Intelligent street lamp layout method and system based on regional pedestrian and vehicle flow analysis

Abstract

The present invention relates to the technical field of street lamp arrangement, and discloses a smart street lamp arrangement method and system based on regional pedestrian and vehicle flow analysis, including a real-time monitoring module, a regional analysis module, a multi-dimensional evaluation module and an arrangement decision module. The smart street lamp arrangement method and system based on regional pedestrian and vehicle flow analysis collects pedestrian and vehicle flow data, environmental data, and installation detection data of road lighting lamps through a real-time monitoring module, the regional analysis module generates a density coefficient, the multi-dimensional evaluation module analyzes the change trend of the density coefficient of each region, and judges the fluctuation level of the pedestrian and vehicle flow in each region, and the dynamic monitoring has high accuracy. The multi-dimensional evaluation module analyzes the vibration amplitude, electromagnetic interference intensity and wind extreme difference of each region, and generates an influence coefficient. The arrangement decision module outputs control instructions through wireless communication technology, checks the connection status of road lighting lamps, judges the rationality of the arrangement of road lighting lamps, and generates corresponding arrangement decisions, so that the optimized arrangement is more scientific and reasonable.

Description

Technical Field

[0001] The present invention relates to the technical field of street lamp arrangement, and specifically to a smart street lamp arrangement method and system based on regional pedestrian and vehicle flow analysis. Background Art

[0002] Road lighting is an important part of modern urban infrastructure. Its basic function is to provide sufficient lighting for the road at night or in low light conditions. Good lighting can significantly improve the safety of nighttime driving, help drivers find obstacles and pedestrians in time, and also allow pedestrians to clearly see the road conditions, reducing the occurrence of traffic accidents. With the promotion of the concept of smart cities, the Internet of Things technology can realize remote monitoring and management of street lights, which can automatically adjust the brightness according to traffic flow and integrate functions such as air quality monitoring. In order to ensure the effectiveness, safety and long-term stability of the road lighting system, the rationality of the design and layout is very important.

[0003] At present, traditional smart street lamp layout methods are often unable to cope with complex and changeable road environments. When road construction or traffic accidents occur, street lamps are easily affected by external forces, resulting in failures or signal loss, and managers find it difficult to detect these problems in time. In addition, there are often deviations between the design layout of street lamps and the actual road environment. When vehicles pass by frequently, it may also cause resonance of lighting lamps on both sides of the road, thereby affecting the service life and safety of street lamps. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides a smart street lamp layout method and system based on regional pedestrian and vehicle flow analysis, which has the advantages of high dynamic monitoring accuracy and more scientific and reasonable optimization layout, and solves the problem of difficulty in coping with complex and changeable road environments and deviations in layout rationality.

[0006] (II) Technical solution

[0007] To achieve the above object, the present invention provides the following technical solution: The smart street lamp arrangement method based on regional pedestrian and vehicle flow analysis includes the following steps:

[0008] Step 1: Divide the roads of the target city into Areas, and then collect the pedestrian and vehicle flow data of all areas, the environmental data of all areas, and the installation and detection data of road lighting in the area. In a single area, there are several road lighting installations;

[0009] Step 2: Analyze the pedestrian density in each area , Vehicle parking density , Traffic density , building density and lighting density , and generate the corresponding dense coefficients ;

[0010] Step 3: Set a monitoring cycle with a fixed duration and a fixed range of fluctuation thresholds , analyze the density coefficient of each area The changing trend of , and determine the fluctuation level of pedestrian and vehicle flows in each area;

[0011] Step 4: Analyze the vibration amplitude of each area , Electromagnetic interference intensity Very bad wind , and generate the corresponding influence coefficient ;

[0012] Step 5: According to the fluctuation level of pedestrian and vehicle flow in each area, the corresponding control instructions are output through wireless communication technology, and the connection status of the road lighting is checked;

[0013] Step 6: Set a fixed range of impact thresholds , combined with the influence coefficient , judge the rationality of the layout of road lighting at the existing time point and generate corresponding layout decisions.

[0014] Preferably, in step 1, within a single day, the pedestrian and vehicle flow data of each area includes the number of roads, pedestrian flow, number of parked vehicles, vehicle load, vehicle flow and vehicle electromagnetic radiation intensity;

[0015] Environmental data for each area include total number of buildings, total area, and wind value;

[0016] The installation inspection data of road lighting in each area includes the installation quantity, unit luminous flux, lamp pole diameter, lamp pole stiffness, excitation frequency and natural frequency.

[0017] Preferably, in step 2, the density coefficient The calculation process is as follows:

[0018] S11, extract the Traffic data of people and vehicles in a region, , and the The number of roads in the area is marked as , will The pedestrian flow in the area is marked as , will The number of vehicles parked in the area is marked as , will The vehicle load in the area is marked as , will The traffic flow in the area is marked as ;

[0019] S12, calculate the Pedestrian density in the area , and its calculation formula is as follows:

[0020] ;

[0021] S13, calculate the Parking density in the area , and its calculation formula is as follows:

[0022] ;

[0023] S14. Vehicle load in the area , will Traffic volume in the area Classified as non-motorized vehicle traffic , passenger vehicle traffic and heavy traffic , among which, the vehicle load of non-motor vehicles is ≤250kg, the vehicle load of passenger cars is ≤250kg, and the vehicle load of heavy vehicles is ≥500kg;

[0024] S15. Calculate the Traffic density in the area , and its calculation formula is as follows:

[0025] ;

[0026] In the formula, It represents the ratio of non-motor vehicle flow to the number of roads, that is, the non-motor vehicle flow density. represents the evaluation weight for non-motor vehicle flow density, It represents the ratio of passenger vehicle flow to the number of roads, that is, the passenger vehicle flow density. represents the evaluation weight for passenger vehicle traffic density, It represents the ratio of heavy vehicle flow to the number of roads, that is, the heavy vehicle flow density. represents the evaluation weight for heavy vehicle flow density, , Indicates according to , and The weights are combined to obtain the non-motor vehicle flow, passenger vehicle flow and heavy vehicle flow. Traffic density in an area;

[0027] S16, extract the The environmental data of each region will be The total number of buildings in the area is marked as , will The total area of ​​the region is marked as , and calculate the Building density in the area , and its calculation formula is as follows:

[0028] ;

[0029] S17, extract the The installation test data of road lighting in each area will be The number of road lighting installations in each area is marked as , will The unit luminous flux of the road lighting in each area is marked as , combined with The total area of ​​the region , calculate the Lighting density of road lighting in each area , and its calculation formula is as follows:

[0030] ;

[0031] In the formula, Indicates The total luminous flux of all road lighting lamps in an area;

[0032] S18, calculate the The density factor of the region , and its calculation formula is as follows:

[0033] ;

[0034] In the formula, represents the evaluation weight for pedestrian density, represents the evaluation weight for vehicle parking density, represents the evaluation weight for traffic density, represents the assessment weight for building density, represents the evaluation weight for lighting density, , Indicates according to , , , and The weights are combined with pedestrian density, vehicle parking density, traffic density, building density and lighting density to obtain the The density factor of a region.

[0035] Preferably, in step 3, the volatility The calculation process is as follows:

[0036] S21. Arrange the monitoring cycles in chronological order from morning to night. within, no. The density factor of the region , and marked as , to From the first time point to the The density coefficient of each time point;

[0037] S22, remove the monitoring cycle Internal, dense coefficient After finding the maximum and minimum values, calculate the The average density factor of the area , and its calculation formula is as follows:

[0038] ;

[0039] S23. Calculate monitoring cycle within, no. The volatility of the regional density coefficient , and its calculation formula is as follows:

[0040] ;

[0041] In the formula, Indicates The density coefficient of each time point, According to the standard deviation formula, the value obtained is The volatility of the regional density coefficient .

[0042] Preferably, in step 3, in the first case, the volatility Exceeding the volatility threshold , indicating that the daily flow of people and vehicles in the area is unstable, and there is intermittent traffic congestion, generating the first level of fluctuation;

[0043] In the second case, the volatility Included in volatility threshold , indicating that the daily flow of people and vehicles in the area is stable, and there is no intermittent traffic congestion, generating the second fluctuation level;

[0044] The stability of the first volatility level is lower than that of the second volatility level.

[0045] Preferably, in step 4, the influence coefficient The calculation process is as follows:

[0046] S31, extract the The installation test data of road lighting in each area, and The pole diameter of the road lighting lamp in each area is marked as , will The pole stiffness of the road lighting in each area is marked as , will The excitation frequency of the road lighting in each area is marked as , will The natural frequency of the road lighting in each area is marked as ;

[0047] S32. According to Diameter of the pole of the road lighting in each area and vehicle load , calculate the vehicle travel to the The impact force generated by the area , and its calculation formula is as follows: ;

[0048] In the formula, represents the dynamic load factor, represents the acceleration due to gravity, represents the conversion factor, It means converting the pole diameter into reaction force;

[0049] S33, calculate the vehicle driving to The vibration amplitude generated when the area , and its calculation formula is as follows:

[0050] ;

[0051] ;

[0052] In the formula, Indicates The average value of the excitation frequency and natural frequency of the road lighting in each area, Indicates The relative frequency difference between the excitation frequency and the natural frequency of the road lighting in each area. When the excitation frequency and the natural frequency are equal, reaches the maximum value, resulting in resonance effect, and the vehicle travels to the The vibration amplitude generated when the area maximum;

[0053] S34, extract the The pedestrian and vehicle flow data of the area will be The electromagnetic radiation intensity of vehicles in the area is marked as , combined with Traffic volume in the area , calculate the electromagnetic interference intensity , and its calculation formula is as follows:

[0054] ;

[0055] S35, extract the The environmental data of each region will be The wind force values ​​for each area are marked as , and calculate the Very bad winds in the area , and its calculation formula is as follows:

[0056] ;

[0057] In the formula, Indicates The maximum wind speed value in the region, Indicates The minimum wind speed value in each area;

[0058] S36, calculate the vehicle travel to The influence coefficient generated when the area , and its calculation formula is as follows:

[0059] ;

[0060] In the formula, represents the evaluation weight for the vibration amplitude, Represents the evaluation weight for electromagnetic interference intensity, represents the assessment weight for extremely poor wind speed, , Indicates according to , and The weight is combined with the vibration amplitude, electromagnetic interference intensity and wind speed difference to obtain the vehicle driving to the first The influence coefficient generated when a region is

[0061] Preferably, in step five, in the first case, when the first fluctuation level is generated, it means that in the area, intermittent traffic congestion causes the road lighting to have a risk of light visibility loss, and it is necessary to output a unified control command to several road lighting in the area through wireless communication technology to increase the current luminous flux by 10%. If the luminous flux of the road lighting in the area does not change, it means that the road lighting has failed due to external force.

[0062] Preferably, step six, influence coefficient Exceeding impact threshold When the signal is detected, it indicates that the layout of the road lighting at the existing time point is unreasonable. When a vehicle drives into this area, the impact force and the environmental wind force cause the road lighting to resonate. There is a risk of loss of service life of the road lighting. In addition, the electromagnetic interference intensity of the vehicle causes a risk of decreased wireless communication quality of the road lighting in this area. In this case, the lamp pole diameter should be increased by 3 cm and the wireless signal transmission power should be increased by 20%.

[0063] Preferably, step six, influence coefficient Included in impact threshold When the monitoring cycle is , regularly inspect and maintain road lighting.

[0064] Smart street light layout system based on regional pedestrian and vehicle flow analysis, including real-time monitoring module, regional analysis module, multi-dimensional evaluation module and layout decision module;

[0065] The real-time monitoring module uses monitoring devices, dynamic weighing devices, electromagnetic radiometers, anemometers, structural detection devices, vibration meters and wireless communication modules to collect data on the flow of people and vehicles in all areas, environmental data in all areas, and detection data on road lighting in the area. In a single area, there are a number of road lighting installations;

[0066] The regional analysis module analyzes the pedestrian density in each area , Vehicle parking density , Traffic density , building density and lighting density , and generate the corresponding dense coefficients ;

[0067] Multi-dimensional evaluation module analyzes the density coefficient of each area The changing trend of , and judge the fluctuation level of pedestrian and vehicle flow in each area. The multi-dimensional evaluation module analyzes the vibration amplitude of each area , Electromagnetic interference intensity Very bad wind , and generate the corresponding influence coefficient ;

[0068] The layout decision module outputs corresponding control instructions through wireless communication technology according to the fluctuation level of pedestrian and vehicle flow in each area, and checks the connection status of road lighting. The layout decision module is set with a fixed range of impact thresholds. , combined with the influence coefficient , judge the rationality of the layout of road lighting at the existing time point and generate corresponding layout decisions.

[0069] Compared with the prior art, the present invention provides a smart street lamp arrangement method and system based on regional pedestrian and vehicle flow analysis, which has the following beneficial effects:

[0070] The present invention uses a monitoring device, a dynamic weighing device, an electromagnetic radiometer, an anemometer, a structural detection device, a vibration meter and a wireless communication module through a real-time monitoring module to collect pedestrian and vehicle flow data of all areas, environmental data of all areas, and detection data of road lighting in the area. The regional analysis module analyzes the pedestrian density of each area. , Vehicle parking density , Traffic density , building density and lighting density , and generate the corresponding dense coefficients , can accurately understand the density of each area, thus providing a scientific basis for subsequent traffic management, facility construction and optimization, and helping to adopt differentiated management and decision-making plans according to the characteristics of different areas, avoiding resource waste and management blind spots under unified standards, and dynamic monitoring with high accuracy.

[0071] The present invention sets a fixed-duration monitoring cycle through a multi-dimensional evaluation module and a fixed range of fluctuation thresholds , analyze the density coefficient of each area The changing trend of , and judge the fluctuation level of pedestrian and vehicle flow in each area, identify and understand the impact of different external factors on the area, and arrange the decision-making module according to the fluctuation level of pedestrian and vehicle flow in each area. Output the corresponding control instructions through wireless communication technology, check the connection status of road lighting, judge the rationality of the layout of road lighting at the existing time point, and generate corresponding layout decisions to ensure that the lighting system is more flexible, intelligent and meets actual needs, maximize traffic safety and energy-saving effects, and optimize the layout more scientifically and reasonably. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 It is a step diagram of the method of the present invention;

[0073] Figure 2 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0074] 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.

[0075] Example 1

[0076] See also Figure 1 The present invention provides a smart street lamp arrangement method based on regional pedestrian and vehicle flow analysis, comprising the following steps:

[0077] Step 1: Divide the roads of the target city into The traditional street lamp layout method often ignores the personalized lighting needs of each area and adopts a one-size-fits-all design solution. The smart street lamp layout method based on regional pedestrian and vehicle flow analysis collects data from a multi-dimensional perspective, which can more accurately understand the characteristics of pedestrian and vehicle flow changes, the degree of environmental changes and actual lighting needs in each area, thus providing a reliable basis for subsequent street lamp layout plans.

[0078] Step 2: Analyze the pedestrian density in each area , Vehicle parking density , Traffic density , building density and lighting density , and generate the corresponding dense coefficients , through comprehensive analysis of regional characteristics, a clearer and more specific regional portrait is constructed for city managers, which helps city managers to accurately grasp the dynamics of the resident population in each area;

[0079] Step 3: Set a monitoring cycle with a fixed duration and a fixed range of fluctuation thresholds , analyze the density coefficient of each area The changing trend of , and judge the fluctuation level of pedestrian and vehicle flow in each area. If the pedestrian and vehicle flow in a single area increases suddenly, and the fluctuation rate Exceeding the set volatility threshold , the management unit should be reminded to adjust the working parameters of street lights in time to avoid possible accidents or traffic jams;

[0080] Step 4: Analyze the vibration amplitude of each area , Electromagnetic interference intensity Very bad wind , and generate the corresponding influence coefficient , clearly understand the potential impact of external environmental factors on the street lighting system, identify in advance the environmental factors that may cause failure or performance degradation of the street lighting system, and take preventive measures;

[0081] Step 5: According to the fluctuation level of pedestrian and vehicle flow in each area, the corresponding control instructions are output through wireless communication technology, and the connection status of the road lighting is checked, so that the lighting and traffic control in each area are more intelligent and the response is more flexible;

[0082] Step 6: Set a fixed range of impact thresholds , combined with the influence coefficient , judge the rationality of the road lighting layout at the existing time point, and generate corresponding layout decisions to ensure that the street lighting layout can effectively meet the lighting needs and improve road safety under different environments and traffic conditions.

[0083] In this embodiment, the roads in the target city are divided into We then collect the pedestrian and vehicle flow data, environmental data, and installation test data of road lighting in all areas, and analyze the density coefficient of each area. , judge the fluctuation level of pedestrian and vehicle flow in each area, adopt differentiated management and decision-making plans according to the characteristics of different areas, avoid resource waste and management blind spots under unified standards, and achieve more efficient and intelligent resource allocation in road lighting facilities, traffic scheduling and public services. By outputting corresponding control instructions through wireless communication technology to check the connection status of road lighting, it can speed up fault location and repair, avoid lighting facility failures during high fluctuation periods, judge the rationality of road lighting layout at the existing time point, and generate corresponding layout decisions, flexibly adjust the brightness, structural stability and signal strength of street lights, thereby ensuring the service life of the street light system.

[0084] Example 2

[0085] This embodiment is an explanation of the embodiment 1. Specifically, in a single day, the pedestrian and vehicle flow data of each area includes the number of roads, pedestrian flow, number of parked vehicles, vehicle load, vehicle flow and vehicle electromagnetic radiation intensity. In a single area, when heavy vehicles frequently drive in and out, it is easy to cause the road lighting to produce a resonance effect, resulting in loose screws, damaged lamps and safety hazards.

[0086] Environmental data for each area includes the total number of buildings, total area and wind speed. If the wind speed fluctuates too much within a single day, it is easy to cause structural fatigue, deformation or even fracture, increasing the risk of collapse.

[0087] The installation inspection data of road lighting in each area includes the number of installations, unit luminous flux, lamp pole diameter, lamp pole stiffness, excitation frequency and natural frequency. The physical properties of different materials determine the stiffness of the lamp pole. The higher the stiffness, the stronger the ability of the street lamp to resist deformation.

[0088] In this embodiment, the collected pedestrian and vehicle flow data of all areas, the environmental data of all areas, and the installation and detection data of road lighting in the area are all short-term data. However, the short-term data accumulated over time provides strong support for deeper trend analysis and prediction in the future, and helps to formulate a more scientific and reasonable road lighting plan.

[0089] Example 3

[0090] This embodiment is an explanation of the embodiment 1. Specifically, the density coefficient The calculation process is as follows:

[0091] S11, extract the Traffic data of people and vehicles in a region, , and the The number of roads in the area is marked as , will The pedestrian flow in the area is marked as , will The number of vehicles parked in the area is marked as , will The vehicle load in the area is marked as , will The traffic flow in the area is marked as ;

[0092] S12, calculate the Pedestrian density in the area , and its calculation formula is as follows:

[0093] ;

[0094] When the number of roads is constant, the pedestrian density The higher it is, the more congested the road conditions are;

[0095] S13, calculate the Parking density in the area , and its calculation formula is as follows:

[0096] ;

[0097] When the number of roads is constant, the parking density The higher it is, the greater the lighting demand;

[0098] S14. Vehicle load in the area , will Traffic volume in the area Classified as non-motorized vehicle traffic , passenger vehicle traffic and heavy traffic Among them, the vehicle load of non-motor vehicles is ≤250kg, the vehicle load of 250kg≤passenger cars is ≤500kg, and the vehicle load of heavy vehicles is ≥500kg. The heavier the vehicle, the greater the frequency and amplitude of the excitation when it passes through the target area frequently, and the higher the risk of damage to the street lamps;

[0099] S15. Calculate the Traffic density in the area , and its calculation formula is as follows:

[0100] ;

[0101] In the formula, It represents the ratio of non-motor vehicle flow to the number of roads, that is, the non-motor vehicle flow density. represents the evaluation weight for non-motor vehicle flow density, It represents the ratio of passenger vehicle flow to the number of roads, that is, the passenger vehicle flow density. represents the evaluation weight for passenger vehicle traffic density, It represents the ratio of heavy vehicle flow to the number of roads, that is, the heavy vehicle flow density. represents the evaluation weight for heavy vehicle flow density, , Indicates according to , and The weights are combined to obtain the non-motor vehicle flow, passenger vehicle flow and heavy vehicle flow. The traffic density of each area is calculated. It not only calculates the total traffic density, but also subdivides the traffic density of different types of vehicles according to the load capacity, and clarifies which types of vehicles use the road sections in this area more frequently, which will help to strengthen the street lamp base and overall structure for the designated road sections in the future to improve the environmental adaptability of road lighting;

[0102] S16, extract the The environmental data of each region will be The total number of buildings in the area is marked as , will The total area of ​​the region is marked as , and calculate the Building density in the area , and its calculation formula is as follows:

[0103] ;

[0104] Building density in a single area The lower the value, the greater the future development space of the area, and the greater the potential lighting demand;

[0105] S17, extract the The installation test data of road lighting in each area will be The number of road lighting installations in each area is marked as , will The unit luminous flux of the road lighting in each area is marked as , combined with The total area of ​​the region , calculate the Lighting density of road lighting in each area , and its calculation formula is as follows:

[0106] ;

[0107] In the formula, Indicates The total luminous flux of all road lighting lamps in an area;

[0108] S18. Please refer to Table 1 for the example diagram of the density coefficient and calculate the The density factor of the region , and its calculation formula is as follows:

[0109] ;

[0110] In the formula, represents the evaluation weight for pedestrian density, represents the evaluation weight for vehicle parking density, represents the evaluation weight for traffic density, represents the assessment weight for building density, represents the evaluation weight for lighting density, , Indicates according to , , , and The weights are combined with pedestrian density, vehicle parking density, traffic density, building density and lighting density to obtain the The density factor of a region.

[0111] Table 1 Example of density coefficient

[0112]

[0113] Table 1 shows an example of a density coefficient. , , , , , , , ,It is judged that the flow of people and vehicles in area 1 is much higher than that in areas 2 and 3, and the demand for road lighting is higher;

[0114] Please refer to Table 2 for an example of volatility. The calculation process is as follows:

[0115] S21. Arrange the monitoring cycles in chronological order from morning to night. within, no. The density factor of the region , and marked as , to From the first time point to the The density coefficient of each time point;

[0116] S22, remove the monitoring cycle Internal, dense coefficient After finding the maximum and minimum values, calculate the The average density factor of the area , and its calculation formula is as follows:

[0117] ;

[0118] It effectively reduces the impact of extreme values ​​and avoids excessive deviation from the calculated average value, thus making the average density coefficient It can better reflect the Normal situation in each region;

[0119] S23. Calculate monitoring cycle within, no. The volatility of the regional density coefficient , and its calculation formula is as follows:

[0120] ;

[0121] In the formula, Indicates The density coefficient of each time point, According to the standard deviation formula, the value obtained is The volatility of the regional density coefficient , which intuitively reflects the uncertainty of factors such as traffic, environment or human flow in the area. Areas with higher volatility may face more management challenges, while areas with lower volatility are more predictable and stable.

[0122] Table 2 Volatility Example Chart

[0123]

[0124] In the first case, the volatility Exceeding the volatility threshold , indicating that the daily flow of people and vehicles in the area is unstable, and there is intermittent traffic congestion, generating the first fluctuation level. When the light intensity is 1-1.05, the daily flow of people and vehicles in the east of the area is unstable, and there is intermittent traffic congestion. The intermittent traffic congestion leads to the risk of light visibility loss of road lighting. It is necessary to output unified control instructions to several road lighting in the area through wireless communication technology to increase the current luminous flux by 10%. If the luminous flux of the road lighting in the area does not change, it means that the road lighting has failed due to external force;

[0125] In the second case, the volatility Included in volatility threshold , indicating that the daily flow of people and vehicles in the area is stable, there is no intermittent traffic congestion, and the second fluctuation level is generated. When the temperature is 1-1.05, the daily flow of people and vehicles in the south and west areas is stable, there is no intermittent traffic congestion, and it is within the normal and controllable range;

[0126] The stability of the first volatility level is lower than that of the second volatility level.

[0127] In this example, by calculating the density coefficient of each area , realizing multi-dimensional data analysis, urban management units can To reasonably allocate resources, give priority to the construction of road lighting facilities, traffic management and public service improvement in high-density areas, and set a fixed-duration monitoring cycle Monitor the density coefficient of each area to ensure that public facilities in different areas can be reasonably configured according to actual needs and improve urban operation efficiency.

[0128] Example 4

[0129] This embodiment is an explanation of the embodiment 3. Specifically, the influence coefficient The calculation process is as follows:

[0130] S31, extract the The installation test data of road lighting in each area, and The pole diameter of the road lighting lamp in each area is marked as , will The pole stiffness of the road lighting in each area is marked as , will The excitation frequency of the road lighting in each area is marked as , will The natural frequency of the road lighting in each area is marked as ;

[0131] S32. According to Diameter of the pole of the road lighting in each area and vehicle load , calculate the vehicle travel to the The impact force generated by the area , and its calculation formula is as follows: ;

[0132] In the formula, It represents the dynamic load factor, which is usually between 1.5 and 2.5, depending on the vehicle speed limit and road conditions of the road section. represents the acceleration due to gravity, represents the conversion factor, It means that converting the lamp pole diameter into reaction force can more accurately calculate the actual impact force of the vehicle on the regional facilities and avoid the error caused by ignoring the reaction force;

[0133] S33, calculate the vehicle driving to The vibration amplitude generated when the area , and its calculation formula is as follows:

[0134] ;

[0135] ;

[0136] In the formula, Indicates The average value of the excitation frequency and natural frequency of the road lighting in each area, Indicates The relative frequency difference between the excitation frequency and the natural frequency of the road lighting in each area. When the excitation frequency and the natural frequency are equal, reaches the maximum value, resulting in resonance effect, and the vehicle travels to the The vibration amplitude generated when the area maximum;

[0137] S34, extract the The pedestrian and vehicle flow data of the area will be The electromagnetic radiation intensity of vehicles in the area is marked as , combined with Traffic volume in the area , calculate the electromagnetic interference intensity , and its calculation formula is as follows:

[0138] ;

[0139] The more traffic there is on a road, the stronger the electromagnetic interference intensity is, and the more serious the interference to the communication quality of the road lighting is;

[0140] S35, extract the The environmental data of each region will be The wind force values ​​for each area are marked as , and calculate the Very bad winds in the area , and its calculation formula is as follows:

[0141] ;

[0142] In the formula, Indicates The maximum wind speed value in the region, Indicates The minimum wind speed value in each area. The greater the wind speed difference, the greater the threat to the stability of road lighting.

[0143] S36, calculate the vehicle travel to The influence coefficient generated when the area , and its calculation formula is as follows:

[0144] ;

[0145] In the formula, represents the evaluation weight for the vibration amplitude, Represents the evaluation weight for electromagnetic interference intensity, represents the assessment weight for extremely poor wind speed, , Indicates according to , and The weight is combined with the vibration amplitude, electromagnetic interference intensity and wind speed difference to obtain the vehicle driving to the first The greater the impact coefficient, the more it will damage the durability of the road lighting;

[0146] Influence coefficient Exceeding impact threshold When the vehicle reaches the area, the impact force and the wind force cause the road lighting to resonate, which may lead to the loss of the service life of the road lighting. In addition, the electromagnetic interference intensity of the vehicle may lead to the risk of decreased wireless communication quality of the road lighting in the area. In this case, the lamp pole diameter should be increased by 3 cm and the wireless signal transmission power should be increased by 20%.

[0147] Influence coefficient Included in impact threshold When the monitoring cycle is , regularly inspect and maintain road lighting.

[0148] In this embodiment, the impact force generated when the vehicle travels to each area is calculated. , Electromagnetic interference intensity and influence coefficient , and comprehensively consider the impact of multiple external factors on the region. By setting thresholds to determine the degree of impact of different external factors on the region, it can help analyze the actual impact of various external factors on traffic facilities and the environment. Based on the analysis results of pedestrian and vehicle flows in the region, the layout of smart street lights can be further optimized to make it more scientific, reasonable, accurate and effective. This process can not only improve the adaptability and reliability of road lighting facilities, but also provide more efficient energy use solutions in a dynamically changing urban environment, improve urban traffic management, and effectively reduce facility damage and maintenance costs caused by external forces.

[0149] Example 5

[0150] See also Figure 2 , a smart street lamp layout system based on regional pedestrian and vehicle flow analysis, including real-time monitoring module, regional analysis module, multi-dimensional evaluation module and layout decision module;

[0151] The real-time monitoring module uses monitoring devices, dynamic weighing devices, electromagnetic radiometers, anemometers, structural detection devices, vibration meters and wireless communication modules to collect data on the flow of people and vehicles in all areas, environmental data in all areas, and detection data on road lighting in the area. In a single area, there are a number of road lighting installations;

[0152] The regional analysis module analyzes the pedestrian density in each area , Vehicle parking density , Traffic density , building density and lighting density , and generate the corresponding dense coefficients ;

[0153] Multi-dimensional evaluation module analyzes the density coefficient of each area The changing trend of , and judge the fluctuation level of pedestrian and vehicle flow in each area. The multi-dimensional evaluation module analyzes the vibration amplitude of each area , Electromagnetic interference intensity Very bad wind , and generate the corresponding influence coefficient ;

[0154] The layout decision module outputs corresponding control instructions through wireless communication technology according to the fluctuation level of pedestrian and vehicle flow in each area, and checks the connection status of road lighting. The layout decision module is set with a fixed range of impact thresholds. , combined with the influence coefficient , judge the rationality of the layout of road lighting at the existing time point and generate corresponding layout decisions.

[0155] In this embodiment, the real-time monitoring module collects the pedestrian and vehicle flow data of all areas, the environmental data of all areas, and the detection data of the road lighting in the area, and the regional analysis module analyzes the density coefficient of each area. , can accurately understand the density of each area, thus providing a scientific basis for subsequent traffic management, facility construction and optimization. The multi-dimensional evaluation module analyzes the density coefficient of each area The changing trend and impact coefficient , and judge the fluctuation level of pedestrian and vehicle flow in each area. These evaluation results can help identify and understand the impact of different external factors on the area. The layout decision module outputs corresponding control instructions through wireless communication technology according to the fluctuation level of pedestrian and vehicle flow in each area, checks the connection status of road lighting, judges the rationality of the layout of road lighting at the current time point, and generates corresponding layout decisions to ensure that the lighting system is more flexible, intelligent and meets actual needs, maximizing traffic safety and energy saving effects.

[0156] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart street lamp arrangement method based on regional pedestrian and vehicle flow analysis, characterized in that: The following steps are involved: Step 1: Divide the roads of the target city into Areas, and then collect the pedestrian and vehicle flow data of all areas, the environmental data of all areas, and the installation and detection data of road lighting in the area. In a single area, there are several road lighting installations; Step 2: Analyze the pedestrian density in each area , Vehicle parking density , Traffic density , building density and lighting density , and generate the corresponding dense coefficients ; Density coefficient The calculation process is as follows: S11, extract the Traffic data of people and vehicles in a region, , and the The number of roads in the area is marked as , will The pedestrian flow in the area is marked as , will The number of vehicles parked in the area is marked as , will The vehicle load in the area is marked as , will The traffic flow in the area is marked as ; S12, calculate the Pedestrian density in the area , and its calculation formula is as follows: ； S13, calculate the Parking density in the area , and its calculation formula is as follows: ； S14. Vehicle load in the area , will Traffic volume in the area Classified as non-motorized vehicle traffic , passenger vehicle traffic and heavy traffic , among which, the vehicle load of non-motor vehicles is ≤250kg, the vehicle load of 250kg≤passenger vehicles is ≤500kg, and the vehicle load of heavy vehicles is ≥500kg; S15. Calculate the Traffic density in the area , and its calculation formula is as follows: ； In the formula, It represents the ratio of non-motor vehicle flow to the number of roads, that is, the non-motor vehicle flow density. represents the evaluation weight for non-motor vehicle flow density, It represents the ratio of passenger vehicle flow to the number of roads, that is, the passenger vehicle flow density. represents the evaluation weight for passenger vehicle traffic density, It represents the ratio of heavy vehicle flow to the number of roads, that is, the heavy vehicle flow density. represents the evaluation weight for heavy vehicle flow density, , Indicates according to , and The weights are combined to obtain the non-motor vehicle flow, passenger vehicle flow and heavy vehicle flow. The traffic density of the area; S16, extract the The environmental data of each region will be The total number of buildings in the area is marked as , will The total area of ​​the region is marked as , and calculate the Building density in the area , and its calculation formula is as follows: ； S17, extract the The installation test data of road lighting in each area will be The number of road lighting installations in each area is marked as , will The unit luminous flux of the road lighting in each area is marked as , combined with The total area of ​​the region , calculate the Lighting density of road lighting in each area , and its calculation formula is as follows: ； In the formula, Indicates The total luminous flux of all road lighting lamps in an area; S18, calculate the The density factor of the region , and its calculation formula is as follows: ； In the formula, represents the evaluation weight for pedestrian density, represents the evaluation weight for vehicle parking density, represents the evaluation weight for traffic density, represents the assessment weight for building density, represents the evaluation weight for lighting density, , Indicates according to , , , and The weights are combined with pedestrian density, vehicle parking density, traffic density, building density and lighting density to obtain the The density coefficient of the region; Step 3: Set a monitoring cycle with a fixed duration and a fixed range of fluctuation thresholds , analyze the density coefficient of each area The changing trend of , and determine the fluctuation level of pedestrian and vehicle flows in each area; Volatility The calculation process is as follows: S21. Arrange the monitoring cycles in chronological order from morning to night. within, no. The density factor of the region , and marked as , to From the first time point to the The density coefficient of each time point; S22, remove the monitoring cycle Internal, dense coefficient After finding the maximum and minimum values, calculate the The average density factor of the area , and its calculation formula is as follows: ； S23. Calculate monitoring cycle within, no. The volatility of the regional density coefficient , and its calculation formula is as follows: ； In the formula, Indicates The density coefficient of each time point, According to the standard deviation formula, the value obtained is The volatility of the regional density coefficient ; Step 4: Analyze the vibration amplitude of each area , Electromagnetic interference intensity Very bad wind , and generate the corresponding influence coefficient ; Influence coefficient The calculation process is as follows: S31, extract the The installation test data of road lighting in each area, and The pole diameter of the road lighting in each area is marked as , will The pole stiffness of the road lighting in each area is marked as , will The excitation frequency of the road lighting in each area is marked as , will The natural frequency of the road lighting in each area is marked as ; S32. According to Diameter of the pole of the road lighting in each area and vehicle load , calculate the vehicle travel to the The impact force generated by the area , and its calculation formula is as follows: ； In the formula, represents the dynamic load factor, represents the acceleration due to gravity, represents the conversion factor, It means converting the pole diameter into reaction force; S33, calculate the vehicle driving to The vibration amplitude generated when the area , and its calculation formula is as follows: ； ； In the formula, Indicates The average value of the excitation frequency and natural frequency of the road lighting in each area, Indicates The relative frequency difference between the excitation frequency and the natural frequency of the road lighting in each area. When the excitation frequency and the natural frequency are equal, reaches the maximum value, resulting in resonance effect, and the vehicle travels to the The vibration amplitude generated when the area maximum; S34, extract the The pedestrian and vehicle flow data of the area will be The electromagnetic radiation intensity of vehicles in the area is marked as , combined with Traffic volume in the area , calculate the electromagnetic interference intensity , and its calculation formula is as follows: ； S35, extract the The environmental data of each region will be The wind force values ​​for each area are marked as , and calculate the Very bad winds in the area , and its calculation formula is as follows: ； In the formula, Indicates The maximum wind speed value in the region, Indicates The minimum wind speed value in each area; S36, calculate the vehicle travel to The influence coefficient generated when the area , and its calculation formula is as follows: ； In the formula, represents the evaluation weight for the vibration amplitude, Represents the evaluation weight for electromagnetic interference intensity, represents the assessment weight for extremely poor wind speed, , Indicates according to , and The weight is combined with the vibration amplitude, electromagnetic interference intensity and wind speed difference to obtain the vehicle driving to the first The impact coefficient generated when there are multiple regions; Step 5: According to the fluctuation level of pedestrian and vehicle flow in each area, the corresponding control instructions are output through wireless communication technology, and the connection status of the road lighting is checked; Step 6: Set a fixed range of impact thresholds , combined with the influence coefficient , judge the rationality of the layout of road lighting at the existing time point and generate corresponding layout decisions.

2. The smart street lamp arrangement method based on regional pedestrian and vehicle flow analysis according to claim 1 is characterized by: In step 1, within a single day, the pedestrian and vehicle flow data of each area includes the number of roads, pedestrian flow, number of parked vehicles, vehicle load, vehicle flow, and vehicle electromagnetic radiation intensity; Environmental data for each area include total number of buildings, total area, and wind value; The installation inspection data of road lighting in each area includes the installation quantity, unit luminous flux, lamp pole diameter, lamp pole stiffness, excitation frequency and natural frequency.

3. The intelligent street lamp arrangement method based on regional pedestrian and vehicle flow analysis according to claim 2 is characterized in that: In step 3, in the first case, volatility Exceeding the volatility threshold , indicating that the daily flow of people and vehicles in the area is unstable, and there is intermittent traffic congestion, generating the first level of fluctuation; In the second case, the volatility Included in volatility threshold , indicating that the daily flow of people and vehicles in the area is stable, and there is no intermittent traffic congestion, generating the second fluctuation level; The stability of the first volatility level is lower than that of the second volatility level.

4. The intelligent street lamp arrangement method based on regional pedestrian and vehicle flow analysis according to claim 3 is characterized in that: Step five, in the first case, when the first fluctuation level is generated, it means that intermittent traffic congestion in the area causes the road lighting to be at risk of light visibility loss. It is necessary to output unified control instructions to several road lighting in the area through wireless communication technology to increase the current luminous flux by 10%. If the luminous flux of the road lighting in the area does not change, it means that the road lighting has failed due to external force.

5. The intelligent street lamp arrangement method based on regional pedestrian and vehicle flow analysis according to claim 4 is characterized in that: Step 6: Influence coefficient Exceeding impact threshold When the signal is detected, it indicates that the layout of the road lighting at the existing time point is unreasonable. When a vehicle drives into this area, the impact force and the environmental wind force cause the road lighting to resonate. There is a risk of loss of service life of the road lighting. In addition, the electromagnetic interference intensity of the vehicle causes a risk of decreased wireless communication quality of the road lighting in this area. In this case, the lamp pole diameter should be increased by 3 cm and the wireless signal transmission power should be increased by 20%.

6. The intelligent street lamp arrangement method based on regional pedestrian and vehicle flow analysis according to claim 5 is characterized in that: Step 6: Influence coefficient Included in impact threshold When the monitoring cycle is , regularly inspect and maintain road lighting.

7. A smart street light arrangement system based on regional pedestrian and vehicle flow analysis, applied to any of the smart street light arrangement methods based on regional pedestrian and vehicle flow analysis in claims 1-6, characterized in that: It includes real-time monitoring module, regional analysis module, multi-dimensional evaluation module and layout decision module; The real-time monitoring module uses monitoring devices, dynamic weighing devices, electromagnetic radiometers, anemometers, structural detection devices, vibration meters and wireless communication modules to collect data on the flow of people and vehicles in all areas, environmental data in all areas, and detection data on road lighting in the area. In a single area, there are a number of road lighting installations; The regional analysis module analyzes the pedestrian density in each area , Vehicle parking density , Traffic density , building density and lighting density , and generate the corresponding dense coefficients ; Multi-dimensional evaluation module analyzes the density coefficient of each area The changing trend of , and judge the fluctuation level of pedestrian and vehicle flow in each area. The multi-dimensional evaluation module analyzes the vibration amplitude of each area , Electromagnetic interference intensity Very bad wind , and generate the corresponding influence coefficient ; The layout decision module outputs corresponding control instructions through wireless communication technology according to the fluctuation level of pedestrian and vehicle flow in each area, and checks the connection status of road lighting. The layout decision module is set with a fixed range of impact thresholds. , combined with the influence coefficient , judge the rationality of the layout of road lighting at the existing time point and generate corresponding layout decisions.

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