A method and device for detecting and warning of high beam headlights of vehicles at night

Abstract

The application discloses a kind of detection and early warning high beam of night vehicle method and device, mainly related to night road traffic safety field.Method includes following steps:S1, the vehicle that each lane is detected to pass through;S2, the vehicle that passes through is carried out headlamp brightness measurement, obtains detection data;S3, according to detection data, analysis determines to open high beam vehicle;S4, to high beam vehicle and surrounding are multi-directional warning.The application realizes in night can real-time continuously for driver provides the early warning information of high beam vehicle in front, effectively reduces the traffic accident caused by high beam in night, guarantees night road traffic safety.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of night road traffic safety, in particular to a method and device for detecting and warning high beam of night vehicle. BACKGROUND

[0002] When the car drives on the road with insufficient light at night, if the oncoming vehicle uses high beam, the driver will be temporarily blinded, which is extremely harmful to road safety and can easily cause traffic accidents.

[0003] According to relevant reports, the misuse of high beam is very common, and has become a major traffic habit that traffic participants most hate. In the statistics of night traffic accidents, most accidents are also related to the misuse of high beam.

[0004] The existing research on this is shallow and there are few devices on the market. The main method is to detect multiple times, modify the vehicle circuit, and operate the high beam switch of the car. Such prevention methods have the problems of complicated detection steps, long detection time, poor warning effect, and being divorced from reality. SUMMARY

[0005] The purpose of the present application is to provide a method and device for detecting and warning high beam of night vehicle, which can provide real-time and continuous warning information of the high beam vehicle in front of the driver at night, effectively reduce traffic accidents caused by high beam blindness at night, and ensure the safety of night road traffic.

[0006] To achieve the above purpose, the present application realizes the following technical solutions:

[0007] A method for detecting and warning high beam of night vehicle, comprising the following steps:

[0008] S1, detecting the vehicle passing through each lane;

[0009] S2, measuring the brightness of the passing vehicle to obtain detection data;

[0010] S3, analyzing and determining the high beam vehicle according to the detection data;

[0011] S4, warning the high beam vehicle and the surrounding in multiple directions.

[0012] Preferably, the steps S1 to S2 are realized by the following method: collecting the vehicle passing through the lane signal, and converting the signal into an electrical signal, the electrical signal as a starting signal, starting the sensor to detect the brightness of the passing vehicle and distinguishing the vehicle light within 2.5 seconds after the sensor is turned on, the detected light intensity and illumination time as detection data.

[0013] Preferably, the analysis determines that the high beam light vehicle is opened, including: the brightness data is classified and stored, and the accumulated data is analyzed by fuzzy clustering to obtain an accurate feature vector interval, the feature vector interval is updated to form a feature vector sample set, and the feature vector sample set is a standard for determining whether the vehicle is opened.

[0014] Preferably, the fuzzy clustering analysis includes: selecting a plurality of collected detection data as a set of initial sample domains, denoted as collected detection data A1(X1, Y1), A2(X2, Y2), A3(X3, Y3), A4(X4, Y4), A5(X5, Y5), wherein X represents the light intensity value, and Y represents the light receiving time; using the Euclidean distance algorithm to establish a similarity relationship; and using the K-Means algorithm to cluster the light intensity value data.

[0015] Preferably, the multi-directional warning is achieved by the following steps:

[0016] Voice reminder field one, voice reminder field two, and voice reminder field three are respectively set.

[0017] Voice reminder field one is played for the warned vehicle.

[0018] Voice reminder field two is played for the vehicle in the opposite lane of the warned vehicle.

[0019] When a vehicle comes from the opposite lane of the warned vehicle, voice reminder field three is played for the warned vehicle.

[0020] The warning duration of the multi-directional warning is 3-5 seconds.

[0021] Preferably, after the step 4 is completed, the multi-directional warning is completed, and a continuous shooting link for the high beam light vehicle is started, and after the continuous shooting link is started, the vehicle information that is shot is uploaded and stored.

[0022] A device for detecting and warning high beam light of a vehicle at night includes a vehicle detection module, an information transmission processing module, a warning module, and a background server. The vehicle detection module includes a geomagnetic sensor installed in the middle of the lane and performs wireless data transmission with the information transmission processing module. The information processing module is installed on the right side of the lane and performs remote data transmission with the background server. The warning module includes a voice warning device installed on the left side of the lane. The voice warning device performs wireless data transmission with the information transmission processing module. The vehicle detection module, the information transmission processing module, and the warning module form a set of modules, and the set of modules are installed at an interval of 300 meters in the same direction lane.

[0023] Preferably, the information transmission processing module comprises a photoelectric sensor, a microcontroller and an Internet of Things transmission module, an output end of the photoelectric sensor is connected with an input end of the microcontroller, and an output end of the geomagnetic sensor is connected with an input end of the photoelectric sensor.

[0024] Preferably, the Internet of Things transmission module is an NB-IOT Internet of Things transmission module, the Internet of Things transmission module is connected to a background server, and the microcontroller is an STC15 series single-chip microcomputer.

[0025] Compared with the prior art, the present application has the following beneficial effects:

[0026] The present application uses a geomagnetic sensor and a photoelectric sensor to detect a vehicle and a light brightness in real time, thereby determining a high beam vehicle and giving a timely warning, effectively preventing traffic accidents caused by dazzling and unclear vision of a high beam when vehicles meet at night, and effectively monitoring road traffic conditions, ensuring timely circulation of road condition information and ensuring safety of vehicle driving at night. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 is a flow chart of the present application.

[0028] Figure 2 is a structural diagram of the present application.

[0029] Figure 3 is an installation schematic diagram of the present application.

[0030] Figure 4 is a partial structural schematic diagram of the present application.

[0031] Reference signs shown in the drawings:

[0032] 1, information transmission processing module; 2, geomagnetic sensor; 3, continuous shooting device; 4, voice warning device; 5, high beam vehicle; 6, opposite lane vehicle; 7, photoelectric sensor, 8, microcontroller; 9, Internet of Things transmission module; 11, lane A; 22, lane B. DETAILED DESCRIPTION

[0033] The present application will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present application and not used to limit the scope of the present application. In addition, it should be understood that after reading the content taught by the present application, those skilled in the art can make various modifications or changes to the present application, and these equivalent forms also fall within the scope defined by the present application.

[0034] Embodiment: as shown in the drawings, a method and device for detecting and warning high beam of vehicle at night Figures 1-4

[0035] Specific implementation steps include: ​

[0036] S1, measuring whether there is a vehicle passing through each lane by a vehicle detection device;

[0037] S2, if there is a vehicle passing through, transmitting a signal to a photoelectric sensor for measuring the brightness of the vehicle light;

[0038] S3, classifying the brightness detection value by fuzzy clustering analysis to analyze and determine the high beam vehicle;

[0039] S4, if a high beam vehicle appears, multi-directional warning is performed on the high beam vehicle and the surrounding area.

[0040] The specific structure of the device includes a vehicle detection module, an information transmission processing module 1, a warning module, a continuous shooting module, etc. The vehicle detection module is installed in the middle of the lane for detecting the presence of vehicles. The information transmission processing module 1 monitors the brightness of the vehicle light in real time and transmits data for brightness value analysis. The warning module is used for warning the presence of high beam in the two-way lane. The continuous shooting module is used to continuously shoot the high beam vehicle 5 after the warning is completed to determine the subsequent brightness and store it for analysis.

[0041] Steps S1 to S2 are performed:

[0042] The vehicle detection module includes a geomagnetic sensor 2, which is installed in the middle of each lane for detecting whether a vehicle passes through.

[0043] The information receiving and processing module includes a photoelectric sensor 7, a microcontroller 8 and an Internet of Things transmission module 9. The photoelectric sensor 7 is arranged at the right side of the road. The output end of the photoelectric sensor 7 is connected to the input end of the microcontroller 8. The output end of the geomagnetic sensor 2 is connected to the input end of the photoelectric sensor 7.

[0044] The geomagnetic sensor 2 is in the default start state. When a car passes through the geomagnetic sensor 2, the geomagnetic sensor 2 converts the geomagnetic signal of the passing vehicle into an electrical signal and sends it to the photoelectric sensor 7. The photoelectric sensor 7 is started immediately. If no vehicle is detected, the geomagnetic sensor 2 remains started.

[0045] When the photoelectric sensor 7 receives the electrical signal from the geomagnetic sensor 2 indicating that a vehicle has passed through, the photoelectric sensor 7 is started immediately and starts detecting the brightness value of the vehicle light. The brightness value detected within 2.5 seconds after the photoelectric sensor 7 is turned on is used as the detection data.

[0046] Step S3 is performed:

[0047] The analysis determines whether the high beam vehicle 5 is turned on by classifying and storing the detection data, and performing fuzzy clustering analysis on the accumulated data to obtain an accurate feature vector interval, which forms a feature vector sample set after being updated, and the feature vector sample set is the standard for determining whether a vehicle has its high beam turned on.

[0048] The specific process of the server performing fuzzy clustering analysis on the accumulated data is as follows:

[0049] The server selects n groups of collected photoelectric sensor 7 import data as a set of initial sample theory domain from the database, and sets the collected data as A1(X1, Y1), A2(X2, Y2), A3(X3, Y3), A4(X4, Y4), and A5(X5, Y5), where X represents the light intensity value, and Y represents the light receiving duration.

[0050] The similarity relationship is established according to the monitoring data, and the Euclidean distance method is used to establish the similarity relationship:

[0051]

[0052] Taking clustering light intensity data as an example, the following are the steps of using K-Means algorithm to cluster and calculate light intensity value data:

[0053] First, determine three centroids according to the detection analysis requirements: low beam brightness cluster B1, high beam brightness cluster B2, and high-intensity light brightness cluster B3;

[0054] Then, calculate the distances between X i (i = 1, 2 …… 5) and B1, B2, and B3 three centroids respectively:

[0055] Taking point i as an example: ΔX i1 = |X i -B1|, ΔX i2 = |X2-B2|, ΔX i3 = |X3-B3|;

[0056] At this time, judge the values of ΔX i1 , ΔX i2 , and ΔX i3 , if ΔX i2 is the smallest, then ΔX i2 is the closest to B2, and if Y i2 also meets the accepted light signal duration, then A i is classified into the high beam brightness cluster B2, and A i is determined as a high beam vehicle. The low beam brightness cluster B1 and the high-intensity light brightness cluster B3 are classified and analyzed in the same way.

[0057] When all the data is "clustered", the average of the sum of Xi in each cluster is recalculated, so that the new centroid of each cluster is obtained as the updated standard detection sample, that is

[0058]

[0059] In the formula, n respectively represents the number of elements in each cluster, X i respectively represent the elements in the low beam brightness cluster, the high beam brightness cluster, and the high-intensity light brightness cluster.

[0060] The above steps are repeated according to the obtained three new centroids E1', E2', and E3', so as to construct a dynamic clustering diagram, until the calculated centroid no longer changes, so as to obtain the standard high beam brightness cluster judgment interval.

[0061] Through fuzzy clustering analysis, it is assumed that X and Y in A data in a sample set {A1, A2, A3, …, A n} meet the high beam light intensity condition parameters and the expected light signal duration condition parameters, respectively, and the set data {A1, A2, A3, …, A n} is marked as a high beam vehicle.

[0062] The light intensity numerical centroid division interval is: low beam brightness cluster B1 [1000cd, 1450cd), high beam brightness cluster B2 [1450cd, 3000cd), and high-intensity light brightness cluster B3 [3000cd, +∞), wherein cd is the unit of light: candela.

[0063] The light signal duration division interval is: low beam brightness duration cluster C1 [0s, 2s), and high beam brightness duration cluster C2 [2s, +∞), wherein s is the unit of time: second.

[0064] After the above fuzzy clustering analysis, if there is a sample that meets the condition parameters, a signal is sent to the microcontroller 8, and the high beam vehicle is determined, and the microcontroller 8 is analyzed and processed.

[0065] Step S4 is performed:

[0066] The warning module includes a voice warning device 4, and the voice warning device 4 is arranged on the left side of the road.

[0067] The specific working process of the warning module is that the voice warning device 4 sets three voice reminder fields as "Please switch to low beam in time", "Please pay attention to the high beam vehicle in the opposite lane, and pay attention to the road conditions in time", and "There is a vehicle coming, please switch to low beam in time". The microcontroller 8 sends the arranged high beam vehicle signal to the voice warning device 4. When the vehicle comes from the lane and the vehicle in the lane is a high beam vehicle, the voice warning devices of the lane A 11 and the lane B 22 start to warn and remind, respectively. The content of the voice warning device 4 for the high beam vehicle in the lane is "Please switch to low beam in time", and the content of the voice warning device 4 for the vehicle 6 in the opposite lane is "Please pay attention to the high beam vehicle in the opposite lane, and pay attention to the road conditions in time".

[0068] If the adjacent geomagnetic sensor 2 of the lane B 22 detects a vehicle coming at this time, the geomagnetic sensor 2 simultaneously transmits the vehicle signal of the opposite lane B 22 to the warning device of the lane A 11. The voice warning device 4 can additionally warn the high beam vehicle 5; "There is a vehicle coming, please switch to low beam in time".

[0069] After steps S1 to S4 are performed, the snapshot reporting is performed, and the specific implementation is as follows:

[0070] The continuous shooting module includes an electronic continuous shooting device 3, the electronic continuous shooting device 3 and the voice warning device 4 are arranged on the left side of the road, and the output end of the electronic continuous shooting device 3 is connected with the input end of the microcontroller 8.

[0071] The specific working mode of the continuous shooting module is that the continuous shooting module is started immediately after the voice warning device 4 ends the warning, and the continuous shooting link of 5 photos with an interval of 0.5 seconds and a duration of 2 seconds is performed, which is used to detect whether the high beam vehicle 5 is switched to the low beam in time. If the vehicle still maintains the high beam after the continuous shooting of several photos, the vehicle information is stored in the background server through the microcontroller 8, and further analysis, processing and information transmission are performed.

[0072] According to the relevant traffic rules formulated by the state, the high beam should be switched to the low beam in most cases, and the high beam and the low beam should be alternately changed for special conditions to achieve the warning effect. Therefore, if the vehicle maintains the low beam and the high beam alternately changes after the continuous shooting, the vehicle is considered to switch the light in time and maintain the traffic order. If the vehicle still maintains the high beam after the continuous shooting, the relevant information is transmitted to the background through the microcontroller 8 for further arrangement and transmission.

[0073] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application but not to limit it. Although the present application has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that the specific embodiments of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and any modification or equivalent replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A method of detecting and warning of high beam headlights of a vehicle at night, characterized in that, The method comprises the following steps: S1, detecting vehicles passing through each lane; S2, measuring the brightness of the vehicle lights to obtain detection data; S3, analyzing and determining the high beam vehicle according to the detection data; S4, multi-directional warning for the high beam vehicle and the surrounding area; The steps S1 to S2 are realized by the following method: a geomagnetic sensor is installed in the middle of each lane to detect whether a vehicle passes through and collect the vehicle passing through lane signal, and the signal is converted into an electrical signal, which is used as a starting signal to start the sensor to detect the brightness of the vehicle lights and distinguish the vehicle lights within 2.5 seconds after the sensor is turned on. The detected light intensity and light duration are used as detection data; The analysis and determination of the high beam vehicle includes: classifying and storing the detection data, and performing fuzzy clustering analysis on the accumulated data to obtain an accurate feature vector interval. The feature vector interval is updated to form a feature vector sample set, which is used as the standard for determining whether the vehicle is turned on the high beam; The fuzzy clustering analysis includes: Selecting 5 groups of collected detection data as a set of initial sample domains, denoted as collected detection data , , , , , wherein represents the light intensity value, represents the length of time of receiving light; The K-Means algorithm is used to cluster and calculate the light intensity numerical data; Three centroids are determined according to the detection analysis requirements: low beam brightness cluster , high beam brightness cluster , and high-intensity light brightness cluster ; Respectively calculate detection data With , , Distance of three centroids: ， ， ， wherein = 1, 2,... 5; Respectively judge , and The value size, if The value is the smallest, if The distance The point is closest, if at the same time The accepted light signal length is met, the Point is classified as high beam brightness cluster At the same time, the Point is judged as a high beam vehicle; low beam brightness cluster And high intensity light brightness cluster The analysis is the same. After all the data has been categorized, the values ​​in each cluster are recalculated. The average of the sums is used to derive the new centroid of each cluster, which serves as the detection sample for the updated standard. ， In the formula, respectively represent the number of elements in each cluster, respectively represent the elements in the low beam brightness cluster, the high beam brightness cluster, and the high-intensity light brightness cluster. According to the derived ’, ’, ’three new centroids repeat the above steps, thereby constructing a dynamic clustering map until the calculated centroids no longer change, thereby obtaining a standard high beam brightness cluster judgment interval; By fuzzy clustering analysis in the assumption sample set { , , ,…, } in the data of , , , when the X index meets the high beam light intensity condition parameter, the index reaches the expected acceptance light signal length condition parameter, the set data { , , , …, } is marked as a high beam vehicle.

2. The method of claim 1, wherein the method further comprises: The multi-directional warning is realized by the following steps: Voice reminder field one, voice reminder field two, and voice reminder field three are set respectively; Voice reminder field one is played for the warned vehicle; Voice reminder field two is played for the vehicle in the opposite lane of the warned vehicle; When a vehicle comes from the opposite lane of the warned vehicle, voice reminder field three is played for the warned vehicle; The warning duration of the multi-directional warning is 3-5 seconds.

3. The method of claim 1, wherein the method further comprises: After the step S4 is completed, i.e., after the multi-directional warning is completed, a continuous shooting link for the high beam vehicle is started. After the continuous shooting link is started, the information of the photographed vehicle is uploaded and stored.

4. A device for detecting and warning of oncoming high beam headlights of a vehicle at night, characterized in that The system comprises a vehicle detection module, an information transmission processing module, a warning module, and a background server. The vehicle detection module comprises a geomagnetic sensor installed in the middle of each lane to detect whether a vehicle passes through and perform wireless data transmission with the information transmission processing module. The information transmission processing module is installed on the right side of the lane and performs remote data transmission with the background server. The warning module comprises a voice warning device installed on the left side of the lane. The voice warning device performs wireless data transmission with the information transmission processing module. The vehicle detection module, the information transmission processing module, and the warning module form a set of modules, and the set of modules is installed at an interval of 300 meters in the same direction lane. The vehicle detection module performs steps S1 to S2 in claim 1, the information transmission processing module performs step S3 in claim 1, the background server performs fuzzy clustering analysis on the accumulated data, and the warning module performs step S4 in claim 1.

5. The device for detecting and warning of high beam of vehicle at night according to claim 4, characterized in that, The information transmission processing module comprises a photoelectric sensor, a microcontroller, and an Internet of Things transmission module. The output end of the photoelectric sensor is connected to the input end of the microcontroller, and the output end of the geomagnetic sensor is connected to the input end of the photoelectric sensor.

6. The device for detecting and warning of high beam of vehicle at night according to claim 5, characterized in that, The Internet of Things transmission module is an NB-IOT Internet of Things transmission module, the Internet of Things transmission module is connected to a background server, and the microcontroller is an STC15 series single-chip microcomputer.

Images