Traffic early warning system based on intelligent street lamp

Abstract

The invention discloses a traffic early warning system based on an intelligent street lamp, and relates to the technical field of traffic. According to the method, traffic data of each road in the subordinate operation area of each smart street lamp is monitored and collected, and then the traffic behavior representation value of each road in the subordinate operation area of each smart street lamp is obtained through analysis, so that the illumination demand of each road can be predicted and planned more accurately, unnecessary energy consumption is reduced, and the energy consumption is reduced. The method provides data support for the system to adjust the light mode of the intersection, finally adjusts the light mode of the intelligent street lamp according to the traffic behavior representation value of each road of the subordinate operation area of each intelligent street lamp, and carries out early warning prompt on an intersection display screen, thereby facilitating the reduction of the risk of traffic accidents, improving the safety of pedestrians and vehicles, and improving the safety of the system. The lighting condition can be accurately mastered, the traffic mobility is improved, and the traffic safety and the living quality of residents can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of traffic technology, and in particular to a traffic warning system based on smart street lamps. Background Art

[0002] In the field of smart city construction and environmental monitoring and management, smart street lights, as one of the infrastructures of smart cities, can be integrated with other intelligent systems to improve the overall operation efficiency of the city and the quality of life of residents. They can also monitor the surface status of the road, help city managers take timely response measures, ensure road safety and smooth traffic, and help improve traffic efficiency and safety.

[0003] Prior art, such as the invention patent with announcement number: CN112396833B, discloses an application method, device, computer equipment and storage medium for a smart street light. The method includes obtaining detection information captured by the smart street light; performing traffic flow analysis based on the detection information to obtain analysis results; uploading the analysis results to a cloud server and a corresponding terminal to store the analysis results on the cloud server and display the analysis results on the corresponding terminal. This invention integrates sensors and cameras on smart street lights, starts the camera to capture videos based on the user's configuration or the sensor's detection, and then uses an AI algorithm to analyze the captured videos and calculate the flow of people and vehicles, thereby forming analysis results, displaying the analysis results on the terminal and uploading them to the cloud server for storage, thereby integrating traffic flow monitoring functions on street lights and enriching the functions of street lights.

[0004] The prior art, such as the invention patent announcement with announcement number: CN111210629B, discloses a smart traffic control method and system based on street light poles. The method includes: when the traffic flow information λnt detected by the street light pole Ln at time t is less than the traffic flow threshold λ, the edge control mode is turned on: judging whether the number of dynamic targets Dnt detected by the street light pole Ln at time t is greater than 0, if so, sending a control instruction to increase the light brightness to the edge computing unit in the street light pole Ln and the street light pole in front of it; if not, judging whether the duration of the number of dynamic targets Dnt=0 detected by the street light pole Ln at time t reaches a preset time, if so, sending a control instruction to reduce the light brightness to the street light pole Ln. The invention can flexibly control the use of light of the lighting module according to the actual traffic situation, which is conducive to saving electricity, reducing traffic costs, and meeting the requirements of green environmental protection.

[0005] Combining the above solutions, it is found that currently in the field of smart street light technology, usually only the traffic status and light usage are analyzed, and the lighting conditions cannot be controlled. The early warning devices are not comprehensive enough to provide favorable support for urban planning and management. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a traffic warning system based on smart street lamps, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a traffic warning system based on smart street lights, including a control center platform for monitoring and collecting traffic data of each road in the operating area of ​​each smart street light.

[0008] The road state analysis module is used to analyze the traffic data of each road in the operating area of ​​each smart street lamp to obtain the traffic behavior characterization value of each road in the operating area of ​​each smart street lamp.

[0009] The road warning control module is used to adjust the lighting mode of the smart street lamps according to the traffic behavior characterization values ​​of each road in the operating area of ​​each smart street lamp, and to issue warning prompts on the intersection display screen.

[0010] Furthermore, the traffic data of each road in the operating area of ​​each smart street lamp includes pedestrian status data, vehicle status data and environmental status data.

[0011] Furthermore, the road state analysis module specifically includes a road pedestrian state monitoring unit, a road driving state monitoring unit and a road environment state monitoring unit, wherein: the road pedestrian state monitoring unit is used to analyze the pedestrian state data of each road in the operating area of ​​each smart street lamp to obtain the pedestrian state characterization value of each road in the operating area of ​​each smart street lamp.

[0012] The road driving state monitoring unit is used to analyze the driving state data of each road in the subordinate operation area of ​​each smart street lamp to obtain the driving state representation value of each road in the subordinate operation area of ​​each smart street lamp.

[0013] The road environment status monitoring unit is used to analyze the environment status data of each road in the operating area of ​​each smart street lamp to obtain the environment status representation value of each road in the operating area of ​​each smart street lamp.

[0014] Furthermore, the pedestrian status characterization value of each road in the subordinate operation area of ​​each smart street lamp is specifically analyzed in the following process: arranging a monitoring cycle, setting a number of monitoring time periods in the monitoring cycle, extracting the number of pedestrians on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period in the pedestrian status data, and then analyzing to obtain the pedestrian status characterization value of each road in the subordinate operation area of ​​each smart street lamp.

[0015] Furthermore, the driving status characterization values ​​of each road in the subordinate operation area of ​​each smart street lamp are specifically analyzed as follows: the driving status characterization values ​​of each road in the subordinate operation area of ​​each smart street lamp include the vehicle index values ​​of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the status index values ​​of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0016] The vehicle index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period, the specific analysis process is to extract the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the area of ​​the subordinate operation area of ​​each smart street lamp in the driving status data, and take the ratio of the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the area of ​​the subordinate operation area of ​​each smart street lamp as the vehicle density of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0017] The speed changes of each vehicle on each road in the operating area of ​​each smart street lamp in each monitoring time period are counted, the duration of the monitoring time period is extracted, and the average acceleration of vehicles on each road in the operating area of ​​each smart street lamp in each monitoring time period is obtained.

[0018] The average vehicle travel time of each road in the operating area of ​​each smart street lamp in each monitoring time period is extracted from the driving status data. Combined with the vehicle density and average vehicle acceleration of each road in the operating area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the vehicle index value of each road in the operating area of ​​each smart street lamp in each monitoring time period.

[0019] Furthermore, the status index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period is specifically analyzed in the following process: extracting the design capacity of each road in the subordinate operation area of ​​each smart street lamp in the driving status data, and taking the ratio of the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the design capacity of each road in the subordinate operation area of ​​each smart street lamp as the utilization rate of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0020] The average vehicle driving time of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period is counted, the reference vehicle driving time stored in the road monitoring database is extracted, and the ratio of the average vehicle driving time of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the reference vehicle driving time is used as the smoothness index of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0021] According to the utilization rate and fluency index of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the status index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0022] Furthermore, the driving status characterization value of each road in the subordinate operation area of ​​each smart street lamp is obtained, and the specific process is: according to the vehicle index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the state index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the driving status characterization value of each road in the subordinate operation area of ​​each smart street lamp.

[0023] Furthermore, the environmental status characterization value of each road in the subordinate operation area of ​​each smart street lamp is specifically analyzed in the following process: extracting the environmental status data of each road in the subordinate operation area of ​​each smart street lamp to obtain the environmental status data set of each road in the subordinate operation area of ​​each smart street lamp, extracting the environmental status comparison data set of each road in the subordinate operation area of ​​each smart street lamp stored in the road monitoring database, and comprehensively analyzing to obtain the environmental status characterization value of each road in the subordinate operation area of ​​each smart street lamp.

[0024] Furthermore, the road warning control module specifically includes a lighting adjustment unit, a warning prompt unit and a traffic light control unit, wherein: the lighting adjustment unit is used to adjust the lighting mode of the smart street lamp according to the traffic behavior characterization value of each road in the operating area to which each smart street lamp belongs.

[0025] The early warning prompt unit is used to traverse and screen each road in the subordinate operation area of ​​each smart street lamp according to the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp and provide early warning prompts.

[0026] The traffic light control unit is used to control the travel time of the smart street light traffic light according to the traffic behavior characterization value of each road in the operating area to which each smart street light belongs.

[0027] Furthermore, the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp specifically includes a pedestrian state characterization value, a vehicle state characterization value, and an environmental state characterization value of each road in the subordinate operation area of ​​each smart street lamp, and the specific generation conditions are:

[0028]

[0029] In the formula, Represents the pedestrian status representation value of the jth road in the operating area of ​​the i-th smart street lamp, Indicates the driving status representation value of the jth road in the operating area of ​​the i-th smart street light, represents the environmental state representation value of the jth road in the operating area of ​​the i-th smart street lamp, g ij→k represents the number of pedestrians on the jth road in the operating area of ​​the ith smart street lamp in the kth monitoring period, Δg represents the set reference number of pedestrians, and μ 1 represents the impact factor corresponding to the set number of pedestrians, γ ij→k represents the vehicle index value of the jth road in the operation area of ​​the ith smart street light in the kth monitoring period, μ 2 Indicates the weight factor corresponding to the set vehicle index value, δ ij→k represents the state index value of the jth road in the operation area of ​​the ith smart street lamp in the kth monitoring period, μ 3 Indicates the weight factor corresponding to the set state indicator value, ε ij→p represents the pth environmental state data of the jth road in the operating area of ​​the i-th smart street lamp, Δε ij→p It represents the comparison value of the pth environmental status data of the jth road in the operating area belonging to the ith smart street lamp, i represents the number of the operating area belonging to each smart street lamp, i=1,2,3,…n, n represents the total number of the operating areas belonging to the smart street lamp, j represents the number of each road belonging to the operating area, j=1,2,3,…m, m represents the total number of roads belonging to the operating area, k represents the number of each monitoring time period, k=1,2,3,…h, h represents the total number of monitoring time periods, p represents the number of each environmental status data, p=1,2,3,…L, L represents the total number of environmental status data.

[0030] The present invention has the following beneficial effects:

[0031] (1) The present invention provides a traffic warning system based on smart street lamps. First, the system monitors and collects traffic data of each road in the operating area of ​​each smart street lamp, which helps the system to more effectively plan and adjust the brightness and lighting time of the street lamps. Then, the system analyzes and obtains the traffic behavior characterization value of each road in the operating area of ​​each smart street lamp, which can provide data support for the adjustment of the lighting mode of the smart street lamp. Finally, the lighting mode of the smart street lamp is adjusted and a warning prompt is issued, thereby improving the efficiency and quality of urban lighting management and improving traffic safety and energy efficiency.

[0032] (2) The present invention obtains the traffic behavior characterization value of each road in the operating area of ​​each smart street lamp by analyzing, which helps the system to more accurately predict and respond to changes in traffic conditions. The system improves the lighting effect and traffic safety of smart street lamps by performing integrated data analysis on traffic data, promotes the intelligence and efficiency of urban management, effectively realizes the accurate grasp of urban lighting conditions, and improves the efficiency of traffic management.

[0033] (3) The present invention can effectively save energy by adjusting the lighting mode of the smart street lamps according to the traffic behavior characterization values ​​of each road in the operating area to which each smart street lamp belongs. It can also accurately adjust the brightness and coverage of the street lamps to improve the visibility of pedestrians and vehicles, thereby enhancing traffic safety. The brightness of the street lamps can be dynamically adjusted according to the real-time status of pedestrians and vehicles, thereby reducing the problems of excessive lighting and light pollution.

[0034] (4) The present invention controls the travel time of smart street lights and traffic lights through a road warning control module, which helps to reduce the risk of traffic accidents, enhance traffic safety, save energy and reduce emissions, enhance road safety, optimize lighting effects, and improve the level of smart city management, thereby achieving accurate grasp of urban lighting conditions, improving urban lighting effects, and providing urban residents with a safer and more efficient urban living environment.

[0035] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0037] Figure 2 Example images representing values ​​for driving status.

[0038] Figure 3 This is a cross-sectional diagram of street light image recognition in a traffic warning system based on smart street lights.

[0039] Figure 4 This is a traffic warning flow chart.

[0040] In the figure, 1, lamp, 2, solar panel, 3, camera, 4, data transmission sensor, 5, highlight sensor. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1 As shown, an embodiment of the present invention provides a technical solution: a traffic warning system based on smart street lamps, including a control center platform for monitoring and collecting traffic data of each road in the operating area of ​​each smart street lamp.

[0043] It should be noted that the control center platform can ensure the quality of street lamps or cameras during their service life. When it detects that the energy used by the street lamps or cameras is insufficient to support their use, it will issue an early warning to prompt maintenance personnel to replace them. The control center platform will reset the time for the street lamps or cameras after they are replaced.

[0044] The road state analysis module is used to analyze the traffic data of each road in the operating area of ​​each smart street lamp to obtain the traffic behavior characterization value of each road in the operating area of ​​each smart street lamp.

[0045] It should be noted that the traffic behavior characterization value of each road in the operating area to which each smart street lamp belongs includes a pedestrian state characterization value, a vehicle state characterization value and an environmental state characterization value.

[0046] The road warning control module is used to adjust the lighting mode of the smart street lamps according to the traffic behavior characterization values ​​of each road in the operating area of ​​each smart street lamp, and to issue warning prompts on the intersection display screen.

[0047] Specifically, the traffic data of each road in the operating area of ​​each smart street lamp includes pedestrian status data, vehicle status data and environmental status data.

[0048] Specifically, the road state analysis module includes a road pedestrian state monitoring unit, a road driving state monitoring unit and a road environment state monitoring unit, wherein: the road pedestrian state monitoring unit is used to analyze the pedestrian state data of each road in the subordinate operation area of ​​each smart street lamp, and obtain the pedestrian state characterization value of each road in the subordinate operation area of ​​each smart street lamp.

[0049] The road driving state monitoring unit is used to analyze the driving state data of each road in the subordinate operation area of ​​each smart street lamp to obtain the driving state representation value of each road in the subordinate operation area of ​​each smart street lamp.

[0050] The road environment status monitoring unit is used to analyze the environment status data of each road in the operating area of ​​each smart street lamp to obtain the environment status representation value of each road in the operating area of ​​each smart street lamp.

[0051] Specifically, the pedestrian status characterization value of each road in the affiliated operation area of ​​each smart street lamp, the specific analysis process is: arrange a monitoring cycle, set a number of monitoring time periods in the monitoring cycle, extract the number of pedestrians on each road in the affiliated operation area of ​​each smart street lamp in each monitoring time period in the pedestrian status data, and then analyze and obtain the pedestrian status characterization value of each road in the affiliated operation area of ​​each smart street lamp.

[0052] It should be noted that the number of pedestrians on each road in the operating area of ​​each smart street lamp in each monitoring time period refers to the total number of pedestrians passing through a road in the operating area of ​​a smart street lamp in the monitoring time period, which is usually obtained through recognition by a camera connected to a computer vision processing unit installed on the smart street lamp system.

[0053] It should be supplemented that the road pedestrian status monitoring unit also includes comparing the number of pedestrians on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period with the set pedestrian number threshold of each road in the subordinate operation area of ​​each smart street lamp. If the number of pedestrians on each road in the subordinate operation area of ​​each smart street lamp in a certain monitoring time period is higher than the set pedestrian number threshold of each road in the subordinate operation area of ​​each smart street lamp, then the monitoring time period is recorded as an abnormal monitoring time period, and the lighting mode of the smart street lamp is adjusted according to the abnormal monitoring time period.

[0054] It should be added that the lighting mode of the smart street lamp is adjusted, wherein the lighting mode is divided into four modes, including normal lighting mode, high brightness illumination mode, light and dark change mode and orange and blue color switching mode.

[0055] It should be noted that the high-brightness illumination mode can produce a high-brightness illumination spot with a brightness that will not cause damage to human vision, reminding drivers to pay attention to pedestrian safety. The light and dark change mode can prompt that excessive traffic has reached an early warning, and then achieve intelligent diversion through the city's CIM system to alleviate traffic congestion. The orange and blue color switching mode can warn moving vehicles, and the early warning indicates that the road environment may have roadbed subsidence, landslides, mudslides, and excessive water accumulation.

[0056] It should be noted that the lighting mode of the smart street lamp is adjusted according to the abnormal monitoring time period. The specific process is to adjust the lighting mode of the smart street lamp to the high-brightness illumination mode during the abnormal monitoring time period, and use the data analysis algorithm to dynamically adjust the passage time of the traffic light based on real-time data and preset safety rules, and send the adjusted passage time information to the city CIM system. The city CIM system adjusts the traffic lights within a radius of 200 meters according to the received instructions, and extends or shortens the green light time to adapt to the current traffic conditions and pedestrian needs.

[0057] Specifically, the driving status characterization values ​​of each road in the subordinate operation area of ​​each smart street lamp, and the specific analysis process is: the driving status characterization values ​​of each road in the subordinate operation area of ​​each smart street lamp include the vehicle index values ​​of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the status index values ​​of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0058] It should be noted that the vehicle index value of each road in the operating area of ​​each smart street lamp in each monitoring time period represents the numerical quantification result obtained by detecting and analyzing the vehicle status of each road, and is used to quantify the impact of the vehicle status of each road on the overall traffic flow of the road.

[0059] It should be noted that the status index value of each road in the operating area of ​​each smart street lamp in each monitoring time period represents the numerical quantification result obtained by detecting and analyzing the traffic flow status of each road, and is used to quantify the impact of the traffic flow status of each road on the overall traffic flow of the road.

[0060] The vehicle index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period, the specific analysis process is to extract the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the area of ​​the subordinate operation area of ​​each smart street lamp in the driving status data, and take the ratio of the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the area of ​​the subordinate operation area of ​​each smart street lamp as the vehicle density of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0061] It should be noted that the number of vehicles on each road in the operating area of ​​each smart street lamp in each monitoring time period refers to the total number of vehicles passing through the road in the operating area of ​​the smart street lamp in a certain monitoring time period, which can be obtained through vehicle detector detection.

[0062] It should be noted that the area of ​​the operating area of ​​each smart street lamp refers to the total area of ​​the geographical area controlled or monitored by each smart street lamp, which is measured using geographic information system tools.

[0063] The speed changes of each vehicle on each road in the operating area of ​​each smart street lamp in each monitoring time period are counted, the duration of the monitoring time period is extracted, and the average acceleration of vehicles on each road in the operating area of ​​each smart street lamp in each monitoring time period is obtained.

[0064] It should be noted that the speed change of each vehicle on each road in the operating area of ​​each smart street lamp in each monitoring time period refers to the change in the speed of the vehicles on the roads monitored by the smart street lamps at different time points in a certain monitoring time period. The camera can be used to analyze the speed of the vehicle, and the speed change can be calculated based on the time and distance when the vehicle passes through the jurisdiction of the smart street lamp at two time points.

[0065] It should be noted that the duration of each monitoring time period is the same.

[0066] It should be noted that the average acceleration of vehicles on each road in the operating area of ​​each smart street lamp in each monitoring time period refers to the average acceleration of all vehicles on the road monitored by the smart street lamp in a certain monitoring time period. The ratio of the speed change of each vehicle on each road in the operating area of ​​each smart street lamp in each monitoring time period to the duration of the monitoring time period is used as the acceleration of each vehicle on each road in the operating area of ​​each smart street lamp in each monitoring time period. The acceleration of each vehicle is accumulated and divided by the total number of vehicles to obtain the average acceleration of the vehicle.

[0067] The average vehicle travel time of each road in the operating area of ​​each smart street lamp in each monitoring time period is extracted from the driving status data. Combined with the vehicle density and average vehicle acceleration of each road in the operating area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the vehicle index value of each road in the operating area of ​​each smart street lamp in each monitoring time period.

[0068] In this embodiment, the vehicle index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period is obtained using the following analysis conditions, specifically:

[0069]

[0070] In the formula, γ ij→k represents the vehicle index value of the jth road in the operation area of ​​the ith smart street light in the kth monitoring period, σ ij→k represents the average vehicle travel time of the jth road in the operating area of ​​the ith smart street light in the kth monitoring period, Δσ represents the set defined vehicle travel time, and θ 1 Represents the weight factor corresponding to the set vehicle travel time, τ ij→k represents the vehicle density of the jth road in the operating area of ​​the ith smart street lamp in the kth monitoring period, Δτ represents the set reference vehicle density, and θ 2 Indicates the weight factor corresponding to the set vehicle density, Q ij→k represents the average vehicle acceleration of the jth road in the operating area of ​​the ith smart street lamp in the kth monitoring period, ΔQ represents the set reference vehicle acceleration, and θ 3 It represents the weight factor corresponding to the set vehicle acceleration, i=1,2,3,…n, n represents the total number of the operating areas of the smart street lamp, j represents the number of each road in the operating area, j=1,2,3,…m, m represents the total number of roads in the operating area, k represents the number of each monitoring time period, k=1,2,3,…h, h represents the total number of monitoring time periods.

[0071] It should be noted that the average vehicle travel time on each road in the operating area of ​​each smart street lamp in each monitoring time period refers to the average time required for vehicles to pass through the road monitored by the smart street lamp in a certain monitoring time period, which is usually measured by a timer.

[0072] It should be noted that in this embodiment, the preset weight factor corresponding to the vehicle travel time, the weight factor corresponding to the vehicle density, and the weight factor corresponding to the vehicle acceleration are obtained from the road monitoring database, and the weight factor corresponding to the vehicle travel time, the weight factor corresponding to the vehicle density, and the weight factor corresponding to the vehicle acceleration are all numbers between 0 and 1.

[0073] In a specific embodiment, through historical data, the relationship between the average vehicle travel time, vehicle density, average vehicle acceleration and vehicle index value of each road in the affiliated operation area of ​​each smart street lamp in each monitoring time period is fitted to obtain a fitting curve, and the weight factor corresponding to the vehicle travel time, the weight factor corresponding to the vehicle density and the weight factor corresponding to the vehicle acceleration are determined according to the fitting curve. The average vehicle travel time, vehicle density and average vehicle acceleration of each road in the affiliated operation area of ​​each smart street lamp in each real-time monitoring time period are substituted into the fitting curve to obtain the corresponding weight factor.

[0074] It should be explained that the analysis method of this embodiment obtains the vehicle index value of each road in the operating area of ​​each smart street lamp in each monitoring time period by combining the average vehicle travel time, vehicle density and average vehicle acceleration of each road in the operating area of ​​each smart street lamp in each monitoring time period, which can effectively optimize the lighting system of smart street lamps and improve the quality of life and safety.

[0075] It should be added that the average vehicle travel time, vehicle density and average vehicle acceleration of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period in this formula are related and do not exist independently. For example: Under normal circumstances, the average vehicle travel time is negatively correlated with the vehicle density. A high vehicle density may cause road congestion, thereby increasing the average vehicle travel time. Areas with high vehicle density often affect the average acceleration of vehicles. High vehicle density will limit the space and time for vehicle acceleration and deceleration, resulting in a lower average acceleration. A higher average acceleration of vehicles indicates that the average vehicle travel time is shorter, which in turn affects the vehicle density of the road. Comprehensive analysis of the average vehicle travel time, vehicle density and average vehicle acceleration of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period can accurately evaluate the vehicle index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0076] In this implementation scheme, analyzing the average vehicle travel time of each road in the operating area of ​​each smart street lamp in each monitoring time period can identify traffic congestion problems in busy traffic sections, analyzing the vehicle density of each road in the operating area of ​​each smart street lamp in each monitoring time period can provide traffic flow distribution maps of roads in different time periods, which helps to optimize road planning and traffic flow, analyzing the average vehicle acceleration of each road in the operating area of ​​each smart street lamp in each monitoring time period helps to evaluate the smoothness of the road, and analyzing the vehicle index values ​​of each road in the operating area of ​​each smart street lamp in each monitoring time period can monitor road usage and traffic conditions in real time, provide more accurate adjustment and management for smart street lighting, save energy and improve environmental benefits.

[0077] Specifically, the status index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period, and the specific analysis process is: extract the design capacity of each road in the subordinate operation area of ​​each smart street lamp in the driving status data, and take the ratio of the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the design capacity of each road in the subordinate operation area of ​​each smart street lamp as the utilization rate of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0078] It should be noted that the design capacity of each road in the operating area of ​​each smart street lamp refers to the maximum traffic flow or vehicle throughput capacity that each road in the operating area of ​​each smart street lamp can support under ideal conditions, which is usually obtained from the control center platform.

[0079] The average vehicle driving time of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period is counted, the reference vehicle driving time stored in the road monitoring database is extracted, and the ratio of the average vehicle driving time of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the reference vehicle driving time is used as the smoothness index of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0080] It should be noted that the average vehicle travel time on each road in the operating area of ​​each smart street lamp in each monitoring time period refers to the average time required for all vehicles to travel from the starting point to the end point on the road monitored by the smart street lamp in a certain monitoring time period. Sensors are used to collect real-time data of vehicles passing through different sections of the road, including passing timestamps. The travel time of each vehicle is calculated based on the passing timestamp between the starting point and the end point. The average travel time in a certain time period can be obtained by averaging the travel time of all vehicles.

[0081] According to the utilization rate and fluency index of each road in the operating area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the status index value of each road in the operating area of ​​each smart street lamp in each monitoring time period.

[0082] In this embodiment, the state index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period is obtained using the following analysis conditions, specifically:

[0083]

[0084] In the formula, δ ij→k It represents the status index value of the jth road in the operation area of ​​the ith smart street lamp in the kth monitoring time period. represents the utilization rate of the jth road in the operation area of ​​the ith smart street lamp in the kth monitoring time period, represents the utilization rate of the defined road, θ 4 Indicates the impact factor corresponding to the utilization rate of the set road, ω ij→k represents the smoothness index of the jth road in the operation area of ​​the ith smart street lamp in the kth monitoring period, Δω represents the smoothness index of the set reference road, and θ 5 It represents the influence factor corresponding to the set road fluency index, i=1,2,3,…n, n represents the total number of operating areas of the smart street lamp, j represents the number of each road in the operating area, j=1,2,3,…m, m represents the total number of roads in the operating area, k represents the number of each monitoring time period, k=1,2,3,…h, h represents the total number of monitoring time periods.

[0085] In a specific embodiment, Table 1 shows the status index values ​​corresponding to the utilization rates and smoothness indexes of different roads. The influencing factors corresponding to the utilization rates of the roads and the influencing factors corresponding to the smoothness index of the roads are both numbers between 0 and 1. In this embodiment, the influencing factor corresponding to the utilization rate of the roads is 0.5, the influencing factor corresponding to the smoothness index of the roads is 0.5, the utilization rate of the defined roads is 0.7, and the smoothness index of the reference roads is 0.5.

[0086] Table 1 State index values ​​corresponding to utilization rate and smoothness index of different roads

[0087] Road number Utilization Fluency Index Status indicator value 1 0.7 0.6 2.2073 2 0.9 0.6 2.4605 3 0.7 0.9 2.1331 4 0.9 0.9 2.3863

[0088] It should be explained that in Table 1, as the utilization rate of the road increases, the state index value of the road increases accordingly, and as the smoothness index of the road increases, the state index value of the road decreases accordingly. Table 1 lists the utilization rates and smoothness indexes of 4 different roads, and the state index values ​​of the roads are obtained through the formula. The state index values ​​of these roads provide the degree of influence of the utilization rates and smoothness indexes of different roads on the state index values. The state index values ​​comprehensively consider the utilization rate and smoothness index of the road, and provide data support for the lighting mode adjustment of the smart street lamp, thereby improving the accurate grasp of the lighting conditions of the road.

[0089] It should be noted that, in this embodiment, the impact factor corresponding to the utilization rate of the preset road and the impact factor corresponding to the smoothness index of the road are obtained from the road monitoring database.

[0090] In a specific embodiment, through historical data, the relationship between the utilization rate, fluency index and status index value of each road in the affiliated operation area of ​​each smart street lamp in each monitoring time period is fitted to obtain a fitting curve, and the influencing factor corresponding to the utilization rate of the road and the influencing factor corresponding to the fluency index of the road are determined according to the fitting curve. The utilization rate and fluency index of each road in the affiliated operation area of ​​each smart street lamp in each real-time monitoring time period are substituted into the fitting curve to obtain the corresponding influencing factor.

[0091] It should be explained that the analysis method of this embodiment obtains the status index value of each road in the operating area of ​​each smart street lamp in each monitoring time period by combining the utilization rate and fluency index of each road in the operating area of ​​each smart street lamp in each monitoring time period, which can provide real-time traffic condition analysis, thereby helping to optimize road design and improve traffic fluidity.

[0092] It should be added that the utilization rate and fluency index of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period in this formula are correlated and do not exist independently. For example: when the utilization rate of a road in the subordinate operation area of ​​a smart street lamp increases, that is, the number of vehicles on the road increases, it may cause traffic congestion and reduced fluency. This is because the increase in vehicles may make it impossible to effectively adjust the signal light cycle, thereby affecting the smoothness of road traffic. Comprehensive analysis of the utilization rate and fluency index of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period can accurately evaluate the status index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period.

[0093] In this implementation scheme, analyzing the utilization rate of each road in the operating area of ​​each smart street lamp in each monitoring time period is helpful for real-time analysis of the traffic load and congestion of the road. Analyzing the smoothness index of each road in the operating area of ​​each smart street lamp in each monitoring time period is helpful for adjusting the traffic flow and optimizing route planning, improving the utilization efficiency of the road. Analyzing the status index value of each road in the operating area of ​​each smart street lamp in each monitoring time period is helpful for the smart street lamp system to accurately grasp the road status, which can achieve safer and more sustainable transportation, reduce traffic congestion, and improve residents' travel experience.

[0094] Specifically, the driving status characterization value of each road in the subordinate operation area of ​​each smart street lamp is obtained. The specific process is: according to the vehicle index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the state index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the driving status characterization value of each road in the subordinate operation area of ​​each smart street lamp.

[0095] Specifically, the environmental status characterization value of each road in the subordinate operation area of ​​each smart street lamp, and the specific analysis process is: extract the environmental status data of each road in the subordinate operation area of ​​each smart street lamp, obtain the environmental status data set of each road in the subordinate operation area of ​​each smart street lamp, extract the environmental status comparison data set of each road in the subordinate operation area of ​​each smart street lamp stored in the road monitoring database, and comprehensively analyze to obtain the environmental status characterization value of each road in the subordinate operation area of ​​each smart street lamp.

[0096] It should be noted that the environmental status characterization value of each road in the operating area to which each smart street lamp belongs represents a numerical quantification result obtained by analyzing the environmental data of the road, and is used to quantify the impact of the environmental data on the overall state of the road.

[0097] It should be supplemented that the environmental status data set of each road in the subordinate operation area of ​​each smart street lamp includes the environmental status data of each road in the subordinate operation area of ​​each smart street lamp, and the environmental status data of each road in the subordinate operation area of ​​each smart street lamp includes but is not limited to the visibility, flatness, number of cracks, and water accumulation depth of each road in the subordinate operation area of ​​each smart street lamp.

[0098] It needs to be explained that in rainy, snowy or foggy weather, road visibility is usually poor. Lower road visibility may cause the driver to be unable to clearly see the road conditions ahead and around him, and may therefore be unable to make safe driving decisions and reduce the incidence of accidents. Therefore, early warning prompts may be required.

[0099] It needs to be explained that roads built in areas with complex terrain, such as low-lying areas or near river banks, are prone to water accumulation. Deeper water depth may cause the vehicle to lose traction and even create the risk of loss of control, so early warning prompts may be required.

[0100] It should be noted that the environmental status data of each road in the operating area of ​​each smart street lamp include but are not limited to the visibility, flatness, number of cracks, and water depth of each road in the operating area of ​​each smart street lamp. The visibility of the road refers to the degree to which objects can be seen and identified at a certain time and place, which is usually measured by photoelectric sensors or laser rangefinders. The flatness of the road refers to the flatness or surface roughness of the road surface, which is usually measured by high-precision laser rangefinders, vehicle-mounted sensors or ground contact sensors. The number of cracks on the road refers to the number of cracks on the road surface, which can be identified and calculated through video surveillance, camera image analysis or special road detection instruments. The depth of water accumulation on the road refers to the depth of water accumulation on the road, which is usually measured by water level sensors, laser rangefinders or image processing technology.

[0101] It should be added that the environmental status data set of each road in the operating area of ​​each smart street lamp contains parameters in multiple aspects, and the various parameters are related to each other and do not exist independently. For example, a large number of cracks on a road may cause splashing after water accumulation on rainy days, affecting road visibility.

[0102] It should be supplemented that, the data set of comparison of the environmental status of each road in the subordinate operation area of ​​each smart street lamp includes the comparison values ​​of the environmental status data of each road in the subordinate operation area of ​​each smart street lamp, and the comparison values ​​of the environmental status data of each road in the subordinate operation area of ​​each smart street lamp include but are not limited to the visibility comparison value, flatness comparison value, crack number comparison value, and water depth comparison value of each road in the subordinate operation area of ​​each smart street lamp.

[0103] It should be noted that the comparison values ​​of the environmental status data of each road in the subordinate operation area of ​​each smart street lamp include but are not limited to the visibility comparison value, flatness comparison value, crack number comparison value, and water depth comparison value of each road in the subordinate operation area of ​​each smart street lamp. Each comparison value in the comparison values ​​of the environmental status data of each road in the subordinate operation area of ​​each smart street lamp is usually obtained by statistical analysis of historical data. The specific steps are to count the specific values ​​of the historical road environmental status data, and calculate the average value of these values ​​to obtain each comparison value. By way of example, it is assumed that the average value of the water depth of a certain road in the subordinate operation area of ​​a smart street lamp in the historical data is 10 mm. According to the statistical results, it can be obtained that the comparison value of the water depth of the road in the subordinate operation area of ​​the smart street lamp is 10 mm.

[0104] It should be added that what needs to be understood here is that the environmental status data set of each road in the subordinate operation area of ​​each smart street lamp and the data in the environmental status comparison data set of each road in the subordinate operation area of ​​each smart street lamp correspond to each other.

[0105] Specifically, the road warning control module includes a lighting adjustment unit, a warning prompt unit and a traffic light control unit, wherein: the lighting adjustment unit is used to adjust the lighting mode of the smart street lamp according to the traffic behavior characterization value of each road in the operating area to which each smart street lamp belongs.

[0106] It should be supplemented that the lighting mode of the smart street lamp is adjusted according to the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp. The specific process is to compare the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp with the set traffic behavior characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, including comparing the pedestrian state characterization value of each road in the subordinate operation area of ​​each smart street lamp with the set pedestrian state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp. If the pedestrian state characterization value of a certain road in the subordinate operation area of ​​a certain smart street lamp is higher than or equal to the set pedestrian state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, the lighting mode of the smart street lamp is adjusted to the high-brightness illumination mode; if the pedestrian state characterization value of a certain road in the subordinate operation area of ​​a certain smart street lamp is lower than the set pedestrian state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, the lighting mode of the smart street lamp is adjusted to the normal lighting mode.

[0107] The driving state characterization value of each road in the subordinate operation area of ​​each smart street lamp is compared with the set driving state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp. If the driving state characterization value of a road in the subordinate operation area of ​​a smart street lamp is higher than or equal to the set driving state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, the lighting mode of the smart street lamp is adjusted to the light and dark change mode. If the driving state characterization value of a road in the subordinate operation area of ​​a smart street lamp is lower than the set driving state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, the lighting mode of the smart street lamp is adjusted to the normal lighting mode.

[0108] The environmental state characterization value of each road in the subordinate operation area of ​​each smart street lamp is compared with the set environmental state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp. If the environmental state characterization value of a road in the subordinate operation area of ​​a smart street lamp is higher than or equal to the set environmental state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, the lighting mode of the smart street lamp is adjusted to the orange-blue color switching mode. If the environmental state characterization value of a road in the subordinate operation area of ​​a smart street lamp is lower than the set environmental state characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, the lighting mode of the smart street lamp is adjusted to the normal lighting mode.

[0109] The early warning prompt unit is used to traverse and screen each road in the subordinate operation area of ​​each smart street lamp according to the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp and provide early warning prompts.

[0110] It should be added that, according to the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp, each road in the subordinate operation area of ​​each smart street lamp is traversed and screened, and early warning prompts are given. The specific process is to compare the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp with the set traffic behavior characterization threshold of each road in the subordinate operation area of ​​each smart street lamp. If the traffic behavior characterization value of a certain road in the subordinate operation area of ​​a certain smart street lamp is higher than or equal to the set traffic behavior characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, the road in the subordinate operation area of ​​the smart street lamp is marked as an abnormal road, all abnormal roads are traversed and screened, and abnormal prompts are sent to the intersection display screen through the control center platform.

[0111] The traffic light control unit is used to control the travel time of the smart street light traffic light according to the traffic behavior characterization value of each road in the operating area to which each smart street light belongs.

[0112] It should be added that the travel time of the smart street light traffic lights is controlled according to the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street light. The specific process is that if the vehicle density of a road in the subordinate operation area of ​​a smart street light is higher than or equal to the set vehicle density threshold of the road, the road traffic lights of the road will be dynamically adjusted through the city CIM system to shorten the red light time and lengthen the green light time. At the same time, the red light time of the smart street light in the subordinate operation area where the vehicle density of the road is lower than the set vehicle density threshold of the road will be extended, and the green light time will be shortened to alleviate traffic congestion.

[0113] Specifically, the traffic behavior representation value of each road in the subordinate operation area of ​​each smart street lamp specifically includes the pedestrian state representation value, the driving state representation value, and the environmental state representation value of each road in the subordinate operation area of ​​each smart street lamp, and the specific generation conditions are:

[0114]

[0115] In the formula, Represents the pedestrian status representation value of the jth road in the operating area of ​​the i-th smart street lamp, Indicates the driving status representation value of the jth road in the operating area of ​​the i-th smart street light, represents the environmental state representation value of the jth road in the operating area of ​​the i-th smart street lamp, g ij→k represents the number of pedestrians on the jth road in the operating area of ​​the ith smart street lamp in the kth monitoring period, Δg represents the set reference number of pedestrians, and μ 1 represents the impact factor corresponding to the set number of pedestrians, γ ij→k represents the vehicle index value of the jth road in the operation area of ​​the ith smart street light in the kth monitoring period, μ 2 Indicates the weight factor corresponding to the set vehicle index value, δ ij→k represents the state index value of the jth road in the operation area of ​​the ith smart street lamp in the kth monitoring period, μ 3 Indicates the weight factor corresponding to the set state indicator value, ε ij→p represents the pth environmental state data of the jth road in the operating area of ​​the i-th smart street lamp, Δε ij→p It represents the comparison value of the pth environmental status data of the jth road in the operating area belonging to the ith smart street lamp, i represents the number of the operating area belonging to each smart street lamp, i=1,2,3,…n, n represents the total number of the operating areas belonging to the smart street lamp, j represents the number of each road belonging to the operating area, j=1,2,3,…m, m represents the total number of roads belonging to the operating area, k represents the number of each monitoring time period, k=1,2,3,…h, h represents the total number of monitoring time periods, p represents the number of each environmental status data, p=1,2,3,…L, L represents the total number of environmental status data.

[0116] It needs to be explained that Figure 2 As shown, Figure 2: is an example image of the driving state characterization value, where the x-axis represents the vehicle index value and the y-axis represents the driving state characterization value. In this embodiment, the weight factor corresponding to the vehicle index value is 0.3, and the weight factor corresponding to the state index value is 0.7. Three different groups of example parameters are defined in the figure, corresponding to different situations of the three curves, represented by solid lines, dashed lines and dotted lines respectively, and the corresponding curve labels are a, b, and c respectively.

[0117] It needs to be explained that when the state index value is 1.0, the functional relationship between the vehicle index value and the driving state characterization value is shown in curve a, when the state index value is 1.2, the functional relationship between the vehicle index value and the driving state characterization value is shown in curve b, and when the state index value is 1.3, the functional relationship between the vehicle index value and the driving state characterization value is shown in curve c. The driving state characterization value increases with the increase of the vehicle index value, and when the state index value increases, the driving state characterization value increases accordingly. The driving state characterization value can be obtained quickly and accurately through the curve, which solves the problem in the prior art that the driving state characterization value cannot be accurately measured due to the lack of detailed analysis process, thereby achieving accurate grasp of the city's lighting conditions.

[0118] It should be noted that in this embodiment, the influence factor corresponding to the preset number of pedestrians, the weight factor corresponding to the vehicle index value, and the weight factor corresponding to the state index value are obtained from the road monitoring database, and the influence factor corresponding to the number of pedestrians, the weight factor corresponding to the vehicle index value, and the weight factor corresponding to the state index value are all numbers between 0 and 1.

[0119] In a specific embodiment, through historical data, the relationship between the number of pedestrians on each road in the affiliated operation area of ​​each smart street lamp in each monitoring time period and the pedestrian status characterization value is fitted to obtain a fitting curve, and the impact factor corresponding to the number of pedestrians is determined according to the fitting curve. The real-time number of pedestrians on each road in the affiliated operation area of ​​each smart street lamp in each monitoring time period is substituted into the fitting curve to obtain the corresponding impact factor.

[0120] In a specific embodiment, through historical data, the relationship between the vehicle index value, state index value and driving state characterization value of each road in the affiliated operation area of ​​each smart street lamp in each monitoring time period is fitted to obtain a fitting curve, and the weight factor corresponding to the vehicle index value and the weight factor corresponding to the state index value are determined according to the fitting curve. The vehicle index value and the state index value of each road in the affiliated operation area of ​​each smart street lamp in each real-time monitoring time period are substituted into the fitting curve to obtain the corresponding weight factor.

[0121] It should be explained that the analysis method of this embodiment combines the vehicle index values ​​of each road in the operating area of ​​each smart street lamp in each monitoring time period and the state index values ​​of each road in the operating area of ​​each smart street lamp in each monitoring time period for analysis, so as to obtain the driving state characterization value of each road in the operating area of ​​each smart street lamp. This helps the smart street lamp system to intelligently adjust the brightness and lighting range of the street lamps according to the real-time road usage, which can save energy while ensuring good visibility of the road surface and improve nighttime driving safety.

[0122] It should be noted that adjusting the brightness of lights will consume a certain amount of electricity, but the smart street light system can achieve overall energy savings by precisely controlling and optimizing the working mode of street lights. The smart street light system can dynamically adjust the brightness of street lights according to real-time ambient lighting conditions and road usage. This real-time adjustment method avoids unnecessary energy consumption at fixed brightness.

[0123] In this implementation scheme, analyzing the vehicle index values ​​of each road in the affiliated operation area of ​​each smart street lamp in each monitoring time period helps the smart street lamp to intelligently adjust the lighting brightness and range according to the vehicle flow conditions on the roads in different time periods. For example, during peak traffic hours, the smart street lamp can increase the brightness to provide better road lighting. Analyzing the status index values ​​of each road in the affiliated operation area of ​​each smart street lamp in each monitoring time period helps to improve traffic fluidity and improve the utilization efficiency of roads by timely adjusting street lamp lighting. Analyzing the driving status characterization values ​​of each road in the affiliated operation area of ​​each smart street lamp helps to improve the accuracy and efficiency of lighting management.

[0124] It should be noted that Figure 3 The middle lamp 1 provides road lighting function, the solar panel 2 collects solar energy and converts it into electrical energy to provide a continuous power supply for the smart street lamp, the camera 3 performs road image recognition and monitors traffic conditions and vehicle behavior on the road, and the data transmission sensor 4 is responsible for transmitting the data collected from the camera 3 and the highlight sensor 5 to the control center platform.

[0125] It should be added that Figure 4 The central control center platform sets the traffic behavior characterization threshold of each road in the subordinate operation area of ​​each smart street lamp, obtains road flow information according to the camera installed on the road, and the control center platform performs intelligent calculation and analysis on the obtained information and adjusts the lighting mode. Then, the control center platform transmits the obtained road flow information to the city CIM system, and the city CIM system performs intelligent calculation and analysis on the obtained data to regulate the city traffic lights.

[0126] It should be noted that the urban CIM system refers to the urban infrastructure management system, which is an integrated information management system designed to effectively manage and monitor various urban infrastructures, including but not limited to roads, bridges, parks, lighting facilities, water supply pipes, and sewage treatment systems.

[0127] It should be noted that a traffic warning system based on smart street lights also includes a road monitoring database, which is used to store the pedestrian number threshold of each road in the affiliated operation area of ​​each smart street light obtained by analyzing historical data, the defined vehicle travel time, the reference vehicle density, the reference vehicle acceleration, the weight factor corresponding to the vehicle travel time, the weight factor corresponding to the vehicle density, the weight factor corresponding to the vehicle acceleration, the reference vehicle driving time, the utilization rate of the defined road, the reference road smoothness index, the influencing factor corresponding to the utilization rate of the road, the influencing factor corresponding to the road smoothness index, the comparison data set of the environmental status of each road in the affiliated operation area of ​​each smart street light, the reference pedestrian number, the influencing factor corresponding to the pedestrian number, the weight factor corresponding to the vehicle index value and the weight factor corresponding to the status index value.

[0128] It should be added that compared with existing intelligent technologies, the smart street lights of the present invention can achieve accurate grasp of the city’s lighting conditions, the early warning device is more comprehensive, and provides favorable support for urban planning and management. The equipment is time-limited and recyclable, which can reduce energy consumption and maintenance costs.

[0129] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0130] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A traffic warning system based on smart street lights, characterized in that: include: The control center platform is used to monitor and collect traffic data of each road in the operating area of ​​each smart street lamp; A road state analysis module is used to analyze the traffic data of each road in the subordinate operation area of ​​each smart street lamp to obtain the traffic behavior representation value of each road in the subordinate operation area of ​​each smart street lamp; The road warning control module is used to adjust the lighting mode of the smart street lamps according to the traffic behavior characterization values ​​of each road in the operating area of ​​each smart street lamp, and to issue warning prompts on the intersection display screen.

2. According to claim 1, a traffic warning system based on smart street lamps is characterized in that: The traffic data of each road in the operating area of ​​each smart street lamp includes pedestrian status data, vehicle status data and environmental status data.

3. The traffic warning system based on smart street lamps according to claim 1 is characterized in that: The road state analysis module specifically includes a road pedestrian state monitoring unit, a road vehicle state monitoring unit and a road environment state monitoring unit, wherein: The road pedestrian status monitoring unit is used to analyze the pedestrian status data of each road in the subordinate operation area of ​​each smart street lamp to obtain the pedestrian status representation value of each road in the subordinate operation area of ​​each smart street lamp; The road driving state monitoring unit is used to analyze the driving state data of each road in the subordinate operation area of ​​each smart street lamp to obtain the driving state representation value of each road in the subordinate operation area of ​​each smart street lamp; The road environment status monitoring unit is used to analyze the environment status data of each road in the operating area of ​​each smart street lamp to obtain the environment status representation value of each road in the operating area of ​​each smart street lamp.

4. The traffic warning system based on smart street lamps according to claim 2 is characterized in that: The pedestrian status representation value of each road in the subordinate operation area of ​​each smart street lamp, the specific analysis process is: Arrange a monitoring cycle, set several monitoring time periods in the monitoring cycle, extract the number of pedestrians on each road in the operating area of ​​each smart street lamp in each monitoring time period in the pedestrian status data, and then analyze and obtain the pedestrian status representation value of each road in the operating area of ​​each smart street lamp.

5. The traffic warning system based on smart street lamps according to claim 2 is characterized in that: The driving state representation value of each road in the subordinate operation area of ​​each smart street lamp, the specific analysis process is: The driving state characterization value of each road in the subordinate operation area of ​​each smart street lamp includes the vehicle index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the state index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period; The vehicle index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period is specifically analyzed by extracting the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the area of ​​the subordinate operation area of ​​each smart street lamp in the driving status data, and taking the ratio of the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the area of ​​the subordinate operation area of ​​each smart street lamp as the vehicle density of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period; Count the speed changes of each vehicle on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period, extract the duration of the monitoring time period, and statistically obtain the average acceleration of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period; The average vehicle travel time of each road in the operating area of ​​each smart street lamp in each monitoring time period is extracted from the driving status data. Combined with the vehicle density and average vehicle acceleration of each road in the operating area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the vehicle index value of each road in the operating area of ​​each smart street lamp in each monitoring time period.

6. The traffic warning system based on smart street lamps according to claim 5 is characterized in that: The specific analysis process of the status index value of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period is as follows: Extract the design capacity of each road in the subordinate operation area of ​​each smart street lamp in the driving status data, and use the ratio of the number of vehicles on each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the design capacity of each road in the subordinate operation area of ​​each smart street lamp as the utilization rate of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period; The average vehicle driving time of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period is counted, the reference vehicle driving time stored in the road monitoring database is extracted, and the ratio of the average vehicle driving time of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period to the reference vehicle driving time is used as the smoothness index of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period; According to the utilization rate and fluency index of each road in the operating area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the status index value of each road in the operating area of ​​each smart street lamp in each monitoring time period.

7. The traffic warning system based on smart street lamps according to claim 2 is characterized in that: The specific process of obtaining the driving state representation value of each road in the subordinate operation area of ​​each smart street lamp is as follows: According to the vehicle index values ​​of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period and the state index values ​​of each road in the subordinate operation area of ​​each smart street lamp in each monitoring time period, a comprehensive analysis is performed to obtain the driving state characterization values ​​of each road in the subordinate operation area of ​​each smart street lamp.

8. The traffic warning system based on smart street lamps according to claim 2 is characterized in that: The environmental status characterization value of each road in the subordinate operation area of ​​each smart street lamp, the specific analysis process is: The environmental status data of each road in the subordinate operation area of ​​each smart street lamp is extracted to obtain the environmental status data set of each road in the subordinate operation area of ​​each smart street lamp, and the environmental status comparison data set of each road in the subordinate operation area of ​​each smart street lamp stored in the road monitoring database is extracted, and the environmental status characterization value of each road in the subordinate operation area of ​​each smart street lamp is obtained through comprehensive analysis.

9. The traffic warning system based on smart street lamps according to claim 1 is characterized in that: The road warning control module specifically includes a light adjustment unit, a warning prompt unit and a traffic light control unit, wherein: The light adjustment unit is used to adjust the light mode of the smart street lamp according to the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp; The early warning prompt unit is used to traverse and screen each road in the subordinate operation area of ​​each smart street lamp according to the traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp and provide early warning prompts; The traffic light control unit is used to control the travel time of the smart street light traffic light according to the traffic behavior characterization value of each road in the operating area to which each smart street light belongs.

10. The traffic warning system based on smart street lamps according to claim 1 is characterized in that: The traffic behavior characterization value of each road in the subordinate operation area of ​​each smart street lamp specifically includes the pedestrian state characterization value, the driving state characterization value, and the environmental state characterization value of each road in the subordinate operation area of ​​each smart street lamp, and the specific generation conditions are: In the formula, Represents the pedestrian status representation value of the jth road in the operating area of ​​the i-th smart street lamp, Indicates the driving status representation value of the jth road in the operating area of ​​the i-th smart street light, represents the environmental state representation value of the jth road in the operating area of ​​the i-th smart street lamp, g ij→k represents the number of pedestrians on the jth road in the operating area of ​​the ith smart street lamp in the kth monitoring period, Δg represents the set reference number of pedestrians, μ1 represents the impact factor corresponding to the set number of pedestrians, and γ ij→k represents the vehicle index value of the jth road in the operating area of ​​the ith smart street lamp in the kth monitoring time period, μ2 represents the weight factor corresponding to the set vehicle index value, δ ij→k represents the state index value of the jth road in the operation area of ​​the ith smart street lamp in the kth monitoring time period, μ3 represents the weight factor corresponding to the set state index value, ε ij→p represents the pth environmental state data of the jth road in the operating area of ​​the i-th smart street lamp, Δε ij→p It represents the comparison value of the pth environmental status data of the jth road in the operating area belonging to the ith smart street lamp, i represents the number of the operating area belonging to each smart street lamp, i=1,2,3,…n, n represents the total number of the operating areas belonging to the smart street lamp, j represents the number of each road belonging to the operating area, j=1,2,3,…m, m represents the total number of roads belonging to the operating area, k represents the number of each monitoring time period, k=1,2,3,…h, h represents the total number of monitoring time periods, p represents the number of each environmental status data, p=1,2,3,…L, L represents the total number of environmental status data.

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