Comprehensive passenger transport hub passenger flow risk evaluation method
By constructing a risk assessment method for passenger transport hubs and quantifying a safety risk assessment framework of "points," "lines," and "areas," the problem of risk assessment caused by the superposition of multiple passenger flows in passenger transport hubs has been solved. This has enabled risk level assessment and targeted control, and improved the efficiency and safety of passenger flow evacuation.
Patent Information
- Application Number
- CN202511024862.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-24
- Publication Date
- 2026-02-24
AI Technical Summary
Integrated passenger transport hubs, with their connections to multiple modes of transportation, face challenges such as difficulties in organizing passenger flow, numerous safety risks, and difficulties in quantifying and assessing risks due to the overlapping effects of multiple passenger flows.
A passenger flow risk assessment method based on the building structure and functional zoning of passenger transport hubs is constructed. By quantifying the safety risk assessment framework of 'points', 'lines', and 'areas', the difference in passenger flow safety risk assessment is calculated, and the passenger flow risk level is determined.
It assists operations managers in assessing passenger flow risk status, improving passenger evacuation efficiency, reducing safety risks, and providing targeted control measures.
Smart Images
Figure CN121563176A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of passenger transport hub safety risk and carrying capacity assessment technology, specifically, to a comprehensive passenger transport hub passenger flow risk assessment method. Background Technology
[0002] Integrated passenger transport hubs are key nodes in multi-modal and multi-level transportation networks, characterized by their massive spatial scale, complex three-dimensional structure, multiple connecting modes of transportation, diverse passenger sources, and high intensity of passenger gathering and dispersal. This invention proposes a passenger flow risk assessment method for integrated passenger transport hubs. Based on the architectural structure and functional zoning of integrated passenger transport hubs, it analyzes key locations within the hub and their corresponding passenger flow information collection needs, and constructs a quantitative identification and classification method for passenger flow risk of integrated passenger transport hubs as a whole. This method can assist operation managers in assessing the passenger flow risk status of integrated passenger transport hubs based on passenger flow risk indices and passenger flow risk levels, and then take targeted control measures.
[0003] Integrated passenger transport hubs are key nodes in multi-modal, multi-level transportation networks. They are characterized by their vast spatial scale, complex three-dimensional structure, multiple connecting modes of transportation, diverse passenger origins, and high intensity of passenger flow. They play a vital role in improving the efficiency of integrated transportation networks, optimizing transportation structures, accelerating the transformation and development of transportation, and enhancing people's quality of life and convenience. Within these hubs, various modes of transportation are interconnected, such as railways, urban rail transit, buses, taxis, ride-hailing services, and shared bicycles. The complex and diverse facilities provide passengers with efficient transfer services and meet the diverse and personalized travel needs of cross-regional passengers.
[0004] Currently, the following issues in passenger flow organization within the hub urgently need to be addressed: 1. While providing convenient transfers for passengers traveling across different modes of transportation, integrated passenger transport hubs face multiple overlapping passenger flows (overlapping long-distance and short-distance passenger flows, overlapping intra-city and inter-city passenger flows, overlapping commercial travel passenger flows, etc.), making passenger flow organization difficult. In particular, systemic disruptions in a certain mode of transportation (such as large-scale railway delays or subway emergencies) can easily lead to problems such as crowding and passenger congestion within the hub.
[0005] 2. The hub has many internal functional areas, complex equipment and facilities, and diverse transportation connections, resulting in numerous safety risks and difficulties in quantifying and assessing these risks during operation. Summary of the Invention
[0006] The purpose of this invention is to provide a comprehensive passenger flow risk assessment method for passenger transport hubs to solve the problems mentioned in the background art.
[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for assessing passenger flow risk in a comprehensive passenger transport hub, comprising the following steps: S100. Obtain passenger flow safety early warning information from passenger transport hubs, form a safety early warning information sequence, and construct a continuously changing differential supplementary sequence; S200. Construct a safety risk assessment framework by combining the safety early warning information sequence with the variability difference supplementary sequence, and calculate the difference in safety risk assessment and analysis of hub passenger flow. In step S200, a safety risk assessment framework is constructed by quantifying "points", "lines", and "surfaces" at the spatial level of passenger transport hubs. Multiple passenger flow risk hub "points" constitute passenger flow risk hub "lines", and multiple passenger flow risk hub "lines" constitute passenger flow risk hub "surfaces". The difference in hub passenger flow safety risk assessment and analysis is calculated through multiple layers of passenger flow risk hub "surfaces". S300: The passenger flow safety risk assessment and analysis differences between "points," "lines," and "areas" at the hubs are used to determine the passenger flow risk level using passenger flow safety risk assessment methods. The passenger flow risk levels are "Level 1," "Level 2," and "Level 3."
[0008] Preferably, the information data source in the safety warning information sequence in S100 is the passenger flow density, flow rate, speed of each monitoring area, and passenger flow information obtained by any acquisition technology; Passenger flow information sets form a safety early warning information sequence, which is used to calculate the difference in passenger flow safety risk assessment and analysis at the hub. Each different time period will generate a continuously changing difference supplement sequence, which is used to perform differential supplement calculations on the safety warning information sequence.
[0009] Preferably, in S200, the degree of passenger congestion in the pedestrian facilities of the passenger station, such as the walking area, waiting area, and escalators, is described. The passenger flow information obtained by arbitrary collection technologies such as passenger flow density, speed, and flow rate in S100 is used to form quantitative indicators, and a key passenger flow risk assessment indicator system is constructed. The "points" of passenger flow risk hubs are formed through the key passenger flow risk assessment indicator system. The density index of waiting areas and escalators is dimensionless and the result is the passenger congestion index, calculated using the following formula: ,in, This represents the result of passenger flow density normalization. For horizontal walking areas and stairs, the congestion index comprehensively considers the passenger flow density index and the passenger flow speed index, and takes the average of the two as the passenger flow congestion index value. The calculation formula is as follows: ,in, This is the result of normalized processing of passenger flow speed.
[0010] Preferably, in S200, the "points" of multiple passenger flow risk hubs constitute the "line" of passenger flow risk hubs. The passenger flow risk index of the "line" reflects the index of the distribution and magnitude of passenger flow risk at the "points", and reflects the impact of passenger flow aggregation in each "line" area on the safety of passenger flow at the hub. The passenger flow risk hub "line" is obtained by weighting the passenger flow risk index of each key area through the key area weight.
[0011] Preferably, in S200, multiple flow "lines" in the hub constitute a "surface" in the passenger flow hub. The "surface" in the passenger flow hub quantitatively characterizes the passenger flow risk level of the hub through the weight of the "lines" in the passenger flow hub. The weight index is selected by the passenger flow size in the hub, and the passenger flow risk level is determined by substituting the weight index into the calculation.
[0012] Preferably, the weighting index of the "surface" is divided into the flow line importance weighting index and the importance weighting index processing. The hub passenger flow risk index is calculated by the flow line importance weighting index and the importance weighting index processing.
[0013] Preferably, the hub passenger flow risk index corresponds to the hub passenger flow risk level; The passenger flow risk level of a Level 1 hub corresponds to a hub passenger flow risk index of 1.69-4.38; The passenger flow risk level of a Level 2 hub corresponds to a hub passenger flow risk index of 4.38-7.62; The passenger flow risk level of a Level 3 hub corresponds to a hub passenger flow risk index of 7.62-10.00.
[0014] Preferably, in the S200 calculation of the safety assessment analysis difference, a predictive analysis difference is set, and a specific hub difference weight is set at the passenger flow risk hub "point".
[0015] Preferably, in S100, a specified weight threshold is set. When the number of online passenger tickets reaches a specified value, the specified weight threshold is increased by 1, the weight of the difference between specific hubs is increased by 1, and the predicted analysis difference is increased by 1 when the specified weight threshold and the weight of the difference between specific hubs are increased by 1. The predicted analysis difference is then incorporated into the safety warning information sequence.
[0016] Preferably, in the 100, the continuously changing difference supplement sequence includes a dynamic update unit, which is used to calculate the safety warning information sequence with mean and standard deviation, set multiple threshold adjustment factors, and dynamically adjust the standard range threshold using the threshold adjustment factors in each iteration.
[0017] Compared with the prior art, the beneficial effects of the present invention are: This invention analyzes key locations within a comprehensive passenger transport hub and their corresponding passenger flow information collection needs based on the hub's architectural structure and functional zoning. It constructs a method for quantitative identification and classification of passenger flow risks in a comprehensive passenger transport hub, which can assist operators in assessing the passenger flow risk status of the hub based on the passenger flow risk index and risk level. This allows for targeted control measures to improve the efficiency of passenger flow evacuation and reduce safety risks. Attached Figure Description
[0018] Figure 1 This is a schematic diagram of the evaluation method for passenger flow risk assessment in an embodiment of the present invention. Figure 2 This is a schematic diagram of the framework process for passenger flow risk assessment in an embodiment of the present invention; Figure 3 This is a schematic diagram of the key passenger flow safety risk assessment index system according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the hub passenger flow risk assessment index structure according to an embodiment of the present invention; Detailed Implementation
[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0020] Example 1, such as Figure 1 As shown, this application discloses a method for assessing passenger flow risk in a comprehensive passenger transport hub, comprising the following steps: S100. Obtain passenger flow safety early warning information from passenger transport hubs, form a safety early warning information sequence, and construct a continuously changing differential supplementary sequence; S200. Construct a safety risk assessment framework by combining the safety early warning information sequence with the variability difference supplementary sequence, and calculate the difference in safety risk assessment and analysis of hub passenger flow. In step S200, a safety risk assessment framework is constructed by quantifying "points", "lines", and "surfaces" at the spatial level of passenger transport hubs. Multiple passenger flow risk hub "points" constitute passenger flow risk hub "lines", and multiple passenger flow risk hub "lines" constitute passenger flow risk hub "surfaces". The difference in hub passenger flow safety risk assessment and analysis is calculated through multiple layers of passenger flow risk hub "surfaces". S300: The passenger flow safety risk assessment and analysis difference of "point", "line" and "area" hub passenger flow is used to determine the passenger flow risk level through passenger flow safety risk assessment method. The passenger flow risk level is "Level 1", "Level 2" and "Level 3".
[0021] Specifically, during the operation of a comprehensive transportation hub, the passenger flow risk of any "point" or "line" will continuously affect each other as passenger flow changes, thereby affecting the overall operational safety of the hub. In other words, the passenger flow risk of a comprehensive transportation hub is jointly constituted by the passenger flow risks of each "point" and "line" in the network. Therefore, the calculation of passenger flow risk of a comprehensive transportation hub is based on the passenger flow risks of "points" and "lines" within the hub.
[0022] At the spatial level, the passenger flow risk of a comprehensive transportation hub is jointly determined by the passenger flow risks of each area within the station, while the "line" passenger flow risk is constituted by the passenger flow risks of "points" within the hub. Based on this, a quantitative assessment of the passenger flow risk of a comprehensive transportation hub is achieved by calculating the passenger flow risk values at each spatial level layer by layer. Combining the passenger flow characteristics of the comprehensive transportation hub, passenger flow speed in horizontal walking areas, passenger flow speed on stairs, passenger flow density on escalators, and passenger flow density in platform waiting areas are selected as basic evaluation indicators. A comprehensive transportation hub passenger flow risk level assessment framework is constructed from three dimensions: "point-line-surface".
[0023] like Figure 1 As shown, the information data sources in the safety warning information sequence in S100 are the passenger flow density, flow rate, speed, and passenger flow information obtained by any acquisition technology in each monitoring area; Passenger flow information sets form a safety early warning information sequence, which is used to calculate the difference in passenger flow safety risk assessment and analysis at the hub. Each different time period will generate a continuously changing difference supplement sequence, which is used to perform differential supplement calculations on the safety warning information sequence.
[0024] In S200, the congestion of passenger flow in the pedestrian facilities of the passenger station, such as the walking area, waiting area, and escalators, is described. Passenger flow information obtained by arbitrary collection technologies such as passenger flow density, speed, and flow rate in S100 is used to form quantitative indicators. A key passenger flow risk assessment indicator system is constructed, and the "points" of passenger flow risk hubs are formed through the key passenger flow risk assessment indicator system. The density index of waiting areas and escalators is dimensionless and the result is the passenger congestion index, calculated using the following formula: ,in, This represents the result of passenger flow density normalization. For horizontal walking areas and stairs, the congestion index comprehensively considers the passenger flow density index and the passenger flow speed index, and takes the average of the two as the passenger flow congestion index value. The calculation formula is as follows: ,in, This is the result of normalized processing of passenger flow speed.
[0025] Furthermore, the key area passenger flow risk index reflects the risk status of passenger flow aggregation within the hub, while the degree of regional passenger flow congestion describes the spatial distribution of passenger flow. It only reflects the spatial aggregation aspect of passenger flow risk in the hub area; the temporal duration of this congestion should also be considered. That is, the classification of regional passenger flow aggregation risk levels should comprehensively consider both the degree of regional passenger flow congestion and the duration of congestion. The duration of congestion refers to the duration during which the area reaches a certain congestion level within the statistical period. To eliminate the dimension of the indicator, the duration attribute value is normalized to obtain the duration equivalent. The processing method is as follows: , in the formula, For the duration attribute value, It is the duration equivalent, and its value ranges from [0, 1].
[0026] A method for estimating the passenger flow risk index for key areas is proposed, taking into account both the degree and duration of regional passenger congestion. The calculation formula is as follows: ; in, As a key area passenger flow risk index, The maximum risk index has a value of 10. The minimum risk index has a value of 1; The congestion index for key areas This represents the maximum regional congestion index, with a value of 1. The minimum regional congestion index is 0. The value is calculated for the duration of congestion. This represents the maximum value of the congestion duration equivalent, with a value of 1. This is the minimum value equivalent to the duration of congestion, with a value of 0.
[0027] Based on the congestion duration classification and the congestion index classification of different areas, the passenger flow risk index thresholds for different areas of the hub are calculated using the above formula, as shown in Table 1.
[0028] Table 1. Thresholds for Passenger Flow Risk Index at "Points of Interest"
[0029] Example 2, as follows Figures 1-2 As shown in S200, the "points" of multiple passenger flow risk hubs constitute the "line" of passenger flow risk hubs. The passenger flow risk index of the "line" reflects the index of the distribution and magnitude of passenger flow risk of the "points", and reflects the impact of passenger flow aggregation in each "line" area on the safety of passenger flow in the hub. The passenger flow risk hub "line" is obtained by weighting the passenger flow risk index of each key area through the key area weight.
[0030] The weighting method for the travel area is as follows:
[0031] Walking areas: In station concourses and platforms, passenger flow is a major concern. When passageway capacity is limited, the weighting of weighting for walking areas increases. For horizontal walking areas, a weighting factor considering capacity is used; the smaller the capacity, the greater the weighting. In the formula... For single-area passage capacity, Weighting for a single horizontal travel area. .
[0032] Staircases: Staircases connect different floors within a station. Based on their location and function, they are categorized into entrance / exit staircases, connecting staircases, and transfer staircases. Different types of staircases exhibit varying degrees of controllability in the event of passenger flow incidents. For example, transfer staircases are characterized by high usage intensity and frequency, making incidents more likely to exceed expectations and controllable limits. Therefore, the controllability of staircase use is considered as a weighted indicator; the lower the controllability, the greater the weight. The calculation formula is as follows: ; In the formula, For regional controllability, As for the building's weight, .
[0033] Escalators: Escalators have similar physical properties to stairs and also use a weighted index that considers controllability. The calculation formula is as follows: ; In the formula, For escalator weight, .
[0034] Waiting areas have high passenger density and long waiting times, meaning that a larger number of passengers would be affected in the event of a passenger flow incident. Therefore, a weighted index considering the probability of historical risk events is used; the higher the probability of a risk event, the greater the weight. The calculation formula is as follows: ; In the formula, The number of risk events occurring in the region. As the weight of the waiting area, .
[0035] Different types of "points," as components of the hub's flow "line" units, have varying degrees of importance to the hub. The passenger flow risk index for each flow "line" is calculated using a linear weighting method, as shown in the following formula: ; in, Weights are assigned to horizontal walking areas, stairs, escalators, and waiting areas. The passenger flow risk index for the horizontal walking area. For the risk index of passenger flow on the stairs, The escalator passenger flow risk index Passenger flow risk index in waiting area.
[0036] The various areas within the hub "point" are spatially parallel, and their passenger flow risk index classifications conform to the same standards. Therefore, the importance index of different types of areas is used as the weight to calculate the threshold for the hub flow passenger flow risk index classification. The calculation formula is as follows: ; ; In the formula, ; These are the lower and upper limits of the Nth-level passenger flow risk index for the hub "point". These are the lower and upper limits of the Nth level passenger flow risk index for the walking area. These are the lower and upper limits of the passenger flow risk index for escalator level N. These are the lower and upper limits of the Nth level passenger flow risk index for the waiting area. Coefficients for walking areas, stairs, escalators, and waiting areas.
[0037] In passenger flow layout, the walking area has the largest space, the longest possible walking distance, and the most points of conflict between passenger flows, making it the most significant influencing passenger flow risk assessment. The waiting area has a fixed space, and the higher the passenger flow density, the greater the probability of passenger flow risk, thus having the second largest impact on passenger flow risk assessment. Among stairs and escalators, the movement patterns of passengers on stairs are greatly affected by density. Escalators have a relatively stable passenger transport speed, and when passenger flow is large, the capacity of escalators is not significantly affected, thus having the smallest impact on passenger flow risk assessment.
[0038] Therefore, take .
[0039] when , =0.2, When the threshold of the passenger flow risk index is 0.1, the result is the same as the hub passenger flow risk level corresponding to the hub passenger flow risk index, as shown in Table 2: Table 2 Thresholds for Passenger Flow Risk Level Index of Hub "Lines"
[0040] like Figures 1-2As shown in S200, multiple flow "lines" in the hub constitute a "surface" in the passenger flow hub. The "surface" in the passenger flow hub quantitatively characterizes the passenger flow risk level of the hub through the weight of the "lines" in the passenger flow hub. The weight index is selected by the passenger flow size in the hub, and the passenger flow risk level is determined by substituting the weight index into the calculation.
[0041] Hub passenger flow risk assessment, based on the identification of passenger congestion, evaluates the probability of passenger flow risks occurring and the severity of their consequences. Therefore, based on hub passenger flow risk assessment indicators, the importance weight of each traffic flow line within the hub is comprehensively considered to quantitatively characterize the hub's passenger flow risk level. When selecting weighting indicators, the passenger volume carried by each flow line within the hub is comprehensively considered.
[0042] The weighting index of the "surface" is divided into the importance weighting index of the streamline and the importance weighting index. The hub passenger flow risk index is calculated by the importance weighting index of the streamline and the importance weighting index.
[0043] Specifically, the streamline importance weighting indicators include: a. Passenger Flow Inflow: The importance of a passenger flow line in a hub is reflected in the directional passenger flow along the flow line direction. The greater the value, the more important the flow line is in the hub, defined as... .
[0044] b. Passenger Flow Intersection Ratio: Risks are prone to occur at passenger flow intersections. The more intersections there are within a hub, the greater the probability of risk. The passenger flow intersection ratio is the ratio of the number of intersections between incoming and outgoing passenger flow lines to the total number of flow lines, which can be obtained through on-site surveys. Passenger flow organization within a hub should minimize flow line intersections. The number of passenger flow intersections directly affects the overall safety and operational efficiency of the hub and is an important indicator for measuring the distribution of passenger flow risks. The formula is: ; in, For statistical purposes, The ratio of internal passenger flow intersections, To count the number of streamline intersections within a given time period, This represents the total number of passenger flow lines.
[0045] c. Congestion Duration Ratio: The occurrence of flow line congestion risk is often accompanied by hub congestion. The congestion duration ratio measures the impact of congestion risk. Different flow lines within the same hub are interconnected and influence each other. If a large passenger flow event occurs on one flow line, it may affect the passenger flow of adjacent flow lines, thus triggering a chain reaction. The congestion duration ratio is defined as the ratio of the cumulative time of density greater than level three congestion density to the total time. This value can be obtained through on-site video monitoring. The calculation formula is as follows: The higher the value, the more important the flow line is in the hub. ; in, For statistical time The cumulative time value of internal density exceeding the third level of crowding density. For statistical purposes, the time frame is specified.
[0046] Furthermore, the importance weighting index calculation includes three indicators: passenger flow inflow, flow line intersection ratio, and congestion duration, which can reflect the importance of flow lines in the hub from different perspectives. To eliminate the dimensions of each importance index and narrow its range of variation, the importance index is processed as follows: ; ; ; in, This represents the processed value of the k-th indicator, where k = 1, 2, 3.
[0047] Streamline Importance Weighting: The streamline importance index consists of three indicators. Different weight values can be assigned to these three indicators according to different scenarios to calculate the streamline importance weight, reflecting the differences in the importance of streamlines within the hub under different scenarios, and the varying impacts of streamline passenger flow risk on hub passenger flow risk under different scenarios. In daily hub risk monitoring, the streamline importance weight is calculated by weighted summation of the importance of the three indicators, using the following formula: ,in, + + =1, thus obtaining The set of importance weight attribute values for each streamline in the internal hub To ensure that the sum of the importance weights after processing is 1, the weight attribute values are processed as follows: , in the formula, As the importance weight of streamlines, The number of streamlines in the hub; Obtain the set of hub importance weights within the statistical time granularity. .
[0048] The hub passenger flow risk index is a comprehensive descriptive indicator of passenger flow risk within a hub, reflecting the overall level of passenger flow risk. The formula for calculating the hub risk index is as follows: ,in, As a hub passenger flow risk index, As a passenger flow risk index, Importance of streamline.
[0049] The aforementioned classification of passenger flow risk levels for nodes and circulation routes has been established, and the risk index thresholds for each level have been calibrated. When evaluating passenger flow risk at a hub, different circulation routes coexist in parallel within the hub, and the risk index level classification standards are consistent. The calculation formula is as follows: ; ; in, , They are respectively the hubs The lower and upper limits of the passenger flow risk index. =1, 2, 3; , The streamlines are respectively The lower and upper limits of the passenger flow risk index. =1, 2, 3; because The above formula for calculating the passenger flow risk index grading threshold can be simplified to the following formula: ; ; The hub passenger flow risk index corresponds to the hub passenger flow risk level; The passenger flow risk level of a Level 1 hub corresponds to a hub passenger flow risk index of 1.69-4.38; The passenger flow risk level of a Level 2 hub corresponds to a hub passenger flow risk index of 4.38-7.62; The passenger flow risk level of a Level 3 hub corresponds to a hub passenger flow risk index of 7.62-10.00.
[0050] like Figure 3 As shown, the magnitude of passenger flow safety risk at a hub "point" is the result of the combined effect of passenger flow risk at various passenger service facilities and equipment within the hub, including transfer points, exits, entrances, ticket counters, manual ticket checkpoints, and turnstiles, and the areas within which they are located. The passenger flow and status at different pedestrian facilities within the hub reflect its congestion level, indirectly reflecting the local risk level of the hub. Based on passenger movement patterns and facility characteristics, key areas of the hub are divided into the station plaza, entrances, exits, ticket check areas, ticket sales areas, passageways, waiting areas, platforms, and transfer areas.
[0051] Key passenger flow risk comprehensively reflects the overall level of passenger flow risk in all pedestrian facilities within a transportation hub's key areas. As passenger volume gradually increases in key areas, passenger density rises, passenger speed decreases, and congestion occurs when the hub's capacity cannot meet acceptable service levels. Assessing key passenger flow risk requires establishing indicators that comprehensively reflect the degree and spatiotemporal distribution of passenger congestion. The degree of congestion in pedestrian facilities such as walking areas, waiting areas, and escalators / stairs is described using indicators such as passenger density and speed. Furthermore, key passenger flow risk is not only affected by the degree of congestion but also by the duration of congestion and passenger and environmental risks. Taking into account the impact of these factors on key passenger flow risk, a key passenger flow risk assessment indicator system is constructed.
[0052] The degree of passenger congestion in different areas of the hub is mainly described by two indicators: passenger flow speed and passenger flow density, which are given by the following formulas.
[0053] X1. Passenger Flow Density: Passenger flow density represents the ratio of the number of people gathered in a region to the effective area of the region within a certain statistical period. The calculation formula is as follows: ; in, For the statistical period, inner area Passenger flow density, in person / m²; Statistical period, inner area The number of people gathered, in units of people; Passenger gathering area Effective area, unit: m².
[0054] X2. Passenger Flow Speed: The magnitude of passenger flow speed can also reflect the congestion level in different areas of the hub, which is the ratio of the distance traveled by passengers through a certain area to the time taken. The calculation formula is as follows: ; in, The passenger flow speed through a certain area i, in m / s; The lengths are all horizontal, in meters. The elapsed time is measured in seconds (s).
[0055] Example 3: In the S200 calculation of safety assessment analysis difference, a predictive analysis difference is set, and a specific hub difference weight is set at the passenger flow risk hub "point".
[0056] Specifically, a special set point is set in the passenger flow risk hub "point" corresponding to the specific hub difference weight, that is, the "point" most likely to be congested, such as the two ticket gates and security checkpoints closest to the entrance gate in the station entrance. Differential weights are given to these special "points".
[0057] In S100, a specified weight threshold is set. When the number of online passenger tickets reaches a specified value, the specified weight threshold is increased by 1, the weight of the difference between specific hubs is increased by 1, and the predicted analysis difference is increased by 1 when the specified weight threshold and the weight of the difference between specific hubs are increased by 1. The predicted analysis difference is then incorporated into the safety warning information sequence.
[0058] In the 100, the continuously changing difference supplement sequence includes a dynamic update unit, which is used to calculate the safety warning information sequence with mean and standard deviation, set multiple threshold adjustment factors, and dynamically adjust the standard range threshold using the threshold adjustment factors in each iteration.
[0059] The linkage mechanism between the designated weight threshold and the number of online passenger tickets is based on the close relationship between passenger flow and passenger flow risk. The number of online passenger tickets, to a certain extent, reflects the expected passenger flow at a hub. When the number of tickets reaches a certain value, it signifies a significant increase in passenger flow and a corresponding increase in passenger flow risk. Therefore, a designated weight threshold is set and linked to the number of online passenger tickets. When the number of tickets reaches the designated value, the designated weight threshold automatically increments by 1. Simultaneously, the weight of the specific hub difference also increments by 1, further strengthening the assessment of key risk points. The predictive analysis difference is dynamically updated based on changes in the designated weight threshold and the weight of the specific hub difference. Its calculation formula is: Predictive Analysis Difference = Initial Predictive Analysis Difference + Change in Designated Weight Threshold + Change in Weight of Specific Hub Difference. This approach achieves an organic combination of passenger flow prediction and passenger flow risk assessment, improving the foresight and accuracy of risk assessment.
[0060] During each iteration, the standard range threshold is dynamically adjusted based on the calculated mean, standard deviation, and a set threshold adjustment factor. The specific adjustment method is: New standard range threshold = Original standard range threshold × (1 + Threshold adjustment factor). This method ensures that the standard range threshold automatically adjusts as passenger flow information changes, guaranteeing that the risk assessment standards always adapt to the actual situation. The technical solutions described in the above embodiments of this application have at least the following technical effects or advantages: Compared to Embodiment 1 and Embodiment 2, the specific hub difference weighting focuses on the most congested special locations among the passenger flow risk hub "points," such as the ticket gates and security checkpoints closest to the entrance gates at the station entrance. This targeted setting can accurately capture key nodes of passenger flow risk, making risk assessment more focused on areas where problems may actually occur, avoiding errors caused by average assessment, thereby significantly improving the accuracy of risk assessment and providing a strong basis for hub operation managers to formulate targeted prevention and control measures in advance.
[0061] On the other hand, the linkage mechanism between the specified weight threshold and the number of online passenger tickets, as well as the dynamic update of the predictive analysis difference, provides a certain degree of foresight. When the number of online passenger tickets reaches a specified value, the dynamic adjustment of the weight threshold triggers an update of the predictive analysis difference, which is then integrated into the safety early warning information sequence. This allows risk assessment to respond in advance based on potential changes in passenger flow, adjust risk assessment results promptly, and provide early warnings for hub operators to allocate resources and optimize passenger flow organization, effectively preventing passenger congestion and risk events, and ensuring the safe and efficient operation of the hub.
[0062] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A method for assessing passenger flow risk in a comprehensive passenger transport hub, characterized in that, Includes the following steps: S100. Obtain passenger flow safety early warning information from passenger transport hubs, form a safety early warning information sequence, and construct a continuously changing differential supplementary sequence; S200. Construct a safety risk assessment framework by combining the safety early warning information sequence with the variability difference supplementary sequence, and calculate the difference in safety risk assessment and analysis of hub passenger flow. In step S200, a safety risk assessment framework is constructed by quantifying "points", "lines", and "surfaces" at the spatial level of passenger transport hubs. Multiple passenger flow risk hub "points" constitute passenger flow risk hub "lines", and multiple passenger flow risk hub "lines" constitute passenger flow risk hub "surfaces". The difference in hub passenger flow safety risk assessment and analysis is calculated through multiple layers of passenger flow risk hub "surfaces". S300: The passenger flow safety risk assessment and analysis difference of "point", "line" and "area" hub passenger flow is used to determine the passenger flow risk level through passenger flow safety risk assessment method. The passenger flow risk level is "Level 1", "Level 2" and "Level 3".
2. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 1, characterized in that: The information data sources in the safety warning information sequence in S100 are the passenger flow density, flow rate, speed, and passenger flow information obtained by any acquisition technology in each monitoring area; Passenger flow information sets form a safety early warning information sequence, which is used to calculate the difference in passenger flow safety risk assessment and analysis at the hub. Each different time period will generate a continuously changing difference supplement sequence, which is used to perform differential supplement calculations on the safety warning information sequence.
3. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 1, characterized in that: In S200, the congestion of passenger flow in the pedestrian facilities of the passenger station, such as the walking area, waiting area, and escalators, is described. The passenger flow information obtained by arbitrary collection technologies such as passenger flow density, speed, and flow rate in S100 is used to form quantitative indicators. A key passenger flow risk assessment indicator system is constructed, and the "points" of passenger flow risk hubs are formed through the key passenger flow risk assessment indicator system. The density index of waiting areas and escalators is dimensionless and the result is the passenger congestion index, calculated using the following formula: ,in, This represents the result of passenger flow density normalization. For horizontal walking areas and stairs, the congestion index comprehensively considers the passenger flow density index and the passenger flow speed index, and takes the average of the two as the passenger flow congestion index value. The calculation formula is as follows: ,in, This is the result of normalized processing of passenger flow speed.
4. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 3, characterized in that: In the S200, the "points" of multiple passenger flow risk hubs constitute the "line" of passenger flow risk hubs. The passenger flow risk index of the "line" reflects the distribution and magnitude of passenger flow risk at the "points", and reflects the impact of passenger flow aggregation in each "line" area on the safety of passenger flow at the hub. The passenger flow risk hub "line" is obtained by weighting the passenger flow risk index of each key area through the key area weight.
5. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 4, characterized in that: In S200, multiple flow "lines" in the hub constitute a "surface" in the passenger flow hub. The "surface" in the passenger flow hub quantitatively characterizes the passenger flow risk level of the hub through the weight of the "lines" in the passenger flow hub. The weight index is selected by the passenger flow size in the hub, and the passenger flow risk level is determined by substituting the weight index into the calculation.
6. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 5, characterized in that: The weighting index of the "surface" is divided into the importance weighting index of the streamline and the importance weighting index. The hub passenger flow risk index is calculated by the importance weighting index of the streamline and the importance weighting index.
7. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 6, characterized in that: The hub passenger flow risk index corresponds to the hub passenger flow risk level; The passenger flow risk level of a Level 1 hub corresponds to a hub passenger flow risk index of 1.69-4.38; The passenger flow risk level of a Level 2 hub corresponds to a hub passenger flow risk index of 4.38-7.62; The passenger flow risk level of a Level 3 hub corresponds to a hub passenger flow risk index of 7.62-10.
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8. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 1, characterized in that: The S200 calculates the safety assessment analysis difference and sets the predictive analysis difference, and sets specific hub difference weights at the passenger flow risk hub "points".
9. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 8, characterized in that: In S100, a specified weight threshold is set. When the number of online passenger tickets reaches a specified value, the specified weight threshold is increased by 1, the weight of the difference between specific hubs is increased by 1, and the predicted analysis difference is increased by 1 when the specified weight threshold and the weight of the difference between specific hubs are increased by 1. The predicted analysis difference is then incorporated into the safety warning information sequence.
10. The method for assessing passenger flow risk in a comprehensive passenger transport hub according to claim 1, characterized in that: In the 100, the continuously changing difference supplement sequence includes a dynamic update unit, which is used to calculate the safety warning information sequence with mean and standard deviation, set multiple threshold adjustment factors, and dynamically adjust the standard range threshold using the threshold adjustment factors in each iteration.