Intelligent lighting control method and system along urban traffic road

Abstract

The invention provides an urban traffic road line intelligent lighting control method and system, and the method comprises the steps: carrying out the big data analysis of an urban traffic road network, obtaining the traffic flow state information of the road network, and recognizing a target road line region needing the active lighting adjustment; object existence state information is visually identified from the area along the target road, so that a sub-area needing illumination adjustment is determined, and accurate position guidance is provided for follow-up illumination equipment to carry out directional illumination adjustment on the area along the target road; and based on the distribution position information of all the illumination devices in the area along the target road and the sub-area needing illumination adjustment, identifying the matched illumination device for performing illumination adjustment on the sub-area needing illumination adjustment, and adjusting the illumination state of the matched illumination device on the sub-area in combination with the illumination feature information of the matched illumination device. The traffic condition of the urban traffic road is effectively combined to accurately adjust the work of the lighting equipment along the road, and the intelligent lighting control of the area along the road is realized.

Description

Technical Field

[0001] The present invention relates to the field of smart city management, and in particular to a smart lighting control method and system along urban traffic roads. Background Art

[0002] As a vehicle driving road, urban traffic roads have specific requirements for lighting. Under normal circumstances, if the traffic volume of a certain traffic road can maintain a high level for a long time, at this time, even if the street lamp equipment along the road is damaged and cannot be illuminated normally at night, the corresponding lighting requirements can be met by relying solely on the headlights of vehicles traveling on the traffic road, and there is no need to increase the luminous intensity of the street lamp equipment; if the traffic volume of a certain traffic road continues to be at a low level, the headlights of vehicles traveling on the traffic road cannot meet the most basic lighting needs. At this time, it is necessary to make targeted lighting adjustments to the street lamp equipment, maximize the lighting function of the street lamp equipment under the limited lighting capacity of the street lamp equipment, and ensure that effective lighting conditions can be maintained along the traffic road. The existing technology lacks a lighting adjustment control solution for urban traffic roads, and cannot effectively adjust the work of the street lamp equipment along the road in combination with the traffic conditions of urban traffic roads, and cannot achieve intelligent and efficient lighting control of the areas along the road. Summary of the invention

[0003] The purpose of the present invention is to provide a smart lighting control method and system along urban traffic roads, conduct big data analysis on the urban traffic road network, obtain road network traffic status information, thereby identifying target road areas that need active lighting adjustment, and identify different road areas in combination with road traffic conditions to determine areas where there is a need for auxiliary lighting equipment; visually identify the existence status information of objects in the target road area to determine the sub-area where the lighting needs to be adjusted, and provide accurate position guidance for subsequent lighting equipment to perform directional lighting adjustments on the target road area; also based on the distribution position information of all lighting equipment in the target road area and the sub-area where the lighting needs to be adjusted, identify matching lighting equipment for lighting adjustment of the sub-area where the lighting needs to be adjusted, and adjust its lighting status for the sub-area in combination with its lighting feature information, effectively combine the traffic conditions of the urban traffic roads to accurately adjust the operation of the lighting equipment along the road, and realize intelligent lighting control of the road area.

[0004] The present invention is achieved through the following technical solutions: The intelligent lighting control method along the urban traffic road includes: Performing big data analysis on the urban traffic road network to obtain traffic status information of the road network; based on the traffic status information of the road network, identifying target road areas within the urban traffic road network that require active lighting adjustment; Performing visual recognition on the target road area to obtain object existence status information in the target road area; based on the object existence status information, identifying a sub-area within the target road area that needs to adjust lighting; Based on the distribution position information of all lighting devices in the area along the target road and the sub-area that needs lighting adjustment, identify the matching lighting device for lighting adjustment of the sub-area that needs lighting adjustment; based on the lighting characteristic information of the matching lighting device, adjust the lighting state of the sub-area that needs lighting adjustment by the matching lighting device.

[0005] Optionally, a big data analysis is performed on the urban traffic road network to obtain the road network traffic state information; based on the road network traffic state information, target road areas within the urban traffic road network that require active lighting adjustment are identified, including: Based on the location information of the urban traffic road network, traffic big data of the urban traffic road network corresponding to a preset time interval is obtained; wherein the traffic big data includes global vehicle travel path big data and global vehicle travel speed big data within the urban traffic road network; the traffic big data is analyzed to obtain the traffic density change state information of all road sections within the urban traffic road network, and use it as the traffic state information of the road network; wherein the traffic density change state information includes the change information of the number of vehicles within a unit length range in each road section over time; Based on the traffic density change status information and vehicle lighting range information of all road sections, determine whether the area along each road section obtains sufficient vehicle lighting; if not, determine the area along the corresponding road section as the target road area along the urban traffic road network that requires active lighting adjustment; if so, do not determine the area along the corresponding road section as the target road area along the urban traffic road network that requires active lighting adjustment.

[0006] Optionally, based on the traffic density change state information and vehicle lighting range information of all road sections, determining whether the area along each road section obtains sufficient vehicle lighting includes: Extracting the information on the change of the number of vehicles per unit length in each road section contained in the traffic density change state information; Obtaining a first lighting evaluation coefficient according to information on changes in the number of vehicles within a unit length range in each road section over time; Wherein, the first lighting evaluation coefficient is obtained by the following formula: Among them, K 01represents the first lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of unit time is 1min-6min; F ij F represents the number of vehicles that pass through the jth unit time of the i-th unit length; ij-1 F represents the number of vehicles that pass through the i-th unit length in the j-1th unit time; bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-th unit length; F bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-1th unit length; F zi represents the median value of the number of vehicles corresponding to m units of time of the i-th unit length; F maxi F represents the maximum number of vehicles corresponding to m units of time of the i-th unit length; bz represents the median standard deviation of the number of vehicles corresponding to m unit time of n unit length; F bmax It represents the maximum value of the standard deviation of the number of vehicles corresponding to m unit time of n unit length; Extract vehicle lighting range information; Obtaining a second lighting evaluation coefficient using the vehicle lighting range information; The second lighting evaluation coefficient is obtained by the following formula: Among them, K 02 represents the second lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of the unit time is 1min-6min; S ij S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-th unit time; ij-1 S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-1th unit time; bi S represents the standard deviation of the vehicle lighting range area of ​​the i-th unit length; bi-1 represents the standard deviation of the vehicle lighting range area of ​​the i-1th unit length; Obtaining a comprehensive lighting evaluation coefficient using the first lighting evaluation coefficient and the second lighting evaluation coefficient; The comprehensive lighting evaluation coefficient is obtained by the following formula: Wherein, K represents the comprehensive lighting evaluation coefficient; K 01 Represents the first lighting evaluation coefficient; K 02 represents the second lighting evaluation coefficient; Comparing the comprehensive lighting evaluation coefficient with a preset evaluation coefficient threshold; When the comprehensive lighting evaluation coefficient exceeds a preset evaluation coefficient threshold, it indicates that the area along the road section has sufficient vehicle lighting; When the comprehensive lighting evaluation coefficient does not exceed the preset evaluation coefficient threshold, it indicates that the area along the road section does not obtain sufficient vehicle lighting.

[0007] Optionally, visually identifying the target road area to obtain object existence status information in the target road area; and identifying a sub-area in the target road area that needs to adjust lighting based on the object existence status information, includes: The target road area is photographed in three dimensions to obtain a three-dimensional image of the target road area; object contours are recognized on the three-dimensional image of the target road area to obtain three-dimensional space existence status information of objects in the target road area; wherein the three-dimensional space existence status information of objects includes the area range information of all static objects in the target road area in three-dimensional space; Based on the three-dimensional space existence status information of the object, the shielding range formed by all static objects in the area along the target road is located and identified, so as to obtain the sub-area in the area along the target road where the lighting needs to be adjusted.

[0008] Optionally, based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; and based on the lighting feature information of the matching lighting device, adjusting the lighting state of the sub-area where lighting adjustment is required by the matching lighting device, comprises: Based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, estimating the lighting influence value of each lighting device on the sub-area where lighting adjustment is required; based on the lighting influence value, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; Based on the adjustable range of the illumination light emission angle and the adjustable range of the illumination light intensity of the matching illumination device, the illumination angle and / or illumination intensity of the matching illumination device for the sub-area requiring illumination adjustment is adjusted.

[0009] Smart lighting control system along urban traffic roads, including: The traffic flow status determination module is used to perform big data analysis on the urban traffic road network to obtain the traffic flow status information of the road network; A target road area identification module, used to identify target road areas that require active lighting adjustment within the urban traffic road network based on the road network traffic state information; An object existence status recognition module is used to perform visual recognition on the area along the target road to obtain object existence status information in the area along the target road; A lighting adjustment sub-area identification module, used to identify the sub-area within the target road area where lighting needs to be adjusted based on the object existence status information; A lighting equipment matching determination module, configured to identify a matching lighting equipment for performing lighting adjustment on the sub-area requiring lighting adjustment based on the distribution position information of all lighting equipment in the area along the target road and the sub-area requiring lighting adjustment; The lighting state adjustment module is used to adjust the lighting state of the sub-area that needs to be adjusted by the matching lighting device based on the lighting feature information of the matching lighting device.

[0010] Optionally, the traffic flow state determination module is used to perform big data analysis on the urban traffic road network to obtain road network traffic flow state information, including: Based on the location information of the urban traffic road network, traffic big data of the urban traffic road network corresponding to a preset time interval is obtained; wherein the traffic big data includes global vehicle travel path big data and global vehicle travel speed big data within the urban traffic road network; the traffic big data is analyzed to obtain the traffic density change state information of all road sections within the urban traffic road network, and use it as the traffic state information of the road network; wherein the traffic density change state information includes the change information of the number of vehicles within a unit length range in each road section over time; The target road area identification module is used to identify the target road area that needs active lighting adjustment inside the urban traffic road network based on the road network traffic state information, including: Based on the traffic density change status information and vehicle lighting range information of all road sections, determine whether the area along each road section obtains sufficient vehicle lighting; if not, determine the area along the corresponding road section as the target road area along the urban traffic road network that requires active lighting adjustment; if so, do not determine the area along the corresponding road section as the target road area along the urban traffic road network that requires active lighting adjustment.

[0011] Optionally, based on the traffic density change state information and vehicle lighting range information of all road sections, determining whether the area along each road section obtains sufficient vehicle lighting includes: Extracting the information on the change of the number of vehicles per unit length in each road section contained in the traffic density change state information; Obtaining a first lighting evaluation coefficient according to information on changes in the number of vehicles within a unit length range in each road section over time; Wherein, the first lighting evaluation coefficient is obtained by the following formula: Among them, K 01 represents the first lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of unit time is 1min-6min; F ij F represents the number of vehicles that pass through the jth unit time of the i-th unit length; ij-1 F represents the number of vehicles that pass through the i-th unit length in the j-1th unit time; bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-th unit length; F bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-1th unit length; F zi represents the median value of the number of vehicles corresponding to m units of time of the i-th unit length; F maxi F represents the maximum number of vehicles corresponding to m units of time of the i-th unit length; bz represents the median standard deviation of the number of vehicles corresponding to m unit time of n unit length; F bmax It represents the maximum value of the standard deviation of the number of vehicles corresponding to m unit time of n unit length; Extract vehicle lighting range information; Obtaining a second lighting evaluation coefficient using the vehicle lighting range information; The second lighting evaluation coefficient is obtained by the following formula: Among them, K 02 represents the second lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of the unit time is 1min-6min; S ij S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-th unit time; ij-1 S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-1th unit time; bi S represents the standard deviation of the vehicle lighting range area of ​​the i-th unit length; bi-1 represents the standard deviation of the vehicle lighting range area of ​​the i-1th unit length; Obtaining a comprehensive lighting evaluation coefficient using the first lighting evaluation coefficient and the second lighting evaluation coefficient; The comprehensive lighting evaluation coefficient is obtained by the following formula: Wherein, K represents the comprehensive lighting evaluation coefficient; K 01 Represents the first lighting evaluation coefficient; K 02 represents the second lighting evaluation coefficient; Comparing the comprehensive lighting evaluation coefficient with a preset evaluation coefficient threshold; When the comprehensive lighting evaluation coefficient exceeds a preset evaluation coefficient threshold, it indicates that the area along the road section has sufficient vehicle lighting; When the comprehensive lighting evaluation coefficient does not exceed the preset evaluation coefficient threshold, it indicates that the area along the road section does not obtain sufficient vehicle lighting.

[0012] Optionally, the object existence status recognition module is used to perform visual recognition on the area along the target road to obtain object existence status information in the area along the target road, including: The target road area is photographed in three dimensions to obtain a three-dimensional image of the target road area; object contours are recognized on the three-dimensional image of the target road area to obtain three-dimensional space existence status information of objects in the target road area; wherein the three-dimensional space existence status information of objects includes the area range information of all static objects in the target road area in three-dimensional space; The lighting adjustment sub-area identification module is used to identify the sub-area that needs to adjust the lighting inside the area along the target road based on the object existence state information, including: Based on the three-dimensional space existence status information of the object, the shielding range formed by all static objects in the area along the target road is located and identified, so as to obtain the sub-area in the area along the target road where the lighting needs to be adjusted.

[0013] Optionally, the lighting device matching determination module is used to identify a matching lighting device for performing lighting adjustment on the sub-area requiring lighting adjustment based on the distribution position information of all lighting devices in the area along the target road and the sub-area requiring lighting adjustment, including: Based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, estimating the lighting influence value of each lighting device on the sub-area where lighting adjustment is required; based on the lighting influence value, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; The lighting state adjustment module is used to adjust the lighting state of the sub-area requiring lighting adjustment by the matching lighting device based on the lighting feature information of the matching lighting device, including: Based on the adjustable range of the illumination light emission angle and the adjustable range of the illumination light intensity of the matching illumination device, the illumination angle and / or illumination intensity of the matching illumination device for the sub-area requiring illumination adjustment is adjusted.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The smart lighting control method and system along urban traffic roads provided in the present application perform big data analysis on the urban traffic road network to obtain traffic status information of the road network, thereby identifying target road areas that require active lighting adjustment, and identifying different road areas in combination with the road traffic conditions to determine areas where there is a need for auxiliary lighting equipment; visually identify the existence status information of objects in the target road area to determine the sub-area where the lighting needs to be adjusted, and provide accurate position guidance for subsequent lighting equipment to perform directional lighting adjustments on the target road area; also based on the distribution position information of all lighting equipment in the target road area and the sub-area where the lighting needs to be adjusted, identify matching lighting equipment for lighting adjustment of the sub-area where the lighting needs to be adjusted, and adjust its lighting status for the sub-area in combination with its lighting feature information, effectively combine the traffic conditions of the urban traffic roads to accurately adjust the operation of the lighting equipment along the road, and realize intelligent lighting control of the road area. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them: Figure 1 A schematic diagram of the flow chart of the intelligent lighting control method along urban traffic roads provided by the present invention.

[0016] Figure 2 This is a schematic diagram of the structure of the intelligent lighting control system along urban traffic roads provided by the present invention. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. It is to be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only some structures related to the present application are shown in the accompanying drawings, rather than all structures. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0018] The terms "including" and "having" and any variations thereof in this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising 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.

[0019] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0020] See also Figure 1 As shown, an embodiment of the present application provides a smart lighting control method along a city traffic road. The smart lighting control method along a city traffic road includes: Perform big data analysis on the urban traffic road network to obtain traffic status information of the road network; based on the traffic status information of the road network, identify target road areas within the urban traffic road network that require active lighting adjustment; Perform visual recognition on the target road area to obtain object existence status information in the target road area; based on the object existence status information, identify the sub-area within the target road area that needs to adjust the lighting; Based on the distribution position information of all lighting devices in the area along the target road and the sub-area that needs lighting adjustment, identify the matching lighting device for lighting adjustment of the sub-area that needs lighting adjustment; based on the lighting characteristic information of the matching lighting device, adjust the lighting state of the sub-area that needs lighting adjustment by the matching lighting device.

[0021] The beneficial effects of the above embodiments are as follows: the intelligent lighting control method along urban traffic roads performs big data analysis on the urban traffic road network to obtain traffic status information of the road network, thereby identifying target road areas that require active lighting adjustment, and identifying different road areas in combination with the road traffic conditions to determine areas where there is a need for auxiliary lighting by lighting equipment; visually identifying the existence status information of objects in the target road area to determine the sub-area where the lighting needs to be adjusted, and providing accurate position guidance for subsequent lighting equipment to perform directional lighting adjustments on the target road area; also based on the distribution position information of all lighting equipment in the target road area and the sub-area where the lighting needs to be adjusted, identifying matching lighting equipment for lighting adjustment of the sub-area where the lighting needs to be adjusted, and adjusting its lighting status for the sub-area in combination with its lighting feature information, effectively combining the traffic conditions of the urban traffic roads to accurately adjust the operation of the lighting equipment along the road, and realizing intelligent lighting control of the road area.

[0022] In another embodiment, a big data analysis is performed on an urban traffic road network to obtain traffic status information of the road network; based on the traffic status information of the road network, target road areas along the urban traffic road network that require active lighting adjustment are identified, including: Based on the location information of the urban traffic road network, traffic big data of the urban traffic road network corresponding to a preset time interval is obtained; wherein the traffic big data includes global vehicle travel path big data and global vehicle travel speed big data within the urban traffic road network; the traffic big data is analyzed to obtain the traffic density change state information of all road sections within the urban traffic road network, and use it as the traffic state information of the road network; wherein the traffic density change state information includes the change information of the number of vehicles within a unit length range in each road section over time; Based on the traffic density change status information and vehicle lighting range information of all road sections, determine whether the area along each road section obtains sufficient vehicle lighting; if not, determine the area along the corresponding road section as the target road area within the urban traffic road network that requires active lighting adjustment; if so, do not determine the area along the corresponding road section as the target road area within the urban traffic road network that requires active lighting adjustment.

[0023] The beneficial effects of the above embodiments are that, in order to ensure the normal operation of the urban traffic road network, street lamps and other lighting equipment will be installed along each traffic road. These lighting equipment usually work automatically at a preset time point or when the external environment brightness is less than a preset brightness threshold, thereby realizing the lighting of the corresponding traffic road area. In the actual traffic road lighting control scenario, the light emitted by the headlights of the vehicles traveling on the traffic road will also provide effective lighting for the areas along the traffic road to a certain extent. In order to save the power consumption of the lighting equipment along the traffic road to the maximum extent, when adjusting and controlling the lighting equipment, it is also necessary to consider the light intensity generated by the vehicles traveling on the traffic road. Based on the location information of the urban traffic road network, the traffic big data of the urban traffic road network corresponding to the preset time interval (such as one week or one month, etc.) is obtained, and the vehicle driving path big data and vehicle driving speed big data within the global scope of the urban traffic road network are characterized by big data on the vehicle driving dynamics of all road sections within the urban traffic road network. In addition, traffic big data is analyzed to obtain the traffic density change status information of all road sections within the urban traffic road network, which is used as the traffic status information of the road network. When the traffic density of a road section can be maintained at a high level for a long period of time, the light emitted by the vehicles traveling on the road section can provide stable and sufficient lighting for the area along the road. It can be seen that determining the change information of the number of vehicles per unit length in each road section over time can provide a reliable data basis for judging whether the area along the road section has sufficient vehicle lighting.

[0024] Whether the light emitted by vehicles can provide stable and sufficient lighting for the areas along the road is also affected by the size of the vehicle lighting range. The larger the vehicle lighting range, the greater the probability that the corresponding road areas will obtain sufficient vehicle lighting. For this reason, based on the traffic density change status information and vehicle lighting range information of all road sections, the lighting range, intensity and duration of the light emitted by vehicles along each road section are fitted and analyzed to determine whether each road section along the area has obtained sufficient vehicle lighting, so as to accurately identify the target road areas that need active lighting adjustment within the urban traffic road network, and identify different road areas in combination with the road traffic conditions to determine the areas where there is a need for auxiliary lighting equipment, which can improve the intelligence of lighting control in urban traffic road areas.

[0025] In another embodiment, based on the traffic density change state information and vehicle lighting range information of all road sections, determining whether the area along each road section obtains sufficient vehicle lighting includes: Extracting the information on the change of the number of vehicles per unit length in each road section contained in the traffic density change state information; Obtaining a first lighting evaluation coefficient according to information on changes in the number of vehicles within a unit length range in each road section over time; Wherein, the first lighting evaluation coefficient is obtained by the following formula: Among them, K 01 represents the first lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of unit time is 1min-6min; F ij F represents the number of vehicles that pass through the jth unit time of the i-th unit length; ij-1 F represents the number of vehicles that pass through the i-th unit length in the j-1th unit time; bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-th unit length; F bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-1th unit length; F zi represents the median value of the number of vehicles corresponding to m units of time of the i-th unit length; F maxi F represents the maximum number of vehicles corresponding to m units of time of the i-th unit length; bz represents the median standard deviation of the number of vehicles corresponding to m unit time of n unit length; F bmax It represents the maximum value of the standard deviation of the number of vehicles corresponding to m unit time of n unit length; Extract vehicle lighting range information; Obtaining a second lighting evaluation coefficient using the vehicle lighting range information; The second lighting evaluation coefficient is obtained by the following formula: Among them, K 02 represents the second lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of the unit time is 1min-6min; S ij S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-th unit time; ij-1 S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-1th unit time; bi S represents the standard deviation of the vehicle lighting range area of ​​the i-th unit length; bi-1 represents the standard deviation of the vehicle lighting range area of ​​the i-1th unit length; Obtaining a comprehensive lighting evaluation coefficient using the first lighting evaluation coefficient and the second lighting evaluation coefficient; The comprehensive lighting evaluation coefficient is obtained by the following formula: Wherein, K represents the comprehensive lighting evaluation coefficient; K 01 Represents the first lighting evaluation coefficient; K 02 represents the second lighting evaluation coefficient; Comparing the comprehensive lighting evaluation coefficient with a preset evaluation coefficient threshold; When the comprehensive lighting evaluation coefficient exceeds a preset evaluation coefficient threshold, it indicates that the area along the road section has sufficient vehicle lighting; When the comprehensive lighting evaluation coefficient does not exceed the preset evaluation coefficient threshold, it indicates that the area along the road section does not obtain sufficient vehicle lighting.

[0026] The beneficial effect of the above embodiment is that by comprehensively considering the traffic density change state information and the vehicle lighting range information, the solution can more accurately evaluate the lighting conditions along each road section. This comprehensive evaluation method is more comprehensive and accurate than considering only a single factor (such as the number of vehicles or the lighting range).

[0027] The evaluation coefficients in the scheme (including the first lighting evaluation coefficient and the second lighting evaluation coefficient) are dynamically calculated based on the number of vehicles per unit time and unit length and the lighting range data. This means that the scheme can be adaptively adjusted as the road traffic conditions change, thereby providing more real-time lighting evaluation results. The first lighting evaluation coefficient, the second lighting evaluation coefficient and the comprehensive lighting evaluation coefficient calculated by the formula provide quantitative indicators for the evaluation of road lighting conditions. This allows decision makers to more objectively and scientifically judge whether the road lighting is sufficient, and provide data support for subsequent improvement measures. By accurately evaluating the road lighting conditions, the scheme helps to promptly identify areas with insufficient lighting and take corresponding improvement measures. This can not only improve the driving safety of drivers, but also reduce traffic accidents caused by insufficient lighting. Based on the results of the comprehensive lighting evaluation coefficient, decision makers can more accurately determine which road sections need to add lighting facilities or improve lighting conditions, thereby optimizing the configuration of lighting resources and avoiding unnecessary waste. The scheme combines information on traffic density and vehicle lighting range, and embodies the idea of ​​data fusion and intelligent decision-making in intelligent transportation systems. This helps to promote the development and application of intelligent transportation technology and improve the level of intelligence in road transportation.

[0028] In another embodiment, visual recognition is performed on the target road area to obtain object existence status information in the target road area; and based on the object existence status information, a sub-area in the target road area that needs to adjust lighting is identified, including: The target road area is photographed in three dimensions to obtain a three-dimensional image of the target road area; object contours are recognized in the three-dimensional image of the target road area to obtain three-dimensional space existence status information of objects in the target road area; wherein the three-dimensional space existence status information of objects includes the area range information of all static objects in the target road area in three-dimensional space; Based on the three-dimensional space existence status information of the object, the shielding range formed by all static objects in the area along the target road is located and identified, so as to obtain the sub-area in the area along the target road where the lighting needs to be adjusted.

[0029] The beneficial effect of the above-mentioned embodiment is that a large number of trees and other vegetation will be planted along the urban traffic roads. These vegetation will block the light emitted by lighting equipment such as street lamps during their growth, making it impossible for certain sub-areas inside the target road area to be effectively illuminated by the lighting equipment, seriously reducing the lighting stability and sustainability of the target road area. In order to accurately determine the effect of vegetation on the light blocking of lighting equipment in the target road area, the target road area is photographed in three dimensions to obtain a three-dimensional image of the target road; the object contours of the three-dimensional image of the target road are identified to obtain the three-dimensional space existence status information of the objects in the target road area, thereby globally and quantitatively characterizing the area occupied by all static objects in the target road area in three-dimensional space. In addition, the three-dimensional existence status information of the object is compared with the occupancy range information of the area along the target road, so as to locate and identify the shielding range formed by all static objects in the area along the target road, thereby obtaining the sub-area in the area along the target road that needs to adjust the lighting. In this way, the sub-area in the area along the target road that cannot obtain sufficient light from the current lighting status of the lighting equipment can be accurately located from within the area along the target road, providing accurate position guidance for the subsequent lighting equipment to perform directional lighting adjustments on the area along the target road.

[0030] In another embodiment, based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; and based on the lighting feature information of the matching lighting device, adjusting the lighting state of the sub-area where lighting adjustment is required by the matching lighting device, comprises: Based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, estimating the lighting impact value of each lighting device on the sub-area where lighting adjustment is required; based on the lighting impact value, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; Based on the adjustable range of the illumination light emission angle and the adjustable range of the illumination light intensity of the matching illumination device, the illumination angle and / or illumination intensity of the matching illumination device for the sub-area requiring illumination adjustment is adjusted.

[0031] The beneficial effect of the above embodiment is that in actual operation, the lighting coverage of the sub-area that needs to be adjusted by the lighting equipment located at different positions along the target road is not the same. Generally speaking, the lighting equipment that is closer to the sub-area that needs to be adjusted or the lighting equipment with a larger lighting range has a greater lighting impact on the sub-area that needs to be adjusted. For this reason, based on the distribution position information of all lighting equipment along the target road and the area range of the sub-area that needs to be adjusted, the corresponding neural network model is used to calculate the lighting impact degree value of each lighting equipment on the sub-area that needs to be adjusted. If the lighting impact degree value is larger, it indicates that the lighting impact of the corresponding lighting equipment on the sub-area that needs to be adjusted is also greater. If the lighting impact degree value is greater than or equal to the preset degree threshold, the corresponding lighting equipment is determined as a matching lighting equipment for lighting adjustment of the sub-area that needs to be adjusted, so that it is convenient to perform lighting control only for the matching lighting equipment in the future, thereby improving the concentration and intelligence of lighting control. In addition, based on the adjustable range of the lighting light emission angle and the adjustable range of the lighting light intensity of the matching lighting device, the lighting angle and / or lighting intensity of the matching lighting device for the sub-area that needs to be adjusted in lighting is adjusted, so that the matching lighting device can emit light at the sub-area that needs to be adjusted in lighting, thereby realizing intelligent and efficient lighting control of the area along the road.

[0032] See also Figure 2 As shown, an embodiment of the present application provides a smart lighting control system along a city traffic road. The smart lighting control system along a city traffic road includes: The traffic flow status determination module is used to perform big data analysis on the urban traffic road network to obtain the traffic flow status information of the road network; A target road area identification module is used to identify target road areas that require active lighting adjustment within the urban traffic road network based on the traffic status information of the road network; An object existence status recognition module is used to visually recognize the area along the target road to obtain object existence status information in the area along the target road; A lighting adjustment sub-area identification module is used to identify the sub-area along the target road where lighting needs to be adjusted based on the object existence status information; A lighting equipment matching determination module, used to identify a matching lighting equipment for performing lighting adjustment on the sub-area requiring lighting adjustment based on the distribution position information of all lighting equipment in the area along the target road and the sub-area requiring lighting adjustment; The lighting state adjustment module is used to adjust the lighting state of the matching lighting device for the sub-area that needs to adjust the lighting based on the lighting feature information of the matching lighting device.

[0033] The beneficial effects of the above embodiments are as follows: the smart lighting control system along urban traffic roads performs big data analysis on the urban traffic road network to obtain traffic status information of the road network, thereby identifying target road areas that require active lighting adjustment, and identifying different road areas in combination with the road traffic conditions to determine areas where there is a need for auxiliary lighting equipment; visually identifies the existence status information of objects in the target road area to determine the sub-area where the lighting needs to be adjusted, and provides accurate position guidance for subsequent lighting equipment to perform directional lighting adjustments on the target road area; also based on the distribution position information of all lighting equipment in the target road area and the sub-area where the lighting needs to be adjusted, identifies matching lighting equipment for lighting adjustment of the sub-area where the lighting needs to be adjusted, and adjusts its lighting status for the sub-area in combination with its lighting feature information, effectively and accurately adjusts the operation of lighting equipment along the road in combination with the traffic conditions of the urban traffic roads, and realizes intelligent lighting control of the road area.

[0034] In another embodiment, the traffic flow state determination module is used to perform big data analysis on the urban traffic road network to obtain road network traffic flow state information, including: Based on the location information of the urban traffic road network, traffic big data of the urban traffic road network corresponding to a preset time interval is obtained; wherein the traffic big data includes global vehicle travel path big data and global vehicle travel speed big data within the urban traffic road network; the traffic big data is analyzed to obtain the traffic density change state information of all road sections within the urban traffic road network, and use it as the traffic state information of the road network; wherein the traffic density change state information includes the change information of the number of vehicles within a unit length range in each road section over time; The target road area identification module is used to identify the target road area that needs active lighting adjustment within the urban traffic road network based on the road network traffic state information, including: Based on the traffic density change status information and vehicle lighting range information of all road sections, determine whether the area along each road section obtains sufficient vehicle lighting; if not, determine the area along the corresponding road section as the target road area within the urban traffic road network that requires active lighting adjustment; if so, do not determine the area along the corresponding road section as the target road area within the urban traffic road network that requires active lighting adjustment.

[0035] The beneficial effects of the above embodiments are that, in order to ensure the normal operation of the urban traffic road network, street lamps and other lighting equipment will be installed along each traffic road. These lighting equipment usually work automatically at a preset time point or when the external environment brightness is less than a preset brightness threshold, thereby realizing the lighting of the corresponding traffic road area. In the actual traffic road lighting control scenario, the light emitted by the headlights of the vehicles traveling on the traffic road will also provide effective lighting for the areas along the traffic road to a certain extent. In order to save the power consumption of the lighting equipment along the traffic road to the maximum extent, when adjusting and controlling the lighting equipment, it is also necessary to consider the light intensity generated by the vehicles traveling on the traffic road. Based on the location information of the urban traffic road network, the traffic big data of the urban traffic road network corresponding to the preset time interval (such as one week or one month, etc.) is obtained, and the vehicle driving path big data and vehicle driving speed big data within the global scope of the urban traffic road network are characterized by big data on the vehicle driving dynamics of all road sections within the urban traffic road network. In addition, traffic big data is analyzed to obtain the traffic density change status information of all road sections within the urban traffic road network, which is used as the traffic status information of the road network. When the traffic density of a road section can be maintained at a high level for a long period of time, the light emitted by the vehicles traveling on the road section can provide stable and sufficient lighting for the area along the road. It can be seen that determining the change information of the number of vehicles per unit length in each road section over time can provide a reliable data basis for judging whether the area along the road section has sufficient vehicle lighting.

[0036] Whether the light emitted by vehicles can provide stable and sufficient lighting for the areas along the road is also affected by the size of the vehicle lighting range. The larger the vehicle lighting range, the greater the probability that the corresponding road areas will obtain sufficient vehicle lighting. For this reason, based on the traffic density change status information and vehicle lighting range information of all road sections, the lighting range, intensity and duration of the light emitted by vehicles along each road section are fitted and analyzed to determine whether each road section along the area has obtained sufficient vehicle lighting, so as to accurately identify the target road areas that need active lighting adjustment within the urban traffic road network, and identify different road areas in combination with the road traffic conditions to determine the areas where there is a need for auxiliary lighting equipment, which can improve the intelligence of lighting control in urban traffic road areas.

[0037] In another embodiment, based on the traffic density change state information and vehicle lighting range information of all road sections, determining whether the area along each road section obtains sufficient vehicle lighting includes: Extracting the information on the change of the number of vehicles per unit length in each road section contained in the traffic density change state information; Obtaining a first lighting evaluation coefficient according to information on changes in the number of vehicles within a unit length range in each road section over time; Wherein, the first lighting evaluation coefficient is obtained by the following formula: Among them, K 01 represents the first lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of unit time is 1min-6min; F ij F represents the number of vehicles that pass through the jth unit time of the i-th unit length; ij-1 F represents the number of vehicles that pass through the i-th unit length in the j-1th unit time; bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-th unit length; F bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-1th unit length; F zi represents the median value of the number of vehicles corresponding to m units of time of the i-th unit length; F maxi F represents the maximum number of vehicles corresponding to m units of time of the i-th unit length; bz represents the median standard deviation of the number of vehicles corresponding to m unit time of n unit length; F bmax It represents the maximum value of the standard deviation of the number of vehicles corresponding to m unit time of n unit length; Extract vehicle lighting range information; Obtaining a second lighting evaluation coefficient using the vehicle lighting range information; The second lighting evaluation coefficient is obtained by the following formula: Among them, K 02 represents the second lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of the unit time is 1min-6min; S ij S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-th unit time; ij-1 S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-1th unit time; bi S represents the standard deviation of the vehicle lighting range area of ​​the i-th unit length; bi-1 represents the standard deviation of the vehicle lighting range area of ​​the i-1th unit length; Obtaining a comprehensive lighting evaluation coefficient using the first lighting evaluation coefficient and the second lighting evaluation coefficient; The comprehensive lighting evaluation coefficient is obtained by the following formula: Wherein, K represents the comprehensive lighting evaluation coefficient; K 01 Represents the first lighting evaluation coefficient; K 02 represents the second lighting evaluation coefficient; Comparing the comprehensive lighting evaluation coefficient with a preset evaluation coefficient threshold; When the comprehensive lighting evaluation coefficient exceeds a preset evaluation coefficient threshold, it indicates that the area along the road section has sufficient vehicle lighting; When the comprehensive lighting evaluation coefficient does not exceed the preset evaluation coefficient threshold, it indicates that the area along the road section does not obtain sufficient vehicle lighting.

[0038] The beneficial effect of the above embodiment is that by comprehensively considering the traffic density change state information and the vehicle lighting range information, the solution can more accurately evaluate the lighting conditions along each road section. This comprehensive evaluation method is more comprehensive and accurate than considering only a single factor (such as the number of vehicles or the lighting range).

[0039] The evaluation coefficients in the scheme (including the first lighting evaluation coefficient and the second lighting evaluation coefficient) are dynamically calculated based on the number of vehicles per unit time and unit length and the lighting range data. This means that the scheme can be adaptively adjusted as the road traffic conditions change, thereby providing more real-time lighting evaluation results. The first lighting evaluation coefficient, the second lighting evaluation coefficient and the comprehensive lighting evaluation coefficient calculated by the formula provide quantitative indicators for the evaluation of road lighting conditions. This allows decision makers to more objectively and scientifically judge whether the road lighting is sufficient, and provide data support for subsequent improvement measures. By accurately evaluating the road lighting conditions, the scheme helps to promptly identify areas with insufficient lighting and take corresponding improvement measures. This can not only improve the driving safety of drivers, but also reduce traffic accidents caused by insufficient lighting. Based on the results of the comprehensive lighting evaluation coefficient, decision makers can more accurately determine which road sections need to add lighting facilities or improve lighting conditions, thereby optimizing the configuration of lighting resources and avoiding unnecessary waste. The scheme combines information on traffic density and vehicle lighting range, and embodies the idea of ​​data fusion and intelligent decision-making in intelligent transportation systems. This helps to promote the development and application of intelligent transportation technology and improve the level of intelligence in road transportation.

[0040] In another embodiment, the object existence status recognition module is used to perform visual recognition on the target road area to obtain object existence status information on the target road area, including: The target road area is photographed in three dimensions to obtain a three-dimensional image of the target road area; object contours are recognized in the three-dimensional image of the target road area to obtain three-dimensional space existence status information of objects in the target road area; wherein the three-dimensional space existence status information of objects includes the area range information of all static objects in the target road area in three-dimensional space; The lighting adjustment sub-area identification module is used to identify the sub-area that needs to adjust the lighting inside the area along the target road based on the object existence state information, including: Based on the three-dimensional space existence status information of the object, the shielding range formed by all static objects in the area along the target road is located and identified, so as to obtain the sub-area in the area along the target road where the lighting needs to be adjusted.

[0041] The beneficial effect of the above-mentioned embodiment is that a large number of trees and other vegetation will be planted along the urban traffic roads. These vegetation will block the light emitted by lighting equipment such as street lamps during their growth, making it impossible for certain sub-areas inside the target road area to be effectively illuminated by the lighting equipment, seriously reducing the lighting stability and sustainability of the target road area. In order to accurately determine the effect of vegetation on the light blocking of lighting equipment in the target road area, the target road area is photographed in three dimensions to obtain a three-dimensional image of the target road; the object contours of the three-dimensional image of the target road are identified to obtain the three-dimensional space existence status information of the objects in the target road area, thereby globally and quantitatively characterizing the area occupied by all static objects in the target road area in three-dimensional space. In addition, the three-dimensional existence status information of the object is compared with the occupancy range information of the area along the target road, so as to locate and identify the shielding range formed by all static objects in the area along the target road, thereby obtaining the sub-area in the area along the target road that needs to adjust the lighting. In this way, the sub-area in the area along the target road that cannot obtain sufficient light from the current lighting status of the lighting equipment can be accurately located from within the area along the target road, providing accurate position guidance for the subsequent lighting equipment to perform directional lighting adjustments on the area along the target road.

[0042] In another embodiment, the lighting device matching determination module is used to identify a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, including: Based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, estimating the lighting impact value of each lighting device on the sub-area where lighting adjustment is required; based on the lighting impact value, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; The lighting state adjustment module is used to adjust the lighting state of the matching lighting device for the sub-area that needs to adjust the lighting based on the lighting feature information of the matching lighting device, including: Based on the adjustable range of the illumination light emission angle and the adjustable range of the illumination light intensity of the matching illumination device, the illumination angle and / or illumination intensity of the matching illumination device for the sub-area requiring illumination adjustment is adjusted.

[0043] The beneficial effect of the above embodiment is that in actual operation, the lighting coverage of the sub-area that needs to be adjusted by the lighting equipment located at different positions along the target road is not the same. Generally speaking, the lighting equipment that is closer to the sub-area that needs to be adjusted or the lighting equipment with a larger lighting range has a greater lighting impact on the sub-area that needs to be adjusted. For this reason, based on the distribution position information of all lighting equipment along the target road and the area range of the sub-area that needs to be adjusted, the corresponding neural network model is used to calculate the lighting impact degree value of each lighting equipment on the sub-area that needs to be adjusted. If the lighting impact degree value is larger, it indicates that the lighting impact of the corresponding lighting equipment on the sub-area that needs to be adjusted is also greater. If the lighting impact degree value is greater than or equal to the preset degree threshold, the corresponding lighting equipment is determined as a matching lighting equipment for lighting adjustment of the sub-area that needs to be adjusted, so that it is convenient to perform lighting control only for the matching lighting equipment in the future, thereby improving the concentration and intelligence of lighting control. In addition, based on the adjustable range of the lighting light emission angle and the adjustable range of the lighting light intensity of the matching lighting device, the lighting angle and / or lighting intensity of the matching lighting device for the sub-area that needs to be adjusted in lighting is adjusted, so that the matching lighting device can emit light at the sub-area that needs to be adjusted in lighting, thereby realizing intelligent and efficient lighting control of the area along the road.

[0044] In general, the intelligent lighting control method and system along urban traffic roads conducts big data analysis on the urban traffic road network to obtain traffic status information of the road network, thereby identifying target road areas that require active lighting adjustment, and identifying different road areas in combination with road traffic conditions to determine areas where there is a need for auxiliary lighting equipment; visually identifies the existence status information of objects in the target road area to determine the sub-area where lighting adjustment is required, and provides accurate position guidance for subsequent lighting equipment to perform directional lighting adjustment on the target road area; also based on the distribution position information of all lighting equipment in the target road area and the sub-area where lighting adjustment is required, identifies matching lighting equipment for lighting adjustment of the sub-area where lighting adjustment is required, and adjusts its lighting status for the sub-area in combination with its lighting feature information, effectively combining the traffic conditions of urban traffic roads to accurately adjust the operation of lighting equipment along the road, and realizes intelligent lighting control of the road area.

[0045] The above is only a specific implementation of the present invention, and any other improvements made based on the concept of the present invention are considered to be within the protection scope of the present invention.

Claims

1. A smart lighting control method along urban traffic roads, characterized in that: include: Performing big data analysis on the urban traffic road network to obtain traffic status information of the road network; based on the traffic status information of the road network, identifying target road areas within the urban traffic road network that require active lighting adjustment; Performing visual recognition on the target road area to obtain object existence status information in the target road area; based on the object existence status information, identifying a sub-area within the target road area that needs to adjust lighting; Based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; Based on the lighting characteristic information of the matching lighting device, the lighting state of the matching lighting device on the sub-area requiring lighting adjustment is adjusted.

2. The intelligent lighting control method along urban traffic roads according to claim 1, characterized in that: Performing big data analysis on the urban traffic road network to obtain road network traffic status information; based on the road network traffic status information, identifying target road areas within the urban traffic road network that require active lighting adjustment, including: Based on the location information of the urban traffic road network, traffic big data of the urban traffic road network corresponding to a preset time interval is obtained; wherein the traffic big data includes global vehicle travel path big data and global vehicle travel speed big data within the urban traffic road network; the traffic big data is analyzed to obtain the traffic density change state information of all road sections within the urban traffic road network, and use it as the traffic state information of the road network; wherein the traffic density change state information includes the change information of the number of vehicles within a unit length range in each road section over time; Based on the traffic density change status information and vehicle lighting range information of all road sections, determine whether the area along each road section obtains sufficient vehicle lighting; if not, determine the area along the corresponding road section as the target road area along the urban traffic road network that requires active lighting adjustment; if so, do not determine the area along the corresponding road section as the target road area along the urban traffic road network that requires active lighting adjustment.

3. The intelligent lighting control method along urban traffic roads as claimed in claim 2, characterized in that: Based on the traffic density change status information and vehicle lighting range information of all road sections, determine whether the area along each road section has sufficient vehicle lighting, including: Extracting the information on the change of the number of vehicles per unit length in each road section contained in the traffic density change state information; Obtaining a first lighting evaluation coefficient according to information on changes in the number of vehicles within a unit length range in each road section over time; Wherein, the first lighting evaluation coefficient is obtained by the following formula: Among them, K 01 represents the first lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of unit time is 1min-6min; F ij F represents the number of vehicles that pass through the jth unit time of the i-th unit length; ij-1 F represents the number of vehicles that pass through the i-th unit length in the j-1th unit time; bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-th unit length; F bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-1th unit length; F zi represents the median value of the number of vehicles corresponding to m units of time of the i-th unit length; F maxi F represents the maximum number of vehicles corresponding to m units of time of the i-th unit length; bz represents the median standard deviation of the number of vehicles corresponding to m unit time of n unit length; F bmax It represents the maximum value of the standard deviation of the number of vehicles corresponding to m unit time of n unit length; Extract vehicle lighting range information; Obtaining a second lighting evaluation coefficient using the vehicle lighting range information; The second lighting evaluation coefficient is obtained by the following formula: Among them, K 02 represents the second lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of the unit time is 1min-6min; S ij S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-th unit time; ij-1 S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-1th unit time; bi S represents the standard deviation of the vehicle lighting range area of ​​the i-th unit length; bi-1 represents the standard deviation of the vehicle lighting range area of ​​the i-1th unit length; Obtaining a comprehensive lighting evaluation coefficient using the first lighting evaluation coefficient and the second lighting evaluation coefficient; The comprehensive lighting evaluation coefficient is obtained by the following formula: Wherein, K represents the comprehensive lighting evaluation coefficient; K 01 Represents the first lighting evaluation coefficient; K 02 represents the second lighting evaluation coefficient; Comparing the comprehensive lighting evaluation coefficient with a preset evaluation coefficient threshold; When the comprehensive lighting evaluation coefficient exceeds a preset evaluation coefficient threshold, it indicates that the area along the road section has sufficient vehicle lighting; When the comprehensive lighting evaluation coefficient does not exceed the preset evaluation coefficient threshold, it indicates that the area along the road section does not obtain sufficient vehicle lighting.

4. The intelligent lighting control method along urban traffic roads according to claim 1, characterized in that: Performing visual recognition on the area along the target road to obtain information on the existence status of objects in the area along the target road; Based on the object existence status information, identifying a sub-area within the target road area where lighting needs to be adjusted, including: The target road area is photographed in three dimensions to obtain a three-dimensional image of the target road area; object contours are recognized on the three-dimensional image of the target road area to obtain three-dimensional space existence status information of objects in the target road area; wherein the three-dimensional space existence status information of objects includes the area range information of all static objects in the target road area in three-dimensional space; Based on the three-dimensional space existence status information of the object, the shielding range formed by all static objects in the area along the target road is located and identified, so as to obtain the sub-area in the area along the target road where the lighting needs to be adjusted.

5. The intelligent lighting control method along urban traffic roads according to claim 1, characterized in that: Based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; Adjusting the lighting state of the sub-area requiring lighting adjustment by the matching lighting device based on the lighting characteristic information of the matching lighting device includes: Based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, estimating the lighting influence value of each lighting device on the sub-area where lighting adjustment is required; based on the lighting influence value, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; Based on the adjustable range of the illumination light emission angle and the adjustable range of the illumination light intensity of the matching illumination device, the illumination angle and / or illumination intensity of the matching illumination device for the sub-area requiring illumination adjustment is adjusted.

6. Intelligent lighting control system along urban traffic roads, characterized by: include: The traffic flow status determination module is used to perform big data analysis on the urban traffic road network to obtain the traffic flow status information of the road network; A target road area identification module, used to identify target road areas that require active lighting adjustment within the urban traffic road network based on the road network traffic state information; An object existence status recognition module is used to visually recognize the area along the target road to obtain object existence status information in the area along the target road; A lighting adjustment sub-area identification module, used to identify the sub-area within the area along the target road where lighting needs to be adjusted based on the object existence status information; A lighting equipment matching determination module, configured to identify a matching lighting equipment for performing lighting adjustment on the sub-area requiring lighting adjustment based on the distribution position information of all lighting equipment in the area along the target road and the sub-area requiring lighting adjustment; The lighting state adjustment module is used to adjust the lighting state of the sub-area that needs to be adjusted by the matching lighting device based on the lighting feature information of the matching lighting device.

7. The intelligent lighting control system along the urban traffic road as claimed in claim 6, characterized in that: The vehicle flow state determination module is used to perform big data analysis on the urban traffic road network to obtain road network vehicle flow state information, including: Based on the location information of the urban traffic road network, traffic big data of the urban traffic road network corresponding to a preset time interval is obtained; wherein the traffic big data includes global vehicle travel path big data and global vehicle travel speed big data within the urban traffic road network; the traffic big data is analyzed to obtain the traffic density change state information of all road sections within the urban traffic road network, and use it as the traffic state information of the road network; wherein the traffic density change state information includes the change information of the number of vehicles within a unit length range in each road section over time; The target road area identification module is used to identify the target road area that needs active lighting adjustment inside the urban traffic road network based on the road network traffic state information, including: Based on the traffic density change status information and vehicle lighting range information of all road sections, determine whether the area along each road section obtains sufficient vehicle lighting; if not, determine the area along the corresponding road section as the target road area along the urban traffic road network that requires active lighting adjustment; if so, do not determine the area along the corresponding road section as the target road area along the urban traffic road network that requires active lighting adjustment.

8. The intelligent lighting control system along the urban traffic road as claimed in claim 7, characterized in that: Based on the traffic density change status information and vehicle lighting range information of all road sections, determine whether the area along each road section has sufficient vehicle lighting, including: Extracting the information on the change of the number of vehicles per unit length in each road section contained in the traffic density change state information; Obtaining a first lighting evaluation coefficient according to information on changes in the number of vehicles within a unit length range in each road section over time; Wherein, the first lighting evaluation coefficient is obtained by the following formula: Among them, K 01 represents the first lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of unit time is 1min-6min; F ij F represents the number of vehicles that pass through the jth unit time of the i-th unit length; ij-1 F represents the number of vehicles that pass through the i-th unit length in the j-1th unit time; bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-th unit length; F bi represents the standard deviation of the number of vehicles corresponding to m units of time of the i-1th unit length; F zi represents the median value of the number of vehicles corresponding to m units of time of the i-th unit length; F maxi F represents the maximum number of vehicles corresponding to m units of time of the i-th unit length; bz represents the median standard deviation of the number of vehicles corresponding to m unit time of n unit length; F bmax It represents the maximum value of the standard deviation of the number of vehicles corresponding to m unit time of n unit length; Extract vehicle lighting range information; Obtaining a second lighting evaluation coefficient using the vehicle lighting range information; Wherein, the second lighting evaluation coefficient is obtained by the following formula: Among them, K 02 represents the second lighting evaluation coefficient; n represents the number of unit lengths contained in each road section; m represents the number of unit time experienced by each unit length, and the value of the unit time is 1min-6min; S ij S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-th unit time; ij-1 S represents the average area of ​​the vehicle lighting range of the vehicle passing through the i-th unit length in the j-1th unit time; bi S represents the standard deviation of the vehicle lighting range area of ​​the i-th unit length; bi-1 represents the standard deviation of the vehicle lighting range area of ​​the i-1th unit length; Obtaining a comprehensive lighting evaluation coefficient using the first lighting evaluation coefficient and the second lighting evaluation coefficient; The comprehensive lighting evaluation coefficient is obtained by the following formula: Wherein, K represents the comprehensive lighting evaluation coefficient; K 01 Represents the first lighting evaluation coefficient; K 02 represents the second lighting evaluation coefficient; Comparing the comprehensive lighting evaluation coefficient with a preset evaluation coefficient threshold; When the comprehensive lighting evaluation coefficient exceeds a preset evaluation coefficient threshold, it indicates that the area along the road section has sufficient vehicle lighting; When the comprehensive lighting evaluation coefficient does not exceed the preset evaluation coefficient threshold, it indicates that the area along the road section does not obtain sufficient vehicle lighting.

9. The intelligent lighting control system along the urban traffic road as claimed in claim 6, characterized in that: The object existence status recognition module is used to perform visual recognition on the area along the target road to obtain object existence status information in the area along the target road, including: The target road area is photographed in three dimensions to obtain a three-dimensional image of the target road area; object contours are recognized on the three-dimensional image of the target road area to obtain three-dimensional space existence status information of objects in the target road area; wherein the three-dimensional space existence status information of objects includes the area range information of all static objects in the target road area in three-dimensional space; The lighting adjustment sub-area identification module is used to identify the sub-area that needs to adjust the lighting inside the area along the target road based on the object existence state information, including: Based on the three-dimensional space existence status information of the object, the shielding range formed by all static objects in the area along the target road is located and identified, so as to obtain the sub-area in the area along the target road where the lighting needs to be adjusted.

10. The intelligent lighting control system along the urban traffic road as claimed in claim 6, characterized in that: The lighting device matching determination module is used to identify a matching lighting device for performing lighting adjustment on the sub-area requiring lighting adjustment based on the distribution position information of all lighting devices in the area along the target road and the sub-area requiring lighting adjustment, including: Based on the distribution position information of all lighting devices in the area along the target road and the sub-area where lighting adjustment is required, estimating the lighting influence value of each lighting device on the sub-area where lighting adjustment is required; based on the lighting influence value, identifying a matching lighting device for performing lighting adjustment on the sub-area where lighting adjustment is required; The lighting state adjustment module is used to adjust the lighting state of the sub-area requiring lighting adjustment by the matching lighting device based on the lighting feature information of the matching lighting device, including: Based on the adjustable range of the illumination light emission angle and the adjustable range of the illumination light intensity of the matching illumination device, the illumination angle and / or illumination intensity of the matching illumination device for the sub-area requiring illumination adjustment is adjusted.

Images