A method, device, and storage medium for regulating a lighting lamp

Abstract

This application discloses a method, device, equipment, and storage medium for controlling road lighting fixtures, relating to the field of electronic digital data processing technology. The method defines a set of several consecutive natural numbers, where each natural number corresponds to a consecutive lighting quantity based on the lane lighting fixture; defines a driving speed range with zero as the minimum value and the current road speed limit as the maximum value; divides the driving speed range into several driving speed sub-ranges, each corresponding to a consecutive lighting quantity, with the number of consecutive lights increasing linearly as the driving speed in the sub-range increases; obtains the current driving speed of the currently traveling vehicle through adjacent driving detection devices; and obtains the driving speed sub-range matching the current driving speed, along with the corresponding number of consecutive lights. This reduces energy waste in lighting fixtures and lowers the maintenance and repair costs of road lighting systems.

Description

Technical Field

[0001] This application relates to the field of electronic digital data processing technology, and in particular to a method, apparatus, device and storage medium for controlling road lighting fixtures. Background Technology

[0002] With economic development, urban population growth, and rapid expansion of municipal roads, lighting systems have been installed to ensure traffic safety. Based on relevant regulations and the needs of pedestrians and vehicles, municipal roads are equipped with various lighting systems, including vehicular lighting, pedestrian lighting, and non-motorized vehicle lane lighting. The number of lighting fixtures is enormous, and these systems need to operate continuously at night due to the needs of both vehicles and pedestrians. Road lighting systems aim to create a good visual environment for drivers and pedestrians at night, thereby ensuring traffic safety, improving transportation efficiency, and facilitating people's lives.

[0003] Currently, on some roads with low traffic and pedestrian flow, especially suburban roads and mountain roads, there are long periods of time at night when no vehicles or pedestrians pass by, but the road lighting is always on, resulting in energy waste and increasing the maintenance and repair costs of the road lighting system. Summary of the Invention

[0004] The main objective of this application is to provide a method, device, equipment, and storage medium for controlling road lighting fixtures, in order to solve the problem in the prior art where there are long periods of no vehicles or pedestrians on certain roads with low traffic and pedestrian flow, especially suburban roads and mountain roads, but the road lighting is always in operation, resulting in energy waste and increased maintenance and repair costs for the road lighting system.

[0005] To achieve the above objectives, this application provides the following technical solution:

[0006] A method for controlling road lighting fixtures, the road lighting fixtures comprising a plurality of lane lighting fixtures uniformly arranged along a lane in the same scenario, each lane lighting fixture being equipped with a vehicle detection device, the control method comprising:

[0007] Step S1: Divide the driving lane into several continuous driving areas along the radial centerline of the driving lane, and each driving area includes a driving lane lighting fixture.

[0008] Step S2: Define a set of several consecutive natural numbers, where each natural number in the set corresponds to a consecutive number of lights to be turned on based on the driving lane lighting fixtures;

[0009] Step S3: Define the driving speed range with zero as the minimum value of the range and the current road speed limit as the maximum value of the range;

[0010] Step S4: Divide the driving speed range into several driving speed sub-ranges. Each driving speed sub-range corresponds to a number of consecutive lights. As the driving speed of the driving speed sub-range increases linearly, the number of consecutive lights also increases linearly.

[0011] Step S5: Obtain the current driving speed of the currently driving vehicle through adjacent driving detection devices;

[0012] Step S6: Obtain the driving speed sub-range that matches the current driving speed, and the corresponding number of consecutive lights;

[0013] Step S7: Detect the driving area where the currently driving vehicle is located using all driving detection devices and define it as a vehicle-occupied area;

[0014] Step S8: Starting from the area with vehicles, turn on or brighten the lane lighting fixtures along the current driving direction of the vehicles, matching the corresponding number of consecutive lights.

[0015] As a further improvement to this application, the road lighting fixtures also include a plurality of sidewalk lighting fixtures evenly arranged along the sidewalk in the same scene, each sidewalk lighting fixture being equipped with a pedestrian detection device, and the control method further includes:

[0016] Step S10: Divide the sidewalk into several continuous pedestrian areas along the pedestrian radial centerline, with each pedestrian area including a sidewalk lighting fixture.

[0017] Step S20: Detect the pedestrian area where the current pedestrian is located using all pedestrian detectors and define it as a pedestrian-only area;

[0018] Step S30: Starting from the pedestrian area, turn on or brighten a preset number of pedestrian lighting fixtures in both directions of the pedestrian walkway.

[0019] As a further improvement to this application, step S30, starting from the pedestrian area, involves turning on or brightening a preset number of pedestrian lighting fixtures in both directions along the sidewalk, including:

[0020] Step S301: In a sunny, sunny environment with all pedestrian lighting fixtures off, acquire the first image data for each pedestrian area.

[0021] Step S302: Obtain the average brightness of the first image for each first image data using a visual algorithm;

[0022] Step S303: In a nighttime environment with all lighting fixtures on, acquire second image data for each pedestrian area.

[0023] Step S304: Obtain the average brightness of the second image for each second image data using the visual algorithm;

[0024] Step S305: Define at least two consecutive brightness ranges in ascending order of visible light brightness values;

[0025] Step S306: Define a viewing distance weighting coefficient based on each brightness range. The magnitude of all viewing distance weighting coefficients decreases from low to high as the brightness values ​​of all visible light increase.

[0026] Step S307: Classify the average brightness of all first images and the average brightness of all second images into all brightness ranges using a classification algorithm. Obtain a first weight coefficient based on the average brightness of each first image and a second weight coefficient based on the average brightness of each second image.

[0027] Step S308: Obtain the coefficient difference between the first weight coefficient and the second weight coefficient of the pedestrian area, and determine whether the coefficient difference exceeds a preset difference threshold. If the coefficient difference exceeds the preset difference threshold, then execute step S309.

[0028] Step S309: Starting from the pedestrian area, turn on each pedestrian lighting fixture in both directions of the pedestrian walkway until the difference between the lighting fixture and the coefficient does not exceed the preset difference threshold.

[0029] As a further improvement to this application, step S302, obtaining the average brightness of the first image for each first image data using a visual algorithm, includes:

[0030] Step S3021: Import the cv2 package using Python's import statement;

[0031] Step S3022: Read each first image data and store it in the img variable using the cv2.imread function of the cv2 software package;

[0032] Step S3023: Convert all the first image data in the img variable into a first grayscale image and store it in the gray variable using the cv2.cvtColor function of the cv2 software package;

[0033] Step S3024: Obtain the first average brightness of each first grayscale image in the gray variable using the cv2.mean function of the cv2 software package and store it in the average_brightness variable;

[0034] Step S3025: Define all first average brightness values ​​in the average_brightness variable as the average brightness value of all first images.

[0035] As a further improvement to this application, step S304, obtaining the average second image brightness of each second image data using the visual algorithm, includes:

[0036] Step S3041: Initialize the img variable, the gray variable, and the average_brightness variable;

[0037] Step S3042: Read each second image data and store it in the img variable using the cv2.imread function;

[0038] Step S3043: Convert all the second image data in the img variable into a second grayscale image and store it in the gray variable using the cv2.cvtColor function;

[0039] Step S3044: Obtain the second average brightness of each second grayscale image in the gray variable using the cv2.mean function and store it in the average_brightness variable;

[0040] Step S3045: Define all the second average brightness values ​​in the average_brightness variable as the average brightness value of all second images.

[0041] As a further improvement to this application, step S309 involves sequentially turning on each pedestrian lighting fixture along both directions of the pedestrian walkway, starting from the pedestrian area, until the difference between the lighting fixture and the coefficient does not exceed a preset difference threshold. Afterwards, the process includes:

[0042] Step S100: Obtain the sunrise time of the area where the scene is located;

[0043] Step S200: Generate a light-off signal based on the sunrise time;

[0044] Step S300: Turn off all driving lane lighting fixtures and all pedestrian lighting fixtures according to the shutdown signal.

[0045] As a further improvement to this application, step S309 involves sequentially turning on each pedestrian lighting fixture along both directions of the pedestrian walkway, starting from the pedestrian area, until the difference between the lighting fixture and the coefficient does not exceed a preset difference threshold. Afterwards, the process includes:

[0046] Step S1000: Monitor the lighting intensity of all driving lane lights and all pedestrian lights in real time;

[0047] Step S2000: Define the driving lane lighting fixtures and the pedestrian lighting fixtures with zero illumination intensity as faulty lighting fixtures;

[0048] Step S3000: Obtain the geographical location of the faulty lighting fixture and send it to the external monitoring terminal.

[0049] To achieve the above objectives, this application also provides the following technical solutions:

[0050] A control device for a road lighting fixture, the control device being applied to the control method described above, the control device comprising:

[0051] The lane division module is used to divide the lane into several continuous driving areas along the radial centerline of the driving lane, and each driving area includes a driving lane lighting fixture.

[0052] The continuous lighting quantity definition module is used to define a set of several consecutive natural numbers, wherein each natural number in the set corresponds to a continuous lighting quantity based on the driving lane lighting fixtures;

[0053] The vehicle speed range definition module is used to define a vehicle speed range with zero as the minimum value and the current road speed limit as the maximum value.

[0054] The driving speed range division module is used to divide the driving speed range into several driving speed sub-ranges on an average basis. Each driving speed sub-range corresponds to a number of consecutive lights. As the driving speed of the driving speed sub-range increases linearly, the number of consecutive lights also increases linearly.

[0055] The current vehicle speed acquisition module is used to acquire the current vehicle speed through adjacent vehicle detection devices;

[0056] The current vehicle speed matching module is used to obtain the vehicle speed sub-range that matches the current driving speed, as well as the corresponding number of consecutive lights;

[0057] The vehicle area definition module is used to detect the driving area where the currently driving vehicle is located through all driving detection devices and define it as a vehicle area.

[0058] The lane lighting activation module is used to turn on or brighten lane lighting fixtures that match the corresponding number of consecutive lights, starting from the area with vehicles and moving along the direction of travel of the currently traveling vehicles.

[0059] To achieve the above objectives, this application also provides the following technical solutions:

[0060] An electronic device includes a processor and a memory coupled to the processor, the memory storing program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the control method for road lighting fixtures as described above.

[0061] To achieve the above objectives, this application also provides the following technical solutions:

[0062] A storage medium storing program instructions, which, when executed by a processor, enable the control method for road lighting fixtures as described above.

[0063] This application divides the driving lane into several continuous driving areas along the radial centerline of the driving lane, with each driving area including one driving lane lighting fixture; defines a set of several consecutive natural numbers, where each natural number corresponds to a continuous lighting quantity based on the driving lane lighting fixture; defines a driving speed range with zero as the minimum value and the current road speed limit as the maximum value; divides the driving speed range into several driving speed sub-ranges, each driving speed sub-range corresponding to a continuous lighting quantity, and the continuous lighting quantity increases linearly with the driving speed of the driving speed sub-range; obtains the current driving speed of the currently driving vehicle through adjacent driving detection devices; obtains the driving speed sub-range matching the current driving speed and the corresponding continuous lighting quantity; detects the driving area where the currently driving vehicle is located through all driving detection devices and defines it as a vehicle-occupied area; and turns on or brightens the driving lane lighting fixtures matching the corresponding continuous lighting quantity along the driving direction of the currently driving vehicle, starting from the vehicle-occupied area. This application determines the number of streetlights to turn on or brighten by identifying the real-time speed of vehicles, thereby reducing energy waste caused by excessive or continuous lighting and simultaneously reducing the maintenance and repair costs of road lighting systems. Attached Figure Description

[0064] Figure 1 This is a schematic flowchart illustrating the steps of one embodiment of the lighting fixture control method of this application;

[0065] Figure 2 This is a schematic diagram of the functional modules of one embodiment of the control device for lighting fixtures according to this application;

[0066] Figure 3 This is a schematic diagram of the structure of an embodiment of the electronic device of this application;

[0067] Figure 4 This is a schematic diagram of the structure of one embodiment of the storage medium of this application. Detailed Implementation

[0068] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0069] The terms "first," "second," and "third" in this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0070] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0071] like Figure 1 As shown, this embodiment provides an example of a method for controlling road lighting fixtures. In this embodiment, the road lighting fixtures include several lane lighting fixtures evenly arranged along the driving lanes in the same scenario, and each lane lighting fixture is equipped with a driving detection device.

[0072] Preferably, the lighting fixtures for driving lanes are mostly streetlights, and there are several streetlights on a road. In order to achieve the "brightness enhancement" function mentioned below in this embodiment, all streetlights can have at least two lighting intensities with increasing brightness, such as a first level of 200 lux, a second level of 400 lux, a third level of 600 lux, and so on. Lighting fixtures with lighting intensity level switching are already mature existing technologies, and this embodiment will not elaborate on the detailed structure, model, etc. of various lighting fixtures.

[0073] It is worth noting that the above examples are only used to illustrate the numerical values ​​of the "brighten" function, and the numerical values ​​mentioned above are not intended to limit this embodiment, and the same applies below.

[0074] Specifically, the regulation method includes the following steps:

[0075] Step S1: Divide the driving lane into several continuous driving areas along the radial centerline of the driving lane, and each driving area includes a driving lane lighting fixture.

[0076] Preferably, the radial centerline of the road is the dividing line. Step S1 involves dividing the road perpendicular to the dividing line, rather than directly using the dividing line, to ensure that each street light has its own plot of land.

[0077] Step S2: Define a set of several consecutive natural numbers, where each natural number in the set corresponds to a consecutive number of lights to be turned on based on the traffic lane lighting fixtures.

[0078] Preferably, if the set starts from 0, it means that the streetlights are not turned on or brightened when the vehicle speed is 0; if the set starts from 1, it means that one streetlight is turned on or brightened when the vehicle speed is 0, and the streetlight is located on the plot where the vehicle is located; if the set starts from 2, it means that two streetlights are turned on or brightened when the vehicle speed is 0, and the two streetlights are located on the plot where the vehicle is located and on a plot ahead of the vehicle. That is, the number of streetlights turned on or brightened increases sequentially from the plot where the vehicle is located to the plot ahead of the vehicle, and so on.

[0079] Step S3: Define the driving speed range with zero as the minimum value of the range and the current road speed limit as the maximum value of the range.

[0080] Preferably, the purpose of step S3, which uses the speed limit as the maximum value of the interval, is to encourage law-abiding driving and not speeding.

[0081] Step S4: Divide the driving speed range into several driving speed sub-ranges. Each driving speed sub-range corresponds to a number of consecutive lights. As the driving speed of the driving speed sub-range increases linearly, the number of consecutive lights also increases linearly.

[0082] For example, suppose the speed limit on a suburban road is 70 km / h. If the suburban road does not have a center line, the maximum speed is 40 km / h; if there is only one lane for motor vehicles in the same direction, the maximum speed is 70 km / h.

[0083] Therefore, the relationship between the driving speed sub-range and the number of consecutive lights can be set in the form of Table 1 below:

[0084]

[0085]

[0086] Table 1: Relationship between driving speed sub-range and number of consecutive lights.

[0087] Step S5: Obtain the current driving speed of the currently driving vehicle through the adjacent driving detection device.

[0088] Preferably, the current driving speed can be calculated by the time difference between the vehicle passing two consecutive streetlights. The distance between the two consecutive streetlights can be directly measured and obtained by dividing the distance by the time difference.

[0089] Step S6: Obtain the driving speed sub-range that matches the current driving speed, and the corresponding number of consecutive lights.

[0090] For example, a vehicle passes the k-th street light at 50 km / h. Following the steps above, 9 street lights need to be turned on or brightened. Then, counting backwards 8 blocks from the vehicle's location, the street lights in these 9 blocks need to be turned on or brightened. The vehicle then passes the (k+1)-th street light at 40 km / h. Following the steps above, 8 more street lights need to be turned on or brightened. Then, counting backwards 7 blocks from the vehicle's location, the street lights in these 8 blocks need to be turned on or brightened. At this point, since the k-th street light... The (k+8)th street light (out of 9) is either on or brightened. Counting from the (k+1)th street light to the (k+8)th street light covers exactly 8 plots. At this point, there is no need to turn on or brighten any subsequent street lights. However, since the vehicle has already reached the (k+1)th street light, the (k)th street light needs to be turned off or dimmed. That is, if a street light that has already been turned on and brightened still needs to be turned on or brightened in the next judgment, no action is taken; otherwise, it is turned off or dimmed. It is worth noting that the vehicle, which serves as the judgment benchmark, is constantly moving, and the benchmark point needs to be updated in real time.

[0091] Step S7: Detect the driving area where the currently driving vehicle is located using all driving detection devices and define it as a vehicle-occupied area.

[0092] Step S8: Starting from the area with vehicles, turn on or brighten the lane lights along the direction of travel of the currently traveling vehicles, matching the corresponding number of consecutive lights.

[0093] Preferably, step S7 is the activation step of steps S1 to S6, and step S8 is the result step generated after activation by steps S1 to S6.

[0094] It is worth noting that the vehicle continuously activates steps S1 to S6 in different vehicle-occupied areas through the detection in step S7, so as to achieve the effect of real-time updates.

[0095] Furthermore, steps S1 to S8 are vehicle-based control steps, and this embodiment further provides pedestrian-based control steps.

[0096] Specifically, the road lighting fixtures also include several pedestrian lighting fixtures evenly arranged along the sidewalk in the same scenario, and each pedestrian lighting fixture is equipped with a pedestrian detection device.

[0097] Therefore, the control method also includes the following steps:

[0098] Step S10: Divide the sidewalk into several continuous pedestrian zones along the pedestrian radial centerline, with each pedestrian zone including a pedestrian lighting fixture.

[0099] Step S20: Detect the pedestrian area where the current pedestrian is located using all pedestrian detectors and define it as a pedestrian-only area.

[0100] Step S30: Starting from the pedestrian area, turn on or brighten a preset number of pedestrian lighting fixtures in both directions of the pedestrian walkway.

[0101] Preferably, since pedestrians move slower than vehicles, this embodiment directly turns on or brightens a certain number of streetlights (for example, two plots in front of and two plots behind the pedestrian area, for a total of five), or sets the number of streetlights to be turned on or brightened through the steps below, so as to ensure that the sidewalk has good lighting brightness.

[0102] Further, in step S30, a preset number of pedestrian lighting fixtures are turned on or brightened in both directions along the pedestrian walkway, starting from the pedestrian area, including:

[0103] Step S301: Under sunny conditions and with all pedestrian lighting fixtures off, acquire the first image data for each pedestrian area.

[0104] Step S302: Obtain the average brightness of the first image for each first image data using a visual algorithm.

[0105] Step S303: In a nighttime environment with all lighting fixtures on, acquire second image data for each pedestrian area.

[0106] Preferably, the first image data and the second image data can be directly captured by an external camera, and there is no difficulty in acquiring them. However, the same shooting angle should be used as much as possible to ensure the accuracy of subsequent brightness detection.

[0107] Step S304: Obtain the average brightness of the second image for each second image data using a visual algorithm.

[0108] Step S305: Define at least two consecutive brightness ranges in ascending order of visible light brightness values.

[0109] For example, four brightness ranges can be defined sequentially, specifically [0,100), [100,300), [300,500), and [500,+∞), and the threshold values ​​can be adjusted according to actual needs.

[0110] Step S306: Define a viewing distance weighting coefficient for each brightness range. The magnitude of all viewing distance weighting coefficients decreases from low to high as the brightness values ​​of all visible light increase.

[0111] Preferably, since the brightness increases sequentially, the first interval represents the least bright interval, and the weighting coefficients of the four intervals mentioned above can be 4, 3, 2, and 1 respectively.

[0112] Step S307: Classify the average brightness of all first images and the average brightness of all second images into all brightness ranges using a classification algorithm. Obtain a first weight coefficient based on the average brightness of each first image and a second weight coefficient based on the average brightness of each second image.

[0113] Preferably, the classification algorithm in this embodiment uses Naive Bayes classification to prevent subjective errors in manual classification.

[0114] Step S308: Obtain the coefficient difference between the first weight coefficient and the second weight coefficient of the pedestrian area, and determine whether the coefficient difference exceeds the preset difference threshold. If the coefficient difference exceeds the preset difference threshold, then execute step S309.

[0115] Preferably, the preset threshold can be set to half of the median of all weight coefficients. Using the above 4, 3, 2, 1, the median is 2.5, and half of the median is 1.25.

[0116] Step S309: Starting from the pedestrian area, turn on each pedestrian lighting fixture in both directions of the pedestrian walkway until the difference between the light and the coefficient does not exceed the preset difference threshold.

[0117] Preferably, the streetlights around the reference point can enhance the illumination brightness of the reference point.

[0118] Further, in step S302, the average brightness of the first image data for each first image is obtained using a visual algorithm, including:

[0119] Step S3021: Import the cv2 package using Python's import statement.

[0120] Step S3022: Read each first image data and store it in the img variable using the cv2.imread function of the cv2 package.

[0121] Step S3023: Convert all the first image data in the img variable into a first grayscale image and store it in the gray variable using the cv2.cvtColor function of the cv2 package.

[0122] Step S3024: Obtain the first average brightness of each first grayscale image in the gray variable using the cv2.mean function of the cv2 software package and store it in the average_brightness variable.

[0123] Step S3025: Define all first average brightness values ​​in the average_brightness variable as the average brightness value of all first images.

[0124] Preferably, steps S3021 to S3025 can be implemented using the following code:

[0125]

[0126] Further, step S304 involves obtaining the average brightness of the second image for each second image data point using a visual algorithm, including:

[0127] Step S3041: Initialize the img variable, gray variable, and average_brightness variable.

[0128] Step S3042: Read each second image data and store it in the img variable using the cv2.imread function.

[0129] Step S3043: Convert all the second image data in the img variable into a second grayscale image and store it in the gray variable using the cv2.cvtColor function.

[0130] Step S3044: Use the cv2.mean function to obtain the second average brightness of each second grayscale image in the gray variable and store it in the average_brightness variable.

[0131] Step S3045: Define all second average brightness values ​​in the average_brightness variable as the average brightness value of all second images.

[0132] Preferably, the codes for steps S3041 to S3045 are the same as those for steps S3021 to S3025 described above.

[0133] Further, in step S309, starting from the pedestrian area, each pedestrian lighting fixture is turned on sequentially in both directions along the pedestrian walkway until the difference from the coefficient does not exceed a preset difference threshold. Afterwards, the process includes:

[0134] Step S100: Obtain the sunrise time of the area where the scene is located.

[0135] Step S200: Generate a light-off signal based on sunrise time.

[0136] Step S300: Turn off all driving lane lighting fixtures and all pedestrian lighting fixtures according to the closing signal.

[0137] Further, in step S309, starting from the pedestrian area, each pedestrian lighting fixture is turned on sequentially in both directions along the pedestrian walkway until the difference from the coefficient does not exceed a preset difference threshold. Afterwards, the process includes:

[0138] Step S1000: Monitor the lighting intensity of all driving lane lights and all pedestrian lights in real time.

[0139] In step S2000, lane lighting fixtures with zero illumination intensity and sidewalk lighting fixtures with zero illumination intensity are defined as faulty lighting fixtures.

[0140] Step S3000: Obtain the geographical location of the faulty lighting fixture and send it to the external monitoring terminal.

[0141] This embodiment divides the driving lane into several continuous driving areas along the radial centerline of the driving lane, with each driving area including one driving lane lighting fixture; defines a set of several consecutive natural numbers, where each natural number corresponds to a consecutive lighting quantity based on the driving lane lighting fixture; defines a driving speed range with zero as the minimum value and the current road speed limit as the maximum value; divides the driving speed range into several driving speed sub-ranges, each driving speed sub-range corresponding to a consecutive lighting quantity, and the consecutive lighting quantity increases linearly with the driving speed of the driving speed sub-range; obtains the current driving speed of the currently driving vehicle through adjacent driving detection devices; obtains the driving speed sub-range that matches the current driving speed, and the corresponding consecutive lighting quantity; detects the driving area where the currently driving vehicle is located through all driving detection devices and defines it as a vehicle-occupied area; starts from the vehicle-occupied area and turns on or brightens the driving lane lighting fixtures that match the corresponding consecutive lighting quantity along the driving direction of the currently driving vehicle. This embodiment determines the number of streetlights to turn on or brighten by identifying the real-time speed of vehicles, thereby reducing energy waste caused by excessive or continuous lighting and lowering the maintenance and repair costs of the road lighting system.

[0142] like Figure 2 As shown, this embodiment provides an example of a control device for road lighting fixtures. In this embodiment, the control device is applied to the control method described in the above embodiment.

[0143] Specifically, the control device includes a lane division module 1, a continuous illumination quantity definition module 2, a driving speed range definition module 3, a driving speed range division module 4, a current vehicle speed acquisition module 5, a current vehicle speed matching module 6, a vehicle area definition module 7, and a lane lighting fixture activation module 8, which are connected in sequence.

[0144] The system comprises the following modules: Lane Division Module 1 divides the driving lane into several continuous driving areas along the radial centerline of the driving lane, with each driving area including one driving lane lighting fixture; Continuous Illumination Quantity Definition Module 2 defines a set of several consecutive natural numbers, where each natural number corresponds to a continuous illumination quantity based on the driving lane lighting fixture; Driving Speed ​​Range Definition Module 3 defines a driving speed range with zero as the minimum value and the current road speed limit as the maximum value; and Driving Speed ​​Range Division Module 4 divides the driving speed range into several driving speed sub-ranges, each driving speed sub-range corresponding to a continuous illumination quantity, which increases with the driving speed... The vehicle speed sub-range increases linearly, and the number of consecutive lights also increases linearly; the current vehicle speed acquisition module 5 is used to acquire the current vehicle speed through adjacent vehicle detection devices; the current vehicle speed matching module 6 is used to acquire the vehicle speed sub-range that matches the current vehicle speed, as well as the corresponding number of consecutive lights; the vehicle area definition module 7 is used to detect the driving area where the current vehicle is located through all vehicle detection devices and define it as a vehicle area; the lane lighting fixture activation module 8 is used to turn on or brighten the lane lighting fixtures that match the corresponding number of consecutive lights along the driving direction of the current vehicle, starting from the vehicle area.

[0145] Furthermore, the road lighting control system also includes a pedestrian crossing module, a pedestrian zone module, and a pedestrian crossing lighting control module that are electrically connected in sequence; the pedestrian crossing module can be electrically connected to the lane division module 1 or to the lane lighting control module 8.

[0146] The pedestrian walkway division module is used to divide the pedestrian walkway into several continuous pedestrian areas along the pedestrian radial centerline, and each pedestrian area includes a pedestrian walkway lighting fixture; the pedestrian area module is used to detect the pedestrian area where the current pedestrian is located through all pedestrian detection devices and define it as a pedestrian area; the pedestrian walkway lighting fixture control module is used to turn on or brighten a preset number of pedestrian walkway lighting fixtures in both directions of the pedestrian walkway, starting from the pedestrian area.

[0147] Furthermore, the pedestrian lighting control module specifically includes a first row pedestrian lighting control sub-module, a second row pedestrian lighting control sub-module, a third row pedestrian lighting control sub-module, a fourth row pedestrian lighting control sub-module, a fifth row pedestrian lighting control sub-module, a sixth row pedestrian lighting control sub-module, a seventh row pedestrian lighting control sub-module, an eighth row pedestrian lighting control sub-module, and a ninth row pedestrian lighting control sub-module that are electrically connected in sequence; the first row pedestrian lighting control sub-module is electrically connected to the pedestrian area module.

[0148] The system comprises the following modules: The first row of pedestrian lighting control submodules acquires first image data for each pedestrian area under sunny conditions with all pedestrian lights off; the second row uses a visual algorithm to acquire the average brightness of the first image data for each first image; the third row acquires second image data for each pedestrian area under nighttime conditions with all lights on; the fourth row acquires the average brightness of the second image data for each second image using a visual algorithm; the fifth row defines at least two consecutive brightness ranges from low to high based on visible light intensity; and the sixth row defines... A viewing distance weighting coefficient is defined, and the magnitude of all viewing distance weighting coefficients decreases as the value of all visible light brightness increases. The seventh row of the pedestrian lighting fixture control submodule is used to classify the average brightness of all first images and the average brightness of all second images into all brightness intervals using a classification algorithm. A first weighting coefficient is obtained based on the average brightness of each first image, and a second weighting coefficient is obtained based on the average brightness of each second image. The eighth row of the pedestrian lighting fixture control submodule is used to obtain the coefficient difference between the first weighting coefficient and the second weighting coefficient in the pedestrian area and determine whether the coefficient difference exceeds a preset difference threshold. The ninth row of the pedestrian lighting fixture control submodule is used to turn on each pedestrian lighting fixture sequentially in both directions of the pedestrian area if the coefficient difference exceeds the preset difference threshold, until the coefficient difference does not exceed the preset difference threshold.

[0149] Furthermore, the second row of pedestrian lighting control submodule specifically includes a first pedestrian lighting control unit, a second pedestrian lighting control unit, a third pedestrian lighting control unit, a fourth pedestrian lighting control unit, and a fifth pedestrian lighting control unit that are electrically connected in sequence; the first pedestrian lighting control unit is electrically connected to the first row of pedestrian lighting control submodule, and the fifth pedestrian lighting control unit is electrically connected to the third row of pedestrian lighting control submodule.

[0150] The system comprises the following components: a first pedestrian lighting control unit that imports the cv2 software package using Python's import statement; a second pedestrian lighting control unit that reads each first image data and stores it in the img variable using the cv2.imread function of the cv2 software package; a third pedestrian lighting control unit that converts all first image data in the img variable into a first grayscale image and stores it in the gray variable using the cv2.cvtColor function of the cv2 software package; a fourth pedestrian lighting control unit that obtains the first average brightness of each first grayscale image in the gray variable and stores it in the average_brightness variable using the cv2.mean function of the cv2 software package; and a fifth pedestrian lighting control unit that defines all first average brightness values ​​in the average_brightness variable as the average brightness value of all first images.

[0151] Furthermore, the fourth row of pedestrian lighting control submodules specifically includes a sixth pedestrian lighting control unit, a seventh pedestrian lighting control unit, an eighth pedestrian lighting control unit, a ninth pedestrian lighting control unit, and a tenth pedestrian lighting control unit that are connected in sequence. The sixth pedestrian lighting control unit is electrically connected to the third row of pedestrian lighting control submodules, and the tenth pedestrian lighting control unit is electrically connected to the fifth row of pedestrian lighting control submodules.

[0152] The sixth pedestrian lighting control unit is used to initialize the `img`, `gray`, and `average_brightness` variables; the seventh pedestrian lighting control unit is used to read each second image data and store it in the `img` variable using the `cv2.imread` function; the eighth pedestrian lighting control unit is used to convert all second image data in the `img` variable into a second grayscale image and store it in the `gray` variable using the `cv2.cvtColor` function; the ninth pedestrian lighting control unit is used to obtain the second average brightness of each second grayscale image in the `gray` variable and store it in the `average_brightness` variable using the `cv2.mean` function; and the tenth pedestrian lighting control unit is used to define all the second average brightness in the `average_brightness` variable as the average brightness of all second images.

[0153] Furthermore, the control device also includes a scene sunrise time acquisition module, a lamp off signal generation module, and a lighting lamp off module that are electrically connected in sequence; the scene sunrise time acquisition module is electrically connected to the ninth row of pedestrian walkway lighting lamp control submodule.

[0154] The scene sunrise time acquisition module is used to acquire the sunrise time of the area where the scene is located; the lighting fixture turn-off signal generation module is used to generate a lighting fixture turn-off signal based on the sunrise time; and the lighting fixture turn-off module is used to turn off all driving lane lighting fixtures and all pedestrian lighting fixtures according to the turn-off signal.

[0155] Furthermore, the control device also includes a lighting intensity monitoring module, a fault lighting definition module, and a fault lighting transmission module that are connected in sequence; the lighting intensity monitoring module is electrically connected to the ninth row of pedestrian lighting control sub-modules.

[0156] The lighting intensity monitoring module is used to monitor the lighting intensity of all driving lane lighting fixtures and all pedestrian lighting fixtures in real time; the faulty lighting fixture definition module is used to define driving lane lighting fixtures and pedestrian lighting fixtures with zero lighting intensity as faulty lighting fixtures; and the faulty lighting fixture sending module is used to obtain the geographical location of the faulty lighting fixtures and send it to the external monitoring terminal.

[0157] It should be noted that this embodiment is a functional module embodiment based on the above method embodiment. For additional content such as preferred options, extensions, and examples of this embodiment, please refer to the above method embodiment. This embodiment will not repeat them here.

[0158] This embodiment divides the driving lane into several continuous driving areas along the radial centerline of the driving lane, with each driving area including one driving lane lighting fixture; defines a set of several consecutive natural numbers, where each natural number corresponds to a consecutive lighting quantity based on the driving lane lighting fixture; defines a driving speed range with zero as the minimum value and the current road speed limit as the maximum value; divides the driving speed range into several driving speed sub-ranges, each driving speed sub-range corresponding to a consecutive lighting quantity, and the consecutive lighting quantity increases linearly with the driving speed of the driving speed sub-range; obtains the current driving speed of the currently driving vehicle through adjacent driving detection devices; obtains the driving speed sub-range that matches the current driving speed, and the corresponding consecutive lighting quantity; detects the driving area where the currently driving vehicle is located through all driving detection devices and defines it as a vehicle-occupied area; starts from the vehicle-occupied area and turns on or brightens the driving lane lighting fixtures that match the corresponding consecutive lighting quantity along the driving direction of the currently driving vehicle. This embodiment determines the number of streetlights to turn on or brighten by identifying the real-time speed of vehicles, thereby reducing energy waste caused by excessive or continuous lighting and lowering the maintenance and repair costs of the road lighting system.

[0159] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Figure 3As shown, the electronic device 9 includes a processor 91 and a memory 92 coupled to the processor 91.

[0160] The memory 92 stores program instructions for implementing the control method of the lighting fixture in any of the above embodiments.

[0161] The processor 91 is used to execute program instructions stored in the memory 92 to control the road lighting fixtures.

[0162] The processor 91 can also be referred to as a CPU (Central Processing Unit). The processor 91 may be an integrated circuit chip with signal processing capabilities. The processor 91 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0163] Furthermore, Figure 4 This is a schematic diagram of the structure of a storage medium according to an embodiment of this application. See also: Figure 4 The storage medium 10 in this embodiment stores program instructions 101 capable of implementing all the above methods. These program instructions 101 can be stored in the storage medium as a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, or terminal devices such as computers, servers, mobile phones, and tablets.

[0164] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0165] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for controlling road lighting fixtures, wherein the road lighting fixtures include a plurality of lane lighting fixtures evenly arranged along the driving lanes in the same scenario, and each lane lighting fixture is equipped with a vehicle detection device, characterized in that, The control method includes: Step S1: Divide the driving lane into several continuous driving areas along the radial centerline of the driving lane, and each driving area includes a driving lane lighting fixture. Step S2: Define a set of several consecutive natural numbers, where each natural number in the set corresponds to a consecutive number of lights to be turned on based on the driving lane lighting fixtures; Step S3: Define the driving speed range with zero as the minimum value of the range and the current road speed limit as the maximum value of the range; Step S4: Divide the driving speed range into several driving speed sub-ranges. Each driving speed sub-range corresponds to a number of consecutive lights. As the driving speed of the driving speed sub-range increases linearly, the number of consecutive lights also increases linearly. Step S5: Obtain the current driving speed of the currently driving vehicle through adjacent driving detection devices; Step S6: Obtain the driving speed sub-range that matches the current driving speed, and the corresponding number of consecutive lights; Step S7: Detect the driving area where the currently driving vehicle is located using all driving detection devices and define it as a vehicle-occupied area; Step S8: Starting from the area with vehicles, turn on or brighten the lane lighting fixtures that match the corresponding number of consecutive lights along the current driving direction of the vehicles. The road lighting fixtures also include several pedestrian lighting fixtures evenly arranged along the sidewalk in the same scenario, each pedestrian lighting fixture being equipped with a pedestrian detection device. The control method further includes: Step S10: Divide the sidewalk into several continuous pedestrian areas along the pedestrian radial centerline, with each pedestrian area including a sidewalk lighting fixture. Step S20: Detect the pedestrian area where the current pedestrian is located using all pedestrian detectors and define it as a pedestrian-only area; Step S30: Starting from the pedestrian area, turn on or brighten a preset number of pedestrian lighting fixtures in both directions of the pedestrian walkway; Step S30, starting from the pedestrian area, turning on or brightening a preset number of pedestrian lighting fixtures in both directions along the sidewalk, including: Step S301: In a sunny, sunny environment with all pedestrian lighting fixtures off, acquire the first image data for each pedestrian area. Step S302: Obtain the average brightness of the first image for each first image data using a visual algorithm; Step S303: In a nighttime environment with all lighting fixtures on, acquire second image data for each pedestrian area. Step S304: Obtain the average brightness of the second image for each second image data using the visual algorithm; Step S305: Define at least two consecutive brightness ranges in ascending order of visible light brightness values; Step S306: Define a viewing distance weighting coefficient based on each brightness range. The magnitude of all viewing distance weighting coefficients decreases from low to high as the brightness values ​​of all visible light increase. Step S307: Classify the average brightness of all first images and the average brightness of all second images into all brightness ranges using a classification algorithm. Obtain a first weight coefficient based on the average brightness of each first image and a second weight coefficient based on the average brightness of each second image. Step S308: Obtain the coefficient difference between the first weight coefficient and the second weight coefficient of the pedestrian area, and determine whether the coefficient difference exceeds a preset difference threshold. If the coefficient difference exceeds the preset difference threshold, then execute step S309. Step S309: Starting from the pedestrian area, turn on each pedestrian lighting fixture in both directions of the pedestrian walkway until the difference between the lighting fixture and the coefficient does not exceed the preset difference threshold.

2. The control method according to claim 1, characterized in that, Step S302, obtaining the average brightness of the first image for each first image data using a visual algorithm, including: Step S3021: Import the cv2 package using Python's import statement; Step S3022: Read each first image data and store it in the img variable using the cv2.imread function of the cv2 software package; Step S3023: Convert all the first image data in the img variable into a first grayscale image and store it in the gray variable using the cv2.cvtColor function of the cv2 software package; Step S3024: Obtain the first average brightness of each first grayscale image in the gray variable using the cv2.mean function of the cv2 software package and store it in the average_brightness variable; Step S3025: Define all first average brightness values ​​in the average_brightness variable as the average brightness value of all first images.

3. The control method according to claim 2, characterized in that, Step S304, obtaining the average second image brightness of each second image data using the visual algorithm, including: Step S3041: Initialize the img variable, the gray variable, and the average_brightness variable; Step S3042: Read each second image data and store it in the img variable using the cv2.imread function; Step S3043: Convert all the second image data in the img variable into a second grayscale image and store it in the gray variable using the cv2.cvtColor function; Step S3044: Obtain the second average brightness of each second grayscale image in the gray variable using the cv2.mean function and store it in the average_brightness variable; Step S3045: Define all the second average brightness values ​​in the average_brightness variable as the average brightness value of all second images.

4. The control method according to claim 1, characterized in that, Step S309: Starting from the pedestrian area, sequentially turn on each pedestrian lighting fixture along both directions of the pedestrian walkway until the difference between the light fixture and the coefficient does not exceed a preset difference threshold. Afterwards, the process includes: Step S100: Obtain the sunrise time of the area where the scene is located; Step S200: Generate a light-off signal based on the sunrise time; Step S300: Turn off all driving lane lighting fixtures and all pedestrian lighting fixtures according to the shutdown signal.

5. The control method according to claim 1, characterized in that, Step S309: Starting from the pedestrian area, sequentially turn on each pedestrian lighting fixture along both directions of the pedestrian walkway until the difference between the light fixture and the coefficient does not exceed a preset difference threshold. Afterwards, the process includes: Step S1000: Monitor the lighting intensity of all driving lane lights and all pedestrian lights in real time; Step S2000: Define the driving lane lighting fixtures and the pedestrian lighting fixtures with zero illumination intensity as faulty lighting fixtures; Step S3000: Obtain the geographical location of the faulty lighting fixture and send it to the external monitoring terminal.

6. A control device for a road lighting fixture, wherein the control device is applied to the control method as described in any one of claims 1 to 5, characterized in that, The control device includes: The lane division module is used to divide the lane into several continuous driving areas along the radial centerline of the driving lane, and each driving area includes a driving lane lighting fixture. The continuous lighting quantity definition module is used to define a set of several consecutive natural numbers, wherein each natural number in the set corresponds to a continuous lighting quantity based on the driving lane lighting fixtures; The vehicle speed range definition module is used to define a vehicle speed range with zero as the minimum value and the current road speed limit as the maximum value. The driving speed range division module is used to divide the driving speed range into several driving speed sub-ranges on an average basis. Each driving speed sub-range corresponds to a number of consecutive lights. As the driving speed of the driving speed sub-range increases linearly, the number of consecutive lights also increases linearly. The current vehicle speed acquisition module is used to acquire the current vehicle speed through adjacent vehicle detection devices; The current vehicle speed matching module is used to obtain the vehicle speed sub-range that matches the current driving speed, as well as the corresponding number of consecutive lights; The vehicle area definition module is used to detect the driving area where the currently driving vehicle is located through all driving detection devices and define it as a vehicle area. The lane lighting activation module is used to turn on or brighten lane lighting fixtures that match the corresponding number of consecutive lights, starting from the area with vehicles and moving along the direction of travel of the currently traveling vehicles.

7. An electronic device, characterized in that, The system includes a processor and a memory coupled to the processor, the memory storing program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the control method as described in any one of claims 1 to 5.

8. A storage medium, characterized in that, The storage medium stores program instructions, which, when executed by a processor, can implement the control method as described in any one of claims 1 to 5.

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