A traffic signal state monitoring method and a traffic signal system

Abstract

The application provides a traffic signal lamp state monitoring method and a traffic signal system, and relates to the technical field of intelligent traffic.The application collects current data of traffic signal lamps in each direction, extracts current characteristics of each traffic signal lamp, performs fault diagnosis, determines the operation state of each traffic signal lamp, and realizes automatic and accurate detection of the traffic signal lamp.Compared with the manual patrol and inspection mode, the application can detect faults through the current of the traffic signal lamp, shortens the fault discovery time length of the traffic signal lamp, and improves the patrol and inspection efficiency of the traffic signal system.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to a method for monitoring the status of traffic lights and a traffic signal system. Background Technology

[0002] Traffic lights play a crucial role in modern intelligent transportation systems, and their normal operation directly affects traffic safety and efficiency. Failure to promptly detect and address power outages, signal controller malfunctions, or signal light failures can lead to traffic congestion and accidents. Traffic lights at signalized intersections are diverse in type and function, including those for motor vehicles, non-motor vehicles, pedestrian crossings, directional indicators, lane markings, intersections, U-turns (at some intersections), and flashing warning lights (in special circumstances). These various types of traffic lights work together to form a complex intersection traffic signal control system. The different operating methods and applicable scenarios of different types of traffic lights make the operation and management of the entire traffic signal system extremely complex.

[0003] Currently, there is a method for detecting traffic light faults by detecting the effective value of the traffic light's current. However, for scenarios with a wide variety of traffic lights and variable signal durations, relying solely on detecting the effective value of the current can easily lead to misjudgments. For example, in scenarios with variable signal durations, the changes in the duration of red and green lights cause changes in the effective value of the traffic light's current. Using only the effective value of the current for threshold determination can result in misjudgments of the traffic light's status.

[0004] Given the potential for misjudgment when using the effective value of current for status determination, traffic light status detection requires the cooperation of local police officers and auxiliary police in patrolling and inspecting the traffic lights. However, this manual inspection method suffers from problems such as slow feedback, poor real-time performance, and high costs. Summary of the Invention

[0005] This invention provides a method for monitoring the status of traffic lights and a traffic signal system, which can achieve accurate detection of traffic lights and improve the inspection efficiency of the traffic signal system.

[0006] In a first aspect, the present invention provides a method for monitoring the status of traffic lights, applied to a monitoring terminal. The monitoring terminal is connected to a monitoring platform and current sensors of multiple traffic lights. The method includes: acquiring current sampling data of multiple traffic lights during the current time period, the current sampling data including the power supply current of the signal at each moment of the current time period and the main red light current in each direction; calculating the current characteristics of each traffic light during the current time period based on the current sampling data of multiple traffic lights during the current time period; performing fault diagnosis based on the current characteristics of each traffic light during the current time period to determine the operating status of each traffic light; if the operating status of any traffic light is a fault state, generating and sending a first reporting information to the monitoring platform based on the operating status, location information and occurrence time of that traffic light.

[0007] In one possible implementation, based on current sampling data of multiple traffic lights during the current time period, the current characteristics of each traffic light during the current time period are calculated, including: generating current sampling samples based on the current sampling data of each traffic light during the current time period, where each sample in the current sampling samples represents the current at any moment during the current time period; sorting the samples in the current sampling samples according to their size to obtain current sorted samples; splitting the current sorted samples to obtain open samples and closed samples; the open samples are the first T samples sorted from largest to smallest, and the closed samples are the first T samples sorted from smallest to largest; where T is a positive integer; calculating the open average based on the open samples; the open average is used to characterize the average current when the traffic light is on; calculating the closed average based on the closed samples; the closed average is used to characterize the average current when the traffic light is off; determining the maximum average current difference based on the open average and the closed average; and calculating the average current difference for each sliding time window based on the current sorted samples.

[0008] In one possible implementation, fault diagnosis is performed based on the current characteristics of each traffic light during the current time period to determine the operating status of each traffic light. This includes: determining whether the traffic light is working normally based on the maximum average current difference and / or the average current difference of each sliding time window; if the traffic light is working normally, the operating status of the traffic light is determined to be normal; and updating the normal opening current and normal closing current of the traffic light based on the average opening current, the average closing current, and the average current difference; if the traffic light is malfunctioning, the number of consecutive malfunctions of the traffic light is recorded; if the number of consecutive malfunctions of the traffic light is greater than a preset number, the operating status of the traffic light is determined to be faulty.

[0009] In one possible implementation, any current data in the current sampling data is obtained by: acquiring multiple sampling values ​​of the current sensor corresponding to the current data in the current time period; determining multiple acquisition voltages based on the multiple sampling values ​​of the current sensor corresponding to the current data in the current time period, the resolution of the acquisition device, and the reference voltage of the acquisition device; performing DC bias removal and sum of squares calculation based on the multiple acquisition voltages to obtain the voltage sum of squares; and performing root mean square calculation based on the voltage sum of squares, the sensing resistor, and the turns ratio of the current sensor to obtain the any current data.

[0010] In one possible implementation, after fault diagnosis based on the current characteristics of each traffic light during the current time period to determine the operating status of each traffic light, the process further includes: if the target traffic light is in a faulty state, generating an input vector based on the current characteristics of the target traffic light; the target traffic light is any one of multiple traffic lights; based on the input vector and a preset fault detection model, obtaining the fault type of the target traffic light; based on the fault type of the target traffic light and the location information of the target traffic light, determining the impact range when the target traffic light malfunctions; based on the fault type and the impact range, determining the repair time limit; based on the fault type, impact range, and repair time limit of the target traffic light, generating second reporting information; and sending the second reporting information to maintenance personnel.

[0011] Secondly, embodiments of the present invention provide a method for monitoring the status of traffic lights, applied to a monitoring platform. The monitoring platform connects to multiple monitoring terminals, and each monitoring terminal connects to current sensors of multiple traffic lights. The method includes: acquiring current sampling data of multiple traffic lights within the current time period reported by the multiple monitoring terminals, the current sampling data including the power supply current of the signal at each moment of the current time period and the main red light current in each direction; calculating the current characteristics of each traffic light in the current time period based on the current sampling data of multiple traffic lights; performing fault diagnosis based on the current characteristics of each traffic light in the current time period to determine the operating status of each traffic light; if the operating status of any traffic light is a fault state, generating an operation and maintenance instruction based on the operating status, location information, and occurrence time of that traffic light, the operation and maintenance instruction being used to instruct operation and maintenance personnel to repair that traffic light.

[0012] In one possible implementation, the method further includes: acquiring current sampling data of multiple traffic lights malfunctioning during historical periods, and the malfunction type of each traffic light; performing feature extraction based on the circuit sampling data of each traffic light malfunctioning to determine the current characteristics of each traffic light; generating multiple training samples based on the current characteristics of each traffic light and the malfunction type of each traffic light; and constructing a fault detection model based on the multiple training samples using a decision tree algorithm.

[0013] In one possible implementation, the current characteristics include the average current during the open period before and after the traffic light malfunctions, the average current during the closed period, the maximum average current difference, the average current difference across each sliding time window, the peak current, the valley current, the current fluctuation range, the current trend, the current cycle, and each harmonic current. Based on multiple training samples, a fault detection model is constructed using a decision tree algorithm, including: initializing the decision tree model and determining its constraints, such as the maximum depth of the decision tree, the maximum number of leaf nodes, and the minimum number of samples per node; traversing each current characteristic and calculating its Gini index; determining the root node of the decision tree model based on its Gini index; splitting the node based on the root node and multiple training samples to determine multiple subsets, each subset corresponding to a branch in the decision tree model; constructing the decision tree model based on the subsets and constraints; and pruning the constructed decision tree model to determine the fault detection model.

[0014] In one possible implementation, the method further includes: receiving first and / or second reporting information from each monitoring terminal; extracting current sampling data of each faulty traffic light based on the first and / or second reporting information from each monitoring terminal; extracting current characteristics of each faulty traffic light based on the current sampling data; determining the fault type of each faulty traffic light based on the current characteristics of each faulty traffic light and a fault detection model; determining whether there is a collective fault in the traffic signal system based on the fault type, location information, and occurrence time of each faulty traffic light; a collective fault indicates that the faults of multiple faulty traffic lights are caused by the same reason; if there is a collective fault in the traffic signal system, generating a fault analysis result based on the location information of the multiple faulty traffic lights that have experienced a collective fault, the fault analysis result including the fault type, location information, and suspected fault cause of the multiple faulty traffic lights that have experienced a collective fault; generating third reporting information based on the fault analysis result; and sending the third reporting information to maintenance personnel.

[0015] Thirdly, embodiments of the present invention provide a traffic light status monitoring device, applied to a monitoring terminal. The monitoring terminal is connected to a monitoring platform and current sensors of multiple traffic lights. The device includes: a communication module and a processing module. The communication module is used to acquire current sampling data of multiple traffic lights in the current time period. The current sampling data includes the power supply current of the signal at each moment in the current time period and the main red light current in each direction. The processing module is used to calculate the current characteristics of each traffic light in the current time period based on the current sampling data of multiple traffic lights in the current time period; perform fault diagnosis based on the current characteristics of each traffic light in the current time period to determine the operating status of each traffic light; if the operating status of any traffic light is a fault state, then generate and send a first reporting information to the monitoring platform based on the operating status, location information and occurrence time of that traffic light.

[0016] Fourthly, this invention provides a traffic light status monitoring device applied to a monitoring platform. The monitoring platform connects to multiple monitoring terminals, and each monitoring terminal connects to current sensors of multiple traffic lights. The device includes a communication module and a processing module. The communication module is used to acquire current sampling data of multiple traffic lights within the current time period reported by the multiple monitoring terminals. The current sampling data includes the power supply current of the traffic lights at each moment of the current time period and the main red light current in each direction. The processing module is used to calculate the current characteristics of each traffic light in the current time period based on the current sampling data of multiple traffic lights; perform fault diagnosis based on the current characteristics of each traffic light in the current time period to determine the operating status of each traffic light; if the operating status of any traffic light is a fault state, generate an operation and maintenance instruction based on the operating status, location information, and occurrence time of that traffic light. The operation and maintenance instruction is used to instruct operation and maintenance personnel to repair that traffic light.

[0017] Fifthly, embodiments of the present invention provide a traffic signal system, the traffic signal system including an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, the processor being configured to call and run the computer program stored in the memory to perform the method as described in any of the possible implementations of the first aspect above, or any of the possible implementations of the second aspect above.

[0018] In a sixth aspect, embodiments of the present invention provide a computer-readable storage medium storing a computer program, characterized in that, when executed by a processor, the computer program implements the steps of the method as described in the first aspect and any possible implementation thereof.

[0019] This invention provides a method for monitoring the status of traffic lights and a traffic signal system. By collecting current data from traffic lights in each direction and extracting the current characteristics of each light, this invention performs fault diagnosis to determine the operating status of each traffic light, achieving automatic and accurate detection of traffic lights. Compared to manual inspection, this invention can detect faults through traffic light current, shortening the fault detection time and improving the inspection efficiency of the traffic signal system. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the architecture of a smart traffic alarm linkage control system provided in an embodiment of the present invention; Figure 2 This is a flowchart illustrating a traffic light status monitoring method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a traffic signal light status monitoring device provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0022] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0023] In the description of this invention, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, "at least one" and "more than one" refer to two or more. The terms "first," "second," etc., do not limit the quantity or order of execution, and "first," "second," etc., do not necessarily imply differences.

[0024] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner to facilitate understanding.

[0025] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not limited to the steps or modules listed, but may optionally include other steps or modules not listed, or may optionally include other steps or modules inherent to such process, method, product, or device.

[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0027] As described in the background section, current traffic signal systems suffer from problems such as slow feedback, poor real-time performance, and high cost in traffic light status detection. To address these technical issues, such as... Figure 1 As shown in the figure, this embodiment of the invention provides an intelligent traffic alarm linkage control system. The system includes a monitoring terminal and a monitoring platform. By monitoring the current of multiple traffic lights in the traffic signal system in real time, intelligent inspection of the traffic signal system is achieved.

[0028] In this embodiment, the monitoring platform is connected to the monitoring terminals via a wireless network, such as a 4G wireless network. Each monitoring terminal is connected to the current sensors of multiple traffic lights. For example, each monitoring terminal can monitor multiple traffic lights at an intersection, such as traffic lights for motor vehicles, non-motor vehicles, pedestrian crossings, directional indicators, lanes, intersections, U-turns (at some intersections), and flashing warning lights (in special circumstances).

[0029] In some embodiments, the monitoring terminal is responsible for collecting the current data of traffic lights and transmitting the data to the monitoring platform via a wireless communication module. Regarding current acquisition, current transformers are installed on the traffic light lines to monitor the power supply current of the signal controller and the main red light current in each direction, based on the working principle of the traffic lights. Under normal operation, these currents are within a specific range, and there is a specific current change pattern when the yellow light flashes, which is used to determine the working status of the traffic lights. For example, the normal red light current should remain within a certain value range; if the current suddenly disappears or exceeds the range, it may indicate a red light malfunction.

[0030] The monitoring terminal's built-in wireless communication module supports multiple network standards and can communicate with the monitoring platform in real time. The terminal possesses stable wireless communication capabilities, ensuring timely and reliable data transmission. During data processing and transmission, the collected current data is first preprocessed, including filtering and amplification, to improve data quality. Then, the data is encapsulated and transmitted to the monitoring platform according to the set communication protocol.

[0031] In some embodiments, the monitoring platform primarily performs functions such as real-time monitoring, fault diagnosis, and data analysis of traffic light status. The real-time monitoring function receives data uploaded from monitoring terminals, processes and analyzes it, and displays the traffic light status in an intuitive interface. The fault diagnosis function determines the fault type based on a preset fault diagnosis algorithm and a current characteristic-based pattern recognition algorithm. Once a fault is detected, an alarm notification is immediately sent to maintenance personnel via methods such as WeChat and pop-ups, ensuring that maintenance personnel receive fault information promptly. The data analysis and report generation function performs in-depth analysis of historical data, generating detailed reports to provide decision-making support for traffic management departments. It can optimize maintenance plans and resource allocation based on the frequency and time distribution of traffic light faults.

[0032] based on Figure 1 The intelligent traffic alarm linkage control system shown is as follows: Figure 2 As shown, this embodiment of the invention provides a method for monitoring the status of traffic lights. Applied to a monitoring terminal, the monitoring terminal is connected to a monitoring platform and current sensors for multiple traffic lights. The method includes steps S101-S104.

[0033] S101. Obtain current sampling data of multiple traffic lights during the current time period.

[0034] In this embodiment of the application, the current sampling data includes the power supply current of the signal at each moment of the current time period and the main red light current in each direction.

[0035] For example, the signal power supply current is acquired using a single current acquisition channel, achieved by installing a current transformer on the power line. The main red light current is acquired using four current acquisition channels, also with current transformers, to accurately obtain the main red light current in each direction. Considering equipment size and installation convenience, for multi-signal light detection, the detection targets are rationally selected to avoid excessive current transformers leading to overly large equipment and installation difficulties. The monitoring terminal also has a 485 interface, which can expand the detection channels to adapt to different application scenarios.

[0036] For example, the built-in wireless communication module of the monitoring equipment can communicate with the monitoring platform in real time and promptly report detected faults. Data upload rules are set according to different situations, such as uploading an alarm and the status of all channels when no current flows through four channels for more than 10 seconds; uploading an alarm when the current value of a certain channel is 50% lower than the normal value for 10 minutes, etc. These rules ensure that the monitoring platform can promptly grasp changes in the status of traffic lights and effectively provide fault warnings.

[0037] For example, in this embodiment of the invention, after collecting the current sampling data of traffic lights, the current sampling data can be directly transmitted to the monitoring platform via a wireless network, and the monitoring platform can then perform analysis of the current sampling data, as shown in steps S301-S304.

[0038] In another exemplary embodiment of the invention, after collecting the current sampling data of the traffic lights, the monitoring terminal can directly analyze the current sampling data and send the analysis results, i.e., the first reporting information and / or the second reporting information, to the monitoring platform. See steps S102-S104 and S201-S206. After receiving the first reporting information and / or the second reporting information, the monitoring platform performs a summary analysis. See steps S501-S508.

[0039] As one possible implementation, any current data in the current sampling data can be obtained through steps A1-A4.

[0040] A1. Obtain multiple sample values ​​of the current sensor corresponding to any given current data in the current time period.

[0041] A2. Based on the multiple sampled values ​​of the current sensor corresponding to any current data in the current time period, the resolution of the acquisition device, and the reference voltage of the acquisition device, determine multiple acquisition voltages.

[0042] A3. Based on multiple acquired voltages, DC bias removal and sum of squares calculation are performed to obtain the sum of squares of voltages.

[0043] A4. Based on the sum of squares of the voltage, the turns ratio of the sensing resistor and the current sensor, perform root mean square calculation to obtain the current data for any given current.

[0044] For example, in this invention, the red light fault is mainly determined by detecting whether the current is abnormal. Therefore, the current detection stage is particularly important. The internal algorithms include filtering and root mean square (RMS) calculation.

[0045] This invention uses a digital-to-analog converter (ADC) to sample the output signal of a current transformer and convert the sampled value (digital quantity) into an actual voltage value. This process involves mapping between a reference voltage and the ADC resolution. Assuming the sampled value at a certain moment in the current time period is x, the reference voltage is Vref, and the maximum resolution of the ADC is Nmax (Nmax = 4095 for a 12-bit ADC), then the formula for calculating the voltage value Vout is: ; The above process converts the ADC value into a voltage value. The current value is then obtained by RMS calculation of the acquired sine wave.

[0046] In some embodiments, the DC bias is removed before calculating the RMS value. For example, the voltage value obtained by the above conversion for the i-th sampled signal is... DC bias is Then the AC component of the i-th sampled signal for: .

[0047] Sum of squares calculation: This invention squares and adds the AC components of each sampled value within the current time period to obtain the sum of squares. : .

[0048] Root mean square calculation: Where N is the number of sampling points in the current time period. The obtained RMS value is used to calculate the actual red light current value: R is the sensing resistor, K is the turns ratio of the current transformer, and A is the amplification factor of the operational amplifier in the digital-to-analog converter. Finally, an average value filter is used to obtain a stable current value.

[0049] S102. Based on the current sampling data of multiple traffic lights in the current time period, calculate the current characteristics of each traffic light in the current time period.

[0050] In some embodiments, the current characteristics include the average value when open, the average value when closed, the maximum average current difference, and the average current difference for each sliding time window during the current period.

[0051] In some embodiments, the current characteristics also include the open average value, the closed average value, the maximum average current difference, the average current difference of each sliding time window, the current peak value, the current valley value, the current fluctuation range, the current change trend, the current change period, and each harmonic current for a set period before and after the fault.

[0052] As one possible implementation, step S102 can be specifically implemented as steps S1021-S1027.

[0053] S1021. Generate current sampling samples based on the current sampling data of each traffic light in the current time period.

[0054] In some embodiments, each sample in the current sampling sample is the current at any time during the current time period.

[0055] S1022. Sort the samples in the current sampling sample according to their size to obtain the current sorted sample.

[0056] S1023. Split the current sorting samples to obtain open samples and closed samples.

[0057] In some embodiments, open samples are the first T samples sorted from largest to smallest, and closed samples are the first T samples sorted from smallest to largest; where T is a positive integer.

[0058] S1024. Based on the open sample, the open average value is calculated.

[0059] In some embodiments, the open average is used to characterize the average current when the traffic light is turned on.

[0060] S1025. Based on the closed samples, the average closed value is calculated.

[0061] In some embodiments, the closing average is used to characterize the average current when the traffic light is off.

[0062] S1026. Determine the maximum average current difference based on the open average and the closed average.

[0063] S1027. Based on the current sorting samples, perform sliding time window calculations to obtain the average current difference for each sliding time window.

[0064] S103. Based on the current characteristics of each traffic light in the current time period, perform fault diagnosis and determine the operating status of each traffic light.

[0065] As one possible implementation, step S103 can be specifically implemented as steps S1031-S1034.

[0066] S1031. Based on the maximum average current difference and / or the average current difference of each sliding time window, a threshold judgment is made to determine whether the traffic light is working properly.

[0067] S1032. If the traffic lights are working normally, the operating status of the traffic lights is determined to be normal; and the normal opening current and normal closing current of the traffic lights are updated based on the average value of opening and closing, as well as the average current difference.

[0068] S1033. If the traffic lights malfunction, record the number of times the traffic lights malfunction continuously.

[0069] S1034. If the number of times the traffic signal light malfunctions continuously exceeds the preset number, the traffic signal light's operating status is determined to be a fault state.

[0070] For example, embodiments of the present invention can employ a dynamic signal integrity analysis algorithm to analyze current sampling data and obtain the operating status of traffic lights. This algorithm detects current anomalies by dynamically analyzing signal integrity and is suitable for real-time monitoring and fault diagnosis of multi-channel current signals. The algorithm determines whether the signal is normal through sampling, sorting, averaging, and threshold comparison, and updates the threshold or reports a fault based on the detection results. The main process is as follows: Signal sampling: Sample the signal of each channel multiple times and store the sampled values.

[0071] Data sorting: Sort the sampled values ​​and extract the maximum and minimum values.

[0072] Threshold calculation: Based on the sorted data, calculate the normal value and the zero point value (alarm value).

[0073] Status judgment: Based on the comparison between the calculated value and the preset threshold, determine whether the signal status is normal or faulty.

[0074] Fault handling: If the signal status is abnormal, record the fault and trigger the reporting logic.

[0075] For example, (1) in the sampling stage, this embodiment of the invention can collect N samples for each channel c: ;in, Let be the i-th sampled current.

[0076] (2) Sorting and averaging: Sort the samples in ascending order.

[0077] and ; Calculate the average of the top and bottom T samples to obtain the open average. and closing average .

[0078] ; (3) Calculate the difference and calculate the open average. and closing average The difference, i.e., the maximum average current difference. . .

[0079] It should be noted that the maximum average current difference This represents the difference between the average current when the traffic light is on and the average current when it is off during the current time period, which is also the difference in average current when the traffic light is on and off. The maximum average current difference... A value greater than or equal to the threshold indicates a large difference in the maximum average current, meaning a large difference in the average current when the traffic light is on and off, which indicates that the traffic light is working normally.

[0080] When the maximum average current difference If the value is less than the threshold, it means that the difference in the maximum average current is small, that is, the difference in the average current when the traffic light is on and off is small. This indicates that the current when the traffic light is on is similar to the current when it is off, that the traffic light is in a normally open or normally closed state, and that the traffic light is malfunctioning.

[0081] (4) Threshold comparison to determine whether the difference exceeds the threshold.

[0082] like If the condition is met, update the normal value and the zero value. Otherwise, increment the fault count and report the fault.

[0083] Where R represents the judgment error, and L is the judgment threshold. For example, R can be 0.7, representing the maximum average current difference. If the current difference is 0.7 times greater than the judgment threshold, it indicates a large current difference between the traffic light's on and off states, suggesting the traffic light is functioning normally. Setting a judgment error can reduce the probability of false judgments by traffic lights and improve the accuracy of traffic light fault detection.

[0084] For example, the judgment threshold L can be determined and updated based on normal values ​​and zero values. For instance, the difference between the normal value and the zero value can be directly determined as the judgment threshold. Alternatively, 0.5 times or 0.6 times the difference between the normal value and the zero value can be directly determined as the judgment threshold.

[0085] Another example is that the judgment threshold can also be determined and updated based on the open average and the closed average. For instance, the difference between the open average and the closed average can be directly used as the judgment threshold. Alternatively, 0.5 times or 0.6 times the difference between the open average and the closed average can be directly used as the judgment threshold.

[0086] Another example is that, in an embodiment of the present invention, the normal value and the zero value can be updated based on the open average value and the closed average value.

[0087] For example, after a traffic light is replaced, the normal and zero values ​​of the newly replaced traffic light will change compared to the original traffic light. Correspondingly, the detection threshold for that traffic light in the monitoring terminal or platform should also be changed accordingly to prevent misjudgments and improve detection accuracy.

[0088] For example, after a traffic light has been in use for a period of time, its normal operating current may change, possibly increasing or decreasing slightly. This invention adjusts the judgment threshold based on the average value when the traffic light is on and the average value when it is off, which can reduce the probability of misjudgment caused by changes in the traffic light's operating conditions and improve the overall accuracy of traffic light misjudgment.

[0089] For example, embodiments of the present invention can also set upper and lower limits for the judgment threshold based on the factory settings information of the traffic light. When the average current of the traffic light exceeds the upper or lower limit, it indicates that the traffic light may be faulty and further judgment is required. This can prevent errors caused by continuous adjustment of the judgment threshold. That is, when the judgment threshold exceeds the normal range, the judgment threshold is limited and corrected by the upper and lower limits.

[0090] In some embodiments, if This indicates that the traffic light is working properly and updates the normal and zero values.

[0091] In some embodiments, if This indicates that the traffic light is malfunctioning and requires continuous counting of traffic light faults to generate the first reporting information and report it to the monitoring platform.

[0092] (5) Update the normal value and the zero value. In this embodiment of the invention, the normal value and the zero value can be updated according to the following formula.

[0093] ; Among them, normal value This indicates the operating current of the traffic light when it is normally turned on; zero value. This indicates the operating current when the traffic light is normally off.

[0094] (6) Fault detection, if If the signal fails K times consecutively, it indicates that the traffic light is in a faulty state and its working status needs to be reported.

[0095] (7) Adaptive threshold update: In this embodiment of the invention, an exponentially weighted moving average (EWMA) can also be introduced to adapt to changes in the working signal of the traffic lights.

[0096] ; in, As a smoothing factor, . This represents the normal start-up current during the (k+1)th adjustment cycle. This represents the normal shutdown current during the (k+1)th adjustment cycle. This represents the normal start-up current during the k-th adjustment cycle. This represents the normal shutdown current during the kth adjustment cycle. To turn off the average value, Enable the average value. Maximum average current difference To determine the error.

[0097] (8) Sliding window fault detection: In this embodiment of the invention, the average difference of the sliding window can be used to detect faults.

[0098] like If the signal is malfunctioning, it indicates that the traffic light is in a faulty state and the fault needs to be reported.

[0099] in, .

[0100] This represents the maximum average current difference in the i-th time window. In other words, for the current sorting samples in step S1022, a sliding time window is applied to the current sorting samples to obtain multiple time windows. This represents the difference between the average current in the i-th time window and the average current in the (i+1)-th time window. This represents the average of the maximum average current differences over K time windows. R represents the judgment error. L represents the judgment threshold.

[0101] This invention can improve the accuracy of traffic light fault detection by calculating the average current difference after dividing the current of the current period into sliding time windows and making a judgment, thereby avoiding the influence of harmonics in traffic light faults.

[0102] For example, in a scenario where traffic lights are flashing abnormally, judging the traffic lights as working normally based on the maximum average current difference would be a misjudgment. However, detecting the fault by using the average difference over a sliding time window can determine that the traffic lights are in an abnormal state, thus improving the accuracy of fault detection.

[0103] S104. If any traffic light is in a fault state, then based on the operating status, location information and occurrence time of that traffic light, generate and send the first reporting information to the monitoring platform.

[0104] This invention provides a method for monitoring the status of traffic lights. By collecting current data from traffic lights in each direction and extracting the current characteristics of each traffic light, fault diagnosis is performed to determine the operating status of each traffic light, achieving automatic and accurate detection of traffic lights. Compared to manual inspection, this invention can detect faults through traffic light current, shortening the fault detection time and improving the inspection efficiency of the traffic signal system.

[0105] It should be noted that the extraction and analysis of traffic light current characteristics can be performed by either the monitoring terminal or the monitoring platform. When performed by the monitoring terminal, the data processing load on the monitoring platform is reduced, allowing for faster response and improved processing capacity and speed. When performed by the monitoring platform, it can aggregate the overall fault information of multiple traffic lights, perform a comprehensive diagnosis of the traffic signal system, identify common faults, and improve the diagnostic efficiency and accuracy of the traffic signal system.

[0106] Optionally, the traffic light status monitoring method provided in this embodiment of the invention further includes steps S201-S206 after step S103.

[0107] S201. If the target signal light is in a fault state, an input vector is generated based on the current characteristics of the target signal light.

[0108] In some embodiments, the target traffic light is any one of a plurality of traffic lights.

[0109] S202. Based on the input vector and the preset fault detection model, the fault type of the target traffic light is obtained.

[0110] In some embodiments, fault types include indicator lights that are always on, indicator lights that are always off, and abnormal flashing.

[0111] In some embodiments, the fault types also include uncontrollable traffic lights and errors in the lighting mechanism of traffic lights in different directions.

[0112] Accordingly, the present invention can also, in real time, form an input vector based on the current characteristics of the target traffic light and the current characteristics of traffic lights with different directions from the target traffic light, in order to detect the control mode and lighting mechanism of the traffic light.

[0113] S203. Based on the fault type of the target traffic light and the location information of the target traffic light, determine the impact range when the target traffic light malfunctions.

[0114] For example, the location information of the target traffic light can be a pedestrian crossing traffic light, a motor vehicle lane traffic light, a U-turn lane traffic light, etc.

[0115] Alternatively, the location information of the target traffic light can be divided according to traffic flow, such as traffic lights with high traffic flow, like those in the city center; and traffic lights with low traffic flow, like those in the suburbs.

[0116] The impact range of traffic lights varies depending on their location and the type of malfunction. This invention can classify the impact range based on the malfunction type and location information to determine the impact level of the target traffic light malfunction. For example, it can classify it into Level 1, Level 2, and Level 3 impact levels.

[0117] S204. Determine the repair timeframe based on the fault type and scope of impact.

[0118] For example, embodiments of the present invention can determine the repair time limit based on the impact level. For instance, the repair time limit for a level 1 impact can be 1 day, the repair time limit for a level 2 impact can be 8 hours, and the repair time limit for a level 3 impact can be 2 hours.

[0119] S205. Based on the fault type, impact range, and repair time limit of the target traffic light, generate the second reporting information.

[0120] S206. Send the second reporting information to the maintenance personnel.

[0121] Thus, embodiments of the present invention can analyze current characteristics through a fault detection model to automatically determine the possible fault types of traffic lights, facilitating maintenance personnel to repair and improving the maintenance efficiency of traffic signal systems.

[0122] based on Figure 1 The intelligent traffic alarm linkage control system shown in this invention also provides a method for monitoring the status of traffic lights. Applied to a monitoring platform, the platform connects to multiple monitoring terminals, and each monitoring terminal connects to multiple current sensors for traffic lights. The method includes steps S301-S304.

[0123] S301. Obtain current sampling data of multiple traffic lights within the current time period reported by multiple monitoring terminals.

[0124] In some embodiments, the current sampling data includes the power supply current of the signal at each moment of the current time period and the main red light current in each direction.

[0125] For example, after the monitoring terminal detects the sampling current of each current sensor, it can directly send the sampling current to the monitoring platform for analysis.

[0126] S302. Based on the current sampling data of multiple traffic lights, calculate the current characteristics of each traffic light in the current time period.

[0127] For example, the monitoring platform can perform the method as in steps S1021-S1027 to calculate the current characteristics of each traffic light in the current time period.

[0128] S303. Based on the current characteristics of each traffic light during the current period, perform fault diagnosis and determine the operating status of each traffic light.

[0129] For example, the monitoring platform can execute the method as described in steps S1031-S1034 to determine the operating status of each traffic light.

[0130] S304. If any traffic light is in a fault state, then a maintenance instruction is generated based on the operating status, location information, and occurrence time of that traffic light.

[0131] In this embodiment of the application, the maintenance instruction is used to instruct maintenance personnel to inspect any traffic light.

[0132] This invention provides a method for monitoring the status of traffic lights. By collecting current data from traffic lights in each direction and extracting the current characteristics of each traffic light, fault diagnosis is performed to determine the operating status of each traffic light, achieving automatic and accurate detection of traffic lights. Compared to manual inspection, this invention can detect faults through traffic light current, shortening the fault detection time and improving the inspection efficiency of the traffic signal system.

[0133] Optionally, the traffic light status monitoring method provided in this embodiment of the invention further includes steps S401-S406.

[0134] S401. Obtain current sampling data when multiple traffic lights malfunction during a historical period, as well as the malfunction type of each traffic light. S402. Based on the circuit sampling data when each traffic light malfunctions, feature extraction is performed to determine the current characteristics of each traffic light.

[0135] In some embodiments, the current characteristics include the average value of the traffic light when it is open and the average value when it is closed for a set period before and after the traffic light malfunctions, the maximum average current difference, the average current difference for each sliding time window, the peak current, the valley current, the current fluctuation range, the current change trend, the current change period, and each harmonic current.

[0136] S403. Based on the current characteristics of each traffic light and the fault type of each traffic light, generate multiple training samples. S404. Based on multiple training samples, a fault detection model is constructed using the decision tree algorithm.

[0137] As one possible implementation, step S404 can be specifically implemented as steps B1-B5.

[0138] B1. Initialize the decision tree model and determine its constraints, including the maximum depth of the decision tree, the maximum number of leaf nodes, and the minimum number of samples per node; traverse each current feature and calculate the Gini index for each current feature. B2. Determine the root node of the decision tree model based on the Gini index of each current characteristic; B3. Based on the root node of the decision tree model and multiple training samples, split the node to determine multiple subsets, each subset corresponding to a branch in the decision tree model. B4. Construct a decision tree model based on multiple subsets and constraints; B5. Prune the constructed decision tree model to determine the fault detection model.

[0139] Thus, embodiments of the present invention can improve the efficiency and accuracy of traffic light fault detection by constructing a fault detection model to detect the operating status of traffic lights.

[0140] Furthermore, decision tree models can address traffic light fault diagnosis with minimal hard drive and memory usage, making them suitable for scenarios like monitoring terminals where both hard drive space and memory are limited. This allows the monitoring platform to build the fault detection model, which is then run by the monitoring terminal, reducing the platform's memory overhead and improving its processing capabilities.

[0141] Optionally, the traffic light status monitoring method provided in this embodiment of the invention further includes, after step S404: the monitoring platform sends a model file of the fault detection model to the monitoring terminal, so as to instruct the monitoring terminal to detect the traffic light based on the fault detection model.

[0142] like Figure 1 As shown, the intelligent traffic alarm linkage control system may also include a sub-control platform, which is connected to the monitoring platform to perform processing tasks assigned by the monitoring platform, such as the current monitoring task of traffic lights in a certain area, thereby reducing the pressure on the monitoring platform.

[0143] Optionally, the traffic light status monitoring method provided in this embodiment of the invention further includes steps S501-S508.

[0144] S501, Receive the first and / or second reporting information transmitted back from each monitoring terminal.

[0145] S502. Based on the first and / or second reporting information returned by each monitoring terminal, extract the current sampling data of each fault indicator light.

[0146] S503. Based on the current sampling data of each fault indicator light, extract the current characteristics of each fault indicator light.

[0147] S504. Based on the current characteristics of each fault indicator light and the fault detection model, determine the fault type of each fault indicator light.

[0148] For example, in an embodiment of the present invention, the current characteristics of any fault indicator light can be directly used as an input vector to input into the fault detection model to obtain the fault type.

[0149] Another exemplary embodiment of the present invention can determine the correlation between various fault indicator lights, and based on the correlation, identify several groups of related fault indicator lights. Based on the current characteristics of each group of related fault indicator lights, an input vector is constructed and input into the fault detection model to obtain the fault type, thereby achieving comprehensive analysis of multiple fault indicator lights.

[0150] S505. Based on the fault type, location information, and occurrence time of each faulty signal light, determine whether there is a collective fault in the traffic signal system.

[0151] In some embodiments, a collective fault indicates that the faults of multiple fault indicator lights are caused by the same reason.

[0152] For example, if multiple faulty traffic lights all indicate that the fault type is "normally closed," it may be due to a power outage. If multiple faulty traffic lights at an intersection are either normally open or flashing abnormally, it may be due to a traffic signal malfunction.

[0153] S506. If there is a collective fault in the traffic signal system, a fault analysis result is generated based on the location information of the multiple faulty traffic lights that have experienced the collective fault.

[0154] In some embodiments, the fault analysis results include the fault type, location information, and suspected fault cause of multiple fault indicator lights that have experienced a collective fault.

[0155] In some embodiments, suspected causes of failure include power outages and signal malfunctions.

[0156] S507. Based on the fault analysis results, generate third reporting information.

[0157] In some embodiments, the third reported information includes the fault type, location information, and cause of the fault signal light.

[0158] S508, Send the third reporting information to the maintenance personnel.

[0159] Thus, embodiments of the present invention can comprehensively analyze multiple faulty traffic lights through a monitoring platform, facilitating maintenance personnel in repairs and improving the efficiency of repairs when traffic signal systems malfunction.

[0160] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0161] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0162] Figure 3 A schematic diagram of a traffic signal light status monitoring device according to an embodiment of the present invention is shown. The status monitoring device 600 includes a communication module 601 and a processing module 602.

[0163] When the status detection device 600 is applied to the monitoring terminal, the communication module 601 and the processing module 602 perform the following steps.

[0164] The communication module 601 is used to acquire current sampling data of multiple traffic lights during the current time period. The current sampling data includes the power supply current of the signal lights at each moment during the current time period and the main red light current in each direction.

[0165] The processing module 602 is used to calculate the current characteristics of each traffic light in the current time period based on the current sampling data of multiple traffic lights in the current time period; to perform fault diagnosis based on the current characteristics of each traffic light in the current time period and determine the operating status of each traffic light; if the operating status of any traffic light is a fault state, then based on the operating status, location information and occurrence time of any traffic light, a first reporting information is generated and sent to the monitoring platform.

[0166] When the status detection device 600 is applied to the monitoring platform, the communication module 601 and the processing module 602 perform the following steps.

[0167] The communication module 601 is used to acquire current sampling data of multiple traffic lights during the current time period reported by multiple monitoring terminals. The current sampling data includes the power supply current of the signal lights at each moment of the current time period and the main red light current in each direction.

[0168] The processing module 602 is used to calculate the current characteristics of each traffic light in the current time period based on the current sampling data of multiple traffic lights; to perform fault diagnosis based on the current characteristics of each traffic light in the current time period and determine the operating status of each traffic light; if the operating status of any traffic light is a fault state, then based on the operating status, location information and occurrence time of any traffic light, the operation and maintenance instruction is generated, which is used to instruct operation and maintenance personnel to repair any traffic light.

[0169] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Figure 4 As shown, the electronic device 700 includes: a processor 701, a memory 702, and a computer program 703 stored in the memory 702 and executable on the processor 701. When the processor 701 executes the computer program 703, it implements the steps in the above-described method embodiments, for example... Figure 2The steps S101-S104 are shown. Alternatively, when the processor 701 executes the computer program 703, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 3 The functions of the communication module 601 and the processing module 602 shown are illustrated.

[0170] For example, the computer program 703 can be divided into one or more modules / units, which are stored in the memory 702 and executed by the processor 701 to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 703 in the electronic device 700. For example, the computer program 703 can be divided into... Figure 3 The communication module 601 and the processing module 602 are shown.

[0171] The processor 701 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0172] The memory 702 can be an internal storage unit of the electronic device 700, such as a hard disk or memory of the electronic device 700. The memory 702 can also be an external storage device of the electronic device 700, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 700. Furthermore, the memory 702 can include both internal and external storage units of the electronic device 700. The memory 702 is used to store the computer program and other programs and data required by the terminal. The memory 702 can also be used to temporarily store data that has been output or will be output.

[0173] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for monitoring the status of traffic lights, characterized in that, The method, applied to a monitoring terminal connected to a monitoring platform and current sensors of multiple traffic lights, includes: Acquire current sampling data of multiple traffic lights during the current time period, including the power supply current of the signal controller at each moment of the current time period and the main red light current in each direction; Based on the current sampling data of the multiple traffic lights in the current time period, the current characteristics of each traffic light in the current time period are calculated; the current characteristics include the average value when the lights are on, the average value when the lights are off, and the maximum average current difference in the current time period. Based on the current characteristics of each traffic light in the current time period, fault diagnosis is performed to determine the operating status of each traffic light. Based on the maximum average current difference, a threshold judgment is made to determine whether the traffic light is working properly; when the maximum average current difference is greater than or equal to the threshold, the traffic light is working properly; when the maximum average current difference is less than the threshold, the traffic light is malfunctioning. The threshold value is determined and updated based on the normal value and the zero value, or based on the average value when the traffic light is on and the average value when it is off; the normal value is the operating current when the traffic light is on normally; the zero value is the operating current when the traffic light is off normally. If any traffic light is in a fault state, then based on the operating status, location information and occurrence time of that traffic light, a first reporting message is generated and sent to the monitoring platform. Any current data in the current sampling data is obtained as follows: multiple sampling values ​​of the current sensor corresponding to the current data in the current time period are obtained; based on the multiple sampling values ​​of the current sensor corresponding to the current data in the current time period, the resolution of the acquisition device, and the reference voltage of the acquisition device, multiple acquisition voltages are determined; based on the multiple acquisition voltages, DC bias removal and sum of squares calculation are performed to obtain the voltage sum of squares; based on the voltage sum of squares, the detection resistor, and the turns ratio of the current sensor, the root mean square calculation is performed to obtain the any current data. The calculation of the current characteristics of each traffic light during the current time period based on the current sampling data of the multiple traffic lights includes: Based on the current sampling data of each traffic light in the current time period, a current sampling sample is generated, wherein each sample in the current sampling sample is the current at any time in the current time period; Sort the samples in the current sampling sample according to their size to obtain the current sorted sample; The current sorting samples are split into open samples and closed samples; the open samples are the first T samples when sorted from largest to smallest, and the closed samples are the first T samples when sorted from smallest to largest; where T is a positive integer; Based on the open samples, the open average value is calculated; the open average value is used to characterize the average current when the traffic light is turned on; Based on the closed samples, the average closed value is calculated; the average closed value is used to characterize the average current when the traffic light is off; The maximum average current difference is determined based on the open average value and the closed average value.

2. The traffic signal light status monitoring method according to claim 1, characterized in that, The process of fault diagnosis based on the current characteristics of each traffic light during the current time period, and determining the operating status of each traffic light, includes: Based on the maximum average current difference, a threshold judgment is performed to determine whether the traffic lights are working properly. If the traffic light is working properly, then the operating status of the traffic light is determined to be normal; and based on the average value of opening and closing, as well as the average current difference, the normal opening current and normal closing current of the traffic light are updated. If the traffic light malfunctions, record the number of times the traffic light malfunctions continuously. If the number of times the traffic light malfunctions continuously exceeds a preset number, then the traffic light is determined to be in a fault state.

3. The method for monitoring the status of traffic lights according to any one of claims 1 to 2, characterized in that, After determining the operating status of each traffic light by performing fault diagnosis based on the current characteristics of each traffic light in the current time period, the method further includes: If the target traffic light is in a faulty state, an input vector is generated based on the current characteristics of the target traffic light; the target traffic light is any one of the plurality of traffic lights. Based on the input vector and the preset fault detection model, the fault type of the target traffic light is obtained; Based on the fault type of the target traffic light and the location information of the target traffic light, the impact range when the target traffic light malfunctions is determined; Based on the fault type and the scope of impact, a repair timeframe is determined; Based on the fault type, impact range, and repair time limit of the target traffic light, a second reporting information is generated; Send the second reporting information to the operations and maintenance personnel.

4. A method for monitoring the status of traffic lights, characterized in that, The method is applied to a monitoring platform that connects multiple monitoring terminals, each monitoring terminal being connected to multiple current sensors for traffic lights. The system acquires current sampling data of multiple traffic lights within the current time period reported by multiple monitoring terminals. The current sampling data includes the power supply current of the signal controller at each moment of the current time period and the main red light current in each direction. Based on the current sampling data of the multiple traffic lights, the current characteristics of each traffic light in the current time period are calculated; the current characteristics include the average value when the light is on, the average value when the light is off, and the maximum average current difference in the current time period. Based on the current characteristics of each traffic light in the current time period, fault diagnosis is performed to determine the operating status of each traffic light. Based on the maximum average current difference, a threshold judgment is made to determine whether the traffic light is working properly; when the maximum average current difference is greater than or equal to the threshold, the traffic light is working properly; when the maximum average current difference is less than the threshold, the traffic light is malfunctioning. The threshold value is determined and updated based on the normal value and the zero value, or based on the average value when the traffic light is on and the average value when it is off; the normal value is the operating current when the traffic light is on normally; the zero value is the operating current when the traffic light is off normally. If any traffic light is in a fault state, then based on the operating status, location information and occurrence time of that traffic light, a first reporting message is generated and sent to the monitoring platform. Any current data in the current sampling data is obtained as follows: multiple sampling values ​​of the current sensor corresponding to the current data in the current time period are obtained; based on the multiple sampling values ​​of the current sensor corresponding to the current data in the current time period, the resolution of the acquisition device, and the reference voltage of the acquisition device, multiple acquisition voltages are determined; based on the multiple acquisition voltages, DC bias removal and sum of squares calculation are performed to obtain the voltage sum of squares; based on the voltage sum of squares, the detection resistor, and the turns ratio of the current sensor, the root mean square calculation is performed to obtain the any current data. The calculation of the current characteristics of each traffic light during the current time period based on the current sampling data of the multiple traffic lights includes: Based on the current sampling data of each traffic light in the current time period, a current sampling sample is generated, wherein each sample in the current sampling sample is the current at any time in the current time period; Sort the samples in the current sampling sample according to their size to obtain the current sorted sample; The current sorting samples are split into open samples and closed samples; the open samples are the first T samples when sorted from largest to smallest, and the closed samples are the first T samples when sorted from smallest to largest; where T is a positive integer; Based on the open samples, the open average value is calculated; the open average value is used to characterize the average current when the traffic light is turned on; Based on the closed samples, the average closed value is calculated; the average closed value is used to characterize the average current when the traffic light is off; The maximum average current difference is determined based on the open average value and the closed average value.

5. The traffic signal light status monitoring method according to claim 4, characterized in that, The method further includes: Acquire current sampling data when multiple traffic lights malfunctioned during historical periods, as well as the malfunction type of each traffic light; Feature extraction is performed based on the current sampling data when each traffic light malfunctions to determine the current characteristics of each traffic light. Multiple training samples are generated based on the current characteristics of each traffic light and the fault type of each traffic light. Based on the multiple training samples, a fault detection model is constructed using the decision tree algorithm.

6. The traffic signal light status monitoring method according to claim 5, characterized in that, The fault detection model is constructed based on the multiple training samples using a decision tree algorithm, including: Initialize the decision tree model and determine its constraints, including the maximum depth of the decision tree, the maximum number of leaf nodes, and the minimum number of samples per node; traverse each current feature and calculate the Gini index for each current feature. The root node of the decision tree model is determined based on the Gini index of each current characteristic. Based on the root node of the decision tree model and the multiple training samples, the node is split to determine multiple subsets, each subset corresponding to a branch in the decision tree model. Based on the multiple subsets and the constraints, a decision tree model is constructed; The constructed decision tree model is pruned to determine the fault detection model.

7. A traffic signal system, characterized in that, The traffic signal system includes an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor is used to call and run the computer program stored in the memory to perform the method as claimed in any one of claims 1 to 3, or any one of claims 4 to 6.

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