensors, and thus infer whether the lane line is solid or dashed.

[0026] Furthermore, the laying of the magnetic marker units includes embedding magnetic tags in the road surface and arranging them in the center of the road. Compared with arranging them on lane lines, the above arrangement is conducive to saving magnetic tags through reasonable distribution and can achieve the same accuracy.

[0027] Furthermore, the interval between the magnetic markers depends on the required positioning accuracy and the road structure. The shorter the interval between the magnetic markers, the more accurate the vehicle positioning.

[0028] Furthermore, the laying of the magnetic marker unit includes: Assume road structure 1: left and right turning road ends, curvature 12m, installation interval 1m or 2m; Assume road structure 2: curved section, curvature 30m, installation interval 1m, 2m or 8m; Assume road structure three: straight road, installation interval 2m, 8m or 16m; Since lane markings are not only used to restrict vehicles to drive in a standardized manner, but also the arrow marks on the lane lines guide drivers to the correct driving path, this invention adopts an innovative magnetic tag arrangement method to effectively solve this problem.

[0029] like Figure 3-5 As shown, the circles represent magnetic tags applied to the solid lanes, and the oblique square icons represent magnetic tags applied to the dashed lanes; The magnetic sensors located on the vehicle monitor the magnetic induction intensity of the magnetic tags on the ground to accurately calculate the distance between the vehicle and these magnetic tags. Considering that the position of the magnetic tags and the actual lane lines are fixed, this technology can indirectly deduce the precise position of the actual lane lines, thereby generating highly simulated virtual lane lines on the vehicle system.

[0030] Furthermore, the magnet detection algorithm: Step 1: Preprocessing, first apply Gaussian kernel smoother to denoise the real-time magnetometer data; Step 2: Derivation,After data preprocessing, the first-order derivative of the smoothed data is,calculated using the Savitzky-Golay (SG) filter, which can effectively eliminate,most of the unwanted zero-crossings and high-frequency noise.

[0031] Step 3: Peak / valley detection. Peaks / valleys can be reliably detected by searching for downward / upward zero crossings in the first-order derivative data. In order to eliminate false zero crossings caused by random noise, the slope data of the derivative data is introduced and a threshold-based detection algorithm is implemented. The slope caused by noise is smaller than the slope caused by the magnet. Therefore, the slope of each zero crossing pair is first calculated, and then the slope threshold reflecting the influence of the surrounding environment is initialized. Finally, the slope exceeding the threshold means that there is a candidate magnet. In order to further eliminate false positives, an amplitude threshold is introduced for each candidate zero crossing point. Specifically, the original candidate data point is compared with the amplitude difference between the preset value based on the magnet and the threshold. Formula definition:

[0032] Where M is the magnetic moment vector of the magnetic dipole, r is the distance between the tensor measurement point and the magnetic dipole, and m1, m2, and m3 represent the projections of m on the x, y, and z axes of the coordinate system, respectively.

[0033] The meaning is expressed as r is the relative position vector between the tensor measurement point and the magnetic dipole, n1, n2, n3 represent the projection of n on the x, y, z axis of the coordinate system respectively; Figure 6 As shown: 1. First, read the magnetic induction intensity measurement results Bi of all on-board magnetometers (i=1, 2, 3,...) 2. Calculate the magnetic gradient tensor at points A and B The four magnetometers 1, 2, 3, and 4 form a square tensor measurement matrix to complete the measurement of GA of magnetic tag A. The calculation formula is as follows:

[0034] in:

[0035] It represents the average value of the k component of the magnetic field between two different magnetometers i and j, which is approximately equal to the magnetic field value at the midpoint of the line connecting the two magnetometers in space.

[0036] Similarly, the measurement of GB of magnetic label B can also be shown as the above formula; like Figure 7 As shown in the figure, H is the direction of the magnet. P = (x1,y1,z1) represents the spatial point where the magnetic sensor is placed. H0 represents the magnetic direction of the magnet.

Claims

1. A lane positioning system based on magnetic markers, characterized in that: include: Sensor configuration: The vehicle is equipped with magnetic sensors, usually located on the front and / or bottom of the vehicle, which are able to detect the changes in the magnetic field generated by the magnetic marker; Data processing: When a vehicle passes through a road section with magnetic markings, the magnetic field data captured by the sensor is sent to the vehicle's central processing unit, which analyzes the data to determine the vehicle's position relative to the lane markings; Real-time feedback: The system processes magnetic field data in real time and feeds the vehicle's position information back to the driver assistance system or autonomous driving system, allowing the vehicle to accurately stay in the center of the lane under different road conditions or change lanes as needed.

2. The lane positioning system based on magnetic markers according to claim 1, characterized in that: The magnetic marker setting includes magnetic marker unit encoding and magnetic marker unit laying.

3. The lane line positioning system based on magnetic markers according to claim 2, characterized in that: The magnetic marking unit encodes lane lines into dotted lines and solid lines. The dotted lines and solid lines are set to distinguish different road conditions. The specific magnetic lane label used for longitudinal marking is modeled as a tuple {?, ?}, where ? is the polarity, i.e. "N" or "S", and ? is the polarity direction.

4. The lane line positioning system based on magnetic markers according to claim 2, characterized in that: The laying of the magnetic marker units includes embedding magnetic tags in the road surface and arranging them in the center of the road. Compared with arranging them on the lane lines, the above arrangement is conducive to saving magnetic tags through reasonable distribution and can achieve the same accuracy.

5. The lane line positioning system based on magnetic markers according to claim 2, characterized in that: The interval between the magnetic markers depends on the required positioning accuracy and the road structure. The shorter the interval between the magnetic markers, the more accurate the vehicle positioning.

6. The lane line positioning system based on magnetic markers according to claim 2, characterized in that: The magnetic marker unit laying includes: Assume road structure 1: left and right turning road ends, curvature 12m, installation interval 1m or 2m; Assume road structure 2: curved section, curvature 30m, installation interval 1m, 2m or 8m; Assume road structure three: straight road, installation interval 2m, 8m or 16m.

7. The lane positioning system based on magnetic markers according to claim 1, characterized in that: The magnet detection algorithm: Step 1: Preprocessing, first apply Gaussian kernel smoother to denoise the real-time magnetometer data; Step 2: Derivation,After data preprocessing, the first-order derivative of the smoothed data is,calculated using the Savitzky-Golay (SG) filter, which can effectively eliminate,most of the unwanted zero-crossings and high-frequency noise.

8. Step 3: Peak / Valley Detection. Peaks / valleys can be reliably detected by searching for downward / upward zero crossings in the first-order derivative data. In order to eliminate false zero crossings caused by random noise, the slope data of the derivative data is introduced and a threshold-based detection algorithm is implemented. The slope caused by noise is smaller than the slope caused by the magnet. Therefore, the slope of each zero crossing pair is first calculated, and then the slope threshold reflecting the influence of the surrounding environment is initialized. Finally, the slope exceeding the threshold means the presence of a candidate magnet. In order to further eliminate false alarms, an amplitude threshold is introduced for each candidate zero crossing point. Specifically, the original candidate data point is compared with the amplitude difference between the magnet-based preset value and the threshold.

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