An intelligent control method, system and tunnel lamp for tunnel lamps

Abstract

The present invention relates to the technical field of lighting control, and specifically to an intelligent control method, system and tunnel light for tunnel lights, including the following steps: collecting in real time the operating parameters and the number of faults of each type of lamp in the tunnel, comparing the operating parameters of each type of lamp with the corresponding preset risk threshold respectively, and generating a preliminary analysis result of the operating risk of the lamp. In the present invention, by collecting in real time the operating parameters and the number of faults of the tunnel lamps and combining the comparative analysis of the preset risk threshold, the operating state of the lamps can be quantitatively risk-assessed and classified. This dynamic comprehensive probability calculation mode enables the potential problems of the lamps to be accurately predicted, avoiding the omission of potential hazards that may be caused by the static judgment of a single parameter. On this basis, based on the operating state and brightness load of the lamps, load balancing is carried out, and through the prediction of the brightness trend change, the accuracy and efficiency of the dynamic adjustment of the lamp brightness are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting control, and in particular to a tunnel lamp intelligent control method, system and tunnel lamp. Background Art

[0002] The intelligent control method of tunnel lights is an intelligent control technology designed specifically for tunnel lighting needs. By integrating sensors, control systems and communication technologies, the light brightness is dynamically adjusted according to the environmental conditions inside and outside the tunnel (such as light intensity, traffic volume, etc.), optimizing energy consumption and improving driving safety, while also ensuring uniform lighting inside the tunnel.

[0003] Existing technologies have difficulty in timely detecting potential problems in terms of lamp failure risk monitoring, which may lead to abnormal accumulation of lamp operating status, further affecting the overall operating efficiency of the system. For example, the existing model fails to conduct real-time evaluation based on the deviation of lamp operating parameters, which may lead to problems that are not warned, increasing equipment damage and subsequent maintenance costs. There are also deficiencies in the adaptive adjustment to changes in vehicle speed and traffic dynamics in the tunnel. In this case, the lighting inside the tunnel may not match the actual operating needs of the vehicle, increasing driving safety hazards. In addition, the method of handling the difference in light intensity inside and outside the tunnel is relatively limited. When faced with frequent changes in ambient light intensity, it is difficult to achieve a smooth transition of lighting at the entrance and exit of the tunnel, which can easily cause visual adaptation difficulties for drivers and affect driving comfort and safety. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a tunnel lamp intelligent control method, system and tunnel lamp.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: a tunnel lamp intelligent control method, comprising the following steps:

[0006] S1: Collect the operating parameters and fault counts of each type of lamp in the tunnel in real time, compare the operating parameters of each type of lamp with the corresponding preset risk threshold, and generate preliminary analysis results of lamp operation risks;

[0007] S2: calculating the comprehensive probability of lamp failure according to the lamp operation parameters observed in the preliminary analysis result of the lamp operation risk, dividing the risk level corresponding to the lamp according to the comprehensive probability of lamp failure, and generating a lamp operation status classification result;

[0008] S3: According to the risk level of the target luminaire in the classification result of the luminaire operation status, obtain the brightness load values of the target luminaire and its adjacent luminaires and perform load balancing processing. By predicting the future offset trend of the brightness of the target luminaire after load balancing processing, dynamically optimize the brightness distribution of the target luminaire and its adjacent luminaires according to the future offset trend, and generate the luminaire load balancing result in the tunnel;

[0009] S4: Real-time monitor the vehicle speed of the vehicle driving in the tunnel at each time point, compare the vehicle speed with the preset speed threshold range, adjust the luminaire load balancing result in the tunnel according to the comparison result, and optimize the output effect of the luminaires after brightness distribution, and generate the dynamic safety control result of the tunnel lights;

[0010] S5: Real-time monitor the external ambient light intensity value of the tunnel, analyze the difference between the brightness of the luminaires at the tunnel entrance and exit after optimizing the brightness distribution in the luminaire load balancing result in the tunnel and the external ambient light intensity value of the tunnel, obtain the light intensity difference information inside and outside the tunnel, compare the light intensity difference information inside and outside the tunnel with the preset light intensity requirement threshold range, and adjust the brightness of the luminaires at the tunnel entrance and exit according to the comparison result, and generate the dynamic adjustment result of the light intensity inside and outside the tunnel.

[0011] As a further solution of the present invention, the obtaining step of the preliminary analysis result of the luminaire operation risk is specifically as follows:

[0012] S101: Obtain the luminaire operation parameters and the number of faults in the tunnel. The luminaire operation parameters include the cumulative operation time, operation temperature, voltage fluctuation, and brightness load. Compare the luminaire operation parameters with the corresponding preset risk thresholds respectively to generate the operation parameter comparison result;

[0013] S102: Obtain the deviation value between the luminaire operation parameter and the corresponding preset risk threshold from the operation parameter comparison result. Judge whether the current deviation exceeds the preset risk threshold according to the deviation value, and mark the luminaire operation parameter that exceeds the preset risk threshold as the risk state to obtain the preliminary analysis result of the luminaire operation risk.

[0014] As a further solution of the present invention, the obtaining step of the classification result of the luminaire operation status is specifically as follows:

[0015] S201: According to the preliminary analysis result of the luminaire operation risk, take the probability that each type of luminaire operation parameter exceeds the preset risk threshold under the condition of luminaire failure and under the condition of no luminaire failure as the conditional probability, take the probability of luminaire failure and the probability of no luminaire failure obtained according to the number of luminaire faults as the prior probability, combine the conditional probability and the prior probability, and through the Bayesian model, use the formula:

[0016] ;

[0017] Based on the set of observed operating parameters of the lamps Calculate the occurrence of lamp failures of the combined probability ;

[0018] Wherein, represents the probability that the category of lamp operating parameters exceeds the preset risk threshold under the condition that the lamp fails , represents the probability that the lamp fails , represents the overall probability that the category of lamp operating parameters exceeds the preset risk threshold. The overall probability includes the probabilities of exceeding the preset risk threshold in both cases where the lamp fails and does not fail. The calculation formula is: , is the probability that the category of lamp operating parameters exceeds the preset risk threshold under the condition that the lamp does not fail , is the probability that the lamp does not fail . The calculation formula is: , represents the item of the weight factor of the lamp operating parameters is the total number of lamp operating parameters;

[0019] S202: According to the combined probability of the occurrence of the lamp failure, analyze the operating state of the current lamp and determine the risk level according to the operating state, and generate a classification result of the lamp operating state.

[0020] As a further solution of the present invention, the step of obtaining the lamp load balance result in the tunnel is specifically as follows:

[0021] S301: Based on the classification result of the lamp operating state, obtain the risk level of the target lamp and the brightness values of the target lamp and its adjacent lamps, and perform corresponding brightness compensation on the target lamp and its adjacent lamps according to different risk levels to generate a preliminary load balance result;

[0022] S302: Based on the preliminary load balance result, through the Lagrange interpolation method, use the formula:

[0023] ;

[0024] Calculate the brightness value of the target lamp at the future moment after the preliminary load balance processing , and obtain the future offset trend of the brightness of the target lamp;

[0025] Among them, is the polynomial order of the brightness value of the target lamp, is the brightness value of the target lamp at the th time point in the preliminary load balancing result, is the future time point to be predicted set according to the preliminary load balancing result, is related to the brightness value corresponding to the th time point, is the time point used to construct the Lagrange basis function, is the iteration index of the Lagrange basis function, and construct the interpolation polynomial, is the Lagrange basis function part, indicating the iteration index for traversing all Lagrange basis functions , indicates that the construction of the current Lagrange basis function needs to exclude the th time point corresponding to the brightness value , indicates the value range of to ;

[0026] S303: According to the future offset trend of the brightness of the target lamp, referring to the preset trend change range, analyze whether the brightness change of the target lamp is obvious, and dynamically optimize the brightness distribution of the target lamp and its adjacent lamps according to the obvious degree of the brightness change of the target lamp, and generate the load balancing result of the lamps in the tunnel.

[0027] As a further solution of the present invention, the steps for obtaining the dynamic safety control result of the tunnel lamp are specifically as follows:

[0028] S401: Based on the vehicle speed monitoring sensor, monitor the vehicle speed of the vehicle driving in the tunnel at each time point in real time, calculate the position change of the vehicle at different time points in the tunnel according to the speed data of the vehicle driving in the tunnel, and determine the instantaneous speed of the vehicle with reference to the position change, and generate the vehicle instantaneous speed information;

[0029] S402: Compare the vehicle instantaneous speed information with the preset speed threshold range, and adjust the output effect of the lamps with optimized brightness distribution in the load balancing result of the lamps in the tunnel according to the comparison result. The output effect includes the color temperature, brightness, and flashing mode of the lamps, and generate the dynamic safety control result of the tunnel lamp.

[0030] As a further solution of the present invention, the steps for obtaining the dynamic adjustment result of the light intensity inside and outside the tunnel are specifically as follows:

[0031] S501: Collect the light intensity value of the external environment of the tunnel monitored in real time by the light intensity sensor of the external environment of the tunnel. By calculating the difference between the brightness of the lamps at the tunnel entrance and exit after optimizing the brightness distribution in the tunnel lamp load balance result and the light intensity value of the external environment of the tunnel, analyze the difference between the brightness of the lamps at the tunnel entrance and exit and the light intensity value of the external environment of the tunnel according to the difference, and generate the light intensity difference information inside and outside the tunnel.

[0032] S502: Compare the light intensity difference information inside and outside the tunnel with the preset light intensity requirement threshold range. According to the comparison result, adjust the brightness of the lamps at the tunnel entrance and exit. When the comparison result is within the light intensity requirement threshold range, there is no need to further adjust the brightness of the lamps. When the comparison result exceeds or is lower than the light intensity requirement threshold range, it is necessary to adjust the brightness of the lamps at the tunnel entrance and exit to decrease or increase, and generate the dynamic adjustment result of the light intensity inside and outside the tunnel.

[0033] An intelligent control system for tunnel lights, which is used to execute the above intelligent control method for tunnel lights. The system includes:

[0034] The lamp operation risk assessment module compares each type of lamp operation parameter with the corresponding preset risk threshold based on the operation parameters and failure times of the lamps collected in real time in the tunnel, and obtains the preliminary analysis result of the lamp operation risk. According to the observed parameters in the preliminary analysis result of the lamp operation risk, calculate the comprehensive probability of the lamp failure, divide the lamps into different risk levels according to the comprehensive probability, and generate the classification result of the lamp operation status.

[0035] The lamp load dynamic optimization module obtains the brightness load values of the target lamp and its adjacent lamps based on the target lamp risk level in the lamp operation status classification result, performs load balancing processing on them, predicts the future offset trend of the brightness of the target lamp after the load balancing processing, and dynamically optimizes the brightness distribution of the target lamp and its adjacent lamps according to the future offset trend, and generates the tunnel lamp load balance result.

[0036] The vehicle speed brightness regulation module monitors the vehicle speed of the vehicle driving in the tunnel at each time point in real time based on the tunnel lamp load balance result, compares the vehicle speed with the preset speed threshold range, adjusts the tunnel lamp load balance result according to the comparison result, and optimizes the output effect of the lamps after the brightness distribution, and generates the dynamic safety control result of the tunnel lights.

[0037] Based on the dynamic safety control result of the tunnel lights, the entrance and exit light intensity difference adjustment module monitors the external environmental light intensity value of the tunnel in real time, analyzes the difference between the brightness of the lights located at the tunnel entrance and exit after the brightness distribution of the lights in the tunnel is optimized and the external environmental light intensity value of the tunnel, obtains the light intensity difference information inside and outside the tunnel, compares the light intensity difference information inside and outside the tunnel with the preset light intensity requirement threshold range, adjusts the brightness of the lights at the tunnel entrance and exit according to the comparison result, and generates the dynamic adjustment result of the light intensity inside and outside the tunnel.

[0038] A tunnel light includes a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the tunnel light intelligent control system as described above is implemented.

[0039] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the tunnel light intelligent control method as described above are implemented.

[0040] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0041] In the present invention, by collecting the operation parameters and failure times of the tunnel lights in real time and combining the comparative analysis of the preset risk threshold, the risk of the operation state of the lights can be quantified and classified. This dynamic comprehensive probability calculation mode enables accurate early warning of potential problems of the lights and avoids omission of potential hazards caused by static judgment of a single parameter. On this basis, load balancing is performed based on the operation state and brightness load of the lights. Through prediction of the brightness trend change, the accuracy and efficiency of the dynamic adjustment of the light brightness are realized, and the uniformity of the illumination in the tunnel and the energy consumption utilization rate are significantly improved. The real-time monitoring and data analysis of the vehicle speed and the external light intensity of the tunnel ensure that the illumination adjustment can better meet the dynamic traffic and environmental requirements, optimize the safety of the driving environment, and reduce unnecessary energy waste. Through hierarchical, dynamic, and real-time multi-parameter collaborative processing, the light transition inside and outside the tunnel is smoother, effectively alleviating the visual fatigue of the driver when entering or exiting the tunnel, and significantly improving the intelligent level of the tunnel lighting system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of the working process of the present invention;

[0043] Figure 2 It is a flowchart of obtaining the preliminary analysis result of the operation risk of the lights of the present invention;

[0044] Figure 3 It is a flowchart of obtaining the classification result of the operation state of the lights of the present invention;

[0045] Figure 4 It is a flowchart of obtaining the load balance result of the lights in the tunnel of the present invention;

[0046] Figure 5 This is the flowchart for obtaining the dynamic safety control result of the tunnel lights in the present invention;

[0047] Figure 6 This is the flowchart for obtaining the dynamic adjustment result of the light intensity inside and outside the tunnel in the present invention. Specific embodiments

[0048] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0049] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0050] Please refer to Figure 1 , the present invention provides a technical solution: an intelligent control method for tunnel lights, including the following steps:

[0051] S1: Collect the operation parameters and the number of failures of each type of lamp in the tunnel in real time, compare the operation parameters of each type of lamp with the corresponding preset risk threshold respectively, and generate a preliminary analysis result of the operation risk of the lamp;

[0052] S2: Calculate the comprehensive probability of the lamp failure according to the observed lamp operation parameters in the preliminary analysis result of the lamp operation risk, divide the risk level corresponding to the lamp according to the comprehensive probability of the lamp failure, and generate a classification result of the lamp operation state;

[0053] S3: According to the risk level of the target lamp in the classification result of the lamp operation state, obtain the brightness load values of the target lamp and its adjacent lamps and perform load balancing processing, predict the future offset trend of the brightness of the target lamp after the load balancing processing, and dynamically optimize the brightness distribution of the target lamp and its adjacent lamps according to the future offset trend, and generate a load balancing result of the lamps in the tunnel;

[0054] S4: Monitor the vehicle speed of the vehicle traveling in the tunnel at each time point in real time, compare the vehicle speed with the preset speed threshold range, adjust the tunnel lighting load balance result according to the comparison result, optimize the output effect of the lamps after brightness allocation, and generate the tunnel lamp dynamic safety control result;

[0055] S5: Monitor the external ambient light intensity value of the tunnel in real time, analyze the difference between the brightness of the lamps at the tunnel entrance and exit after optimizing the brightness allocation in the tunnel lighting load balance result and the external ambient light intensity value of the tunnel, obtain the tunnel internal and external light intensity difference information, compare the tunnel internal and external light intensity difference information with the preset light intensity requirement threshold range, and adjust the brightness of the lamps at the tunnel entrance and exit according to the comparison result to generate the tunnel internal and external light intensity dynamic adjustment result.

[0056] Please refer to Figure 2 , the steps for obtaining the preliminary analysis result of the lamp operation risk are specifically as follows:

[0057] S101: Obtain the lamp operation parameters and the number of faults in the tunnel. The lamp operation parameters include the cumulative operation time, operation temperature, voltage fluctuation, and brightness load. Compare the lamp operation parameters with the corresponding preset risk thresholds respectively to generate the operation parameter comparison result;

[0058] The lamp operation parameters of the tunnel lamp are collected in real time through the monitoring module arranged in the tunnel lighting management system, including the cumulative operation time, operation temperature, voltage fluctuation value, and brightness load value of the tunnel lamp. Combine the asset management software used (such as "IBM Maximo" or "SAP equipment management system") to obtain the number of faults of the tunnel lamp. Compare the lamp operation parameters with the preset risk thresholds item by item. The threshold of the cumulative operation time is set to 90% of the nominal life of the tunnel lamp. For example, if the nominal life of the tunnel lamp is 50,000 hours, the risk threshold is 45,000 hours. The threshold of the operation temperature is set to the maximum allowable working temperature of the lamp. For example, the maximum working temperature of the tunnel lamp is 80 °C. The threshold of the voltage fluctuation value is ±10% of the rated voltage of the lamp. For example, if the rated voltage is 220V, the risk threshold is ±22V. The threshold of the brightness load value is 90% of the rated power of the lamp. For example, if the rated power of the tunnel lamp is 120W, the risk threshold is 108W. Compare the collected value of each type of lamp operation parameter with the threshold one by one and record the comparison result.

[0059] S102: Obtain the deviation value between the lamp operation parameter and the corresponding preset risk threshold from the operation parameter comparison result. Determine whether the current deviation exceeds the preset risk threshold according to the deviation value, and mark the lamp operation parameter that exceeds the preset risk threshold as the risk state to obtain the preliminary analysis result of the lamp operation risk;

[0060] For obtaining the deviation value between the lamp operation parameter and the corresponding preset risk threshold, use the formula:

[0061] ;

[0062] Calculate the deviation value of the th item of the luminaire operation parameters ;

[0063] Among them, represents the actual value of the th item of the luminaire operation parameters of the tunnel lamp, including the cumulative operation time, operation temperature, voltage fluctuation value, and brightness load value, represents the preset risk threshold of the th item of the luminaire operation parameters of the tunnel lamp.

[0064] Suppose the following actual values are collected: the cumulative operation time of the luminaire hours, the operation temperature °C, the voltage fluctuation V, the brightness load W. According to the design and specifications of the tunnel lamp, determine the following preset risk thresholds: the cumulative operation time threshold hours, the operation temperature threshold °C, the voltage fluctuation threshold V (i.e., the range of ±22V), and the brightness load value threshold W.

[0065] The deviation value of the cumulative operation time: ;

[0066] The deviation value of the operation temperature: ;

[0067] The deviation value of the voltage fluctuation: ;

[0068] The deviation value of the brightness load: .

[0069] Result indicates that the cumulative operation time of the tunnel lamp has exceeded the risk threshold by 3000 hours, prompting that the luminaire is approaching the end of its service life and may require maintenance or replacement, indicates that the operation temperature of the tunnel lamp exceeds the risk threshold by 5°C, and there may be problems such as insufficient heat dissipation or too high ambient temperature, indicates that the voltage fluctuation reaches the upper limit of the risk threshold, indicating that there may be an unstable power supply situation, indicates that the brightness load slightly exceeds the threshold, prompting that the luminaire may be operating near full load, and the rationality of the power configuration needs to be evaluated.

[0070] Please refer to Figure 3 , and the specific steps for obtaining the classification result of the luminaire operation status are as follows:

[0071] S201: Based on the preliminary analysis results of the operating risks of the lamps, take the probabilities that the operating parameters of each type of lamp exceed the preset risk threshold under the conditions of lamp failure and no lamp failure respectively as conditional probabilities, take the probabilities of lamp failure and no lamp failure obtained according to the number of lamp failures as prior probabilities, and combine the conditional probabilities and prior probabilities. Through the Bayesian model, use the formula:

[0072] ;

[0073] Calculate the comprehensive probability of lamp failure based on the observed set of lamp operating parameters ; ;

[0074] Among them, includes the cumulative operating time , operating temperature , voltage fluctuation , brightness load ; represents the probability that the operating parameters of the th type of lamp exceed the preset risk threshold under the condition of lamp failure , which is obtained based on historical data statistics. represents the probability of lamp failure , which is obtained by statistically calculating the proportion of the historical failure times of a certain type of lamp in the total number of samples. For example, among 1000 lamps, 200 lamps have had failures, then ; represents the overall probability that the operating parameters of the th type of lamp exceed the preset risk threshold, including the probabilities of exceeding the preset risk threshold in both the cases of lamp failure and no lamp failure. The calculation formula is: ; is the th type of lamp operating parameter's probability of exceeding the preset risk threshold under the condition of no lamp failure , is the probability of no lamp failure , and the calculation formula is: ; represents the weight factor of the th item of lamp operating parameters, reflecting the influence degree of this parameter on the comprehensive probability of lamp failure. The weights are quantitatively set by statistically calculating the influence degrees of various lamp operating parameters on lamp failure. For example: combining historical data, if the operating temperature has a significantly higher influence on lamp failure than the brightness load, then the weight value of the operating temperature should be relatively higher. is the total number of lamp operating parameters.

[0075] Suppose the following data is collected during the operation monitoring of the lamps: Among 200 faulty lamps, the number of lamps with cumulative operating time exceeding the threshold is 160, the number of lamps with operating temperature exceeding the threshold is 140, the number of lamps with voltage fluctuation exceeding the threshold is 120, and the number of lamps with brightness load exceeding the threshold is 100. Then: , , , .

[0076] Suppose the following data is collected during the operation monitoring of the lamps: Among 800 non-faulty lamps, the number of lamps with cumulative operating time exceeding the threshold is 160, the number of lamps with operating temperature exceeding the threshold is 120, the number of lamps with voltage fluctuation exceeding the threshold is 80, and the number of lamps with brightness load exceeding the threshold is 40. Then: , , , .

[0077] Calculate the overall probability for each type of lamp operating parameter. Cumulative operating time :

[0078] ;

[0079] Operating temperature :

[0080] ;

[0081] Voltage fluctuation :

[0082] ;

[0083] Brightness load :

[0084] ;

[0085] Calculation of the comprehensive failure probability :

[0086] ;

[0087] Suppose the weight factors are set according to the importance of the lamp operating parameters: The weight factor of cumulative operating time , the weight factor of operating temperature , the weight factor of voltage fluctuation , the weight factor of brightness load .

[0088] ;

[0089] ;

[0090] ;

[0091] ;

[0092] ;

[0093] The results show that the comprehensive failure probability .

[0094] S202: Analyze the operating state of the current luminaire according to the comprehensive probability of luminaire failure and determine the risk level according to the operating state, generating the classification result of the luminaire operating state;

[0095] According to the calculation result of the comprehensive failure probability , substitute it into the risk level division process, and define the risk level division criteria as follows: Low risk: The comprehensive failure probability , indicating that the luminaire is in a stable operating state, the luminaire operating parameters do not exceed the reasonable range, and the probability of failure is low, and no special maintenance needs to be arranged; Medium risk: The comprehensive failure probability , indicating that some of the luminaire operating parameters exceed the threshold, there is a certain risk of failure, and regular inspections and key monitoring need to be arranged; High risk: The comprehensive failure probability , indicating that the luminaire operating parameters greatly exceed the threshold, the risk of failure is high, and repair or replacement should be arranged as soon as possible. The calculated comprehensive failure probability falls within the interval of . According to the risk division criteria, the luminaire can be determined to be in a medium-risk state. Combining the historical trend of the luminaire operating parameters, evaluate whether it may develop into a high-risk state in the short term. If it is confirmed that it is possible, arrange preventive maintenance in advance. Suppose that in subsequent monitoring, the operating temperature of the luminaire gradually exceeds the threshold within the next week, resulting in and the statistical values change. At this time, recalculate the comprehensive failure probability . If the new value reaches , then its risk level needs to be adjusted to high risk and repair should be arranged immediately. In addition, by introducing real-time monitoring data and dynamic probability calculation, the risk level division can reflect the latest changes in the luminaire operating state.

[0096] Please refer to Figure 4 . The specific steps for obtaining the luminaire load balance result in the tunnel are as follows:

[0097] S301: Based on the classification result of the operating status of the lamps, obtain the risk level of the target lamp and the brightness values of the target lamp and its adjacent lamps. Perform corresponding brightness compensation on the target lamp and its adjacent lamps according to different risk levels to generate a preliminary load balancing result;

[0098] First, obtain the risk level of the target lamp and the real-time brightness load values of the target lamp and its adjacent lamps through the CityTouch lighting management system. Determine the brightness load adjustment method in combination with the risk level of the target lamp. For example, when the target lamp is marked as high risk, obtain the current brightness load value of the target lamp through the monitoring system, and retrieve the set brightness load threshold of this lamp from the lamp database. The brightness decrement value is obtained by subtracting the threshold brightness load from the current brightness load value. At the same time, obtain the current brightness load value of the adjacent low-risk lamps of the target lamp from the monitoring data. The brightness compensation range of the low-risk lamps is obtained by subtracting the current brightness load value from the preset brightness upper limit value in the system. For example, if the current brightness load of the target lamp is 120 lumens and its high-risk threshold brightness is 100 lumens, the decrement value directly obtained by the monitoring system is 20 lumens. At the same time, if the current brightness load of the low-risk lamp is 90 lumens and its allowable brightness compensation range is 110 lumens, the compensation value is calculated by the system according to the compensation range as 20 lumens. The brightness balance amount is obtained by comparing the decremented brightness value of the target lamp and the compensated brightness value of the low-risk lamp. At the same time, the brightness load of the medium-risk lamps remains at the existing level. The preliminary brightness load balance is achieved by matching the decremented brightness value of the target lamp with the brightness compensation value of the low-risk lamp, and finally a brightness distribution scheme based on the risk level of the target lamp is formed.

[0099] S302: Based on the preliminary load balancing result, use the Lagrange interpolation method with the formula:

[0100] ;

[0101] Calculate the brightness value of the target lamp at the future moment after the preliminary load balancing process , and obtain the future offset trend of the brightness of the target lamp;

[0102] Among them, is the polynomial order of the brightness value of the target lamp, which is 1 less than the number of brightness sampling points and is determined by the number of brightness data points . For example, if there are 3 historical data points, then , is the brightness value of the target lamp at the th time point in the preliminary load balancing result, which is collected in real time through the monitoring system (CityTouch). For example, the brightness is recorded every 10 minutes to obtain a brightness data sequence, is the future time point to be predicted set according to the preliminary load balancing result. For example, predict the brightness value 15 minutes after the load balancing process. is related to the brightness value corresponding to the th time point. is the time point used to construct the Lagrange basis function. is the iteration index of the Lagrange basis function, and together construct the interpolation polynomial, with the same source as . is the Lagrange basis function part used to construct the interpolation polynomial, calculate the contribution of other data points to the future time point to be predicted, representing the iteration index for traversing all Lagrange basis functions . is to exclude the influence of the th time point, indicating that the construction of the current Lagrange basis function needs to exclude the brightness value corresponding to the th time point to avoid the problem of division by zero. represents and difference, used to calculate the relationship between the target point and . represents and difference, determine the proportional relationship between time points, through multiplication operation, combine the time point relationships of all together to construct the basis function.

[0103] Suppose the historical data points obtained by monitoring are as follows:

[0104] minutes, brightness . minutes, brightness . minutes, brightness , set the target prediction time minutes, need to predict the brightness value at this time , substitute into the formula:

[0105] .

[0106] Expand the basis function calculation:

[0107] The first term ( ):

[0108] .

[0109] The second term ( ):

[0110] ;

[0111] Item 3( ):

[0112] ;

[0113] Summation calculation:

[0114] ;

[0115] The result shows that the calculation obtains , indicating that the predicted brightness value of the lamp at 15 minutes is 92.5 lumens.

[0116] S303: According to the future offset trend of the target lamp brightness, referring to the preset trend change range, analyze whether the change in the target lamp brightness is obvious, and dynamically optimize the brightness distribution of the target lamp and its adjacent lamps according to the obvious degree of the change in the target lamp brightness, and generate the lamp load balance result in the tunnel;

[0117] First, combine the preliminary load balance plan and the future offset trend result to evaluate the brightness change range and load condition of the target lamp at the future offset moment. The specific criteria for judging the range of the trend size are as follows: If the offset trend value is lower than 10% of the current preliminary balanced brightness load, it is considered that the offset trend change is small and no further adjustment is required; if the offset trend value exceeds 10% of the current balanced load, it is considered that the offset trend change is large and the brightness distribution plan needs to be further optimized. For example, the current brightness value of the target lamp is 100 lumens, which is lower than the predicted brightness value within the range of 10% (below 95 lumens), it is determined that the offset trend of the target luminaire is a small change, and no major adjustment to the brightness distribution is required; at the same time, the brightness offset trend of adjacent low-risk luminaires is that the compensated brightness rises to the predicted brightness value of 110 lumens, exceeding 10% of the preliminary load balancing brightness compensation range. Therefore, it is considered that the offset trend change of low-risk luminaires is relatively large and further optimization of the brightness distribution is needed. During the further optimization process, the real-time brightness load values and predicted offset trends of the target luminaire and its adjacent luminaires are called, and the decreasing brightness value of the target luminaire and the compensation brightness range of adjacent low-risk luminaires are readjusted. For example, the high-risk luminaire needs to adjust the brightness decrease amount from the original 20 lumens to 25 lumens according to the future offset trend to cope with the predicted load offset trend in the future. At the same time, the brightness compensation range of low-risk luminaires is dynamically adjusted according to the prediction result, and the originally allowed compensation of 20 lumens is increased to 25 lumens to match the decreasing brightness value of the high-risk luminaire, and it is calculated whether the adjusted brightness balance amount is within the threshold range allowed by the system; for medium-risk luminaires, through the comparison of the brightness load value and the prediction result, if the future offset trend does not exceed 10% of the current brightness load, the existing level is maintained, and if it exceeds, the distribution scheme is dynamically adjusted according to the predicted brightness value. In the final generated load balancing result of the tunnel luminaires, the brightness distribution of each luminaire can adapt to the future offset trend, ensuring that the overall brightness load in the tunnel is in a balanced state. For example, the final brightness decrease of the target luminaire is 95 lumens, the brightness compensation of the low-risk luminaire increases to 115 lumens, and the brightness of the medium-risk luminaire remains unchanged at 100 lumens. After the brightness distribution is adjusted, the future trends of the brightness of each luminaire fall within the range allowed by the system, achieving dynamic load balancing optimization.

[0118] Please refer to Figure 5 , and the specific steps for obtaining the dynamic safety control result of the tunnel lights are as follows:

[0119] S401: Based on the vehicle speed monitoring sensor, the vehicle speed of the vehicle traveling in the tunnel at each time point is monitored in real time. According to the speed data of the vehicle traveling in the tunnel, the position change of the vehicle at different time points in the tunnel is calculated, and the instantaneous speed of the vehicle is determined with reference to the position change, and vehicle instantaneous speed information is generated;

[0120] For determining the instantaneous speed of the vehicle, the formula:

[0121] ;

[0122] Calculate the instantaneous speed of the vehicle at time ; ;

[0123] where is obtained from the speed data of the vehicle traveling in the tunnel, and it is the vehicle at time The displacement value at time [time], in meters (m), is measured using speed monitoring sensors (such as lidar, ultrasonic sensors, or geomagnetic sensors) installed in the tunnel for the vehicle at time The displacement, where the sensor captures the position of the vehicle passing through the monitoring point in real time, is the displacement value of the vehicle at time [time] obtained from the speed data of the vehicle traveling in the tunnel, in meters (m), recorded by the speed monitoring sensor in the tunnel for the vehicle's displacement at the previous time value, is the timestamp of the vehicle at time [time] obtained from the speed data of the vehicle traveling in the tunnel, in seconds (s), for example, the specific time when the speed monitoring sensor records the vehicle passing through monitoring point 2, is the timestamp of the vehicle at the previous time [time] obtained from the speed data of the vehicle traveling in the tunnel, in seconds (s), for example, the specific time when the speed monitoring sensor records the vehicle passing through monitoring point 1, is the time interval between the vehicle at and two times, in seconds (s), is the vehicle at and the change in displacement between two times, in meters (m).

[0124] Assume that when the vehicle passes through the monitoring point, the sensor captures the following data:

[0125] meters, the displacement of the vehicle at seconds, meters, the displacement of the vehicle at seconds, formula calculation process:

[0126] ;

[0127] Calculate the displacement difference: ;

[0128] Calculate the time interval: ;

[0129] Calculate the instantaneous speed: ;

[0130] The result shows that the instantaneous speed of the vehicle at seconds is meters per second.

[0131] S402: Compare the instantaneous vehicle speed information with a preset speed threshold range, and adjust the output effects of the lamps after optimizing the brightness distribution in the tunnel lamp load balance result. The output effects include lamp color temperature, brightness, and flashing mode, and generate a dynamic safety control result for tunnel lamps;

[0132] Adjust the output effects of the lamps after the tunnel lamp load balance result according to the comparison result, based on the calculated vehicle speed value , first compare it with the set speed threshold range . The calculation result shows that the vehicle speed exceeds the upper limit, and it is determined to be in an overspeed state. Therefore, the system will trigger the dynamic control mechanism of the lamps. By performing corresponding actions such as PLC, first call the control parameters of the tunnel lamps at the current vehicle position and at least 3 lamps in front of the vehicle, adjust the working state of the lamps. By increasing the lamp brightness to the maximum value (for example, from 70% to 100%), adjust the color temperature to cold light (for example, from 4000K to 6500K), and at the same time increase the flashing frequency to 2 times per second to remind the vehicle to decelerate. When the vehicle speed is lower than the lower threshold (for example, the vehicle speed is 4 m / s), adjust the brightness of the current lamp and the lamps in front to the intermediate value (for example, from 100% to 85%) through the same system, adjust the color temperature to warm light (for example, from 6500K to 3000K), and adjust the flashing frequency to 1 time per second to remind the vehicle to accelerate. When the vehicle speed is within the threshold range, the system controls the brightness of the lamps to be adjusted in a gradual change manner (for example, the brightness of the front and rear lamps gradually changes from 80% to 100%) to achieve a transitional lighting effect. When the vehicle speed is zero (for example, the monitored speed ), it is determined to be in an accident state. The intelligent control system triggers the focusing mode of the current lamp and the surrounding lamps, raises the brightness to the highest value, adjusts the color temperature to neutral white light (for example, remains at 5000K), and increases the light flashing frequency to 3 times per second to prompt the following vehicles to pay attention to avoidance. The entire control process is based on the monitoring platform sending real-time instructions to the lamp controller to achieve, and after completing the above operations, a dynamic safety control result for tunnel lamps based on the vehicle state is generated.

[0133] Please refer to Figure 6 , the specific steps for obtaining the dynamic adjustment result of the light intensity inside and outside the tunnel are as follows:

[0134] S501: Collect the light intensity value of the tunnel external environment monitored in real time by the tunnel external environment light intensity sensor. By calculating the difference between the brightness of the lamps at the tunnel entrance and exit after optimizing the brightness distribution in the tunnel lamp load balance result and the light intensity value of the tunnel external environment, analyze the difference between the brightness of the lamps at the tunnel entrance and exit and the light intensity value of the tunnel external environment, and generate the light intensity difference information inside and outside the tunnel;

[0135] For the difference between the brightness of the luminaires located at the tunnel entrances and exits after optimizing the brightness distribution in the calculation of the luminaire load balance result in the tunnel and the external ambient light intensity value of the tunnel , the calculation formula is:

[0136] ;

[0137] Among them, is the brightness of the luminaires located at the tunnel entrances and exits after optimizing the brightness distribution in the luminaire load balance result in the tunnel, with the unit of lumen (lm). The current brightness of the luminaires is measured in real time by the luminaire monitoring sensors in the tunnel, is the external ambient light intensity value of the tunnel monitored in real time by the external ambient light intensity sensor, with the unit of lumen (lm).

[0138] Suppose the following data are measured through the monitoring sensors: the brightness of the luminaires at the tunnel entrances and exits , the external ambient light intensity value .

[0139] Formula calculation process:

[0140] ;

[0141] Substitute the values:

[0142] ;

[0143] The result shows that the calculated difference in light intensity inside and outside the tunnel is .

[0144] S502: Compare the difference information of the light intensity inside and outside the tunnel with the preset light intensity requirement threshold range, and adjust the brightness of the luminaires at the tunnel entrances and exits according to the comparison result. When the comparison result is within the light intensity requirement threshold range, there is no need to further adjust the brightness of the luminaires. When the comparison result exceeds or is lower than the light intensity requirement threshold range, it is necessary to adjust the brightness of the luminaires at the tunnel entrances and exits to decrease or increase, and generate the dynamic adjustment result of the light intensity inside and outside the tunnel;

[0145] Based on the difference information of the light intensity inside and outside the tunnel , compare this difference information with the preset light intensity requirement threshold range . The calculation result shows that the difference value is within a reasonable range and there is no need to further adjust the brightness of the luminaires. When the light intensity difference value exceeds the threshold range, for example , it is necessary to reduce the brightness of the luminaires at the tunnel entrances and exits, for example, reduce to , to reduce the light intensity difference between inside and outside the tunnel and prevent the excessive light intensity difference from affecting the driver's visual adaptability. Especially when entering the tunnel from a darker external environment, the excessive brightness of tunnel lights may lead to an increased visual burden and cause glare problems. When the light intensity difference value is below the threshold range, for example , it is necessary to increase the brightness of the lights at the tunnel entrance and exit, for example by raising to , to ensure that when the driver enters the tunnel from a brighter external environment, the light intensity transition is smooth enough to avoid blurred vision due to insufficient light intensity inside the tunnel. Finally, the brightness of the lights at the tunnel entrance and exit is dynamically adjusted according to different light intensity difference conditions to generate the dynamic adjustment result of the light intensity inside and outside the tunnel.

[0146] An intelligent control system for tunnel lights, which is used to execute an intelligent control method for tunnel lights. The system includes:

[0147] The lamp operation risk assessment module compares each type of lamp operation parameter with the corresponding preset risk threshold based on the operation parameters and failure times of the lamps collected in real time inside the tunnel to obtain the preliminary analysis result of the lamp operation risk. According to the observed parameters in the preliminary analysis result of the lamp operation risk, calculate the comprehensive probability of the lamp failing, and divide the lamps into different risk levels according to the comprehensive probability to generate the classification result of the lamp operation status;

[0148] The lamp load dynamic optimization module obtains the brightness load values of the target lamp and its adjacent lamps based on the target lamp risk level in the classification result of the lamp operation status, performs load balancing processing on them, predicts the future offset trend of the brightness of the target lamp after the load balancing processing, and dynamically optimizes the brightness distribution of the target lamp and its adjacent lamps according to the future offset trend to generate the lamp load balance result inside the tunnel;

[0149] The vehicle speed brightness regulation module, based on the lamp load balance result inside the tunnel, monitors the vehicle speed of the vehicle driving inside the tunnel at each time point in real time, compares the vehicle speed with the preset speed threshold range, adjusts the lamp load balance result inside the tunnel according to the comparison result, and optimizes the output effect of the lamps after the brightness distribution to generate the dynamic safety control result of the tunnel lights;

[0150] The entrance and exit light intensity difference adjustment module, based on the dynamic safety control result of the tunnel lights, monitors the external environment light intensity value of the tunnel in real time, analyzes the difference between the brightness of the lights at the tunnel entrance and exit after the brightness distribution of the lamps inside the tunnel is optimized and the external environment light intensity value of the tunnel, obtains the light intensity difference information inside and outside the tunnel, compares the light intensity difference information inside and outside the tunnel with the preset light intensity requirement threshold range, and adjusts the brightness of the lights at the tunnel entrance and exit according to the comparison result to generate the dynamic adjustment result of the light intensity inside and outside the tunnel.

[0151] A tunnel lamp includes a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, a tunnel lamp intelligent control system is implemented.

[0152] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of a tunnel lamp intelligent control method are implemented.

[0153] The above are only the preferred embodiments of the present invention, and do not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical content of the technical solution of the present invention, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A tunnel lamp intelligent control method, characterized in that: The following steps are involved: S1: Collect the operating parameters and fault counts of each type of lamp in the tunnel in real time, compare the operating parameters of each type of lamp with the corresponding preset risk threshold, and generate preliminary analysis results of lamp operation risks; S2: calculating the comprehensive probability of lamp failure according to the lamp operation parameters observed in the preliminary analysis result of the lamp operation risk, dividing the risk level corresponding to the lamp according to the comprehensive probability of lamp failure, and generating a lamp operation status classification result; S3: according to the risk level of the target lamp in the lamp operation status classification result, the brightness load value of the target lamp and its adjacent lamps is obtained and load balancing is performed, and the distribution of the brightness of the target lamp and its adjacent lamps is dynamically optimized according to the future offset trend by predicting the future offset trend of the brightness of the target lamp after the load balancing process, so as to generate the load balancing result of the lamps in the tunnel; The steps for obtaining the load balancing result of the lamps in the tunnel are specifically as follows: S301: Based on the lamp operation status classification result, the risk level of the target lamp and the brightness values ​​of the target lamp and its adjacent lamps are obtained, and corresponding brightness compensation is performed on the target lamp and its adjacent lamps according to different risk levels to generate a preliminary load balancing result; S302: Based on the preliminary load balancing result, the Lagrange interpolation method is used, using the formula: Calculate the brightness value Lt of the target lamp at the future time t after the preliminary load balancing process, and obtain the future deviation trend of the brightness of the target lamp; Where m is the polynomial order of the brightness value of the target lamp, L h is the brightness value of the target lamp at the hth time point in the preliminary load balancing result, t is the future time point that needs to be predicted according to the preliminary load balancing result, and t h is related to the brightness value L h The corresponding h-th time point, t k is the time point used to construct the Lagrangian basis function, k is the iteration index of the Lagrangian basis function, and h constructs the interpolation polynomial, It is the Lagrangian basis function part, which indicates the iteration index k of all Lagrangian basis functions. k≠h indicates that the construction of the current Lagrangian basis function needs to exclude the brightness value L h For the corresponding h-th time point, 0≤k≤m means that the value range of k is from 0 to m; S303: Analyze whether the target lamp brightness changes significantly according to the future deviation trend of the target lamp brightness and the preset trend change range, dynamically optimize the distribution of the target lamp brightness and its adjacent lamp brightness according to the obvious degree of the target lamp brightness change, and generate a lamp load balancing result in the tunnel; S4: Real-time monitoring of the vehicle speed of the vehicle traveling in the tunnel at each time point, comparing the vehicle speed with a preset speed threshold range, adjusting the load balancing result of the lamps in the tunnel according to the comparison result, optimizing the output effect of the lamps after brightness distribution, and generating a dynamic safety control result of the tunnel lights; S5: Real-time monitoring of the ambient light intensity value outside the tunnel, analyzing the difference between the brightness of the lamps located at the entrance and exit of the tunnel after optimizing the brightness distribution in the load balancing result of the lamps in the tunnel and the ambient light intensity value outside the tunnel, obtaining the light intensity difference information inside and outside the tunnel, comparing the light intensity difference information inside and outside the tunnel with the preset light intensity requirement threshold range, adjusting the brightness of the lamps at the entrance and exit of the tunnel according to the comparison result, and generating a dynamic adjustment result of the light intensity inside and outside the tunnel.

2. The intelligent control method for tunnel lights according to claim 1, characterized in that: The specific steps for obtaining the preliminary analysis results of the lamp operation risk are as follows: S101: Obtain operating parameters and fault counts of lamps in the tunnel, where the lamp operating parameters include cumulative operating time, operating temperature, voltage fluctuation, and brightness load, and compare the lamp operating parameters with corresponding preset risk thresholds to generate operating parameter comparison results; S102: Obtain the deviation value between the lamp operating parameter and the corresponding preset risk threshold from the operating parameter comparison result, determine whether the current deviation exceeds the preset risk threshold according to the deviation value, mark the lamp operating parameter that exceeds the preset risk threshold as being in a risky state, and obtain a preliminary analysis result of the lamp operating risk.

3. The intelligent control method for tunnel lights according to claim 1, characterized in that: The steps for obtaining the lamp operation status classification result are specifically as follows: S201: Based on the preliminary analysis results of the lamp operation risk, the probability of each type of lamp operation parameter exceeding the preset risk threshold under the condition that the lamp fails and the condition that the lamp does not fail is taken as the conditional probability, and the probability of the lamp failing and the probability of the lamp not failing obtained according to the number of lamp failures are taken as the prior probability. The conditional probability and the prior probability are combined through the Bayesian model and the formula is adopted: Calculate the comprehensive probability PF|D' of lamp failure F based on the set D' of observed lamp operating parameters; Among them, PD' j |F represents the probability that the operating parameters of the jth type of lamp exceed the preset risk threshold under the condition that the lamp fails F, PF represents the probability that the lamp fails F, PD' j It represents the overall probability that the operating parameters of the j-th type of lamps exceed the preset risk threshold. The overall probability includes the probability of exceeding the preset risk threshold when the lamp fails and when it does not fail. The calculation formula is: The operating parameters of the jth type of lamps when the lamps are not faulty The probability of exceeding the preset risk threshold under the conditions The lamp is not faulty. The probability is calculated as: w j represents the weight factor of the jth lamp operating parameter, and n is the total number of lamp operating parameters; S202: Analyze the current operating state of the lamp according to the comprehensive probability of the lamp failure, determine the risk level according to the operating state, and generate a lamp operating state classification result.

4. The intelligent control method for tunnel lights according to claim 1, characterized in that: The steps for obtaining the dynamic safety control result of the tunnel lamp are specifically as follows: S401: monitoring the speed of the vehicle in the tunnel at each time point in real time based on the vehicle speed monitoring sensor, calculating the position change of the vehicle at different time points in the tunnel according to the speed data of the vehicle in the tunnel, determining the instantaneous speed of the vehicle with reference to the position change, and generating the instantaneous speed information of the vehicle; S402: Compare the instantaneous speed information of the vehicle with a preset speed threshold range, and adjust the output effect of the lamp after optimizing the brightness distribution in the lamp load balancing result in the tunnel according to the comparison result, the output effect including the lamp color temperature, brightness, and flashing mode, to generate a dynamic safety control result of the tunnel lamp.

5. The intelligent control method for tunnel lights according to claim 1, characterized in that: The specific steps for obtaining the dynamic adjustment result of the light intensity inside and outside the tunnel are: S501: collecting the tunnel external ambient light intensity value monitored in real time by the tunnel external ambient light intensity sensor, calculating the difference between the brightness of the lamps at the entrance and exit of the tunnel after optimizing the brightness distribution in the load balancing result of the lamps in the tunnel and the value of the tunnel external ambient light intensity, analyzing the difference between the brightness of the lamps at the entrance and exit of the tunnel and the value of the tunnel external ambient light intensity according to the difference, and generating the light intensity difference information inside and outside the tunnel; S502: Compare the light intensity difference information inside and outside the tunnel with the preset light intensity requirement threshold range, and adjust the brightness of the lamps at the entrance and exit of the tunnel according to the comparison result. When the comparison result is within the light intensity requirement threshold range, there is no need to further adjust the brightness of the lamps. When the comparison result exceeds or is lower than the light intensity requirement threshold range, it is necessary to adjust the brightness of the lamps at the entrance and exit of the tunnel to reduce or increase the brightness, so as to generate a dynamic adjustment result of the light intensity inside and outside the tunnel.

6. A tunnel light intelligent control system, used to implement the tunnel light intelligent control method according to any one of claims 1 to 5, characterized in that: The system comprises: The lamp operation risk assessment module compares the operating parameters of each type of lamp with the corresponding preset risk threshold based on the operating parameters and fault times of the lamps collected in real time in the tunnel, obtains the preliminary analysis results of the lamp operation risk, calculates the comprehensive probability of lamp failure based on the observed parameters in the preliminary analysis results of the lamp operation risk, divides the lamps into different risk levels according to the comprehensive probability, and generates the lamp operation status classification results; The dynamic optimization module of lamp load obtains the brightness load value of the target lamp and its adjacent lamps based on the risk level of the target lamp in the lamp operation status classification result, performs load balancing processing on them, predicts the future deviation trend of the brightness of the target lamp after the load balancing processing, dynamically optimizes the brightness distribution of the target lamp and its adjacent lamps according to the future deviation trend, and generates the load balancing result of the lamps in the tunnel; The vehicle speed and brightness control module monitors the vehicle speed of the vehicle in the tunnel at each time point in real time based on the load balancing result of the lamps in the tunnel, compares the vehicle speed with a preset speed threshold range, adjusts the load balancing result of the lamps in the tunnel according to the comparison result, optimizes the output effect of the lamps after brightness distribution, and generates a dynamic safety control result of the tunnel lights; The entrance and exit light intensity difference adjustment module monitors the ambient light intensity value outside the tunnel in real time based on the dynamic safety control result of the tunnel lamp, analyzes the difference between the brightness of the lamps located at the entrance and exit of the tunnel after the brightness distribution of the lamps in the tunnel is optimized and the ambient light intensity value outside the tunnel, obtains the light intensity difference information inside and outside the tunnel, compares the light intensity difference information inside and outside the tunnel with the preset light intensity requirement threshold range, adjusts the brightness of the lamps at the entrance and exit of the tunnel according to the comparison result, and generates the dynamic adjustment result of the light intensity inside and outside the tunnel.

7. A tunnel lamp, comprising a memory and a processor, characterized in that: The memory stores a computer program, and the processor implements the tunnel light intelligent control system according to claim 6 when executing the computer program.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the tunnel light intelligent control method according to any one of claims 1 to 5 are implemented.

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