Intelligent traffic signal lamp control method based on fiber bragg grating sensing network

Abstract

The invention provides a traffic signal lamp intelligent control method based on a fiber bragg grating sensing network, and relates to the technical field of traffic signal lamps, and the method comprises the steps: obtaining the detection data of each fiber bragg grating sensing line, and enabling the fiber bragg grating sensing lines to be transversely laid at a selected traffic crossroad along a lane, three fiber bragg grating sensing lines parallel to the stop line are laid on each road; determining the length range of the motor vehicle queuing length of each lane according to the detection data of each fiber Bragg grating sensing line; and controlling the working state of the corresponding traffic signal lamp according to the length range of the motor vehicle queuing length of each lane. The actual traffic flow can be determined through the detection data of the fiber Bragg grating sensing lines, the green light time can be dynamically allocated based on the actual traffic flow, the vehicle queuing time is shortened, and the passing efficiency can be effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of traffic signal lights, in particular to an intelligent control method for traffic signal lights based on a fiber grating sensing network. BACKGROUND

[0002] With the development of the times and society and the improvement of people's quality of life, the number of cars has increased dramatically, and traffic congestion occurs from time to time. In particular, during the rush hour, it is often several kilometers of traffic jams at crossroads. The global urbanization rate is over 55%, and the number of private cars increases by 5%-8% annually. The traditional traffic management mode has been unable to cope with high-density traffic. As an important signal to alleviate traffic flow and reduce traffic jams, it is necessary to improve the time of the red and green light signals and promote the development of urban traffic.

[0003] However, the traditional traffic signal light control often adopts a fixed switching mode, which cannot give the best control signal to the actual road traffic. Fixed-length red and green lights are prone to resource mismatch when traffic fluctuates (such as peak hours, emergencies, or road construction). SUMMARY

[0004] Therefore, the present application provides an intelligent control method for traffic signal lights based on a fiber grating sensing network.

[0005] In a first aspect, the present application provides an intelligent control method for traffic signal lights based on a fiber grating sensing network, comprising: obtaining detection data of each fiber Bragg grating sensing line, wherein the fiber Bragg grating sensing line is laid along the lane transversely at a selected traffic intersection, and three fiber Bragg grating sensing lines parallel to the stop line are laid on each road; determining the length range of the motor vehicle queue length of each lane according to the detection data of each fiber Bragg grating sensing line; controlling the working state of the corresponding traffic signal light according to the length range of the motor vehicle queue length of each lane.

[0006] In an embodiment, the three fiber Bragg grating sensing lines laid on the target road are a first fiber sensing line, a second fiber sensing line, and a third fiber sensing line, which are sequentially away from the traffic signal light; and the determination of the length range of the motor vehicle queue length of each lane according to the detection data of each fiber Bragg grating sensing line comprises: judging whether there is a vehicle in the area corresponding to each fiber Bragg grating sensing line according to the detection data of each fiber Bragg grating sensing line of the target lane; In a case where it is determined that the area corresponding to the first fiber sensing line has a vehicle parked and the area corresponding to the second fiber sensing line has no vehicle parked, it is determined that the motor vehicle queue length of the target lane is less than a first interval length, the first interval length being an interval distance between the first fiber sensing line and the second fiber sensing line. In a case where it is determined that the area corresponding to the first fiber sensing line and the area corresponding to the second fiber sensing line have vehicles parked and the area corresponding to the third fiber sensing line has no vehicle parked, it is determined that the motor vehicle queue length of the target lane is greater than the first interval length and less than a second interval length, the second interval length being an interval distance between the first fiber sensing line and the third fiber sensing line. In a case where it is determined that the areas corresponding to the first fiber sensing line, the second fiber sensing line and the third fiber sensing line have vehicles parked respectively, it is determined that the motor vehicle queue length of the target lane is greater than the second interval length.

[0007] In an embodiment, the control of the working state of the corresponding traffic signal lamp according to the length range in which the motor vehicle queue length of each lane is located comprises: In a case where it is determined that the motor vehicle queue length of the target lane is greater than the first interval length and less than the second interval length, the green light time corresponding to the target lane is controlled to be extended according to a preset rule. In a case where it is determined that the motor vehicle queue length of the target lane is greater than the second interval length, the green light corresponding to the target lane is controlled to be extended to a maximum duration.

[0008] In an embodiment, the control of the working state of the corresponding traffic signal lamp according to the length range in which the motor vehicle queue length of each lane is located comprises: In a case where it is determined that the motor vehicle queue length of the target lane is less than the first interval length, the motor vehicle queue length and the motor vehicle queue number of the target lane are obtained based on camera visual data. In a case where the motor vehicle queue length is less than a preset length threshold, the green light time corresponding to the target lane is controlled to be shortened according to the motor vehicle queue number.

[0009] In an embodiment, the control of the working state of the corresponding traffic signal lamp according to the length range in which the motor vehicle queue length of each lane is located comprises: In a case where it is determined that the motor vehicle queue length of the target lane is greater than the second interval length, the congestion situations of each upstream intersection are obtained according to the detection data of each fiber Bragg grating sensing line of the upstream intersection. A target upstream intersection is determined according to the congestion situations of each upstream intersection. The proportion of the red light duration to the green light duration in the cycle time of the traffic signal lamp of the target upstream intersection is increased.

[0010] In an embodiment, the method further comprises: obtaining meteorological data corresponding to the current time; determining a compensation parameter of the traffic signal light according to the meteorological data; compensating the working parameter of the traffic signal light according to the compensation parameter.

[0011] In an embodiment, the method further comprises: when it is determined that there is an emergency vehicle according to the detection data of each fiber Bragg grating sensing line and the camera visual data, controlling the traffic signal light corresponding to the direction in which the emergency vehicle travels to be green, prolonging the duration of the green light to the maximum duration, and prolonging the duration of the red light in the direction conflicting with the direction in which the emergency vehicle travels.

[0012] In a second aspect, the present application further provides a traffic signal light intelligent control device based on a fiber grating sensing network, comprising: an acquisition module configured to acquire detection data of each fiber Bragg grating sensing line, wherein the fiber Bragg grating sensing line is laid transversely along a lane at a selected traffic intersection, and three fiber Bragg grating sensing lines parallel to the stop line are laid for each road; a first processing module configured to determine a length range in which a motor vehicle queue length of each lane is located according to the detection data of each fiber Bragg grating sensing line; a second processing module configured to control the working state of the corresponding traffic signal light according to the length range in which the motor vehicle queue length of each lane is located.

[0013] In a third aspect, the present application further provides an electronic device comprising a processor and a memory; the memory has a computer program stored therein, wherein the computer program, when executed by the processor, implements the traffic signal light intelligent control method based on the fiber grating sensing network as described in the first aspect.

[0014] In a fourth aspect, the present application further provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the traffic signal light intelligent control method based on the fiber grating sensing network as described in the first aspect.

[0015] The traffic signal light intelligent control method based on the fiber grating sensing network of the present application has the following beneficial effects over the related art: 1、In the application, optical fiber Bragg grating sensing lines are laid transversely along the lanes at selected traffic intersections, and three optical fiber Bragg grating sensing lines parallel to the stop line are laid on each road. Since the optical fiber Bragg grating sensing lines can detect whether a vehicle is parked above them, after obtaining the detection data of each optical fiber Bragg grating sensing line, the length range in which the motor vehicle queue length of each lane is located can be determined according to the detection data of each optical fiber Bragg grating sensing line. The green light signal at the selected intersection is dynamically regulated according to the length range in which the motor vehicle queue length of each lane is located, so as to dynamically allocate green light time according to the actual traffic volume, reduce vehicle queue time, and effectively improve the traffic efficiency.

[0016] 2、The application uses optical fiber Bragg grating sensing lines to detect vehicle queue conditions. Since the optical fiber Bragg grating sensing lines have the characteristics of corrosion resistance and electromagnetic interference resistance, they can work stably in extreme environments such as heavy rain, snow and high temperature, have high work reliability, and have a wide application scenario of the optical fiber grating sensing traffic signal lamp intelligent regulation method. In addition, the optical fiber sensing network has a long service life and low maintenance cost, so the cost required to implement the above-mentioned optical fiber grating sensing traffic signal lamp intelligent regulation method is low. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments or the related art, the following will briefly introduce the drawings needed to be used in the embodiment or related art description. Obviously, the drawings in the following description are only some embodiments of the application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0018] Figure 1 The flowchart of the traffic signal lamp intelligent control method based on the optical fiber grating sensing network in an embodiment of the application is shown. Figure 2 The laying structure diagram of the optical fiber Bragg grating sensing line in an embodiment of the application is shown. Figure 3 The flowchart of step S102 in an embodiment of the application is shown. Figure 4 The flowchart of step S103 in an embodiment of the application is shown. Figure 5 The structural diagram of the traffic signal lamp intelligent control device based on the optical fiber grating sensing network in an embodiment of the application is shown. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0020] As described in the background, with the development of the times and society and the improvement of people's quality of life, the number of cars has increased dramatically, and traffic congestion occurs from time to time. Especially during the rush hour, it often takes several kilometers to get through the intersection. The global urbanization rate is more than 55%, and the number of private cars increases by 5%-8% per year. The traditional traffic management mode has been unable to cope with high-density traffic. As an important signal to alleviate traffic flow and reduce congestion, it is necessary to improve the time of the traffic light signal and promote the development of urban traffic.

[0021] However, the traditional traffic light control often uses a fixed switching mode, which cannot give the best control signal to the actual road traffic. Fixed-length traffic lights are prone to resource mismatch when traffic fluctuates (such as peak hours, emergencies, or road construction).

[0022] Based on this, in some embodiments, as shown in Figure 1 The present application provides a traffic light intelligent control method based on a fiber grating sensing network, which comprises the following steps S101-S103.

[0023] S101: Obtain detection data of each fiber Bragg grating sensing line, wherein the fiber Bragg grating sensing line is laid along the lane transversely at a selected traffic intersection, and three fiber Bragg grating sensing lines parallel to the stop line are laid on each road.

[0024] As shown in Figure 2 , the fiber grating pressure and vibration sensor in Figure 2 is a fiber Bragg grating sensing line, and the three fiber Bragg grating sensing lines are arranged at intervals. The interval distance between the three fiber Bragg grating sensing lines can be determined according to actual needs. For example, the distance between two adjacent fiber Bragg grating sensing lines can be 40 meters. When laying the fiber Bragg grating sensing line, a certain depth (for example, 0.3 meters) can be excavated along the lane, and then a waterproof FBG sensor array is pre-buried, the fiber is armored, and high-strength concrete (compressive strength ≥ 30 MPa) is backfilled to realize the paving of the fiber Bragg grating sensing line in the lane.

[0025] It can be understood that the optical fiber Bragg grating sensing line is used to detect the vehicle queuing condition. Since the optical fiber Bragg grating sensing line has the characteristics of corrosion resistance and anti-electromagnetic interference, it can work stably in extreme environments such as heavy rain, snow and high temperature, and has high reliability. The application scene of the optical fiber grating sensing traffic signal lamp intelligent control method is wide. In addition, the optical fiber sensing network has a long service life and low maintenance cost. It should be noted that the wavelength range of the optical fiber Bragg grating sensing line is 1520-1570nm. Each optical fiber Bragg grating sensing line includes at least one FBG sensor. For example, the optical fiber Bragg grating sensing line can include three FBG sensors for detecting vertical pressure (range 0-10 tons), transverse shear force (range 0-5 tons) and vibration frequency (0-200Hz). Among them, the whole vehicle weight of small cars is generally 1-1.5 tons, compact cars is 1.5-1.8 tons, medium cars is 1.8-2.2 tons, and large cars is more than 2.2 tons. The transverse shear force of small vehicles is 0.1-0.5 tons, the transverse shear force of medium vehicles is 0.3-1 ton, and the transverse shear force of large vehicles is generally greater than 0.5 tons. The vibration frequency of a car is 10-50Hz, the vibration frequency of a truck is 5-30Hz, and the vibration frequency of a pedestrian is 50-200Hz. Therefore, based on the detection data of each optical fiber Bragg grating sensing line, motor vehicles, non-motor vehicles and pedestrians can be well divided.

[0026] In the application, a temperature sensor can also be deployed near the FBG sensor to collect the ambient temperature in real time, and then the detection data of the FBG sensor can be compensated according to the ambient temperature. The compensation formula is: Among them, is the real strain, is the measured wavelength shift, is the temperature change, is the temperature sensitivity coefficient, is the strain sensitivity coefficient.

[0027] S102: Determine the length range of the motor vehicle queuing length of each lane according to the detection data of each optical fiber Bragg grating sensing line.

[0028] It can be understood that three optical fiber Bragg grating sensing lines parallel to the stop line are laid along the lane in the transverse direction. When the motor vehicle drives or parks on the sensing line, the weight of the vehicle will generate pressure on the sensing line, causing the reflection wavelength of the optical fiber Bragg grating to shift. The shift is related to the existence of the vehicle and the pressure intensity. Therefore, based on the detection data of each optical fiber Bragg grating sensing line, the approximate parking area of the vehicle can be determined, and then the length range of the motor vehicle queuing length of each lane can be determined.

[0029] S103: Controlling the working state of the corresponding traffic signal light according to the length range of the motor vehicle queue length in each lane.

[0030] It can be understood that when the length of the motor vehicle queue length in the lane is too long, the green light time of the corresponding lane can be extended to increase the traffic volume that can pass within the cycle time and relieve the congestion. When the length of the motor vehicle queue length in the lane is short, the green light time of the corresponding lane can be shortened to facilitate the passage of pedestrians. In addition, when the congestion of other lanes is heavy, the red and green lights of other lanes can be coordinated to relieve the congestion of other lanes.

[0031] The above intelligent control method of the traffic signal light based on the fiber grating sensing network, the optical fiber Bragg grating sensing lines are laid along the lanes transversely at the selected traffic intersection, three optical fiber Bragg grating sensing lines parallel to the stop line are laid on each road. Since the presence of vehicles above the optical fiber Bragg grating sensing lines can be detected by the optical fiber Bragg grating sensing lines, the length range of the motor vehicle queue length in each lane can be determined according to the detection data of each optical fiber Bragg grating sensing line after the detection data of each optical fiber Bragg grating sensing line is obtained. The green light signal of the selected intersection is dynamically regulated and controlled according to the length range of the motor vehicle queue length in each lane, so that the green light time is dynamically allocated according to the actual traffic volume, the vehicle queuing time is reduced, and the traffic efficiency can be effectively improved.

[0032] In some embodiments, the three optical fiber Bragg grating sensing lines laid on the target road (i.e., the lane currently analyzed) are a first optical fiber sensing line, a second optical fiber sensing line, and a third optical fiber sensing line, which are sequentially away from the traffic signal light, for example, A1, A2, and A3 in Figure 2 As shown in Figure 3 , in step S102, the length range of the motor vehicle queue length in each lane is determined according to the detection data of each optical fiber Bragg grating sensing line, which includes the following steps S301 to S304.

[0033] S301: Judging whether there are vehicles staying in the area corresponding to each optical fiber Bragg grating sensing line according to the detection data of each optical fiber Bragg grating sensing line in the target lane.

[0034] Among them, the road, the lane waiting area and the optical fiber Bragg grating sensing line can be numbered in advance to facilitate the determination of the vehicle staying condition of each road. The first part is the road number, that is, the monitored road is given a road number for distinguishing from other roads in the road network. For example, Figure 2As shown, the second part is a lane waiting area number, which reflects the lane information where the fiber grating sensor is located, and is numbered in clockwise direction as A, B, C, D. The third part is the order number of the fiber grating sensor, which reflects the order of the fiber grating sensor in the lane. Taking the A area as an example, the fiber grating sensor close to the stop line is numbered as A1, the middle sensor in the area is numbered as A2, and the last sensor is numbered as A3. The above coding rules can ensure that the coding of each sensing unit in the road network is not repeated, and the coding information can accurately extract the position information of each sensor, thereby laying a foundation for the subsequent intersection traffic parameter calculation.

[0035] The three optical fiber gratings divide a region capable of monitoring traffic information when waiting for a red light. According to the detection data of the target lane fiber Bragg grating sensing line, the dynamic load information corresponding to the target lane is obtained, which can judge the presence of vehicles, i.e., whether there is a vehicle staying at the road surface region at a certain moment according to the dynamic load information. The region divided by each fiber grating pressure sensor is coded, mainly based on the longitudinal position of the fiber grating pressure sensor on the road and the lane where it is located. Through the coding information composed of the above three parts, the correspondence between the road surface unit and the fiber grating sensor can be established, and the traffic information of each fiber grating divided region can be accurately reflected.

[0036] S302: In a case where it is determined that the first fiber sensing line corresponds to a region where a vehicle stays and the second fiber sensing line corresponds to a region where no vehicle stays, it is determined that the target lane motor vehicle queue length is less than the first interval length, and the first interval length is the interval distance between the first fiber sensing line and the second fiber sensing line.

[0037] It can be understood that in a case where the first fiber sensing line corresponds to a region where a vehicle stays and the second fiber sensing line corresponds to a region where no vehicle stays, it can be determined that the target lane motor vehicle exists in a queue, but does not queue to the region corresponding to the second fiber sensing line. Therefore, it can be determined that the target lane motor vehicle queue length is less than the first interval length, the queue length is short, and it belongs to the short queue length range.

[0038] S303: In a case where it is determined that the first fiber sensing line and the second fiber sensing line correspond to regions where vehicles stay and the third fiber sensing line corresponds to a region where no vehicle stays, it is determined that the target lane motor vehicle queue length is greater than the first interval length and less than the second interval length, and the second interval length is the interval distance between the first fiber sensing line and the third fiber sensing line.

[0039] It can be understood that, in the case that the vehicle stays in the area corresponding to the first and second fiber sensing lines and does not stay in the area corresponding to the third fiber sensing line, it can be determined that the target lane motor vehicle queues to the area where the second fiber sensing line is located but does not queue to the area where the third fiber sensing line is located. Therefore, it can be determined that the target lane motor vehicle queue length is greater than the first interval length but less than the second interval length, and the queue length extends beyond the middle area, which belongs to the medium queue length range.

[0040] In the case that it is determined that the areas corresponding to the first, second and third fiber sensing lines all stay with vehicles, it can be determined that the target lane motor vehicle queues beyond the area where the third fiber sensing line is located. Therefore, it can be determined that the target lane motor vehicle queue length is greater than the second interval length, and the queue length is extremely long, which belongs to the long queue length range.

[0041] It can be understood that, in the case that the vehicle stays in the area corresponding to the first and second fiber sensing lines and does not stay in the area corresponding to the third fiber sensing line, it can be determined that the target lane motor vehicle queues to the area where the second fiber sensing line is located but does not queue to the area where the third fiber sensing line is located. Therefore, it can be determined that the target lane motor vehicle queue length is greater than the first interval length but less than the second interval length, and the queue length extends beyond the middle area, which belongs to the medium queue length range.

[0042] In the embodiment, the detection data of the fiber Bragg grating sensing lines in the target lane can be used to determine the length range of the target lane motor vehicle queue length, so that the traffic light signal of the target lane can be dynamically adjusted according to the length range of the target lane motor vehicle queue length. When the queue length is long, the green light signal can be appropriately extended. When the queue length is short, the green light signal can be appropriately shortened, so that the working state of the traffic signal light can be dynamically adjusted according to the traffic flow, and the traffic efficiency can be effectively improved.

[0043] In some embodiments, in step S103, the working state of the corresponding traffic signal light is controlled according to the length range of the queue length of the motor vehicle in each lane, including: in the case that it is determined that the target lane motor vehicle queue length is greater than the first interval length and less than the second interval length, the green light time of the corresponding target lane is controlled to be extended according to a preset rule; and in the case that it is determined that the target lane motor vehicle queue length is greater than the second interval length, the green light of the corresponding target lane is controlled to be extended to the maximum duration.

[0044] It can be understood that the area between the first optical fiber sensing line and the second optical fiber sensing line is a relatively reasonable red light waiting area, that is, when the motor vehicles are queued between the first optical fiber sensing line and the second optical fiber sensing line, the green light time does not need to be extended. When it is determined that the motor vehicle queue length of the target lane is greater than the first interval length, the motor vehicle queue length is too long, and the green light time needs to be extended to alleviate the congestion situation. Further, when it is determined that the motor vehicle queue length of the target lane is between the first interval length and the second interval length, it can be determined that the current belongs to a light congestion situation, and the green light time of the lane can be extended according to a pre-set rule (for example, a fixed value). When the queue length exceeds the second interval length, it can be determined that the current belongs to a heavy congestion situation, and the green light is directly extended to the maximum duration set by the system to maximize the alleviation of the congestion situation and realize dynamic regulation of the traffic signal.

[0045] It should be noted that when the motor vehicle queue length of the target lane is between the first interval length and the second interval length, the camera visual data captured by the monitoring device can be obtained, and after the motor vehicle queue length or the motor vehicle queue number of the target lane is determined according to the camera visual data, the green light extension time can be adjusted according to the motor vehicle queue length or the motor vehicle queue number of the target lane. Exemplarily, the green light extension time can be 0.5*queue vehicle number*2s / vehicle.

[0046] In some embodiments, in step S103, controlling the working state of the corresponding traffic signal according to the length range in which the motor vehicle queue length of each lane is located, can further include: when it is determined that the motor vehicle queue length of the target lane is less than the first interval length, obtaining the motor vehicle queue length and the motor vehicle queue number of the target lane based on the camera visual data; and in the case that the motor vehicle queue length is less than a pre-set length threshold, controlling the green light time of the corresponding target lane to be shortened according to the motor vehicle queue number.

[0047] It can be understood that the area between the first optical fiber sensing line and the second optical fiber sensing line is a relatively reasonable red light waiting area, that is, when the motor vehicles are queued between the first optical fiber sensing line and the second optical fiber sensing line, the green light time does not need to be extended. But in the actual traffic scene, the lanes at the intersection are mutually influenced, therefore, if the motor vehicle queue length of the target lane is extremely short, it means that the traffic volume of the target lane is small, and the green light time of the target lane can be appropriately shortened, thereby facilitating the vehicles on other lanes to pass and facilitating pedestrians to pass.

[0048] On this basis, when it is determined that the motor vehicle queue length of the target lane is less than the first interval length, the system can obtain the motor vehicle queue length and the queue number of the lane in real time based on the camera visual data. If the motor vehicle queue length is further less than a preset length threshold, the green light time of the target lane can be shortened according to the obtained motor vehicle queue number, so as to realize fine adjustment of the traffic signal. It should be noted that the green light time shortening time of the target lane can be a fixed value, or can be determined according to the motor vehicle queue length and / or the queue number. For example, the green light shortening time can be 0.5*queue vehicle number*2s / vehicle.

[0049] In some embodiments, as shown in FIG. 1, in step S103, the working state of the corresponding traffic signal lamp is controlled according to the length range in which the motor vehicle queue length of each lane is located. The step can further include steps S401-S403. Figure 4

[0050] S401: When it is determined that the motor vehicle queue length of the target lane is greater than the second interval length, the congestion of each upstream intersection can be obtained according to the detection data collected by the fiber Bragg grating sensing line of each upstream intersection.

[0051] It can be understood that when it is determined that the motor vehicle queue length of the target lane is greater than the second interval length, the detection data collected by the fiber Bragg grating sensing line pre-laid at each upstream intersection can be obtained. According to the range in which the vehicle queue length of each upstream intersection is located, the congestion of the corresponding upstream intersection can be obtained.

[0052] S402: The target upstream intersection is determined according to the congestion of each upstream intersection.

[0053] In the application, the upstream intersection with lighter congestion can be determined as the target upstream intersection.

[0054] In the application, the motor vehicle queue length of each lane in each upstream intersection can be determined in the manner of the foregoing embodiments. When the motor vehicle queue length of the lane is less than the first interval length, it can be determined that the lane is in a light congestion state. When the motor vehicle queue length of the lane is greater than the first interval length and less than the second interval length, it can be determined that the lane is in a moderate congestion state. When the motor vehicle queue length of the lane is greater than the first interval length and less than the second interval length, it can be determined that the lane is in a heavy congestion state. Then, the light congestion state, the moderate congestion state and the heavy congestion state can correspond to different congestion scores, respectively. The comprehensive congestion score of the upstream intersection can be determined based on the sum of the congestion scores of each lane of the upstream intersection. Finally, the upstream intersection with the minimum comprehensive congestion score or the comprehensive congestion score lower than a preset threshold can be selected as the target upstream intersection.

[0055] ​It should be noted that the association data of each upstream intersection and the target lane within a predetermined time can also be obtained, that is, the historical vehicle data of the target lane in the upstream intersection, the probability of each lane vehicle in the upstream intersection to the target lane is determined according to the historical data, the probability of the lane vehicle to the target lane is taken as the weight of the corresponding lane, and the congestion score of each lane of the upstream intersection is weighted and summed based on the congestion score and the weight of each lane of the upstream intersection to determine the comprehensive congestion score of the upstream intersection.

[0056] S403: The time proportion of red light and green light in the traffic signal light cycle time of the target upstream intersection is increased. It should be noted that the time proportion of red light and green light is increased to a fixed proportion, which can also be determined according to the comprehensive congestion score of the target upstream intersection. The comprehensive congestion score of the upstream intersection is inversely related to the time proportion within the adjustable range.

[0057] It can be understood that the time proportion of red light and green light in a cycle of the traffic signal light of the target upstream intersection is increased and adjusted, that is, the red light duration is relatively prolonged and the green light duration is shortened, so as to reduce the traffic flow of the target lane entering the upstream intersection, thereby relieving the traffic pressure of the target lane and realizing the coordinated guidance of regional traffic.

[0058] In some embodiments, the traffic signal light intelligent control method based on the fiber grating sensing network can further include the steps of: determining the congestion index according to the queue length and the parking delay time, and determining the congestion condition according to the congestion index; determining the target control strategy according to the congestion condition; and adjusting the working state of the traffic signal light based on the target control strategy.

[0059] Among them, the congestion index can be defined as: Among them, x, y are dynamic weight coefficients. The queue length can be determined based on the camera visual data, and the parking delay can be determined according to the traffic signal light working data and the detection data of each fiber Bragg grating sensing line. The parking delay is the total time of the target vehicle waiting for the red light (the target vehicle can be the vehicle at a specific position, or the vehicle with the longest waiting time), and the free flow time is the theoretical time through the intersection without interference.

[0060] When k<0.5, it is determined that the intersection is smooth and does not need to be adjusted; when 0.5≤k<1, it is determined that the intersection is lightly congested, the green light of the congestion direction intersection is prolonged according to the data detected by the sensor, and the green light time of the secondary congestion direction is shortened; when k≥1, the upstream intersection is linked to shunt, the congestion condition of each upstream intersection is determined, and the proportion of red light / green light in the cycle time of the upstream intersection with lighter congestion condition is increased.

[0061] In some embodiments, the traffic signal intelligent control method based on the fiber grating sensing network further comprises: acquiring meteorological data corresponding to the current time; determining a compensation parameter of the traffic signal according to the meteorological data; and compensating the working parameter of the traffic signal according to the compensation parameter.

[0062] It can be understood that severe weather will obviously affect the driving of the vehicle, and therefore, the targeted compensation parameter can be generated according to the meteorological data. For example, the yellow light time is adjusted in foggy weather, when the visibility is less than 100 meters, the yellow light time is increased from 3 seconds to 5 seconds; when the visibility is less than 50 meters, the system determines that it is a first-class dense fog weather, triggers the green light time extension mechanism, and can switch to the red light slow flashing mode at night to remind to slow down; if the road surface temperature is lower than 0℃ and the humidity is more than 80%, it is identified as icing risk, and the yellow light time and the signal light brightness are adjusted synchronously; if it is rainy weather, the green light can be extended by 10% for every 10mm / h increase in rainfall intensity, and the red light of each direction can be extended by 2 seconds in heavy rain to ensure that the intersection vehicles are completely emptied.

[0063] After the compensation parameter is generated, the system implements dynamic correction on the working parameter of the traffic signal through the signal machine: in the scenario of insufficient visibility, the green light time is extended by 2 seconds for every 10 meters decrease in visibility, and the yellow light flashing frequency is also increased synchronously to warn the driver to slow down; for icy road surface, the system will extend the green light interval time (yellow light + full red time) by 3-5 seconds according to the degree of wet and slippery, and increase the signal light intensity to NTSC120% color gamut standard to ensure that the signal is clearly visible in low illumination environment. In addition, for extreme weather such as heavy rain and strong wind, the system will also adjust the signal cycle structure to prioritize the efficiency of main road traffic, and issue real-time road condition information through the variable information board to guide vehicles to bypass dangerous sections. This fine compensation mechanism based on meteorological data can effectively reduce the traffic accident rate in severe weather and further improve the road traffic efficiency.

[0064] In some embodiments, the traffic signal intelligent control method based on the fiber grating sensing network further comprises: when it is determined that there is an emergency vehicle according to the detection data of each fiber Bragg grating sensing line and the camera visual data, controlling the traffic signal in the direction of the emergency vehicle to be green, extending the green light duration to the maximum duration, and extending the red light duration in the direction conflicting with the direction of the emergency vehicle.

[0065] It can be understood that when the wavelength shift signal of a passing vehicle is detected by each fiber Bragg grating sensor line, the vehicle's appearance, lights (such as police lights, sirens) and driving trajectory are identified in combination with the camera's visual data, and the presence of an emergency vehicle (such as an ambulance or fire truck) is confirmed, the traffic light corresponding to the direction of the emergency vehicle's travel is immediately forced to switch to green, and the duration of the green light is extended to the maximum duration preset by the system. At the same time, the duration of the red light in the direction that conflicts with the direction of the emergency vehicle's travel is synchronously extended, so as to ensure that emergency vehicles have priority passage, reduce road traffic delays, and ensure smooth emergency rescue channels.

[0066] In some embodiments, FBG strain sensors may be installed at intervals on the ground at both ends of the crosswalk. The intelligent traffic light control method based on a fiber grating sensor network may also include: determining pedestrian traffic data based on detection data from the FBG strain sensors; and, when the pedestrian traffic data indicates that the pedestrian traffic time overlaps with the red light duration in the direction of the crosswalk, extending the green light duration in the direction of the motor vehicle lane that overlaps with the crosswalk based on the overlap time. A compensation weight may be set, and the product of the overlap time and the compensation weight is determined as the green light extension time.

[0067] For example, the spacing of FBG strain sensors can be 0.5 meters to detect the micro strain caused by pedestrians stepping on them (sensitivity 1με). Figure 2 As shown in the figure, when three sensors in the crosswalk are triggered continuously and the strain change lasts for more than 5 seconds, it is determined that a pedestrian is crossing.

[0068] In some embodiments, as Figure 5 As shown, the present application provides a traffic light intelligent control device 50 based on a fiber grating sensor network, comprising: an acquisition module 51, a first processing module 52 and a second processing module 53; wherein, The acquisition module 51 is used to acquire detection data of each fiber Bragg grating sensor line, wherein the fiber Bragg grating sensor line is laid transversely along the lane at the selected traffic intersection, and each road has three fiber Bragg grating sensor lines laid parallel to the stop line; The first processing module 52 is used to determine the length range of the motor vehicle queue in each lane based on the detection data of each fiber Bragg grating sensor line; The second processing module 53 is used to control the working state of the corresponding traffic light according to the length range of the motor vehicle queue in each lane.

[0069] In some embodiments, the three fiber Bragg grating sensing lines of the target road paving are a first fiber sensing line, a second fiber sensing line and a third fiber sensing line, which are sequentially away from the traffic signal light. The first processing module 52 is further configured to determine whether the areas corresponding to the fiber Bragg grating sensing lines have vehicles parked according to the detection data of the fiber Bragg grating sensing lines; determine that the motor vehicle queue length of the target lane is less than the first interval length when it is determined that the area corresponding to the first fiber sensing line has vehicles parked and the area corresponding to the second fiber sensing line does not have vehicles parked; determine that the motor vehicle queue length of the target lane is greater than the first interval length and less than the second interval length when it is determined that the areas corresponding to the first fiber sensing line and the second fiber sensing line have vehicles parked and the area corresponding to the third fiber sensing line does not have vehicles parked; and determine that the motor vehicle queue length of the target lane is greater than the second interval length when it is determined that the areas corresponding to the first fiber sensing line, the second fiber sensing line and the third fiber sensing line have vehicles parked. The first interval length is the interval distance between the first fiber sensing line and the second fiber sensing line, and the second interval length is the interval distance between the first fiber sensing line and the third fiber sensing line.

[0070] In some embodiments, the second processing module 53 is further configured to control the green light time of the corresponding target lane to be extended according to a preset rule when it is determined that the motor vehicle queue length of the target lane is greater than the first interval length and less than the second interval length, and control the green light of the corresponding target lane to be extended to a maximum duration when it is determined that the motor vehicle queue length of the target lane is greater than the second interval length.

[0071] In some embodiments, the second processing module 53 is further configured to obtain the motor vehicle queue length and the motor vehicle queue number of the target lane based on the camera visual data when it is determined that the motor vehicle queue length of the target lane is less than the first interval length, and control the green light time of the corresponding target lane to be shortened according to the motor vehicle queue number when the motor vehicle queue length is less than a preset length threshold.

[0072] In some embodiments, the second processing module 53 is further configured to obtain the congestion conditions of each upstream intersection according to the detection data of each fiber Bragg grating sensing line of the upstream intersection when it is determined that the motor vehicle queue length of the target lane is greater than the second interval length, determine a target upstream intersection according to the congestion conditions of each upstream intersection, and increase the time proportion of the red light and the green light in the cycle time of the traffic signal light of the target upstream intersection.

[0073] In some embodiments, the traffic signal light intelligent control device 50 based on the fiber grating sensing network further comprises a climate compensation module. The climate compensation module is configured to obtain meteorological data corresponding to the current time, determine a compensation parameter of the traffic signal light according to the meteorological data, and compensate the working parameters of the traffic signal light according to the compensation parameter.

[0074] In some embodiments, the traffic signal intelligent control device 50 based on the fiber grating sensing network further comprises an emergency vehicle confirmation module. The emergency vehicle confirmation module is configured to control the traffic signal corresponding to the direction of the emergency vehicle to be green, extend the green duration to the maximum duration, and extend the red duration of the direction conflicting with the direction of the emergency vehicle when it is determined that there is an emergency vehicle according to the detection data of each fiber Bragg grating sensing line and the camera visual data.

[0075] It should be noted that the traffic signal intelligent control device 50 based on the fiber grating sensing network provided by the embodiments of the present application is based on the same application concept as the traffic signal intelligent control method based on the fiber grating sensing network provided by the embodiments of the present application, and therefore the specific implementation of this embodiment can be referred to the implementation of the aforementioned traffic signal intelligent control method based on the fiber grating sensing network, and the repeated parts will not be described herein.

[0076] In some embodiments, the electronic device provided by the embodiments of the present application comprises a processor and a memory; the memory stores a computer program, wherein the computer program is executed by the processor to implement the aforementioned traffic signal intelligent control method based on the fiber grating sensing network.

[0077] Specifically, the processor may, for example, include a general-purpose microprocessor, an instruction set processor, and / or a related chipset, and / or a special-purpose microprocessor (such as an application-specific integrated circuit (ASIC)), etc. The processor can also include on-board memory for cache purposes. The processor can be a single processing unit or a plurality of processing units for performing different actions of the method process according to the embodiments of the present application.

[0078] The memory may, for example, be any medium capable of containing, storing, communicating, propagating or transmitting instructions. For example, the memory may, for example, include but is not limited to electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices, devices or propagation media. Specific examples of memory include magnetic storage devices such as magnetic tapes or hard disk drives (HDD); optical storage devices such as compact discs (CD-ROM); and also random access memory (RAM) or flash memory; and / or wired / wireless communication links.

[0079] The present application also provides a computer readable medium having a computer program stored thereon, which is executed by a processor to implement the aforementioned traffic signal intelligent control method based on the fiber grating sensing network. The computer readable medium can be included in the device / apparatus / system described in the above embodiments; or it can exist separately and not be assembled into the device / apparatus / system. The aforementioned computer readable medium carries one or more programs, which when executed, implement the method as in the embodiments of the present application.

[0080] According to embodiments of the present application, a computer readable medium can be a computer readable signal medium or a computer readable storage medium or any combination thereof. A computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium can be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, a computer readable signal medium can include a computer readable program code carried by a data signal in a baseband or as part of a carrier wave. Such a propagated signal can take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium can also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium can be transmitted using any appropriate medium, including, but not limited to, wireless, wire line, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0081] It is to be understood that the features mentioned herein can be combined and / or combined in various ways without departing from the scope of the present application. In particular, the features of the various embodiments and / or claims of the present application can be combined with each other as well as with other features not mentioned in the embodiments and / or claims. It is therefore anticipated that each of the features mentioned herein can be combined with any of the other features mentioned herein, without departing from the scope of the present application. It is further understood that features mentioned herein independently form the subject-matter of the various embodiments and / or claims of the present application, irrespective of the presence or absence of one or more of the features mentioned herein. In particular, the various embodiments and / or claims of the present application are not limited to the combination of features as mentioned in the embodiments.

Claims

1. A traffic light intelligent control method based on fiber grating sensor network, characterized in that: include: Acquiring detection data from each fiber Bragg grating (FBG) sensing line, wherein the fiber Bragg grating (FBG) sensing line is laid transversely along lanes at a selected traffic intersection, with each road being laid with three fiber Bragg grating (FBG) sensing lines parallel to the stop line; Determining the length range of the motor vehicle queue in each lane based on the detection data of each fiber Bragg grating sensor line; The working status of the corresponding traffic lights is controlled according to the length range of the motor vehicle queues in each lane.

2. The intelligent control method for traffic lights based on fiber grating sensor network according to claim 1, characterized in that: The three fiber Bragg grating sensing lines laid on the target road are respectively a first fiber optic sensing line, a second fiber optic sensing line, and a third fiber optic sensing line, which are respectively farther away from the traffic light. The determining of the length range of the motor vehicle queue in each lane based on the detection data of each fiber Bragg grating sensing line includes: Determining whether a vehicle is parked in an area corresponding to each fiber Bragg grating sensing line according to detection data of each fiber Bragg grating sensing line in the target lane; When it is determined that a vehicle is parked in the area corresponding to the first optical fiber sensing line and no vehicle is parked in the area corresponding to the second optical fiber sensing line, determining that the length of the motor vehicle queue in the target lane is less than a first interval length, where the first interval length is the distance between the first optical fiber sensing line and the second optical fiber sensing line; If it is determined that a vehicle is parked in the area corresponding to the first and second optical fiber sensing lines, and no vehicle is parked in the area corresponding to the third optical fiber sensing line, determining that the length of the motor vehicle queue in the target lane is greater than the first interval length and less than a second interval length, where the second interval length is the interval between the first and third optical fiber sensing lines; When it is determined that there are vehicles parked in the areas corresponding to the first optical fiber sensing line, the second optical fiber sensing line, and the third optical fiber sensing line, respectively, it is determined that the length of the motor vehicle queue in the target lane is greater than the second interval length.

3. The intelligent control method for traffic lights based on fiber grating sensor network according to claim 2, characterized in that: The controlling of the working state of the corresponding traffic light according to the length range of the motor vehicle queue in each lane includes: When it is determined that the length of the motor vehicle queue in the target lane is greater than the first interval length and less than the second interval length, controlling the extension of the green light time corresponding to the target lane according to a preset rule; When it is determined that the length of the motor vehicle queue in the target lane is greater than the second interval length, the green light corresponding to the target lane is controlled to be extended to a maximum duration.

4. The intelligent control method for traffic lights based on fiber grating sensor network according to claim 2, characterized in that: The controlling of the working state of the corresponding traffic light according to the length range of the motor vehicle queue in each lane includes: When it is determined that the length of the motor vehicle queue in the target lane is less than the first interval length, obtaining the length of the motor vehicle queue and the number of motor vehicles in the queue in the target lane based on camera visual data; When the length of the motor vehicle queue is less than a preset length threshold, the green light time corresponding to the target lane is shortened according to the number of motor vehicles in the queue.

5. The intelligent control method for traffic lights based on fiber grating sensor network according to claim 2, characterized in that: The controlling of the working state of the corresponding traffic light according to the length range of the motor vehicle queue in each lane includes: When it is determined that the length of the motor vehicle queue in the target lane is greater than the second interval length, obtaining the congestion situation of each upstream intersection based on the detection data of the fiber Bragg grating sensor line at each upstream intersection; Determining a target upstream intersection according to the congestion conditions of each upstream intersection; The ratio of the duration of the red light to the duration of the green light within the traffic light cycle time at the target upstream intersection is increased.

6. The intelligent control method for traffic lights based on fiber grating sensor network according to claim 1, characterized in that: The method further comprises: Get the weather data corresponding to the current moment; determining compensation parameters of traffic lights based on the meteorological data; The operating parameters of the traffic light are compensated according to the compensation parameters.

7. The intelligent control method for traffic lights based on fiber grating sensor network according to claim 1, characterized in that: The method further comprises: When the presence of an emergency vehicle is determined based on the detection data of each of the fiber Bragg grating sensor lines and the camera visual data, the traffic light corresponding to the direction of travel of the emergency vehicle is controlled to green, the duration of the green light is extended to the maximum duration, and the duration of the red light in the direction that conflicts with the direction of travel of the emergency vehicle is extended.

8. A traffic light intelligent control device based on fiber grating sensor network, characterized in that: include: an acquisition module for acquiring detection data of each fiber Bragg grating sensing line, wherein the fiber Bragg grating sensing line is laid transversely along the lane at the selected traffic intersection, and each road has three fiber Bragg grating sensing lines laid parallel to the stop line; a first processing module, configured to determine a length range of a queue of motor vehicles in each lane based on detection data of each fiber Bragg grating sensing line; The second processing module is used to control the working state of the corresponding traffic light according to the length range of the motor vehicle queue in each lane.

9. An electronic device, characterized in that: The invention comprises a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the intelligent control method for traffic lights based on a fiber Bragg grating sensor network as claimed in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored thereon, wherein when the computer program is executed by a processor, the intelligent control method for traffic lights based on a fiber Bragg grating sensor network as claimed in any one of claims 1 to 7 is implemented.

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