A smart street lamp control method, system, electronic device and storage medium

Abstract

The present application relates to a smart street light control method, system, electronic device and storage medium, which belongs to the field of street light control technology. The method includes: determining a target road section based on real-time driving data and historical driving data, the target road section is a road section to be adjusted in brightness; determining a target street light based on visual perception information and street light distribution information of the target road section, the target street light is a street light to be adjusted in brightness, and the visual perception information is used to reflect the visible range of the driver on the target road section; generating a brightness strategy based on environmental parameters and the brightness parameters of the target street light, and the brightness parameters are used to reflect the light intensity that the target street light can provide to the target road section. The present application can first locate the target road section, then locate the target street light on the target road section, and ensure the light intensity of the target road section by adjusting the brightness of the target street light in special weather conditions, which has the effect of ensuring nighttime traffic safety.

Description

Technical Field

[0001] The present application relates to the field of street lamp control technology, and in particular to a smart street lamp control method, system, electronic device and storage medium. Background Art

[0002] In extreme weather conditions such as haze and heavy fog, the amount of particulate matter or water vapor in the environment increases, resulting in low visibility on the road, which seriously hinders drivers from obtaining effective visual information when driving at night. In particular, the vision at special sections such as intersections, roundabouts, and turns is severely obstructed, making it impossible for drivers to accurately judge the distance to surrounding vehicles and effectively identify road traffic facilities, making it easy for drivers to make wrong judgments on vehicle speed and distance, increasing the risk of traffic accidents. Summary of the invention

[0003] The present application provides a smart street light control method, system, electronic device and storage medium, which have the characteristics of improving the light intensity for nighttime traffic under extreme weather conditions.

[0004] In a first aspect of the present application, a smart street lamp control method is provided, the method comprising:

[0005] Determine a target road section according to real-time driving data and historical driving data, wherein the target road section is a road section to be brightness adjusted;

[0006] Determining a target street lamp according to visual perception information and street lamp distribution information of the target road section, wherein the target street lamp is a street lamp whose brightness is to be adjusted, and the visual perception information is used to reflect the visual range of a driver on the target road section;

[0007] A brightness strategy is generated according to the environmental parameters and the brightness parameters of the target street lamp, where the brightness parameters are used to reflect the light intensity that the target street lamp can provide to the target road section.

[0008] By adopting the above technical solution, the road section to be adjusted for brightness is first determined based on real-time driving data and historical driving data, and then the street lights that need to be adjusted for brightness are determined based on the distribution of street lights on the road section and the visual perception information of the drivers on the road section. Finally, a brightness strategy is generated based on the determined brightness parameters of the street lights and the current environmental parameters, and the target street lights on the target road section are adjusted through the brightness strategy to ensure that in extreme weather, the light intensity during nighttime traffic can be met by adjusting only some street lights.

[0009] In a possible implementation manner: determining the target streetlight according to the visual perception information and the streetlight distribution information of the target road section includes:

[0010] Determine a sight distance according to the visual perception information, wherein the sight distance is the farthest visible distance of a driver on the target road section;

[0011] Determining a distribution shape according to the street lamp distribution information of the target road section;

[0012] A target street lamp is determined according to the distribution shape and the sight distance.

[0013] In a possible implementation manner, the distribution shape includes a T-shaped distribution, and determining the target street lamp according to the distribution shape and the sight distance includes:

[0014] The street lamp at the T-shaped intersection is determined as the reference street lamp;

[0015] Taking street lamps whose interval from the reference street lamp is an integer multiple of the sight distance as reference street lamps;

[0016] The benchmark streetlight and the reference streetlight are determined as the target streetlight.

[0017] In a possible implementation, the distribution shape includes a linear distribution, and determining the target street lamp according to the distribution shape and the sight distance includes:

[0018] Extracting streetlights on each side of the target road section at intervals of the sight distance;

[0019] The extracted streetlight is determined as the target streetlight.

[0020] By adopting the above technical scheme, different target street lamps are selected according to the distribution shape of the street lamps on the target road section. On the one hand, by adjusting the light intensity provided to the target road section by the target street lamps, the light intensity of the road surface is guaranteed to meet the traffic lighting. On the other hand, because only the target street lamps are adjusted, the adjustment of all street lamps on all road sections is avoided, which plays a role in saving the energy consumption of street lamps.

[0021] In a possible implementation, the brightness parameter includes a lighting coverage range and a luminous intensity range, and the step of generating a brightness strategy according to the environmental parameter and the brightness parameter of the target street lamp includes:

[0022] Calculating a target height of the target street lamp according to the illumination coverage range, wherein the target height refers to a height when the illumination coverage range of the target street lamp overlaps with the illumination coverage range of an adjacent street lamp;

[0023] Calculating the target luminous intensity of the target street lamp according to the environmental parameters and the luminous intensity range, the target luminous intensity refers to the light intensity of the road surface that satisfies the traffic light when the light source of the target street lamp projects light from the target height onto the road surface, and the traffic light refers to the light intensity when the driver's vision is blocked to a degree that does not affect the traffic;

[0024] The brightness strategy is generated according to the target street lamp and the target height and target luminous intensity of the target street lamp.

[0025] By adopting the above technical solution, when adjusting the target street lamp, not only the illumination coverage of the target street lamp can be adjusted, because if the illumination coverage of two street lamps with the same luminous intensity overlaps, the illumination intensity of the overlapping part is higher than the illumination intensity of the non-overlapping part. This principle can be used to increase the illumination intensity provided to the target road section by the target street lamp. At the same time, the illumination intensity provided to the target road section can also be increased by adjusting the luminous intensity of the target street lamp. In other words, by doubly adjusting the target street lamp, the illumination intensity of the road surface can meet the traffic illumination, so as to ensure the safe passage of vehicles in extreme weather.

[0026] In a possible implementation manner: the calculating the target height of the target street lamp according to the illumination coverage range includes:

[0027] Obtaining the illumination coverage of the target street lamp;

[0028] When the illumination coverage range of the target street lamp overlaps the illumination coverage range of the adjacent street lamp to 1 / 4, the target height of the target street lamp is obtained.

[0029] By adopting the above technical solution, as the target street lamp gradually rises, its illumination coverage gradually increases, but the farther away from the road surface, the greater the illumination intensity that needs to be provided to the road surface, and the higher the energy consumption. Therefore, in this application, when the illumination coverage of the target street lamp overlaps with the illumination coverage of the adjacent street lamp to 1 / 4, the height at this time is used as the target height of the target street lamp, so that the illumination coverage of the two street lamps overlaps, and the illumination intensity of the overlapping part compensates for the light intensity lost due to the increase in height, thereby reducing the number of street lamps that adjust the brightness, achieving the purpose of saving energy consumption while meeting the illumination intensity when passing at night.

[0030] In a possible implementation, the step of determining the target road section according to the real-time driving data and the historical driving data includes:

[0031] Determine the congested road section according to the traffic volume and vehicle speed of the real-time driving data;

[0032] Determining, based on the historical driving data, a road section where a frequency of traffic accidents occurs that is higher than a preset frequency threshold;

[0033] The vehicle congested road section and the road section where the frequency of traffic accidents is higher than a preset frequency threshold are determined as the target road section.

[0034] By adopting the above technical solution, congested sections and sections with frequent traffic accidents are identified as target sections, which facilitates the subsequent targeted brightness control of street lights on the target sections, thereby ensuring the light intensity when traveling on the target sections at night.

[0035] In a second aspect of the present application, a smart street light control system is provided, the system comprising:

[0036] A first determination module, used to determine a target road section according to real-time driving data and historical driving data, wherein the target road section is a road section to be brightness adjusted;

[0037] A second determination module is used to determine a target street lamp according to visual perception information and street lamp distribution information of the target road section, wherein the target street lamp is a street lamp whose brightness is to be adjusted, and the visual perception information is used to reflect the visual range of a driver on the target road section;

[0038] The data generation module is used to generate a brightness strategy according to the environmental parameters and the target street lamp and the brightness parameters of the target street lamp, wherein the brightness parameters are used to reflect the light intensity that the target street lamp can provide to the target road section.

[0039] In a third aspect of the present application, a smart street light control device is provided, the device comprising: a memory and a processor, the memory storing a computer program, and the processor implementing any of the above-mentioned smart street light control methods when executing the program.

[0040] In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, any of the above-mentioned smart street lamp control methods is implemented.

[0041] In summary, the present application includes the following beneficial technical effects:

[0042] In extreme weather conditions, congested sections and sections with frequent traffic accidents are marked as target sections. Then, based on the distribution of street lights on the target sections and the visual perception of drivers on the sections, the street lights that need to be adjusted in brightness are determined, i.e., the target street lights. Finally, based on the brightness parameters of the target street lights and the current environmental parameters, a brightness strategy is generated. The target street lights on the target sections are adjusted through the brightness strategy to ensure that in extreme weather conditions, only some street lights can be adjusted to meet the light intensity required for nighttime traffic. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1A schematic diagram of an exemplary operating environment of an embodiment of the present application.

[0044] Figure 2 for Figure 1 The street light structure diagram in the operating environment.

[0045] Figure 3 This is a flow chart of a smart street light control method according to an embodiment of the present application.

[0046] Figure 4 This is a block diagram of a smart street light control system according to an embodiment of the present application.

[0047] Explanation of the accompanying drawings: 1. Street light control system; 11. First determination module; 12. Second determination module; 13. Data generation module; 2. Street light system; 21. Light source; 22. Lamp housing; 23. Lamp pole; 24. Control box; 3. Data acquisition system. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] Figure 1 A schematic diagram of an exemplary operating environment in which the embodiments of the present application can be implemented is shown, and the operating environment includes a street light control system 1 and a street light system 2 that communicates with the street light control system 1 through PLC dual-mode communication technology. The operating environment also includes a data acquisition system 3 that is connected to the street light control system 1 through a wireless network, and the wireless network can be a wide-area Internet of Things system based on 4G network or 5G network, etc., or a local Internet of Things.

[0050] The street light control system 1 is composed of one or more servers. The street light control system 1 can control the street light system 2 according to weather conditions, so that the street light system 2 can adaptively switch lighting modes under different weather conditions.

[0051] like Figure 2As shown, the street lamp system 2 is composed of a plurality of street lamps, and the plurality of street lamps are distributed on both sides of the road. Each street lamp includes a light source 21, a lamp housing 22 and a lamp pole 23. The light source 21 is installed in the lamp housing 22, and the lamp pole 23 is used to fix the lamp housing 22 and the light source 21 above the road. In a specific example, the lamp pole 23 is a retractable lamp pole 23. For example, a cylinder is connected to the end of the lamp pole 23 close to the road, and the cylinder is used to support the lamp pole 23 to do lifting and lowering movements. At the same time, each street lamp is also equipped with a control box 24, which is usually installed on the end of the lamp pole 23 close to the road. A PLC dual-mode communication module and a control chip are arranged in the control box 24. The control chip is such as an MCU chip, an FPGA chip or a DSP chip. The control chip is connected to the street lamp control system 1 through the PLC dual-mode communication module, and is used to receive downlink instructions from the street lamp control system 1, and control the light source 21 to emit light according to the downlink instructions. In addition, the control chip can also control the cylinder to start, and the cylinder starts to drive the lamp pole 23 to do lifting movement, thereby driving the light source 21 to do lifting movement, thereby increasing or reducing the light coverage of the street lamp on the road surface.

[0052] It should be noted that each street lamp has a unique corresponding number, and the control chip located in the street lamp only receives downlink instructions with the same number. If the number in the downlink instruction is inconsistent with the number of the street lamp where the control chip is located, the control chip will forward the downlink instruction to the control chip adjacent to it without making other lighting mode adjustments. In this example, the light source 21 has multiple gears, and the difference between each gear is 1000 lux. The control chip can control the light source 21 to switch between different gears. The larger the gear, the greater the loss to the light source 21 itself, but the greater the luminous intensity. Therefore, on nights with good weather, try to minimize adjusting the light source 21 to a high position, and in extreme weather, it is necessary to sacrifice some energy consumption to increase the light intensity of the road in order to provide lighting for vehicles.

[0053] The data acquisition system 3 is composed of electronic devices such as haze sensors, temperature and humidity sensors, and light sensors. The haze sensors, temperature and humidity sensors, and light sensors are installed on both sides of the road and are located close to the lamp poles 23. The data acquisition system 3 is used to collect environmental parameters such as haze concentration, fog concentration, and light intensity on the road in real time, and upload them to the street light control system 1 in real time through the PLC dual-mode communication module.

[0054] Figure 3 A flow chart of a smart street lamp control method according to an embodiment of the present application is shown. The method is applied in a street lamp control system 1. The following is a description of the main process of the method.

[0055] Step S1: determining a target road section according to real-time driving data and historical driving data, where the target road section is the road section to be brightness adjusted.

[0056] When night falls, the street light control system 1 sends a low-energy consumption instruction to the street light system 2. The low-energy consumption instruction is a kind of instruction in the downlink instruction. Each control chip receives the low-energy consumption instruction to turn on the light source 21, and the light source 21 illuminates the road surface. At this time, the light source 21 is in a low gear. During this period, the data acquisition system 3 collects the visibility of the road surface in real time. Visibility refers to the ratio of the light intensity of the road surface to the haze concentration or the ratio of the light intensity of the road surface to the fog concentration. The light intensity of the road surface is collected by the light sensor, the haze concentration is collected by the haze sensor, and the fog concentration is collected by the temperature and humidity sensor. Based on the obtained visibility of the road surface, the relationship between the visibility and the preset visibility is determined. The preset visibility is a visibility threshold set in advance, which means that when the visibility is above the visibility threshold, the degree of obstruction of the driver's vision does not affect the passage. The visibility threshold can be calculated through a limited number of tests. The corresponding light intensity at the visibility threshold is also referred to as the traffic light. Therefore, when the visibility of the road surface is higher than the preset visibility, the street lamp system 2 maintains the current low-energy consumption lighting mode. Otherwise, when the visibility of the road surface is lower than the preset visibility, the real-time driving data and historical driving data of the road are retrieved.

[0057] Among them, real-time driving data refers to the vehicle traffic conditions on the road at the current time, including traffic volume and vehicle speed, which are collected by cameras and speedometers on the road. Generally, when the visibility of the road is lower than the preset visibility, the driver's vision is blocked and the speed decreases. When the traffic volume increases, the number of vehicles on the road also increases, causing road congestion. In this example, the congested section is determined as the target section.

[0058] Historical driving data includes but is not limited to information such as the frequency of traffic accidents on the road in the past and the time when traffic accidents occurred. In this example, the road sections where the frequency of traffic accidents is higher than the preset frequency threshold are also used as target sections. The preset frequency threshold is also set in advance. In this example, the preset frequency threshold is set to 5 times / month.

[0059] That is to say, the target road sections include congested sections and sections where traffic accidents occur more frequently.

[0060] Step S2: determining a target streetlight according to the visual perception information and the streetlight distribution information of the target road section, wherein the target streetlight is the streetlight whose brightness is to be adjusted, and the visual perception information is used to reflect the visual range of the driver on the target road section.

[0061] First, the sight distance is determined based on visual perception information, which is the environmental level given by drivers on the target road section according to the current environmental conditions.

[0062] In a specific example, first, multiple images related to the environment are sent to the vehicle terminal or mobile phone terminal of the driver on the target road section. The distance between the object displayed on each image and the camera and / or the clarity of the object are different. For example, a road sign is set at 5 meters from the camera. The camera shoots the road sign at this distance and sets different clarity. The distance between the camera and the road sign can also be set to 6, 7, ..., 20 meters, etc., to obtain multiple images with different clarity at the same distance, and multiple images with different distances but possibly the same clarity. Then, the driver selects one or more images similar to the environment in which he is located according to the environment in which he is located, and uploads the selected images to the street light control system 1. Finally, the street light control system 1 uses the pre-trained neural network model to match the images selected by multiple drivers to obtain the line of sight distance corresponding to each image. Specifically, a large number of images taken by the camera in an environment with different visibility are used as training samples. Each image taken has a corresponding visibility, that is, a corresponding visible distance, which is also the farthest visible distance of the driver on the target road section. The neural network model is trained using training samples, and the maximum number of iterations and loss function of the model are set. When the training reaches the maximum number of iterations or the loss function reaches a preset value, the training is completed. Therefore, the visual distance corresponding to each image is matched by the trained neural network model, and the street light control system 1 calculates the mean of the visual distance and uses the mean as the sight distance of the visual perception information.

[0063] The distribution shape is determined based on the street light distribution information of the target road section. Since the target road section is often distributed in T-shaped, straight-line, cross-shaped and roundabout shapes, and the cross-shaped shape is composed of two straight-line sections, the cross-shaped shape can also be identified as two straight-line shapes. Because the street lights are arranged on both sides of the target road section, the distribution shape of the street lights depends on the distribution mode of the target road section, that is, the street lights are divided into three distribution shapes: T-shaped distribution, straight-line distribution and circular distribution. The following specifically describes the process of determining the target street lights for each distribution shape.

[0064] When the distribution shape is a T-shaped distribution, the street lamp at the intersection of the T-shaped distribution is determined as the benchmark street lamp, and the street lamps with an integral multiple of the sight distance from the benchmark street lamp are used as reference street lamps, for example, street lamps with a sight distance of 1 times, 2 times, ..., n times from the benchmark street lamp are used as reference street lamps, n ≥ 2, but the reference street lamps are still located in the target road section. Finally, the obtained benchmark street lamps and reference street lamps are determined as target street lamps.

[0065] When the distribution shape is a linear distribution, street lamps on each side of the target road section are extracted at intervals of sight distance, and the extracted street lamps are determined as target street lamps.

[0066] When the distribution shape is a circular distribution, the street light at the center of the circle is determined as the central street light, that is, the street light at the center of the roundabout is taken as the central street light, and then the street lights on the outer circumference of the circle are extracted at intervals of line of sight to obtain the peripheral street lights, and the central street lights and the peripheral street lights are determined as the target street lights.

[0067] It should be noted that in the above three distribution forms, if one end point of the line of sight distance is determined, for example, the reference street light and the central street light are determined first, and there is no street light at the other end point, then the street light with the shortest distance to the determined street light end point will be selected as the street light, for example, the street light with the shortest distance to the reference street light will be used as the reference street light, and the street light with the shortest distance to the central street light will be used as the peripheral street light.

[0068] It can be seen from this that for target road sections with different distribution shapes of street lights, the target street lights determined may be different, and only some street lights in the target road section are extracted as target street lights.

[0069] Step S3: Generate a brightness strategy according to the environmental parameters and the brightness parameters of the target street lamp, where the brightness parameters are used to reflect the light intensity that the target street lamp can provide to the target road section.

[0070] Environmental parameters have been introduced in the above-mentioned operating environment embodiments, and include but are not limited to data such as haze concentration, fog concentration, and light intensity. Brightness parameters include the illumination coverage range and luminous intensity range of the target street lamp. The light coverage range refers to the range of the road surface illuminated by the street lamp, which is related to the height of the lamp pole 23 of the street lamp. The higher the lamp pole 23, the larger the light coverage range. The luminous intensity range refers to the adjustable range of the light emitted by the lamp source 21 of the street lamp, which is related to the gear position of the lamp source 21. The illumination corresponding to the lowest gear to the highest gear refers to the luminous intensity range. When adjusting the target street lamp, it can only be adjusted within the luminous intensity range.

[0071] Specifically, the target height of the target street lamp is first calculated based on the illumination coverage. The target height refers to the height when the illumination coverage of the target street lamp overlaps with the illumination coverage of the adjacent street lamp. The specific overlap is 1 / 4 of the illumination coverage of the target street lamp, that is, the illumination coverage of the target street lamp and one of the adjacent street lamps must reach 1 / 4 of the illumination coverage of the target street lamp, so that the illumination intensity of the overlapping part is higher than that of the non-overlapping part, thereby enhancing the illumination intensity provided to the target road section. Then, the target luminous intensity of the target street lamp is calculated based on the environmental parameters and the illumination intensity range. The target luminous intensity refers to the illumination intensity of the road surface when the luminous intensity of the target street lamp is projected from the target height to the road surface, and the traffic illumination refers to the illumination intensity when the degree of obstruction of the driver's vision does not affect the passage.

[0072] Finally, the street light control system 1 generates a brightness strategy based on the target street light, the target height of the target street light, and the target luminous intensity, specifically generating an adjustment instruction, which is also a type of instruction in the downlink instruction. Specifically, the adjustment instruction contains the number of the target street light, the target height, and the target luminous intensity. After the street light control system 1 sends the adjustment instruction through the PLC dual-mode communication module, the adjustment instruction is transmitted in the entire street light system 2. The control chip in the street light system 2 recognizes the adjustment instruction. When the number contained in the adjustment instruction is consistent with the number of the street light controlled by the control chip, the street light it controls is adjusted according to the target height and target luminous intensity. Otherwise, the control chip forwards the adjustment instruction to the control chip adjacent to it, thereby quickly adjusting the light intensity provided to the road surface by the target street light.

[0073] To summarize, the implementation principle of a smart street lamp control method in an embodiment of the present application is as follows: in extreme weather, congested sections and sections where traffic accidents frequently occur are marked as target sections, and then some street lamps are selected as target street lamps based on the distribution shape of the street lamps on the target sections and the driver's visual perception information, and then the target height and target luminous intensity of the target street lamps are calculated, so as to adjust the height of the target street lamp to the target height and adjust the luminous intensity of the target street lamp to the target luminous intensity. This not only improves the visibility of the road to above the preset visibility, improves the driver's effective line of sight, and ensures driving safety, but also reduces the energy consumption of the street lamps because only some of the street lamps are turned on, thereby saving the energy consumption of the street lamps.

[0074] Figure 4 A block diagram of a smart street light control system according to an embodiment of the present application is shown, the system comprising a first determination module 11, a second determination module 12 and a data generation module 13.

[0075] The first determination module 11 is used to determine a target road section according to real-time driving data and historical driving data, where the target road section is a road section to be brightness adjusted.

[0076] The second determination module 12 is used to determine the target streetlight according to the visual perception information and the streetlight distribution information of the target road section. The target streetlight is the streetlight whose brightness is to be adjusted. The visual perception information is used to reflect the visual range of the driver on the target road section.

[0077] The data generation module 13 is used to generate a brightness strategy according to the environmental parameters and the target street lamp and the brightness parameters of the target street lamp, where the brightness parameters are used to reflect the light intensity that the target street lamp can provide to the target road section.

[0078] The modules involved in the embodiments described in the present application may be implemented by software or hardware. The modules described may also be set in a processor, for example, it may be described as: a processor includes a first determination module 11, a second determination module 12 and a data generation module 13. The names of these modules do not constitute a limitation on the modules themselves in some cases, for example, the first determination module 11 may also be described as "a module for determining a target road section based on real-time driving data and historical driving data".

[0079] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0080] In order to better execute the program of the above method, the present application also provides an electronic device, which includes a memory and a processor.

[0081] The memory may be used to store instructions, programs, codes, code sets or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the above-mentioned smart street light control method, etc.; the data storage area may store data involved in the above-mentioned smart street light control method, etc.

[0082] The processor may include one or more processing cores. The processor calls the data stored in the memory by running or executing the instructions, programs, code sets or instruction sets stored in the memory, performs various functions of the present application and processes data. The processor may be at least one of a special purpose integrated circuit, a digital signal processor, a digital signal processing device, a programmable logic device, a field programmable gate array, a central processing unit, a controller, a microcontroller and a microprocessor. It is understandable that for different devices, the electronic device used to implement the above-mentioned processor function can also be other, and the embodiments of the present application are not specifically limited.

[0083] The present application also provides a computer-readable storage medium, for example, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes. The computer-readable storage medium stores a computer program that can be loaded by a processor and execute the above-mentioned smart street light control method.

[0084] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present application (but not limited to) by each other to form a technical solution.

Claims

1. A smart street lamp control method, characterized in that: include: Determine a target road section according to real-time driving data and historical driving data, wherein the target road section is a road section to be brightness adjusted; Determining a target street lamp according to visual perception information and street lamp distribution information of the target road section, wherein the target street lamp is a street lamp whose brightness is to be adjusted, and the visual perception information is used to reflect the visual range of a driver on the target road section; Generate a brightness strategy according to the environmental parameters and the brightness parameter of the target street lamp, wherein the brightness parameter is used to reflect the light intensity that the target street lamp can provide to the target road section; The brightness parameters include a lighting coverage range and a luminous intensity range, and the generating of a brightness strategy according to the environmental parameters and the brightness parameters of the target street lamp includes: Calculating a target height of the target street lamp according to the illumination coverage range, wherein the target height refers to a height when the illumination coverage range of the target street lamp overlaps with the illumination coverage range of an adjacent street lamp; Calculating the target luminous intensity of the target street lamp according to the environmental parameters and the luminous intensity range, the target luminous intensity refers to the light intensity of the road surface when the light source (21) of the target street lamp projects light from the target height onto the road surface to meet the traffic light requirement, and the traffic light requirement refers to the light intensity when the driver's vision is blocked to a degree that does not affect the driver's traffic; The brightness strategy is generated according to the target street lamp and the target height and target luminous intensity of the target street lamp.

2. The smart street light control method according to claim 1, characterized in that: The step of determining the target streetlight according to the visual perception information and the streetlight distribution information of the target road section includes: Determine a sight distance according to the visual perception information, wherein the sight distance is the farthest visible distance of a driver on the target road section; Determining a distribution shape according to the street lamp distribution information of the target road section; A target street lamp is determined according to the distribution shape and the sight distance.

3. The intelligent street light control method according to claim 2, characterized in that: The distribution shape includes a T-shaped distribution, and determining the target street lamp according to the distribution shape and the sight distance includes: The street lamp at the T-shaped intersection is determined as the reference street lamp; Taking street lamps whose interval from the reference street lamp is an integer multiple of the sight distance as reference street lamps; The benchmark streetlight and the reference streetlight are determined as the target streetlight.

4. The smart street light control method according to claim 2, characterized in that: The distribution shape includes a linear distribution, and determining the target street lamp according to the distribution shape and the sight distance includes: Extracting streetlights on each side of the target road section at intervals of the sight distance; The extracted streetlight is determined as the target streetlight.

5. The smart street light control method according to claim 1, characterized in that: The calculating the target height of the target street lamp according to the illumination coverage range includes: Obtaining the illumination coverage of the target street lamp; When the illumination coverage range of the target street lamp overlaps the illumination coverage range of the adjacent street lamp to 1 / 4, the target height of the target street lamp is obtained.

6. The intelligent street light control method according to claim 1, characterized in that: Determining the target road section according to the real-time driving data and the historical driving data includes: Determine the congested road section according to the traffic volume and vehicle speed of the real-time driving data; Determining, based on the historical driving data, a road section where a frequency of traffic accidents occurs that is higher than a preset frequency threshold; The congested road section and the road section where the frequency of traffic accidents is higher than a preset frequency threshold are determined as the target road section.

7. A smart street light control system, used to execute the smart street light control method according to any one of claims 1 to 6, characterized in that: include: A first determination module (11) is used to determine a target road section according to real-time driving data and historical driving data, wherein the target road section is a road section to be brightness adjusted; A second determination module (12) is used to determine a target street lamp according to visual perception information and street lamp distribution information of the target road section, wherein the target street lamp is a street lamp whose brightness is to be adjusted, and the visual perception information is used to reflect the visual range of a driver on the target road section; A data generation module (13) is used to generate a brightness strategy based on environmental parameters and the target street lamp and brightness parameters of the target street lamp, wherein the brightness parameters are used to reflect the light intensity that the target street lamp can provide to the target road section.

8. An electronic device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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