CN109910881B - Turning road vision blind area information detection processing method and system - Google Patents
Turning road vision blind area information detection processing method and system Download PDFInfo
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Abstract
The invention discloses a detection processing method and a system for turning road vision blind area information, wherein the method comprises the steps of firstly detecting running objects on a turning road, removing clutter, detecting obstacles, and carrying out data fusion on received geomagnetic sensor data and microwave sensor data by a microcontroller; the fused data are compared with hexadecimal characteristic vector samples, the microcontroller sends the detection data to the LED display screen to be displayed and starts a warning lamp to warn, meanwhile, the microcontroller sends the detection data and the position information to the background server for classified storage, the background server carries out fuzzy clustering analysis on the accumulated data to obtain more accurate characteristic vector intervals, and the characteristic vector intervals are regularly sent to the microcontroller as updated characteristic vector sample sets. The invention can inform the visual blind area information of the turning road to the driver in advance in time, thereby reducing the occurrence rate of traffic accidents.
Description
Technical Field
The invention relates to a detection processing method and a detection processing system for turning road vision blind area information, and belongs to the technical field of road traffic information detection.
Background
In real life, obstacles often exist on the inner side of a turning road to block the sight, so that a blind visual field area is formed, and therefore, a traffic accident frequent zone is arranged at a corner of the road.
At present, methods for detecting road traffic are numerous and mature day by day, but most of the methods are aimed at monitoring traffic flow and accidents of urban conventional roads. And to turning the road, except using comparatively extensive road wide-angle lens at present, and static warning sign that turns round, there is almost no high-efficient intellectual detection system processing method, do accurate processing to the traffic information of the way of turning round to accurately discern the moving object classification on the road, if: pedestrian, vehicle category.
In order to inform the driver of the information in advance and reduce the occurrence rate of traffic accidents, the research on the information detection processing method of the turning road vision blind area has important practical significance.
Disclosure of Invention
Aiming at the defects of the method, the invention provides the detection processing method and the detection processing system for the turning road vision blind area information, which can inform the driver of the turning road vision blind area information in advance in time and reduce the occurrence rate of traffic accidents.
The technical scheme adopted for solving the technical problems is as follows:
the invention provides a detection processing method of turning road vision blind area information, which comprises the following steps:
and 7, the background server stores the received data in a classified manner, performs fuzzy clustering analysis on the accumulated data to obtain a more accurate feature vector interval, and periodically sends the feature vector interval to the microcontroller as an updated feature vector sample set.
As a possible implementation manner of this embodiment, in step 2, the process of performing clutter removal processing on the magnetic field data in the Z-axis direction of the geomagnetic sensor is as follows: reading magnetic field data of a geomagnetic sensor in the Z-axis direction, comparing data transmitted at the previous moment with data transmitted at the current moment by adopting a Kalman filtering algorithm, estimating error data in the data at the current moment, removing error data caused by irrelevant factors, and extracting useful data information.
As a possible implementation manner of this embodiment, in step 4, the specific process of performing data fusion is as follows: the data transmitted by the geomagnetic sensor is stored in the first seven bits of an eight-bit binary number pre-created by the single chip microcomputer, the data of the microwave sensor is put into the eighth bit, and then the eight-bit binary data is converted into hexadecimal data.
As a possible implementation manner of this embodiment, in step 5, a specific process of comparing the fused data with the hexadecimal feature vector sample is as follows: and performing cyclic detection on the fused data and the hexadecimal feature vector samples, matching the detected fused data with each feature vector sample, and returning information corresponding to the feature vector sample if matching is successful.
As a possible implementation manner of this embodiment, in step 6, the specific process that the microcontroller sends the detection data to the LED display screen for displaying and starts the warning light for warning is as follows: the microcontroller calculates the speed of the moving object and the distance information between the moving object and a corner according to the transmitted data by analyzing the data transmitted by the radar sensor, and calls different data to send to the LED display screen for displaying and starts the warning lamp for warning according to the corresponding type of the moving object.
As a possible implementation manner of this embodiment, in step 7, a specific process of performing fuzzy clustering analysis on the accumulated data by the background server is as follows:
step 71, the background server takes out the nearest n groups of fused geomagnetic data and microwave data from the database as a group of initial sample domains, and each group of data is set as X1,X2,…,XmAnd each data has m indexes to represent the characteristics of the data, and the characteristic attribute data of the ith classification object of the initial sample discourse domain is Xi1’,Xi2’,…,Xim’；
Step 72, normalizing the feature attribute data using:
wherein,
step 73, establishing a fuzzy similarity relation matrix, and determining the similarity matrix R as (R) by using the general clustering analysisij)n×n，rijIs XiAnd XjInter-similarity coefficient, wherein
Taking the appropriate value of M to make rijIn [0,1 ]]Dispersing;
step 74, performing a transitive closure operation on the similarity matrix R to obtain t (R) ═ RnAnd on the basis, the confidence level lambda takes different values to obtain different clustering results.
The invention provides a detection processing system for turning road visual blind area information, which comprises a geomagnetic sensor, a microwave sensor, a radar sensor, a micro-controller, a communication module, an LED display screen, a warning lamp and a background server which is arranged on a turning road site and is in remote communication with a microcontroller through the communication module, wherein the geomagnetic sensor, the microwave sensor, the radar sensor, the communication module, the LED display screen and the warning lamp are respectively connected with the microcontroller, the geomagnetic sensor and the microwave sensor are arranged on a straight lane in front of a turning road corner, the geomagnetic sensor and the microwave sensor are arranged in front of and behind the straight lane in the running direction, the radar sensor is arranged on the turning road corner, a probe of the radar sensor faces the straight lane in front of the turning road corner, the microcontroller, the warning lamp and the communication module are arranged on the turning road site, and the microcontroller is arranged in front of the turning, Communication module, LED display screen and warning light set up in turn road corner, and the LED display screen sets up towards the straight lane in turn road corner the place ahead.
As one possible implementation manner of this embodiment, the geomagnetic sensor employs an HMC5883L triaxial geomagnetic sensor for outputting detected moving object data by detecting a metal content of a moving object; the microwave sensor is a microwave sensor with the model number of RCWL-0516 and is used for judging whether a moving object exists or not; the radar sensor adopts a TF03 laser radar sensor and is used for detecting the speed of a moving object and distance information to a corner.
As a possible implementation manner of this embodiment, the communication module employs a SIM868GSM/GPRS/GPS module.
As a possible implementation manner of this embodiment, the detection processing system is applied to a one-way lane road and/or a two-way lane road.
The technical scheme of the embodiment of the invention has the following beneficial effects:
the detection processing method of the turning road vision blind area information comprises the steps of detecting a running object on a turning road, removing clutter, detecting obstacles, and fusing data of received geomagnetic sensor data and microwave sensor data by a microcontroller; the fused data are compared with hexadecimal characteristic vector samples, the microcontroller sends the detection data to an LED display screen for displaying and starts a warning lamp for warning, meanwhile, the microcontroller sends the detection data and the position information to a background server for classified storage, the background server carries out fuzzy clustering analysis on the accumulated data to obtain more accurate characteristic vector intervals, and the characteristic vector intervals are periodically used as updated characteristic vector sample sets to be sent to the microcontroller. The technical scheme of the embodiment of the invention can inform the driver of the turning road vision blind area information in advance in time, thereby reducing the occurrence rate of traffic accidents.
According to the technical scheme of the embodiment of the invention, two sensors are used for outputting data, so that the electronization of output information is realized, and the method is more accurate than the method of visually observing the opposite road information by human eyes through a traditional wide-angle lens; meanwhile, a Kalman filtering algorithm is used for effectively filtering abnormal data transmitted on the road; the data transmitted by the sensors are subjected to fusion processing by adopting a fusion algorithm, so that the data are convenient to transmit, and all the data can be transmitted by only one-time data transmission, so that the transmission efficiency is improved, and the system burden is reduced; different from the traditional threshold value detection method, the fuzzy clustering analysis method is adopted to more accurately and efficiently identify the type information of the running object, such as: useful data are accurately mined by pedestrians, riders and vehicles of different models. The detection method can be used in various fields such as city curved roads, mountain curved roads, residential quarters, underground parking lots and the like, and has wide application range.
The detection processing system for the turning road vision blind area information provided by the embodiment of the invention can realize the same beneficial effects of the detection processing method for the turning road vision blind area information provided by the embodiment of the invention.
Description of the drawings:
FIG. 1 is a flow diagram illustrating a method for detection processing of turning road blind spot information in accordance with an exemplary embodiment;
FIG. 2 is a functional block diagram illustrating a system for detecting blind turn road vision area information in accordance with an exemplary embodiment;
fig. 3 is a front view of a combination of pillars at a side of a corner deviation road a and a side of a corner deviation road B in the embodiment of the detection processing system of the present invention, in which, 1-pillar, 2-LED screen, 3-warning light, 4-power supply, 5-sealing box comprises: microcontroller, SIM868GSM/GPRS/GPS module;
FIG. 4 is a front view of a corner post assembly in an embodiment of the detection processing system of the present invention, showing 6-radar sensor, 7-solar panel;
fig. 5 is a top view of the hardware position layout of the detection processing system of the present invention, in which 8-geomagnetic sensors a, 9-microwave sensors a, 10-corner deviation road a side column and microcontroller, display screen, warning light combination (specifically shown in fig. 3), 11-corner deviation road B side column, solar panel, radar sensor, 12-column, microcontroller, display screen, warning light combination (specifically shown in fig. 3), 13-geomagnetic sensors B, 14-microwave sensors B;
FIG. 6 is a specific flowchart of the present invention for detecting blind spot information on turning roads.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
in order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.
In order to clearly and intuitively explain the effect achieved by the invention, the invention is explained in detail by taking the main city area of Beijing as an example and through a specific implementation mode and the accompanying drawings.
FIG. 1 is a flowchart illustrating a method for detecting turn road blind spot information according to an exemplary embodiment. As shown in fig. 1, a method for detecting and processing blind area information of a turning road according to an embodiment of the present invention includes the following steps:
and 7, the background server stores the received data in a classified manner, performs fuzzy clustering analysis on the accumulated data to obtain a more accurate feature vector interval, and periodically sends the feature vector interval to the microcontroller as an updated feature vector sample set. The micro-controller judges according to the characteristic vector sample set, so that the judgment is more accurate.
In one possible implementation manner of this embodiment, in step 2, the process of performing clutter removal processing on the magnetic field data in the Z-axis direction of the geomagnetic sensor is as follows: reading magnetic field data of a geomagnetic sensor in the Z-axis direction, comparing data transmitted at the previous moment with data transmitted at the current moment by adopting a Kalman filtering algorithm, estimating error data in the data at the current moment, removing error data caused by irrelevant factors, and extracting useful data information.
In a possible implementation manner of this embodiment, in step 4, the specific process of performing data fusion is as follows: the data transmitted by the geomagnetic sensor is stored in the first seven bits of an eight-bit binary number pre-created by the single chip microcomputer, the data of the microwave sensor is put into the eighth bit, and then the eight-bit binary data is converted into hexadecimal data.
Assuming that the types of the traveling objects can be identified as a car, a medium-sized off-road vehicle and a large truck respectively, the data is divided into three ranges, and the output data of the geomagnetic sensor is restricted in a 0000-007F interval through data processing, wherein the data of the small car is set to be about 001E, the data of the medium-sized off-road vehicle is set to be about 003C, and the data of the large truck is set to be about 0064, the data can not exceed 007F at most. Therefore, the eighth bit of the binary data corresponding to the hexadecimal output data of the geomagnetic sensor is idle and can be used for representing the data output by the microwave sensor, the expected output is determined by the hexadecimal code, and the following representation modes are provided according to the identification types:
when no driving object exists, binary numbers 00000000 are sent, and hexadecimal numbers are represented as 0x 00;
when the driving object is only a pedestrian without a vehicle, the binary expression is 10000000-10010000, and the hexadecimal expression is 0x 80-0 x 90;
when the traveling object includes a vehicle, the eighth bit is 1, and the first to seventh bits represent vehicle information, that is, vehicle data +0x 80.
In a possible implementation manner of this embodiment, in step 5, a specific process of comparing the fused data with the hexadecimal feature vector sample is as follows: and performing cyclic detection on the fused data and the hexadecimal feature vector samples, matching the detected fused data with each feature vector sample, and returning information corresponding to the feature vector sample if matching is successful.
In a possible implementation manner of this embodiment, in step 6, the specific process that the microcontroller sends the detection data to the LED display screen for displaying and starts the warning light for warning is as follows: the microcontroller calculates the speed of the moving object and the distance information between the moving object and a corner according to the transmitted data by analyzing the data transmitted by the radar sensor, and calls different data to send to the LED display screen for displaying and starts the warning lamp for warning according to the corresponding type of the moving object.
In a possible implementation manner of this embodiment, in step 7, a specific process of performing fuzzy clustering analysis on the accumulated data by the background server is as follows:
step 71, the background server takes out the nearest n groups of fused geomagnetic data and microwave data from the database as a group of initial sample domains, and each group of data is set as X1,X2,…,XmAnd each data has m indexes to represent the characteristics of the data, and the characteristic attribute data of the ith classification object of the initial sample discourse domain is Xi1’,Xi2’,…,Xim’；
Step 72, normalizing the feature attribute data using:
wherein,
step 73, establishing a fuzzy similarity relation matrix, and determining the similarity matrix R as (R) by using the general clustering analysisij)n×n，rijIs XiAnd XjInter-similarity coefficient, wherein
Taking the appropriate value of M to make rijIn [0,1 ]]Dispersing;
step 74, performing a transitive closure operation on the similarity matrix R to obtain t (R) ═ RnAnd on the basis, the confidence level lambda takes different values to obtain different clustering results.
FIG. 2 is a functional block diagram illustrating a system for detecting blind turn road vision area information in accordance with an exemplary embodiment. As shown in fig. 2, the system for detecting and processing blind area information of a turning road according to an embodiment of the present invention includes a geomagnetic sensor, a microwave sensor, a radar sensor, a microcontroller, a communication module, an LED display screen, a warning light, and a background server in remote communication with the microcontroller through the communication module, where the geomagnetic sensor, the microwave sensor, the radar sensor, the communication module, the LED display screen, and the warning light are respectively connected to the microcontroller, the geomagnetic sensor and the microwave sensor are disposed on a straight lane in front of a turning road corner, and the geomagnetic sensor and the microwave sensor are disposed front and back in a driving direction of the straight lane, the radar sensor is disposed at the turning road corner, and a probe of the radar sensor faces the straight lane in front of the turning road corner, microcontroller, communication module, LED display screen and warning light set up in turn road corner, and the LED display screen sets up towards the straight lane in turn road corner the place ahead.
In one possible implementation manner of this embodiment, the geomagnetic sensor employs an HMC5883L triaxial geomagnetic sensor for outputting detected data of the moving object by detecting a metal content of the moving object; the microwave sensor is a microwave sensor with the model number of RCWL-0516 and is used for judging whether a moving object exists or not; the radar sensor adopts a TF03 laser radar sensor and is used for detecting the speed of a moving object and distance information to a corner.
In a possible implementation manner of this embodiment, the communication module employs a SIM868GSM/GPRS/GPS module.
In a possible implementation manner of this embodiment, the detection processing system is applied to a one-way lane road and/or a two-way lane road.
As shown in fig. 3 to 5, the layout of the hardware required for completing the detection processing method of the turning road vision blind area information is that, assuming that roads at two sides of a corner of a bidirectional lane road are respectively a road a and a road B, 3 upright columns are arranged near the corner of the road, one of the upright columns is arranged at the corner, 2 radar sensors and 1 solar panel are arranged on the upright column, wherein the radar sensors are arranged above the upright columns, probes of the radar sensors face corresponding lanes, and the solar panel is arranged at the top of the upright column. The corner is inclined to one side of road A and the corner is inclined to one side of road B and is set up a stand respectively, wherein set up microcontroller, SIM868GSM/GPRS/GPS module, display screen, circular warning light on the stand, wherein the specific position of every part is for, microcontroller and SIM868GSM/GPRS/GPS module are put together in the seal box, the seal box sets up on the stand top, the circular warning light sets up on stand upper portion, the display screen sets up in circular warning light below. The road A is provided with a geomagnetic sensor and a microwave sensor, the geomagnetic sensor is arranged at a position far away from the corner than the microwave sensor, the microwave sensor is arranged at a position close to the corner, and the road B has the same principle. In order to facilitate installation and later maintenance, the radar sensor is arranged on the upright post, a solar panel is arranged on the upright post provided with the radar sensor, and power is supplied by solar energy; and respectively displaying a screen, a warning lamp, a microcontroller and the like on the upright columns on the side A of the corner deviation road and the side B of the corner deviation road.
The data detected and processed by the sensor on the road A is displayed by the combination of the display screen of the road B and the warning lamp, and the data detected and processed by the sensor on the road B is displayed by the combination of the display screen of the road A and the warning lamp in the same way.
Taking the driving object as a vehicle as an example, the detection flow for the turning road vision blind area information by using the detection processing system mainly comprises the following steps:
And 2, the geomagnetic sensor stores the acquired filtered effective magnetic field data into a micro-controller ROM to wait for data fusion, so that the data processing in the next step is facilitated.
And 3, detecting by a microwave sensor after the object is moved, wherein the microwave sensor sends out microwaves by using a microwave oscillator, and a receiving head of the microwave sensor receives the microwaves reflected by the obstacle.
And 4, outputting a signal to a microcontroller ROM by the microwave sensor to perform data fusion.
And 5, comparing the fused data with the hexadecimal characteristic vector sample by the microcontroller, starting equipment such as a radar sensor and the like if the matching is successful, carrying out the next measurement and display, and if not, giving up the data and restoring the system to the initial state again.
And 6, the radar sensor sends related information to the microcontroller, the microcontroller performs data processing, the processed related data are sent to the warning lamp and the LED display screen, meanwhile, the GPS function of the SIM868GSM/GPRS/GPS module is started to acquire GPS information, and then the data are uniformly packaged and sent to the background server by using the GPRS function of the SIM868GSM/GPRS/GPS module.
And 7, the server stores the received data in a classified manner, fuzzy clustering analysis is carried out after certain data are accumulated to obtain a more accurate characteristic vector interval, the characteristic vector interval is periodically sent to the microcontroller as an updated characteristic vector sample set, and the microcontroller carries out judgment according to the vector sample set, so that the judgment is more accurate.
Taking the traveling object as an example, the detection flow of the turning road vision blind area information by using the detection processing system mainly comprises the following steps:
And 2 ', the microcontroller receives the signal of the geomagnetic sensor, and if no effective signal can be obtained, the step 3' is carried out.
And 3', the pedestrians pass through the microwave sensor, the microwave sensor uses a microwave oscillator to emit microwaves, and a receiving head of the microwave sensor receives the microwaves reflected by the barrier.
And 4', outputting a signal to a microcontroller ROM by the microwave sensor to perform data fusion.
And 5, comparing the fused data with the hexadecimal characteristic vector sample by the microcontroller, starting equipment such as a radar sensor and the like if the matching is successful, carrying out the next measurement and display, and if not, giving up the data and restoring the system to the initial state again.
And 6, the radar sensor sends related information to the microcontroller, the microcontroller performs data processing, the processed related data are sent to the warning lamp and the LED display screen, meanwhile, the GPS function of the SIM868GSM/GPRS/GPS module is started to acquire GPS information, and then the data are uniformly packaged and sent to the background server by using the GPRS function of the SIM868 GS/GPRS/GPS module.
And 7, the server stores the received data in a classified manner, fuzzy clustering analysis is carried out after certain data are accumulated to obtain a more accurate characteristic vector interval, the characteristic vector interval is periodically sent to the microcontroller as an updated characteristic vector sample set, and the microcontroller judges according to the sample set, so that the judgment is more accurate.
The specific method for data fusion is as follows: assuming that the types of traveling objects are car, medium-sized all-terrain vehicle, and large truck, respectively, and the data is divided into three ranges, the output data of the geomagnetic sensor is constrained within the interval of 0x00-007F by data processing, wherein the data of the car is set to about 0x1E, the data of the medium-sized all-terrain vehicle is set to about 0x3C, and the data of the large truck is set to about 0x64, the data will not exceed 0x7F at maximum.
The following data are transmitted from the geomagnetic sensor:
a small car:
0x26,0x20,0x23,0x1C,0x1A,0x18,0x1E,0x21,0x29,0x1D,0x1D, 0x25,0x22,0x21,0x19,0x1A,0x1B,0x1F,0x28,0x23,0x24,0x16, 0x19,0x21,0x26,0x1D,0x18,0x1E,0x1A,0x18,0x24,0x18,0x1F。
the medium-sized cross-country vehicle:
0x42,0x3B,0x3D,0x41,0x45,0x38,0x43,0x40,0x35,0x3B,0x33, 0x3F,0x39,0x3C,0x42,0x33,0x45,0x36,0x34,0x40,0x3E,0x38, x35,0x44,0x3D,0x36,0x34,0x3A,0x3D,0x40,0x45,0x3B,0x3D。
large trucks:
0x6E,0x69,0x6D,0x62,0x61,0x66,0x5D,0x64,0x5F,0x5E,0x65, 0x5C,0x5E,0x6A,0x64,0x5D,0x6F,0x5F,0x6B,0x60,0x5C,0x67, 0x60,0x5B,0x68,0x6A,0x69,0x63,0x5C,0x5D,0x66,0x71,0x61。
after analyzing a plurality of data transmitted by the geomagnetic sensor, it is found that data of vehicles of different models are respectively concentrated in different ranges, and the data is not more than 0x7F at most, so that the eighth bit of the corresponding binary data is idle when the geomagnetic sensor outputs data in hexadecimal, and therefore the eighth bit can be used for representing data output by the microwave sensor, and according to different driving objects, the fused corresponding binary data corresponding to hexadecimal expected output data is shown in table 1.
Table 1:
the specific process of comparing the fused data with the sample set is that the fused data and the hexadecimal feature vector sample are subjected to cyclic detection, the fused data is detected to be most matched with the feature vector sample, if the matching is successful, the information corresponding to the feature vector sample is returned, if the information is not satisfied, the data is considered to be data generated by some irrelevant factors, and the system does not react to the data.
The microcontroller calculates the speed of the moving object and the distance information from the corner according to the data transmitted by the radar sensor by analyzing the data transmitted by the radar sensor, and transfers different data to the display screen and the circular warning lamp according to the corresponding types of the object so as to display the speed and distance information with different shapes and real-time change.
The fuzzy clustering analysis process is described below by taking three types of cars, namely, a sedan, a medium-sized off-road vehicle and a large truck as examples. In the initial stage, n groups of data fused by geomagnetic sensors and microwave sensors are obtained from a database as a group of initial sample domains, and similar features are extracted from each data as feature vectors.
Generating a sample set according to the characteristic vector, wherein the sample set is used as a matching basis of fuzzy clustering analysis, and the fuzzy clustering analysis principle is as follows:
step 71, the background server takes out the nearest n groups of fused geomagnetic data and microwave data from the database as a group of initial sample domains, and each group of data is set as X1,X2,…,XmAnd each data has m indexes to represent the characteristics of the data, and the characteristic attribute data of the ith classification object of the initial sample discourse domain is Xi1’,Xi2’,…,Xim’；
Step 72, normalizing the feature attribute data using:
wherein,
step 73, establishing a fuzzy similarity relation matrix, and determining the similarity matrix R as (R) by using the general clustering analysisij)n×n，rijIs XiAnd XjInter-similarity coefficient, wherein
Taking the appropriate value of M to make rijIn [0,1 ]]Dispersing;
step 74, performing transitive closure operation on the similarity matrix R, wherein t (R) is a transitive closure of the fuzzy similarity matrix R, which is a minimum fuzzy equivalent matrix containing R and can be obtained by a flat method, and squaring the R n times to obtain t (R) ═ RnAnd on the basis, the confidence level lambda takes different values to obtain different clustering results.
The server periodically sends the results of fuzzy clustering analysis of the n groups of data to the microcontroller as updated characteristic vector intervals; and simultaneously, the server stores the result, continuously stores a plurality of groups of fuzzy clustering results, and performs fuzzy clustering analysis on the results again, so as to analogize and continuously analyze. The method aims to count the categories in the data feature set in each analysis result, remove similar and useless categories, and obtain more accurate feature vector intervals through repeated analysis.
The invention uses two sensors to output data, realizes the electronization of output information, and is more accurate than the traditional wide-angle lens in the mode that the information of the opposite road is visually observed by human eyes; meanwhile, a Kalman filtering algorithm is used for effectively filtering abnormal data transmitted on the road; the data transmitted by the sensors are subjected to fusion processing by adopting a fusion algorithm, so that the data are convenient to transmit, and all the data can be transmitted by only one-time data transmission, so that the transmission efficiency is improved, and the system burden is reduced; different from the traditional threshold value detection method, the fuzzy clustering analysis method is adopted to more accurately and efficiently identify the type information of the running object, such as: useful data are accurately mined by pedestrians, riders and vehicles of different models. The detection method can be used in various fields such as urban curved roads, mountain curved roads, residential quarters, underground parking lots and the like, and has wide application range.
The foregoing is only a preferred embodiment of the present invention, and it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and these modifications and improvements are also considered to be within the scope of the present invention.
Claims (6)
1. A detection processing method for turning road vision blind area information is characterized by comprising the following steps:
step 1, detecting a running object on a turning road by using a geomagnetic sensor, if a vehicle is detected, sending magnetic field data of the geomagnetic sensor in the Z-axis direction to a microcontroller, and if not, turning to step 3;
step 2, the microcontroller performs clutter removal processing on the magnetic field data of the geomagnetic sensor in the Z-axis direction and stores effective geomagnetic sensor data information;
step 3, detecting the obstacle by using a microwave sensor, and sending the received microwave signal reflected by the obstacle to a microcontroller;
step 4, the microcontroller stores the received data information of the microwave sensor and performs data fusion on the received data of the geomagnetic sensor and the data of the microwave sensor;
step 5, the microcontroller compares the fused data with the hexadecimal characteristic vector sample, if the matching is successful, the measurement and the display of the step 6 are carried out, otherwise, the step 1 is returned;
step 6, the radar sensor sends the detected data to the microcontroller, the microcontroller sends the detected data to the LED display screen for displaying and starts a warning lamp for warning, and meanwhile, the microcontroller sends the detected data and the position information to the background server;
and 7, the background server stores the received data in a classified manner, performs fuzzy clustering analysis on the accumulated data to obtain a more accurate feature vector interval, and periodically sends the feature vector interval to the microcontroller as an updated feature vector sample set.
2. The method for detecting and processing blind spot information on a turning road according to claim 1, wherein in the step 2, the process of performing clutter removal processing on the magnetic field data in the Z-axis direction of the geomagnetic sensor comprises: reading magnetic field data of a geomagnetic sensor in the Z-axis direction, comparing data transmitted at the previous moment with data transmitted at the current moment by adopting a Kalman filtering algorithm as reference, estimating wrong data in the data at the current moment, removing the wrong data caused by irrelevant factors, and extracting useful data information.
3. The method for detecting and processing the blind vision zone information of the turning road as claimed in claim 1, wherein in the step 4, the specific process of data fusion is as follows: the data transmitted by the geomagnetic sensor is stored in the first seven bits of an eight-bit binary number pre-created by the single chip microcomputer, the data of the microwave sensor is put into the eighth bit, and then the eight-bit binary data is converted into hexadecimal data.
4. The method for detecting and processing the blind vision zone information of the turning road as claimed in claim 1, wherein in the step 5, the specific process of comparing the fused data with the hexadecimal feature vector sample is as follows: and performing cyclic detection on the fused data and the hexadecimal feature vector samples, matching the detected fused data with each feature vector sample, and returning information corresponding to the feature vector sample if the matching is successful.
5. The method for detecting and processing the blind zone information of the turning road as claimed in claim 1, wherein in the step 6, the specific process that the microcontroller sends the detection data to the LED display screen for displaying and starts the warning lamp for warning is as follows: the microcontroller calculates the speed of the moving object and the distance information between the moving object and a corner according to the transmitted data by analyzing the data transmitted by the radar sensor, and calls different data to transmit to the LED display screen to display and starts the warning lamp to warn according to the corresponding type of the moving object.
6. The method for detecting and processing the blind vision zone information of the turning road as claimed in any one of claims 1 to 5, wherein in the step 7, the specific process of the background server performing the fuzzy clustering analysis on the accumulated data is as follows:
step 71, the background server takes out the nearest n groups of fused geomagnetic data and microwave data from the database as a group of initial sample domains, and each group of data is set as X1,X2,…,XmAnd each data has m indexes representing the characteristics of the data, the initial sample domain is the firstThe characteristic attribute data of the i classified objects is Xi1’,Xi2’,…,Xim’；
Step 72, normalizing the feature attribute data using:
wherein,
step 73, establishing a fuzzy similarity relation matrix, and determining a similarity matrix R (R) by using the general clustering analysisij)n×n，rijIs XiAnd XjInter-similarity coefficient, wherein
Taking the appropriate value of M to make rijIn [0,1 ]]Dispersing;
step 74, performing a transitive closure operation on the similarity matrix R to obtain t (R) ═ RnAnd on the basis, the confidence level lambda takes different values to obtain different clustering results.
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