CN116187762A - Method for identifying bottleneck risk of rail transit junction station based on analog - Google Patents
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Abstract
The invention discloses a bottleneck risk identification method for a rail transit junction station based on analog, which comprises the following steps: s1, determining an urban rail transit transfer junction station, and acquiring basic data; s2, dividing bottlenecks into queuing classes and channel classes according to facility functions and passenger flow characteristics, and establishing a bottleneck point evaluation model of the junction station; s3, building a building environment, building a pedestrian behavior model and a train behavior model and building a train intelligent body and a pedestrian intelligent body model based on the analog software, performing simulation of the passenger flow condition of the rail transit station, operating to determine bottleneck points, and collecting bottleneck evaluation indexes of queuing classes or channels; s4, substituting the bottleneck evaluation index of the queuing class or the bottleneck evaluation index of the channel class into a bottleneck point evaluation model of the junction station according to the types of the bottleneck points, and analyzing the bottleneck risk level. The invention can provide decision basis for urban rail transit station centralized and distributed management and control optimization.
Description
Technical Field
The invention relates to a track traffic junction station, in particular to a bottleneck risk identification method for the track traffic junction station based on acrylic.
Background
As a main mode of urban commute, shopping and recreational travel, subways are important transportation means for urban resident travel. Because the passenger flow bearing pressure is large in the morning and evening peak time and the holiday time of working days, crowds of subway stations are crowded and even trample accidents occur, and a lot of passengers occur in bottleneck positions with space structure changes or crossed streamline, so that serious public safety problems are caused. The distributed risk of the bottleneck in the station is evaluated by adopting a simulation and analysis evaluation mode, a reference basis can be provided for the bottleneck identification and risk monitoring of the rail transit station, and operation suggestions are given.
Disclosure of Invention
The invention aims to: the invention aims to provide an analog-based bottleneck risk identification method for a track traffic junction station, which is used for bottleneck distributed risk assessment of the urban track traffic junction station and is used for obtaining a bottleneck risk grade for identifying bottlenecks through a bottleneck point assessment model.
The technical scheme is as follows: the invention discloses a bottleneck risk identification method for an urban rail transit junction station, which comprises the following steps:
s1, determining an urban rail transit transfer junction station, and acquiring basic data; the basic data comprise station physical environment layout, facility equipment parameters, large passenger flow data, a passenger transport organization scheme, a train running scheme and a schedule;
s2, dividing bottlenecks into queuing classes and channel classes according to facility functions and passenger flow characteristics, and establishing a bottleneck point evaluation model of the junction station;
s3, building a building environment, building a pedestrian behavior model and a train behavior model and building a train intelligent body and a pedestrian intelligent body model based on the analog software, performing simulation of the passenger flow condition of the rail transit station, operating to determine bottleneck points, and collecting bottleneck evaluation indexes of queuing or bottleneck evaluation indexes of channels;
s4, substituting the bottleneck evaluation index of the queuing class or the bottleneck evaluation index of the channel class into a bottleneck point evaluation model of the junction station according to the types of the bottleneck points, and analyzing the bottleneck risk level.
Further, in step S2, the specific implementation steps for establishing the bottleneck risk evaluation index system of the hub station are as follows:
s21, analyzing that the types of the bottlenecks of the rail transit stations are queuing types or channel types, and determining bottleneck risk level evaluation indexes according to common people flow risk control points by adopting an operation risk condition evaluation method;
s22, according to the relation between each index value and the distributed risk, the risk grade is expressed by high, medium, general and low, and the corresponding security scores are sequentially 1-5 points, so that the risk grade is obtained; and establishing a relationship between the risk evaluation score and the bottleneck point risk level according to the relationship between the risk state and index scores of various bottlenecks in the actual engineering.
Further, bottleneck evaluation indexes of the queuing class are:
average queuing length: the queuing system queues the average value of the passenger captain passing through a certain passing facility, and can reflect the frequent degree of personnel exposure to dangerous environments;
people stream density: refers to the number of passengers per unit area, the unit is p/m 2 Can reflect the possible consequences of accidents;
panic degree: the degree of speed reduction in the panic state of crowd crowding can reflect the possibility of accident occurrence;
the bottleneck evaluation indexes of the channel class are as follows:
number of intersecting streamline groups: the number of passenger flow groups communicated with the bottleneck point can reflect the possibility L of accident occurrence;
load factor: the ratio of the number of detained people to the number of passers can reflect the frequency of exposure of the personnel to dangerous environments;
regional passenger flow density: refers to the number of passengers per unit area, the unit is p/m 2 Can reflect the possible consequences of accidents. Further, according to the types of the bottleneck points, a bottleneck point evaluation model is established, and the expression is as follows:
D RA1 ＝L 1 ×E 1 ×C s1
wherein D is RA1 Representing a risk assessment score; c (C) s1 Representing regional passenger flow density;
when the bottleneck type is queuing type, L 1 For panic degree, E 1 Representing the average queuing length;
when the bottleneck type is channel type, L 1 For the number of crossed streamline groups E 1 Indicating the load factor.
Further, the calculation expression of the load factor is as follows:
P＝N s /N T
wherein P is the people stream load rate; n (N) s The number of people is the number of people in retention; n (N) T People are people with the flow rate within the specific passing time; t is total evacuation time, s; t (T) 0 S is the moment when crowd retention begins to occur; f (f) i (t) is the crowd flow coefficient at the moment t of the ith branch inlet of the channel, and is people/m.s; f (t) is the crowd flow coefficient at the time t of the channel outlet, and is people/m.s; b (B) i (t) is the width of the people stream at the moment t of i branch inlets, m; b (t) is the width of the people stream at the moment of the channel outlet t, m is usually replaced by the outlet width; q is the number of branch entries.
Further, in step S3, determining a flow chart of pedestrian behavior in the station through the station environment model and the passenger transport organization scheme, establishing a pedestrian behavior model, and describing pedestrian behavior characteristics through simulation parameter setting;
and acquiring the arrival time and the station stay time of the train according to the train schedule, and establishing a train behavior model.
Compared with the prior art, the invention has the following remarkable effects:
1. according to the invention, a station physical environment model is established through station basic data; then, a passenger behavior model and a train operation model are established through a station model and a passenger transport organization scheme, and according to the judgment basis of different types of bottlenecks and the risk evaluation method of reference operation conditions, risk calculation formulas of the different types of bottlenecks are provided, the risk grade of the identified bottlenecks is obtained, and a reference basis is provided for passenger transport organization evaluation of subway transfer junction stations;
2. the urban rail transit junction bottleneck risk identification method based on the acrylic and operation risk evaluation method can be used for bottleneck distributed risk evaluation of urban rail transit transfer junction stations, and decision basis is provided for urban rail transit station distributed management and control optimization.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a schematic diagram of a subway bottleneck evaluation index system;
FIG. 3 is a simulated running diagram of a adult mule-horse city station;
fig. 4 is a logic diagram of a mule Ma Shi station analog simulation model portion.
Detailed Description
The invention is described in further detail below with reference to the drawings and the detailed description.
The invention relates to a bottleneck identification method for urban rail transit junction sites, which is characterized in that a simulation model of an urban rail transit station is built, so that a bottleneck risk evaluation system based on an operation condition risk evaluation method is built to evaluate the risks of the bottlenecks in the station, and finally, the distributed risks of the whole station are determined and precautionary measures are formulated. As shown in fig. 1, the specific steps of implementing the bottleneck identification and evaluation method of the urban rail transit junction station based on acrylic are as follows:
step 1, determining a subway transfer hub and acquiring basic data
The basic data comprise station environment layout, facility equipment parameters, large passenger flow condition passenger flow data, passenger transport organization schemes, train running schemes and train schedules.
Step 2, establishing a bottleneck risk evaluation index system of the hub station
The difficulty of the passenger transport organization of the rail transit transfer hub station is that the diversity of passenger flows and the layout complexity of facility equipment in the station are caused, and meanwhile, the establishment of bottleneck identification indexes needs to take sensitivity, reliability, convenience, intuitiveness and economy principles into consideration, so that different indexes are selected for evaluation on different types of bottlenecks. As shown in fig. 2, bottlenecks are classified into two categories according to facility functions and passenger flow characteristics: queuing classes and channel classes.
Queuing: the queuing facilities in the hub mainly comprise ticket selling windows, security inspection and ticket gate machines for entering and exiting stations, and if the bottlenecks are in the areas, the queuing facilities belong to queuing bottlenecks.
Channel class: various traffic service nodes are connected in the station, and a distributed network facility such as a channel, a station hall and the like which pass through in the horizontal or vertical direction is provided for passengers. If the bottleneck is located in these areas, it belongs to the channel class bottleneck.
Risk evaluation of bottleneck refers to LEC evaluation method (operation risk condition evaluation method) with risk value D RA The expression of (2) is as follows:
D RA ＝L×E s ×C s (1)
wherein L represents the possibility of accident occurrence, E s Indicating how frequently personnel are exposed to hazardous environments, C s Indicating the consequences of an accident.
The specific implementation steps are as follows:
step 21, determining bottleneck evaluation influence factors
The evaluation system of different types of bottlenecks comprises the following indexes:
queuing:
a1, average queuing length: the queuing system is queuing an average of passenger captain passing through a pass through facility. Intuitively reflecting the intensity of passenger flow congestion at bottleneck facilities, reflecting the degree of the current state exceeding the normal load, namely reflecting the frequent degree of personnel exposure to dangerous environments, and being similar to E in the formula (1) s 。
A2, people stream density: refers to the number of passengers per unit area, the unit is p/m 2 . The people flow density of the evaluation index refers to a predicted people flow density value obtained according to subway station evacuation simulation. Visual display of crowd gathering and distributing results can reflect possible consequences of accidents, and is similar to C in the formula (1) s 。
A3, panic degree: the degree of speed reduction in the panic state of crowd crowding reflects the degree of passenger flow congestion at bottleneck facilities, can represent the possibility of accident occurrence, is represented by n, and is similar to L in the formula (1).
Crowd desired speed is affected by crowd density k, so crowd desired speed can be expressed as 0.76f (k), where the coefficient 0.76 is found by simulation testing, f (k) is a speed-density relationship function. The crowd average speed is the average of the section speeds through the queuing facility.
Channel class:
b1, number of crossed streamline groups: refers to the number of groups of passenger flows communicating with the bottleneck point. The goal of the pedestrian walking in the subway station is determined, so that the number of the crossed streamline groups of the bottleneck point can be determined by analyzing the streamline network through the layout in the station. The number of intersecting streamline groups can characterize the likelihood of causing a distributed problem, i.e., can represent the likelihood of an accident occurrence, like L in equation (1).
B2, load factor: refers to the ratio of the number of detainers to the number of passes. The intensity of the bottleneck area exceeding the normal load is represented from the traffic angle, namely the frequency of exposing personnel to dangerous environments can be reflected, and the bottleneck area is similar to E in the formula (1).
The calculation formula of the load factor:
P ＝ N s /N T (3)
wherein P is the people stream load rate; n (N) s The number of people is the number of people in retention; n (N) T For the traffic of people in a specific passing time, according to different channel properties, the passing time of the horizontal channel is 10s, and the passing time of each layer of stairs is 30s; t is total evacuation time, s; t (T) 0 S is the moment when crowd retention begins to occur; f (f) i (t) is the crowd flow coefficient at the moment t of the ith branch inlet of the channel, and is people/m.s; f (t) is the crowd flow coefficient at the time t of the channel outlet, and is people/m.s; b (B) i (t) is the width of the people stream at the moment t of i branch inlets, m; b (t) is the width of the people stream at the moment of the channel outlet t, m is usually replaced by the outlet width; q is the number of branch entries.
B3, regional passenger flow density: refer to unit areaThe number of passengers on the floor is p/m 2 . The people flow density of the evaluation index refers to a predicted people flow density value obtained according to subway station evacuation simulation. Visual display of crowd gathering and distributing results, namely reflecting possible consequences of accidents, similar to C in the formula (1) s 。
In summary, according to the types of the bottleneck points, a bottleneck point evaluation model is established, and the expression is as follows:
D RA1 ＝L 1 ×E s1 ×C s1 (5)
wherein:
D RA1 representing a risk assessment score;
L 1 for the number of crossed streamline groups (when the bottleneck type is channel class), panic degree (when the bottleneck type is queuing class);
C s1 representing regional passenger flow density;
E s1 representing average queuing length (when bottleneck type is queuing class), load rate (when bottleneck type is channel class)
Step 22, bottleneck point scattered risk classification
According to the relation between each index value and distributed risks, the risk grades are expressed by extremely high, relatively high, medium, general and low, the corresponding security scores are sequentially 1-5 points to obtain the risk grades, so that the risk grades corresponding to different index values and the scores thereof can be determined, and as shown in table 1, the risk evaluation score D of each bottleneck is obtained according to the formula (5) RA1 。
Table 1 bottleneck point influencing factor risk status grading and scoring
| Risk status | Score of | Regional passenger flow density | Number of intersecting streamline groups | Load factor | Average queuing length | Panic degree |
| Extremely high | 1 | >2.31 | >6 | >200％ | A | 0.6～1.0 |
| Higher height | 2 | 2.00～2.31 | 5～6 | 170％～200％ | B | 0.4～0.6 |
| Medium and medium | 3 | 1.85～2.00 | 3～4 | 130％～170％ | C | 0.2～0.4 |
| In general | 4 | 1.69～1.85 | 2 | 100％～130％ | D | 0～0.2 |
| Low and low | 5 | Without any means for | <2 | <100％ | E | 0 |
A. B, C, D, E, obtaining: the subway station actual or simulation data is divided into five classes by adopting an unsupervised clustering method, a clustering center is obtained, and intervals of each class are obtained.
Determining a risk evaluation score D according to the relation between the risk state and index scores of various bottlenecks in actual engineering RA1 The relationship between the value of (a) and the risk level of the bottleneck point. As shown in table 2, the risk level may be divided into:
first order (red): extremely dangerous, requiring layout or passenger organization schemes improvement and emergency plans;
secondary (orange): high risk, need to specify improvement strategies;
three-stage (yellow): significant hazards, need to take precautions;
fourth order (blue): general danger, need to strengthen the management;
five-stage (green): the safety is basically high and can be ignored;
TABLE 2 Risk assessment score and Risk grading for Security
| Risk level | Risk assessment score D RA1 | Risk status |
| Primary (Red) | 1～6 | Extremely dangerous, need to be rectified and made emergency plans |
| Second grade (orange) | 7～12 | High risk, need to develop improved strategies |
| Three-stage (yellow) | 13～45 | Significant risk, need to take precautions |
| Four-stage (blue) | 46～80 | General hazards, need to be managed with enhanced |
| Five-stage (Green) | 81～125 | Is basically safe and can be ignored |
Step 3, passenger flow simulation is carried out based on analog
The simulation of passenger flow by adopting analog software is required to be carried out strictly according to the establishment flow of a simulation model, and mainly comprises building environment construction, building of passenger behavior and train operation logic, building of a train intelligent body and pedestrian intelligent body model, determining bottleneck points of simulation operation and collecting data. The specific implementation steps are as follows:
step 31, building a building environment
The physical environment layout of the station is a CAD drawing of station arrangement, in this embodiment, a station in city of mule and mare is selected as an example, as shown in fig. 3, a service area for passengers is determined according to the CAD drawing of station arrangement, and the station environment is depicted by using a space marking module in an analog pedestrian library, so as to construct a station environment model. And setting module attributes after finishing station environment depiction in software, and setting specific characteristics of each link in an attribute interface, including queuing strategies, passenger arrival bases and passenger waiting characteristics.
Step 32, building passenger behavior and train operation logic
And determining a behavior flow chart of pedestrians at the station through the station environment model and the passenger transport organization scheme, establishing a pedestrian behavior model, and describing pedestrian behavior characteristics through simulation parameter setting. The pedestrian behavior model is mainly characterized in that the logic behavior of pedestrians at a station is established, a pedestrian behavior flow chart is determined according to a passenger transport organization scheme of the station, the pedestrian behavior flow chart is converted into a pedestrian logic chart which can be identified by software, three basic pedestrian behavior logic charts of outbound, inbound and transfer are established through analog software, and the pedestrian behavior model is established.
And acquiring the stop time and the stop time of the train through the train schedule, and establishing a train behavior model.
Step 33, building a train agent and pedestrian agent model
The intelligent modeling function of the analog software can realize the encapsulation of the entity function, and the modeling process is simplified. While module functions can be extended through Java programming. The intelligent body model in the embodiment comprises a security check module, a gate module, a ticket purchasing module, a passenger selecting waiting area module and a passenger getting on and off module, and a schedule module is established through the train intelligent body model.
As shown in fig. 4, which is a passenger in-out module packaged by an analog.
Step 34, simulation run determines bottleneck point and gathers data
After the passenger flow volume, the path selection proportion and the facility equipment passing time which are obtained by collecting, sorting and field investigation are imported into a model, the people flow condition in the simulated station is primarily identified, and the possible bottleneck point position in the area is obtained. Acquiring the people flow parameters at the points by utilizing functional modules in analog to obtain index data of bottleneck points within 6 minutes after trains arrive at the subway station, and taking the fact that the people flow and the pedestrian traffic conditions in the subway station are affected by various factors into consideration, so that 50 times of simulation are carried out on the people flow conditions of the subway station, 50 groups of data are obtained for each investigation point, and then 50 times of simulation results are averaged to obtain simulation data of each point: the number of cross-flow lines (when the bottleneck type is a channel class) or panic (when the bottleneck type is a queuing class), regional traffic density, average queuing length (when the bottleneck type is a queuing class), or load factor (when the bottleneck type is a channel class).
Step 4, substituting the substitution related data obtained by simulation into a bottleneck point evaluation model to obtain an evaluation result
And substituting the simulated data into a bottleneck point evaluation model for analysis according to the types of the bottleneck points.
According to the risk evaluation score D RA1 And obtaining the risk grade corresponding to each bottleneck point, obtaining the risk state of the bottleneck point, and analyzing the improvement measures according to the relationship of the risk grades of the bottleneck points.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (6)
1. The bottleneck risk identification method for the urban rail transit junction station based on the acrylic is characterized by comprising the following steps of:
s1, determining an urban rail transit transfer junction station, and acquiring basic data; the basic data comprise station physical environment layout, facility equipment parameters, large passenger flow data, a passenger transport organization scheme, a train running scheme and a schedule;
s2, dividing bottlenecks into queuing classes and channel classes according to facility functions and passenger flow characteristics, and establishing a bottleneck point evaluation model of the junction station;
s3, building a building environment, building a pedestrian behavior model and a train behavior model and building a train intelligent body and a pedestrian intelligent body model based on the analog software, performing simulation of the passenger flow condition of the rail transit station, operating to determine bottleneck points, and collecting bottleneck evaluation indexes of queuing or bottleneck evaluation indexes of channels;
s4, substituting the bottleneck evaluation index of the queuing class or the bottleneck evaluation index of the channel class into a bottleneck point evaluation model of the junction station according to the types of the bottleneck points, and analyzing the bottleneck risk level.
2. The urban rail transit junction station bottleneck risk identification method based on acrylic according to claim 1, wherein in step S2, the specific implementation steps of establishing a junction station bottleneck risk evaluation index system are as follows:
s21, analyzing that the types of the bottlenecks of the rail transit stations are queuing types or channel types, and determining bottleneck risk level evaluation indexes according to common people flow risk control points by adopting an operation risk condition evaluation method;
s22, according to the relation between each index value and the distributed risk, the risk grade is expressed by high, medium, general and low, and the corresponding security scores are sequentially 1-5 points, so that the risk grade is obtained; and establishing a relationship between the risk evaluation score and the bottleneck point risk level according to the relationship between the risk state and index scores of various bottlenecks in the actual engineering.
3. The bottleneck risk identification method for the urban rail transit junction station based on acrylic according to claim 2, wherein the bottleneck evaluation indexes of the queuing class are as follows:
average queuing length: the queuing system queues the average value of the passenger captain passing through a certain passing facility, and can reflect the frequent degree of personnel exposure to dangerous environments;
people stream density: refers to the number of passengers in a unit area, singlyThe bits are p/m 2 Can reflect the possible consequences of accidents;
panic degree: the degree of speed reduction in the panic state of crowd crowding can reflect the possibility of accident occurrence;
the bottleneck evaluation indexes of the channel class are as follows:
number of intersecting streamline groups: the number of passenger flow groups communicated with the bottleneck point can reflect the possibility L of accident occurrence;
load factor: the ratio of the number of detained people to the number of passers can reflect the frequency of exposure of the personnel to dangerous environments;
regional passenger flow density: refers to the number of passengers per unit area, the unit is p/m 2 Can reflect the possible consequences of accidents.
4. The bottleneck risk identification method for the urban rail transit junction station based on the acrylic according to claim 3, wherein a bottleneck point evaluation model is established according to the types of bottleneck points, and the expression is as follows:
D RA1 ＝L 1 ×E 1 ×C s1
wherein D is RA1 Representing a risk assessment score; c (C) s1 Representing regional passenger flow density;
when the bottleneck type is queuing type, L 1 For panic degree, E 1 Representing the average queuing length;
when the bottleneck type is channel type, L 1 For the number of crossed streamline groups E 1 Indicating the load factor.
5. The bottleneck risk identification method for the urban rail transit junction station based on acrylic according to claim 3, wherein the calculation expression of the load factor is as follows:
P＝N s /N T
wherein P isA people stream load rate; n (N) s The number of people is the number of people in retention; n (N) T People are people with the flow rate within the specific passing time; t is total evacuation time, s; t (T) 0 S is the moment when crowd retention begins to occur; f (f) i (t) is the crowd flow coefficient at the moment t of the ith branch inlet of the channel, and is people/m.s; f (t) is the crowd flow coefficient at the time t of the channel outlet, and is people/m.s; b (B) i (t) is the width of the people stream at the moment t of i branch inlets, m; b (t) is the width of the people stream at the moment of the channel outlet t, m is usually replaced by the outlet width; q is the number of branch entries.
6. The bottleneck risk identification method for the urban rail transit junction station based on the acrylic according to claim 1, wherein in the step S3, a behavior flow chart of pedestrians at a station is determined through a station environment model and a passenger transport organization scheme, a pedestrian behavior model is established, and pedestrian behavior characteristics are described through simulation parameter setting;
and acquiring the arrival time and the station stay time of the train according to the train schedule, and establishing a train behavior model.
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| CN117407952A (en) * | 2023-10-12 | 2024-01-16 | 广州地铁设计研究院股份有限公司 | Shunting method for three-line transfer of subway same station |
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