A high flow area early warning management and control method and system

Abstract

The application discloses a high human flow area early warning management and control method and system, relates to the technical field of area early warning, and has the technical scheme as follows: obtaining an initial emergency result according to personnel behavior coordination parameters and emergency resource adaptation parameters of a target area; obtaining an emergency gathering area and an emergency evacuation area according to an initial emergency result and an emergency resource layout condition of the target area; obtaining a first early warning trigger feature set according to a behavior coordination degree, an emergency resource occupancy rate and an evacuation path feature of the emergency gathering area; outputting a first early warning management and control result of the emergency gathering area according to a first correlation coefficient and the first early warning trigger feature set, outputting a second early warning management and control result of the emergency evacuation area according to a second correlation coefficient and a second early warning trigger feature set, and the effect is to improve the efficiency and safety of high human flow area emergency management and control.

Description

Technical Field

[0001] This invention relates to the field of regional early warning technology, and more specifically, to a method and system for early warning and control of high-traffic areas. Background Technology

[0002] In high-traffic areas such as large urban commercial districts, transportation hubs, and scenic spots, traditional emergency management relies heavily on manual patrols or single-function personnel density monitoring. This lacks a comprehensive understanding of personnel behavior and resource status. For example, simply counting people by cameras ignores behavioral characteristics such as the synchronicity and coordination of personnel movements. When people suddenly gather towards the same exit, it is difficult to predict potential congestion risks in a timely manner. At the same time, traditional solutions do not adequately consider the adaptability of emergency resources within the area, often resulting in a mismatch between resource allocation and personnel needs. For instance, if the personnel density in a certain area exceeds the standard, but emergency supplies are still allocated in fixed quantities, it is impossible to perceive the resource carrying capacity pressure in advance, thus leading to a delay in emergency response. Summary of the Invention

[0003] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a method and system for early warning and control of high-traffic areas.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A method for early warning and control of high-traffic areas, comprising the following steps: Initial emergency results are obtained based on the personnel behavior coordination parameters and emergency resource adaptation parameters in the target area; Based on the initial emergency response results and the emergency resource layout in the target area, emergency gathering areas and emergency evacuation areas were divided. The first early warning trigger feature set is obtained based on the behavioral coordination degree of the emergency gathering area, the emergency resource occupancy rate, and the evacuation route characteristics; the second early warning trigger feature set is obtained based on the efficiency of the flow of people in the emergency evacuation area, the response speed of resource scheduling, and the congestion transmission characteristics. The first and second correlation coefficients were obtained by processing and analyzing the historical emergency control data of the target area. The first early warning control result for the emergency gathering area is output based on the first correlation coefficient and the first early warning trigger feature set; the second early warning control result for the emergency evacuation area is output based on the second correlation coefficient and the second early warning trigger feature set; and a broadcast early warning instruction is output based on the first early warning control result and the second early warning control result.

[0005] Preferably, the initial emergency response result is obtained based on the personnel behavior coordination parameters and emergency resource adaptation parameters of the target area, specifically including the following steps: The parameters for personnel behavior coordination in the target area are combined with the parameters for emergency resource adaptation to form a coordination adaptation feature. Obtain emergency control standards; The initial emergency response results are obtained by comparing the collaborative adaptation features with the emergency control standards.

[0006] Preferably, based on the initial emergency response results and the emergency resource layout of the target area, emergency gathering areas and emergency evacuation areas are divided, specifically including the following steps: The resource allocation threshold is preset based on the initial emergency response results; Based on the resource layout classification threshold, the emergency resource layout status of the target area is detected to obtain resource layout characteristics; The layout division results are obtained by dividing the area range corresponding to the resource layout division threshold according to the resource layout characteristics; Preset an emergency overload threshold, and mark the areas in the layout division results whose emergency resource carrying pressure is greater than or equal to the emergency overload threshold as target control areas; Emergency assembly areas and emergency evacuation areas are divided from the target control area.

[0007] Preferably, the emergency assembly area and the emergency evacuation area are divided from the target control area, specifically including the following steps: Obtain information on the resource availability and population flow trends of the target control area; Based on the resource carrying capacity, the regional carrying capacity critical point is determined, and based on the population flow trend, the dominant areas of population residence and the dominant areas of population flow are selected. The resource supply capacity of the main area where the testing personnel are stationed will be used to designate areas with resource supply capacity lower than the demand threshold corresponding to the regional carrying capacity as emergency gathering areas. Assess the traffic capacity of areas with high population flow and designate areas whose traffic capacity meets the preset evacuation requirements as emergency evacuation zones.

[0008] Preferably, the first early warning trigger feature set is obtained based on the behavioral coordination degree, emergency resource occupancy rate, and evacuation route characteristics of the emergency gathering area, specifically including the following steps: Collect data on the synchronicity of movement and coordination of actions of people within the emergency assembly area; Behavioral coordination degree is obtained based on mobile synchronization and action coordination data; The rate of consumption of emergency supplies and the frequency of use of emergency facilities within the emergency assembly area will be monitored. The emergency resource occupancy rate is obtained based on the consumption rate, usage frequency, and the initial total amount of emergency resources. The first early warning trigger feature set is formed by verifying the degree of behavioral coordination, emergency resource occupancy rate and evacuation route characteristics.

[0009] Preferably, a second early warning trigger feature set is obtained based on the efficiency of pedestrian flow management, resource dispatch response speed, and congestion transmission characteristics in the emergency evacuation area, specifically including the following steps: Obtain real-time basic information on the flow of people in the emergency evacuation area, and calculate the flow of people efficiency based on the real-time basic information on the flow of people. Based on the distribution of emergency resources in the emergency evacuation area, we obtain information on the entire process of resource scheduling, and then obtain the resource scheduling response speed based on this information. The starting location and spread direction of the emergency evacuation area are determined based on the efficiency of crowd flow management and the response speed of resource allocation. The degree of impact and spread trend of congestion on the surrounding evacuation channels are judged based on the starting location and spread direction to obtain the congestion transmission characteristics. The efficiency of crowd flow management, the response speed of resource allocation, and the characteristics of congestion transmission are correlated and integrated to form a second early warning trigger feature set.

[0010] Preferably, the historical emergency management data of the target area is processed and analyzed to obtain the first correlation coefficient and the second correlation coefficient, specifically including the following steps: Acquire full-process data of the historical emergency control process of the target area, and extract relevant information on the historical early warning trigger characteristics of emergency gathering scenarios and emergency evacuation scenarios, as well as the implementation feedback information of corresponding control measures based on the full-process data; The degree of fit between information related to early warning triggering characteristics and implementation feedback information in different historical periods is used to obtain the results of the fit analysis; By extracting the target-related elements of early warning triggering characteristics and control implementation feedback in emergency gathering scenarios, we can obtain the gathering scenario-related elements. By extracting the target correlation elements between the early warning triggering characteristics and the control implementation feedback in emergency evacuation scenarios, we can obtain the evacuation scenario correlation elements. The clustered scene-related elements are transformed into a first correlation coefficient that represents the degree of correlation between early warning triggering and control effectiveness; The relevant elements of the evacuation scenario are transformed into a second correlation coefficient that represents the degree of correlation between early warning triggering and control effectiveness.

[0011] Preferably, the first early warning control result for the emergency gathering area is output based on the first correlation coefficient and the first early warning trigger feature set, specifically including the following steps: The first correlation coefficient is matched with the first early warning trigger feature set, and the correlation dimension that matches the first early warning trigger feature set is selected to obtain the feature correlation matching result. Based on the feature association and adaptation results, the priority of control requirements corresponding to the current early warning triggering features of the emergency gathering area is determined, and the target control direction is determined according to the control requirements priority to obtain the priority judgment result. After combining the priority judgment results, effective control elements that match the current target control direction are retrieved from the historical emergency gathering area control. A preliminary control plan is then formed. The suitability of the preliminary control plan with the actual situation of the current emergency gathering area is verified based on the degree of correlation represented by the first correlation coefficient. After optimizing and adjusting the configuration of control elements according to the suitability, the first early warning control result is output.

[0012] Preferably, the second early warning control result for the emergency evacuation area is output based on the second correlation coefficient and the second early warning trigger feature set, specifically including the following steps: The feature weight association result is obtained by correspondingly associating the second correlation coefficient with the second early warning trigger feature set; Based on the feature weight association results, the current target early warning risk points of the emergency evacuation area are determined, and the target optimization direction of evacuation control is determined according to the current target early warning risk points to obtain the risk judgment result; Based on the risk assessment results, extract effective control measures from historical evacuation and control that match the current key optimization directions, and form a preliminary evacuation and control plan; The degree of correlation, as represented by the second correlation coefficient, is used to verify the fit between the preliminary evacuation control plan and the real-time evacuation status of the emergency evacuation area. Based on the fit, control measures are adjusted and the second early warning control result is output.

[0013] A high-traffic area early warning and control system includes: Processing module: Obtains initial emergency results based on personnel behavior coordination parameters and emergency resource adaptation parameters in the target area; The emergency response module is divided into emergency gathering areas and emergency evacuation areas based on the initial emergency response results and the emergency resource layout of the target area. The first analysis module: derives the first early warning trigger feature set based on the behavioral coordination degree of the emergency gathering area, the emergency resource occupancy rate, and the evacuation route characteristics; and derives the second early warning trigger feature set based on the pedestrian flow guidance efficiency, resource scheduling response speed, and congestion transmission characteristics of the emergency evacuation area. The second analysis module processes and analyzes the historical emergency control data of the target area to obtain the first correlation coefficient and the second correlation coefficient; Output module: Outputs the first early warning control result for the emergency gathering area based on the first correlation coefficient and the first early warning trigger feature set; outputs the second early warning control result for the emergency evacuation area based on the second correlation coefficient and the second early warning trigger feature set; outputs broadcast early warning instructions based on the first early warning control result and the second early warning control result.

[0014] Compared with the prior art, the present invention has the following beneficial effects: This invention obtains initial emergency results by combining personnel behavior coordination parameters and emergency resource adaptation parameters. Based on this, it divides emergency gathering and evacuation areas, and processes them separately according to their different characteristics to avoid resource misallocation. For gathering areas, it combines characteristics such as behavioral coordination and resource occupancy rate to form a first early warning trigger feature set; for evacuation areas, it integrates characteristics such as crowd flow management efficiency and resource dispatch speed to form a second early warning trigger feature set. This allows early warning triggering to no longer rely on a single indicator, but rather on a comprehensive judgment of multi-dimensional data, reducing the possibility of false or missed warnings and improving the reliability of early warnings. It improves the efficiency and safety of emergency management in high-traffic areas, enabling control actions to quickly respond to the actual risks in the area, promptly replenishing resources and guiding personnel in gathering areas, and optimizing crowd flow in evacuation areas, ensuring personnel safety and order. Attached Figure Description

[0015] Figure 1 This is a schematic diagram illustrating the steps of a high-traffic area early warning and control method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a module for an early warning and control system for high-traffic areas, provided in an embodiment of the present invention. Detailed Implementation

[0016] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0017] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0018] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0019] Reference Figures 1-2 As shown.

[0020] The embodiments further illustrate the early warning and control method and system for high-traffic areas proposed in this invention.

[0021] A method for early warning and control of high-traffic areas, comprising the following steps: Initial emergency results are obtained based on the personnel behavior coordination parameters and emergency resource adaptation parameters in the target area; Based on the initial emergency response results and the emergency resource layout in the target area, emergency gathering areas and emergency evacuation areas were divided. The first early warning trigger feature set is obtained based on the behavioral coordination degree of the emergency gathering area, the emergency resource occupancy rate, and the evacuation route characteristics; the second early warning trigger feature set is obtained based on the efficiency of the flow of people in the emergency evacuation area, the response speed of resource scheduling, and the congestion transmission characteristics. The first and second correlation coefficients were obtained by processing and analyzing the historical emergency control data of the target area. The first early warning control result for the emergency gathering area is output based on the first correlation coefficient and the first early warning trigger feature set; the second early warning control result for the emergency evacuation area is output based on the second correlation coefficient and the second early warning trigger feature set; and a broadcast early warning instruction is output based on the first early warning control result and the second early warning control result.

[0022] First, the results of the first and second early warning control measures must be comprehensively analyzed and integrated. From the first early warning control results, the specific location, core risk types, key control needs, and risk priorities of the emergency gathering areas must be identified, clarifying the personnel guidance direction and resource replenishment requests for that area. From the second early warning control results, the scope of emergency evacuation routes, key points for traffic management and optimization, risks of congestion transmission, and supporting control measures for the emergency evacuation areas must be extracted, along with the usage requirements of evacuation routes and the direction of resource allocation. Based on this, a correlation mapping between the two types of area information should be established to balance the personnel evacuation needs of the gathering areas with the carrying capacity and resource supply levels of the evacuation areas. This ensures that instructions can effectively mitigate the risks of the gathering areas without exceeding the carrying capacity of the evacuation areas, achieving coordinated adaptation of the control needs of the two types of areas.

[0023] Based on the characteristics of high-traffic areas and people's cognitive habits, the integrated information was simplified and structured. Technical and obscure expressions were abandoned, and concise, clear, and easily understood language was used. Instructions were structured logically, following risk warnings, specific guidelines, and precautions. Differentiated guidelines were developed for different audiences: clear movement directions and required behavioral norms were specified for people in gathering areas; key tasks and coordination requirements were clearly explained to evacuation personnel in evacuation areas; and people in surrounding areas were reminded to be aware of risks and avoid dangerous areas. Simultaneously, specific measures for both types of control outcomes were integrated into the instructions, ensuring personnel clearly understood on-site resource support and procedures, guaranteeing that all personnel could quickly grasp the information and take appropriate action.

[0024] The coverage and transmission methods of broadcasts are determined based on risk priority and dissemination needs to achieve efficient information transmission. For high-priority risks, a multi-channel simultaneous broadcast mode is adopted across the entire area, using multiple carriers such as on-site loudspeakers and emergency broadcast systems to simultaneously broadcast information, increasing the frequency of instruction repetition and ensuring that personnel in all areas receive critical early warning information in a timely manner. For medium- and low-priority risks, a zoned broadcast mode is adopted, broadcasting only in emergency gathering areas, emergency evacuation areas, and surrounding related areas to avoid unnecessary panic caused by broadcasting across the entire area. During the instruction transmission process, the dynamics of emergency resource dispatch are linked, clearly specifying the progress of resource replenishment, the location and responsibilities of on-site personnel, allowing personnel to clearly understand subsequent support measures, achieving seamless connection between early warning instructions and on-site control actions, promoting rapid mitigation of gathering risks and a smooth and orderly evacuation process.

[0025] The initial emergency response results are obtained based on the personnel behavior coordination parameters and emergency resource adaptation parameters in the target area, specifically including the following steps: The parameters for personnel behavior coordination in the target area are combined with the parameters for emergency resource adaptation to form a coordination adaptation feature. Obtain emergency control standards; The initial emergency response results are obtained by comparing the collaborative adaptation features with the emergency control standards.

[0026] Personnel behavior coordination parameters reflect the synchronicity and coordination of personnel actions within a region. For example, in a target area of ​​a large shopping mall, most people move towards the same exit, which means that the personnel behavior coordination parameters in that area are at a high level. Emergency resource adaptation parameters measure the degree of matching between existing emergency resources in the region and the current scale and distribution of personnel. For example, the adaptation relationship between the number of emergency evacuation signs and first aid kits in the shopping mall area and the real-time number of personnel in the area. When there are more personnel but insufficient resources, the emergency resource adaptation parameters decrease.

[0027] Emergency control standards are benchmark requirements based on safety management regulations and emergency response experience in high-traffic areas. For example, for large shopping malls, they specify reasonable ranges for personnel behavior coordination parameters under different personnel densities, as well as the appropriate ratio of emergency resources to personnel.

[0028] The initial emergency response result is obtained by comparing the collaborative adaptation features with the emergency control standards. Specifically, the values ​​corresponding to the collaborative adaptation features are compared with the thresholds set in the emergency control standards. The initial emergency response result = collaborative adaptation feature value - emergency control standard threshold. When the calculation result is less than 0, it means that the current collaborative adaptation features do not meet the emergency control standards, and the initial emergency response result is that basic emergency preparations need to be initiated. When the calculation result is greater than or equal to 0, it means that the current collaborative adaptation features meet the emergency control standards, and the initial emergency response result is that the current state is within a safe and controllable range. Taking a shopping mall area as an example, firstly, data related to movement synchronization is collected through the monitoring and positioning equipment of the target area. For example, the consistency of movement direction of people in the area is statistically analyzed. If 80 out of 100 people are facing the same direction, the direction consistency is 80%. The difference in movement speed is calculated. For example, if the average speed of people is 1.2 m / s and the standard deviation of speed is 0.3 m / s, the difference is 25%. Data on action coordination is also collected. For example, if 70 out of 100 people move synchronously in an emergency, the action synchronization rate is 70%. These indicators are scored from 0 to 100. In motion synchronization, 80% directional consistency corresponds to 80 points, and 25% speed difference corresponds to 75 points, with an average of 77.5 points. In motion coordination, 70% motion synchronization rate corresponds to 70 points. For example, in a shopping mall scenario, with a motion synchronization weight of 0.6 and a motion coordination weight of 0.4, the calculated value for the personnel behavior coordination parameter is 77.5 × 0.6 + 70 × 0.4 = 74.5 points.

[0029] For example, a target shopping mall area is configured with 10 emergency evacuation signs and 5 first-aid kits, while regulations require 1 evacuation sign for every 50 people and 1 first-aid kit for every 100 people. Next, the resource suitability is calculated. If the current area has 400 people, the required number of evacuation signs is 8, and the actual number is 10, resulting in a suitability score of 1.25 (80 points). The required number of first-aid kits is 4, and the actual number is 5, also resulting in a suitability score of 1.25 (80 points). The average of these two scores is 80 points. Considering resource availability adjustments, if 2 signs are faulty, the availability rate is 80%, and the emergency resource suitability parameter value is 80 × 80% = 64 points.

[0030] If the value of the personnel behavior coordination parameter in this area is 74.5 points and the value of the emergency resource adaptation parameter is 64 points, the combined coordination adaptation feature value is (74.5+64) / 2=68.25. The corresponding threshold in the emergency control standard is 50. Since 68.25-50=18.25≥0, the initial emergency result is that the current state of this area is within a safe and controllable range.

[0031] Based on the initial emergency response results and the emergency resource layout of the target area, emergency gathering areas and emergency evacuation areas are divided, specifically including the following steps: The resource allocation threshold is preset based on the initial emergency response results; Based on the resource layout classification threshold, the emergency resource layout status of the target area is detected to obtain resource layout characteristics; The layout division results are obtained by dividing the area range corresponding to the resource layout division threshold according to the resource layout characteristics; Preset an emergency overload threshold, and mark the areas in the layout division results whose emergency resource carrying pressure is greater than or equal to the emergency overload threshold as target control areas; Emergency assembly areas and emergency evacuation areas are divided from the target control area.

[0032] First, a resource allocation threshold is preset based on the initial emergency response results. The initial emergency response results clarify the current safety status of the area. For example, if the current status is within a safe and controllable range, the corresponding resource allocation threshold will be set in combination with the characteristics of the area. Taking a large shopping mall as an example, if the personnel density corresponding to the initial emergency response results is at a medium level, the preset resource allocation threshold is to configure one set of emergency resources per 200 square meters. Here, the resource set includes one sign and one first aid kit.

[0033] The resource layout characteristics are obtained by detecting the emergency resource layout status of the target area based on the resource layout threshold. The actual resource distribution within the target area is statistically analyzed. For example, in a shopping mall with a total area of ​​1000 square meters, according to the threshold, 5 sets of emergency resources should be configured, but only 3 sets are actually configured, and these 3 sets are concentrated on the east side of the area, with none on the west side. In this case, the resource layout characteristics include the actual resource configuration quantity of 3 sets, the standard configuration quantity of 5 sets, and the resource distribution concentrated on the east side. The resource configuration sufficiency rate = actual configuration quantity / standard configuration quantity, which is 3 / 5 = 0.6. Combining this with the distribution uniformity (100% on the east side corresponds to 0.2), the quantified value of the resource layout characteristics is 0.6 × 0.8 + 0.2 × 0.2 = 0.52, where the configuration sufficiency rate has a weight of 0.8 and the distribution uniformity has a weight of 0.2.

[0034] The layout division results are obtained by dividing the area corresponding to the resource layout division threshold based on the resource layout characteristics. The area corresponding to the resource layout division threshold is the entire floor of 1000 square meters. Considering the resource concentration on the east side in the resource layout characteristics, the entire floor is divided into an east resource coverage area and a west resource vacancy area. At the same time, the resource allocation of each sub-area is marked. The 500 square meter east coverage area is allocated 3 sets of resources, and the 500 square meter west vacancy area is allocated 0 sets of resources.

[0035] An emergency overload threshold is preset, and areas in the layout division results where the emergency resource carrying pressure is greater than or equal to the emergency overload threshold are marked as target control areas. The emergency overload threshold is usually set in combination with resource carrying capacity and the number of personnel. Emergency resource carrying pressure = number of personnel in the area / resource allocation in the area. The preset overload threshold is 100, meaning that if each resource group carries more than 100 people, it is overloaded. Assuming that the eastern coverage area has 350 personnel and 3 resource groups, the carrying pressure is 350 / 3≈116.7; the western vacant area has 250 personnel and 0 resource groups, and the carrying pressure is recorded as 200. Both are greater than the threshold of 100, so these two sub-areas are marked as target control areas.

[0036] Emergency gathering areas and emergency evacuation areas are delineated from the target control areas. This step combines the resource carrying capacity of the area with the population flow trend. For example, the eastern coverage area has a longer dwell time (mostly shopping areas), which is a dominant population dwelling area, and its resource supply capacity (3 sets of resources) is lower than the demand threshold (5 sets) corresponding to the area's carrying capacity critical point. Therefore, it is designated as an emergency gathering area. The western vacant area has a lot of people passing through (mostly passageways), which is a dominant population flow area, and its passageway width and connectivity meet the preset evacuation requirements. Therefore, it is designated as an emergency evacuation area.

[0037] The emergency assembly area and the emergency evacuation area are divided from the target control area, specifically including the following steps: Obtain information on the resource availability and population flow trends of the target control area; Based on the resource carrying capacity, the regional carrying capacity critical point is determined, and based on the population flow trend, the dominant areas of population residence and the dominant areas of population flow are selected. The resource supply capacity of the main area where the testing personnel are stationed will be used to designate areas with resource supply capacity lower than the demand threshold corresponding to the regional carrying capacity as emergency gathering areas. Assess the traffic capacity of areas with high population flow and designate areas whose traffic capacity meets the preset evacuation requirements as emergency evacuation zones.

[0038] First, we need to obtain the resource carrying capacity and personnel flow trends of the target control area. Resource carrying capacity refers to the actual load of existing emergency resources in the area. For example, if there are 3 sets of emergency resources in the target control area of ​​a shopping mall, and the standard carrying capacity of each set of resources is 100 people, and there are currently 350 people in the area, the resource carrying capacity is calculated by the resource carrying capacity rate = actual carrying capacity / standard total carrying capacity, i.e., 350 / (3×100)≈1.17, which reflects that the resources have exceeded the standard carrying capacity. Personnel flow trends are obtained by monitoring data to count the direction of movement and the duration of stay. For example, if 60% of the people in the area stay for more than 10 minutes and 40% of the people move at a speed of less than 0.5 m / s, it indicates that the people are mainly staying in one place.

[0039] Based on resource carrying capacity, the regional carrying capacity threshold is determined. Then, based on population flow trends, areas with dominant population dwelling and areas with dominant population movement are selected. The regional carrying capacity threshold is the critical state where resources just barely meet demand. For example, the number of people corresponding to a resource carrying capacity of 1 is the carrying capacity threshold. Taking the above-mentioned areas as an example, the carrying capacity threshold for the three resource groups is 300 people. The selection of population flow trends is based on dwell time and movement characteristics. For example, areas with dwell time exceeding 5 minutes are classified as areas with dominant population dwelling, while areas with movement speed exceeding 1 m / s and dwell time less than 2 minutes are classified as areas with dominant population movement. For instance, the clothing sales area in a shopping mall has long dwell times and belongs to the area with dominant population dwelling; while escalator passages connecting different floors have fast movement and short dwell times, belonging to the area with dominant population movement.

[0040] The resource supply capacity of the main area for personnel to be stationed is used to designate areas with resource supply capacity below the demand threshold corresponding to the area's carrying capacity threshold as emergency gathering areas. Resource supply capacity is the actual support level that resources can provide. Resource supply capacity = actual resource allocation amount × single resource service efficiency. Assuming the single resource service efficiency is 100 people / group, and the area is actually allocated 3 groups of resources, the resource supply capacity is 3 × 100 = 300 people. The demand threshold corresponding to the area's carrying capacity threshold is 300 people. If the current resource supply capacity of the area drops to 250 people due to the failure of some resources, which is lower than the demand threshold of 300 people, then this area where personnel are stationed is designated as an emergency gathering area.

[0041] Assess the traffic capacity of key areas with high pedestrian flow. Areas whose traffic capacity meets the pre-set evacuation requirements are designated as emergency evacuation zones. Traffic capacity is typically measured by the maximum number of people passing through per unit of time. Traffic capacity = passage width × pedestrian density × time. For example, if the passage width of a key area with high pedestrian flow is 4 meters, the pedestrian density is 1.5 people / square meter, and the unit of time is 1 minute, the traffic capacity is 4 × 1.5 × 60 = 360 people / minute. The pre-set evacuation requirement is a traffic capacity of no less than 300 people / minute. This area's traffic capacity of 360 people / minute meets the requirement; therefore, this key area with high pedestrian flow will be designated as an emergency evacuation zone.

[0042] The first early warning trigger feature set is obtained based on the behavioral coordination degree of emergency gathering areas, emergency resource occupancy rate, and evacuation route characteristics. This process includes the following steps: Collect data on the synchronicity of movement and coordination of actions of people within the emergency assembly area; Behavioral coordination degree is obtained based on mobile synchronization and action coordination data; The rate of consumption of emergency supplies and the frequency of use of emergency facilities within the emergency assembly area will be monitored. The emergency resource occupancy rate is obtained based on the consumption rate, usage frequency, and the initial total amount of emergency resources. The first early warning trigger feature set is formed by verifying the degree of behavioral coordination, emergency resource occupancy rate and evacuation route characteristics.

[0043] First, data on the synchronicity and coordination of movement of people within the emergency assembly area are collected. Movement synchronicity data is statistically analyzed using monitoring equipment within the area. For example, in an emergency assembly area (such as a gathering area on a floor of a shopping mall), the movement direction of 100 people is analyzed. If 85 people move towards the same safety exit, the directional synchronization rate is 85%. The standard deviation of movement speed is also analyzed. If the average movement speed is 1.1 m / s and the standard deviation is 0.2 m / s, the speed synchronization level is considered high. Movement coordination data observes the consistency of people's emergency actions. For example, in an emergency, if 78 people in the area simultaneously perform a bending-over-to-protect-the-head protective action, the movement synchronization rate is 78%.

[0044] Behavioral coordination score is derived from motion synchronization and movement coordination data. The behavioral coordination score is a comprehensive quantification of these two types of data: Behavioral Coordination Score = Motion Synchronization Score × 0.6 + Movement Coordination Score × 0.4. The motion synchronization score is calculated based on the conversion between directional synchronization ratio and speed synchronization degree; for example, a directional synchronization ratio of 85% corresponds to 85 points, and a speed standard deviation of 0.2 m / s corresponds to 90 points, with the average of the two being 87.5 points. The movement coordination score is based on a movement synchronization ratio of 78%, corresponding to 78 points. Substituting the data, we get the behavioral coordination score = 87.5 × 0.6 + 78 × 0.4 = 83.7.

[0045] The test measures the consumption rate of emergency supplies and the frequency of use of emergency facilities within the emergency assembly area. The consumption rate of emergency supplies is the amount of supplies reduced per unit of time. For example, if the assembly area initially has 50 first-aid kits, and 15 are consumed within 20 minutes, the consumption rate is 15 / 20 = 0.75 kits / minute. The frequency of use of emergency facilities is the number of times a facility is used. For example, if the emergency call button in the area is pressed 8 times within 30 minutes, the usage frequency is 8 / 30 ≈ 0.27 times / minute.

[0046] The emergency resource occupancy rate is calculated based on the consumption rate, usage frequency, and the initial total allocation of emergency resources. The emergency resource occupancy rate represents the degree to which resources are used. It is calculated as: Emergency Resource Occupancy Rate = (Total Consumption of Materials / Initial Allocation of Materials) × 0.5 + (Total Usage Time of Facilities / Rated Available Time of Facilities) × 0.5. If frequency is used instead of duration, it is adjusted to: Facility Usage Frequency / Rated Usage Frequency of Facilities. Taking first-aid kits and call buttons as an example, the total consumption of materials is 15, and the initial allocation is 50, resulting in an occupancy rate of 15 / 50 = 0.3. The rated usage frequency of the call button is 0.5 times / minute, and the actual usage frequency is 0.27 times / minute, resulting in an occupancy rate of 0.27 / 0.5 = 0.54. Substituting the data, the emergency resource occupancy rate is calculated as: 0.3 × 0.5 + 0.54 × 0.5 = 0.42.

[0047] The first early warning trigger feature set is formed by verifying behavioral coordination, emergency resource occupancy rate, and evacuation route characteristics. Evacuation route characteristics refer to the accessibility and length of the route. For example, if the evacuation route in this gathering area is 3 meters wide and unobstructed, its accessibility score is 90. The verification process compares the values ​​of these three features with preset valid ranges. For example, the valid range for behavioral coordination is 60-100, the valid range for emergency resource occupancy rate is 0-80%, and the valid range for evacuation route accessibility is 70-100. Currently, all three data are within the valid range, indicating that the features are effective. Finally, the behavioral coordination score of 83.7, the emergency resource occupancy rate of 42%, and the evacuation route accessibility score of 90 are integrated into the first early warning trigger feature set.

[0048] The second early warning trigger feature set is obtained based on the efficiency of crowd control, resource allocation response speed, and congestion transmission characteristics in the emergency evacuation area. This process includes the following steps: Obtain real-time basic information on the flow of people in the emergency evacuation area, and calculate the flow of people efficiency based on the real-time basic information on the flow of people. Based on the distribution of emergency resources in the emergency evacuation area, we obtain information on the entire process of resource scheduling, and then obtain the resource scheduling response speed based on this information. The starting location and spread direction of the emergency evacuation area are determined based on the efficiency of crowd flow management and the response speed of resource allocation. The degree of impact and spread trend of congestion on the surrounding evacuation channels are judged based on the starting location and spread direction to obtain the congestion transmission characteristics. The efficiency of crowd flow management, the response speed of resource allocation, and the characteristics of congestion transmission are correlated and integrated to form a second early warning trigger feature set.

[0049] First, obtain real-time basic information on pedestrian flow management in the emergency evacuation area, and then calculate the pedestrian flow management efficiency based on this information. Real-time basic information includes the width of the evacuation area's passageways, the number of people passing through per unit time, and the number of people remaining in the evacuation area. For example, in an emergency evacuation area (such as an escalator passage in a shopping mall), the passageway width is 4 meters. Within 10 minutes, 600 people pass through the passageway, while 20 people remain in the passageway at any given time. The pedestrian flow management efficiency is calculated as follows: (Number of people passing through per unit time / Maximum standard passage capacity of the passageway) × (1 - Percentage of people remaining in the evacuation area). Here, the maximum standard passage capacity of the passageway = passageway width × 1.5 people / square meter × 60 minutes, i.e., the maximum standard passage capacity of the passageway = 4 × 1.5 × 60 = 360 people / 10 minutes. The percentage of people remaining in the evacuation area is 20 / (600+20) ≈ 3.2%. Substituting the data, we get the pedestrian flow management efficiency as follows: (600 / 360) × (1 - 0.032) ≈ 1.61. A higher value indicates better management efficiency.

[0050] Based on the distribution of emergency resources in the emergency evacuation area, the entire resource dispatch process information is obtained, and the resource dispatch response speed is derived from this information. The emergency resource distribution refers to the location distribution of emergency supplies (such as first-aid kits) and facilities (such as emergency broadcasts) within the area. The entire resource dispatch process information includes the time the dispatch instruction is issued and the time it takes for resources to move to the target area. For example, if the emergency broadcast dispatch instruction is issued at 10:00, and the broadcast is completed and covers the evacuation area at 10:02, the total resource dispatch time is 2 minutes; if the instruction to transport the first-aid kit from the storage point to the evacuation area is issued at 10:01, and it arrives at 10:05, the time is 4 minutes. Resource dispatch response speed = 1 / (average time for dispatching various types of resources). Here, the average time for the two types of resources is (2+4) / 2 = 3 minutes. Substituting the data, we get the resource dispatch response speed = 1 / 3 ≈ 0.33. A higher value indicates a faster response.

[0051] The starting location and spread direction of the emergency evacuation area are determined based on the efficiency of pedestrian flow management and the response speed of resource allocation. The congestion transmission characteristics are then derived from these starting locations and spread directions. The starting location refers to the starting point of an area with low pedestrian flow management efficiency. For example, the pedestrian flow management efficiency at the entrance of an evacuation route is only 1.2, lower than the 1.8 efficiency in the middle section of the route; therefore, the starting location is the entrance of the route. The spread direction is determined based on the trend of people moving from the entrance to the middle section of the route. The congestion transmission characteristics assess the degree of impact of congestion on surrounding routes and its spread trend. For example, if the number of people stranded at the current entrance increases by 10 every 5 minutes, at this rate, the congestion area will spread to adjacent pedestrian routes after 15 minutes, affecting the capacity of adjacent routes by 40%, meaning the capacity of adjacent routes will decrease by 40%. These pieces of information collectively constitute the congestion transmission characteristics.

[0052] The efficiency of pedestrian flow management, the response speed of resource scheduling, and the characteristics of congestion transmission are correlated and integrated to form a second early warning trigger feature set. Correlation and integration involves matching the quantitative data of the three features with the corresponding descriptive information. For example, in the case above, the efficiency of pedestrian flow management is 1.61, the response speed of resource scheduling is 0.33, and the congestion transmission characteristic is that it spreads from the entrance to the middle section and affects 40% of the capacity of adjacent passages within 15 minutes. These contents are integrated into the second early warning trigger feature set.

[0053] The first and second correlation coefficients are obtained by processing and analyzing the historical emergency management data of the target area. The specific steps include: Acquire full-process data of the historical emergency control process of the target area, and extract relevant information on the historical early warning trigger characteristics of emergency gathering scenarios and emergency evacuation scenarios, as well as the implementation feedback information of corresponding control measures based on the full-process data; The degree of fit between information related to early warning triggering characteristics and implementation feedback information in different historical periods is used to obtain the results of the fit analysis; By extracting the target-related elements of early warning triggering characteristics and control implementation feedback in emergency gathering scenarios, we can obtain the gathering scenario-related elements. By extracting the target correlation elements between the early warning triggering characteristics and the control implementation feedback in emergency evacuation scenarios, we can obtain the evacuation scenario correlation elements. The clustered scene-related elements are transformed into a first correlation coefficient that represents the degree of correlation between early warning triggering and control effectiveness; The relevant elements of the evacuation scenario are transformed into a second correlation coefficient that represents the degree of correlation between early warning triggering and control effectiveness.

[0054] First, acquire full-process data of the historical emergency control process of the target area. The full-process data covers all control links of historical emergency gathering and emergency evacuation scenarios. For example, data on three emergency gathering scenarios in a shopping mall in the past year, including the behavioral coordination degree and early warning trigger characteristics of emergency resource occupancy rate during each gathering, as well as the corresponding control measures (such as increasing the number of evacuation personnel and replenishing supplies) and implementation feedback information (such as a 30% reduction in the time people stayed after evacuation). At the same time, extract the early warning characteristics of the flow of people and the response speed of resource scheduling in two emergency evacuation scenarios, as well as the feedback of control measures (such as opening backup channels) (such as a 25% increase in traffic capacity).

[0055] The degree of fit between the information related to the warning trigger characteristics and the implementation feedback information in different historical periods is used to obtain the fit analysis results. Fit measures the degree of matching between the control needs corresponding to the warning characteristics and the actual control measures. For example, in an emergency gathering scenario, the warning trigger characteristics show a behavioral coordination degree of 75 and a resource occupancy rate of 60%. The corresponding control measure is to add 2 more evacuation personnel. The implementation feedback is that the time people stay in the area is reduced from 20 minutes to 12 minutes. Fit = (actual effect improvement ratio / expected effect improvement ratio) × 100. If the expected improvement ratio is 40% and the actual improvement ratio is (20-12) / 20 = 40%, then the fit is (40% / 40%) × 100 = 100.

[0056] We extracted the target-related elements for emergency gathering and evacuation scenarios. For emergency gathering scenarios, based on the correspondence between early warning triggering characteristics and control feedback, we extracted the following related elements: for every 10-point increase in behavioral coordination, the post-control dwell time is reduced by 8%; for every 15% decrease in resource occupancy rate, the material replenishment efficiency is increased by 12%. These are the related elements for gathering scenarios. For emergency evacuation scenarios, we extracted the following related elements: for every 0.2-point increase in crowd flow guidance efficiency, the passage capacity is increased by 15%; for every 0.1-point increase in resource dispatch response speed, the emergency response time is reduced by 10%. These are the related elements for evacuation scenarios.

[0057] The related elements are transformed into a first correlation coefficient and a second correlation coefficient. The correlation coefficient is a quantitative integration of the related elements, and the correlation coefficient = Σ (the influence weight of the related element × the degree of influence). Taking the gathering scenario as an example, the influence weight of behavioral coordination on the control effect is 0.6 and the degree of influence is 8% / 10, and the influence weight of resource occupancy rate is 0.4 and the degree of influence is 12% / 15%. Substituting the data, we get the first correlation coefficient = (0.6 × 0.8) + (0.4 × 0.8) = 0.8. Taking the evacuation scenario as an example, the influence weight of crowd flow guidance efficiency is 0.7 and the degree of influence is 15% / 0.2, and the influence weight of resource scheduling response speed is 0.3 and the degree of influence is 10% / 0.1. We calculate the second correlation coefficient = (0.7 × 75) + (0.3 × 100) = 82.5.

[0058] Based on the first correlation coefficient and the first early warning trigger feature set, the first early warning control result for the emergency gathering area is output, specifically including the following steps: The first correlation coefficient is matched with the first early warning trigger feature set, and the correlation dimension that matches the first early warning trigger feature set is selected to obtain the feature correlation matching result. Based on the feature association and adaptation results, the priority of control requirements corresponding to the current early warning triggering features of the emergency gathering area is determined, and the target control direction is determined according to the control requirements priority to obtain the priority judgment result. After combining the priority judgment results, effective control elements that match the current target control direction are retrieved from the historical emergency gathering area control. A preliminary control plan is then formed. The suitability of the preliminary control plan with the actual situation of the current emergency gathering area is verified based on the degree of correlation represented by the first correlation coefficient. After optimizing and adjusting the configuration of control elements according to the suitability, the first early warning control result is output.

[0059] First, the first correlation coefficient is matched with the first early warning trigger feature set to obtain the feature association adaptation result by selecting suitable correlation dimensions. The first correlation coefficient is a quantitative value that represents the degree of correlation between early warning triggering and control effect. The first early warning trigger feature set includes features such as behavioral coordination, emergency resource occupancy rate, and evacuation path, for example, behavioral coordination is 83.7 and emergency resource occupancy rate is 42%. Correlation matching involves matching each feature in the feature set with the historical correlation dimension corresponding to the first correlation coefficient. For example, the dimensions associated by the first correlation coefficient are behavioral coordination and dwell time, and resource occupancy rate and material replenishment. The two features in the current feature set happen to cover these two dimensions. Therefore, the feature association adaptation result is that the current feature set and the core correlation dimensions of the first correlation coefficient are completely matched.

[0060] Based on the feature association and adaptation results, the priority of control needs corresponding to the current early warning triggering features in the emergency gathering area is determined, and the target control direction is determined to obtain the priority judgment result. The control need priority is calculated based on the influence of feature values ​​and association dimensions: Control need priority = Σ (feature value × weight of corresponding association dimension). For example, the weight corresponding to behavioral coordination is 0.6, and the weight corresponding to emergency resource occupancy rate is 0.4. Substituting the data, the control need priority = 83.7 × 0.6 + 42 × 0.4 = 67.02. Generally, the higher the priority value, the more urgent the control need. If a score of 60 or above is preset to correspond to high priority, then the priority judgment result is that the current control need has a high priority, and the target control direction is to prioritize improving the emergency resource supply capacity and assist in optimizing personnel behavioral coordination.

[0061] Based on the priority assessment results, effective control elements matching the current target control direction are retrieved from historical emergency gathering area management to form a preliminary control plan. For example, historical data shows that for high-priority scenarios that require increased resource supply and optimized behavioral coordination, effective control elements include deploying two additional supply personnel, assigning one evacuation guide to guide the movement of people simultaneously, and replenishing 10 first-aid kits. After integrating these elements, the preliminary control plan is to deploy two additional supply personnel, replenish 10 first-aid kits, and assign one evacuation guide to guide the movement of people.

[0062] The suitability of the initial control plan to the actual situation of the current emergency gathering area is verified based on the correlation coefficient, which represents the degree of correlation. After optimization and adjustment, the first early warning control result is output. A first correlation coefficient of 0.8 indicates a high degree of correlation. During verification, it is necessary to compare the differences between historical scenarios and the current scenario. For example, if the number of people in the current area is 20% higher than in historical matching scenarios, the control elements need to be adjusted accordingly: the number of material supply personnel is increased to 3, and the number of first aid kits is increased to 12. The first early warning control result is to dispatch 3 more material supply personnel to replenish 12 first aid kits, and arrange 1 evacuation guide to guide people to move synchronously to the evacuation route.

[0063] Based on the second correlation coefficient and the second early warning trigger feature set, the second early warning control result for the emergency evacuation area is output, specifically including the following steps: The feature weight association result is obtained by correspondingly associating the second correlation coefficient with the second early warning trigger feature set; Based on the feature weight association results, the current target early warning risk points of the emergency evacuation area are determined, and the target optimization direction of evacuation control is determined according to the current target early warning risk points to obtain the risk judgment result; Based on the risk assessment results, extract effective control measures from historical evacuation and control that match the current key optimization directions, and form a preliminary evacuation and control plan; The degree of correlation, as represented by the second correlation coefficient, is used to verify the fit between the preliminary evacuation control plan and the real-time evacuation status of the emergency evacuation area. Based on the fit, control measures are adjusted and the second early warning control result is output.

[0064] First, the second correlation coefficient is correlated with the second early warning trigger feature set to obtain the feature weight correlation result. The second correlation coefficient is a quantitative value characterizing the degree of correlation between early warning triggering and control effect in evacuation scenarios. The second early warning trigger feature set includes crowd flow management efficiency, resource scheduling response speed, and congestion transmission characteristics. Correlation identification involves matching each feature in the feature set with the historical correlation weight corresponding to the second correlation coefficient. For example, the correlation weight of crowd flow management efficiency in the second correlation coefficient is 0.7, and the correlation weight of resource scheduling response speed is 0.3. Since the current feature set covers these two features, the feature weight correlation result is a correlation weight of 0.7 for crowd flow management efficiency and 0.3 for resource scheduling response speed.

[0065] Based on the feature weight association results, the current target early warning risk point in the emergency evacuation area is determined, and the optimization direction of evacuation control is clarified to obtain the risk assessment result. The target early warning risk point is determined by calculating the risk contribution degree by multiplying the feature value and the association weight: Risk contribution degree = Feature value × Corresponding association weight. Substituting the current feature value, the risk contribution degree of the crowd flow guidance efficiency is 1.61 × 0.7 ≈ 1.13, and the risk contribution degree of the resource scheduling response speed is 0.33 × 0.3 ≈ 0.10. The lower the risk contribution degree, the higher the corresponding risk. Therefore, the current target early warning risk point is insufficient resource scheduling response speed, and the corresponding target optimization direction is to improve the resource scheduling response speed.

[0066] By combining risk assessment results with effective control measures from historical evacuation management that match current key optimization directions, a preliminary evacuation management plan is formed. For example, effective control measures for improving resource dispatch response speed, based on historical data, include pre-positioning a set of emergency supplies around the evacuation area and assigning a dedicated dispatcher to shorten instruction transmission time. Integrating these measures, the preliminary evacuation management plan involves pre-positioning a set of first-aid kits and emergency broadcasting equipment at the entrance of the evacuation area and assigning a dedicated dispatcher to be responsible for resource instruction transmission.

[0067] The consistency between the initial evacuation control plan and the real-time evacuation status of the emergency evacuation area is verified based on the correlation coefficient, and the second early warning control result is output after adjustment. A second correlation coefficient of 82.5 indicates a high degree of correlation. During verification, adjustments need to be made in conjunction with the real-time evacuation status. For example, if the number of people in the current evacuation area is 30% higher than in historical matching scenarios, the number of preset emergency supplies needs to be increased to 2 sets, and the number of dedicated dispatchers needs to be increased to 2. The second early warning control result is to preset 1 set of first aid kits and emergency broadcast equipment at the entrance and middle section of the evacuation area, and assign 2 dedicated dispatchers to be responsible for the instruction transmission of supplies and facilities respectively.

[0068] A high-traffic area early warning and control system includes: Processing module: Obtains initial emergency results based on personnel behavior coordination parameters and emergency resource adaptation parameters in the target area; The emergency response module is divided into emergency gathering areas and emergency evacuation areas based on the initial emergency response results and the emergency resource layout of the target area. The first analysis module: derives the first early warning trigger feature set based on the behavioral coordination degree of the emergency gathering area, the emergency resource occupancy rate, and the evacuation route characteristics; and derives the second early warning trigger feature set based on the pedestrian flow guidance efficiency, resource scheduling response speed, and congestion transmission characteristics of the emergency evacuation area. The second analysis module processes and analyzes the historical emergency control data of the target area to obtain the first correlation coefficient and the second correlation coefficient; Output module: Outputs the first early warning control result for the emergency gathering area based on the first correlation coefficient and the first early warning trigger feature set; outputs the second early warning control result for the emergency evacuation area based on the second correlation coefficient and the second early warning trigger feature set; outputs broadcast early warning instructions based on the first early warning control result and the second early warning control result.

[0069] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0070] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for early warning and control of high-traffic areas, characterized in that, The method includes the following steps: Initial emergency results are obtained based on the personnel behavior coordination parameters and emergency resource adaptation parameters in the target area; Based on the initial emergency response results and the emergency resource layout in the target area, emergency gathering areas and emergency evacuation areas were divided. The first early warning trigger feature set is obtained based on the behavioral coordination degree of the emergency gathering area, the emergency resource occupancy rate, and the evacuation route characteristics; the second early warning trigger feature set is obtained based on the efficiency of the flow of people in the emergency evacuation area, the response speed of resource scheduling, and the congestion transmission characteristics. The first and second correlation coefficients were obtained by processing and analyzing the historical emergency management data of the target area, specifically including: Acquire full-process data of the historical emergency control process of the target area, and extract relevant information on the historical early warning trigger characteristics of emergency gathering scenarios and emergency evacuation scenarios, as well as the implementation feedback information of corresponding control measures based on the full-process data; The degree of fit between information related to early warning triggering characteristics and implementation feedback information in different historical periods is used to obtain the results of the fit analysis; By extracting the target-related elements of early warning triggering characteristics and control implementation feedback in emergency gathering scenarios, we can obtain the gathering scenario-related elements. By extracting the target correlation elements between the early warning triggering characteristics and the control implementation feedback in emergency evacuation scenarios, we can obtain the evacuation scenario correlation elements. The clustered scene-related elements are transformed into a first correlation coefficient that represents the degree of correlation between early warning triggering and control effectiveness; The relevant elements of the evacuation scenario are transformed into a second correlation coefficient that represents the degree of correlation between early warning triggering and control effectiveness. Based on the first correlation coefficient and the first early warning trigger feature set, the first early warning control results for the emergency gathering area are output, specifically including: The first correlation coefficient is matched with the first early warning trigger feature set, and the correlation dimension that matches the first early warning trigger feature set is selected to obtain the feature correlation matching result. Based on the feature association and adaptation results, the priority of control requirements corresponding to the current early warning triggering features of the emergency gathering area is determined, and the target control direction is determined according to the control requirements priority to obtain the priority judgment result. After combining the priority judgment results, effective control elements that match the current target control direction are retrieved from the historical emergency gathering area control. A preliminary control plan is then formed. The suitability of the preliminary control plan with the actual situation of the current emergency gathering area is verified based on the degree of correlation represented by the first correlation coefficient. After optimizing and adjusting the configuration of control elements according to the suitability, the first early warning control result is output. Based on the second correlation coefficient and the second early warning trigger feature set, the second early warning control results for the emergency evacuation area are output, specifically including: The feature weight association result is obtained by correspondingly associating the second correlation coefficient with the second early warning trigger feature set; Based on the feature weight association results, the current target early warning risk points of the emergency evacuation area are determined, and the target optimization direction of evacuation control is determined according to the current target early warning risk points to obtain the risk judgment result; Based on the risk assessment results, extract effective control measures from historical evacuation and control that match the current key optimization directions, and form a preliminary evacuation and control plan; The degree of correlation, as represented by the second correlation coefficient, is used to verify the fit between the preliminary evacuation control plan and the real-time evacuation status of the emergency evacuation area. Based on the fit, control measures are adjusted and the second early warning control results are output. Broadcast warning instructions are output based on the results of the first and second early warning control measures.

2. The method for early warning and control of high-traffic areas according to claim 1, characterized in that, The initial emergency response results are obtained based on the personnel behavior coordination parameters and emergency resource adaptation parameters in the target area, specifically including the following steps: The parameters for personnel behavior coordination in the target area are combined with the parameters for emergency resource adaptation to form a coordination adaptation feature. Obtain emergency control standards; The initial emergency response results are obtained by comparing the collaborative adaptation features with the emergency control standards.

3. The method for early warning and control of high-traffic areas according to claim 2, characterized in that, Based on the initial emergency response results and the emergency resource layout in the target area, emergency gathering areas and emergency evacuation areas are divided, specifically including the following steps: The resource allocation threshold is preset based on the initial emergency response results; Based on the resource layout classification threshold, the emergency resource layout status of the target area is detected to obtain resource layout characteristics; The layout division results are obtained by dividing the area range corresponding to the resource layout division threshold according to the resource layout characteristics; Preset an emergency overload threshold, and mark the areas in the layout division results whose emergency resource carrying pressure is greater than or equal to the emergency overload threshold as target control areas; Emergency assembly areas and emergency evacuation areas are divided from the target control area.

4. The method for early warning and control of high-traffic areas according to claim 3, characterized in that, The emergency assembly area and the emergency evacuation area are divided from the target control area, specifically including the following steps: Obtain information on the resource availability and population flow trends of the target control area; Based on the resource carrying capacity, the regional carrying capacity critical point is determined, and based on the population flow trend, the dominant areas of population residence and the dominant areas of population flow are selected. The resource supply capacity of the main area where the testing personnel are stationed will be used to designate areas with resource supply capacity lower than the demand threshold corresponding to the regional carrying capacity as emergency gathering areas. Assess the traffic capacity of areas with high population flow and designate areas whose traffic capacity meets the preset evacuation requirements as emergency evacuation zones.

5. The method for early warning and control of high-traffic areas according to claim 4, characterized in that, The first early warning trigger feature set is obtained based on the behavioral coordination degree of emergency gathering areas, emergency resource occupancy rate, and evacuation route characteristics. This process includes the following steps: Collect data on the synchronicity of movement and coordination of actions of people within the emergency assembly area; Behavioral coordination degree is obtained based on mobile synchronization and action coordination data; The rate of consumption of emergency supplies and the frequency of use of emergency facilities within the emergency assembly area will be monitored. The emergency resource occupancy rate is obtained based on the consumption rate, usage frequency, and the initial total amount of emergency resources. The first early warning trigger feature set is formed by verifying the degree of behavioral coordination, emergency resource occupancy rate and evacuation route characteristics.

6. The method for early warning and control of high-traffic areas according to claim 5, characterized in that, The second early warning trigger feature set is obtained based on the efficiency of crowd control, resource allocation response speed, and congestion transmission characteristics in the emergency evacuation area. This process includes the following steps: Obtain real-time basic information on the flow of people in the emergency evacuation area, and calculate the flow of people efficiency based on the real-time basic information on the flow of people. Based on the distribution of emergency resources in the emergency evacuation area, we obtain information on the entire process of resource scheduling, and then obtain the resource scheduling response speed based on this information. The starting location and spread direction of the emergency evacuation area are determined based on the efficiency of crowd flow management and the response speed of resource allocation. The degree of impact and spread trend of congestion on the surrounding evacuation channels are judged based on the starting location and spread direction to obtain the congestion transmission characteristics. The efficiency of crowd flow management, the response speed of resource allocation, and the characteristics of congestion transmission are correlated and integrated to form a second early warning trigger feature set.

7. A high-crowd area early warning and control system, applied to the high-crowd area early warning and control method according to any one of claims 1 to 6, characterized in that, include: Processing module: Obtains initial emergency results based on personnel behavior coordination parameters and emergency resource adaptation parameters in the target area; The emergency response module is divided into emergency gathering areas and emergency evacuation areas based on the initial emergency response results and the emergency resource layout of the target area. The first analysis module: derives the first early warning trigger feature set based on the behavioral coordination degree of the emergency gathering area, the emergency resource occupancy rate, and the evacuation route characteristics; and derives the second early warning trigger feature set based on the pedestrian flow guidance efficiency, resource scheduling response speed, and congestion transmission characteristics of the emergency evacuation area. The second analysis module processes and analyzes the historical emergency control data of the target area to obtain the first correlation coefficient and the second correlation coefficient; Output module: Outputs the first early warning control result for the emergency gathering area based on the first correlation coefficient and the first early warning trigger feature set; outputs the second early warning control result for the emergency evacuation area based on the second correlation coefficient and the second early warning trigger feature set; outputs broadcast early warning instructions based on the first early warning control result and the second early warning control result.

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