A method for dynamically adjusting and arranging internal isolation devices of public transportation hubs

Abstract

The present invention discloses a method for dynamically adjusting and arranging isolation devices inside public transportation hubs, so as to achieve the addition and adjustment of facilities in key public transportation hubs during major public health events, maintain effective spacing, and avoid excessive crowds. The method includes: simulating and modeling the crowd flow in key public transportation hubs through an improved social force model, with the objective function of minimizing the crowd density per unit area within a fixed time; encoding the position of the isolation device to generate a solution space; initializing the iterative population according to a random seed, using the improved social force model to simulate and calculate the initial objective function value, and constructing a reference set according to the principles of optimality and dispersion; using a hybrid operator to search the solution space, recalculating the objective function value of the new solution, and replacing individuals in the reference set according to probability. Repeated iteration until the termination condition is met, stop iteration, and output the optimal individual.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent transportation and public health management, and in particular to a method for dynamically adjusting and arranging internal isolation devices of a public transportation hub. Background Art

[0002] Public transportation hubs are important nodes where public transportation passenger flows converge. Ensuring passenger safety and efficient travel is the focus of social attention. The density of passenger flow inside transportation hubs is highly concentrated, and various routes are intertwined, which highlights the problem of pedestrian path control. Distance control is particularly important inside public transportation hubs. The reasonable placement of facilities in public transportation hubs will effectively achieve distance control for pedestrians.

[0003] Pedestrian simulation, such as social force models and cellular automata, has been studied in areas such as pedestrian control in public transportation hubs, and reasonable strategies have been given. However, previous methods mainly focus on pedestrian evacuation in emergency scenarios, and the adjustment parameters of the model are also a description of pedestrian behavior in emergency situations. Compared with emergency scenarios, the psychological panic and group behavior of pedestrians in epidemic prevention and control are different: in the face of the epidemic, pedestrians will not have a sense of panic about specific sources of danger, but are more likely to panic about others, so it is less likely to produce group gathering behavior.

[0004] Therefore, it is necessary to provide a method for placing facilities in public transportation hubs that takes into account pedestrian path selection in non-emergency situations from an epidemic perspective, maintain the necessary social distance between pedestrians, and reduce the risk of infection for passengers when riding public transportation. Summary of the invention

[0005] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method for dynamically adjusting and arranging internal isolation devices in public transportation hubs. By establishing a simulation optimization model based on an improved social force model and providing a heuristic method based on a swarm optimization algorithm for solving the problem, the path selection of pedestrians in non-emergency situations is constrained through the placement of facilities, and the necessary social distance is maintained to provide protection for public health safety.

[0006] The objective of the present invention is achieved through the following technical solutions:

[0007] A method for dynamically adjusting and arranging internal isolation devices of a public transportation hub comprises the following steps:

[0008] Step 1: Obtain the building structure and passenger flow information in the public transportation hub to generate an initial passenger flow scene model;

[0009] Step 2: Encode the isolation devices in the public transportation hub, generate the solution space, and generate the initial group according to the random principle;

[0010] Step 3: Introduce alienation force into the traditional social force model to construct an improved social force model, perform numerical simulation on the scene corresponding to the individual according to the improved social force model, calculate the objective function of each individual in the group (the initial group is equal to the initial solution, and the group here means the solution space), and use the optimal criterion and the dispersion criterion to construct a reference set, wherein the individual is a kind of isolation device placement scheme in the initial group, and the scene corresponding to the individual has been modeled when the initialization group is generated;

[0011] Step 4: Use the crossover operator to perform crossover operations on individuals in the group;

[0012] Step 5: Recalculate the individual objective function and update the reference set according to the probability;

[0013] Step 6: Repeat the iteration until the termination condition is met, then the iteration stops and the optimal isolation device placement plan is output;

[0014] Furthermore, the building structure information includes: a public transportation hub waiting hall, an entrance, and a boarding gate.

[0015] Furthermore, the pedestrian flow information includes pedestrian number, pedestrian mass, pedestrian radius, expected speed, pedestrian position and pedestrian acceleration information.

[0016] Furthermore, the placement of the isolation device in the numerical simulation is obtained by discretizing the horizontal plane of the building; specifically, the plane of the public transportation hub is divided into grids of equal size, and the divided grids are numbered in sequence. If there is an isolation device in the grid, then x i =1 otherwise 0, and arranged into a list from small to large according to i to form a representation of the solution.

[0017] Furthermore, the crossover operator selects any two individuals x and x' in the population to form a binary pair (x, x') to generate a new individual x new operation.

[0018] Furthermore, the pedestrian activities in public transportation hubs are simulated through the improved social force model, and the peak value of pedestrian density per unit area in the numerical simulation is calculated as the individual fitness value.

[0019] Furthermore, in the improved social force model, the forces acting on pedestrians include self-driving force, force between people, force between people and boundaries, and alienation force.

[0020] The present invention also provides a system for dynamically adjusting and arranging internal isolation devices of a public transportation hub, including a simulation module, a swarm optimization algorithm module and the following submodules:

[0021] a) Simulation-initialization submodule: used to build a simulation scene of a public transportation hub and initialize pedestrians in the public transportation hub;

[0022] b) Simulation-improved social force submodule: used to build an improved social force model to simulate the walking behavior of pedestrians in public transportation hubs;

[0023] c) Group optimization algorithm - statistical submodule; used to calculate the density of people flow per unit area within a given time and output the density peak value;

[0024] d) Population optimization algorithm-initialization submodule; used to generate an initialization population according to a random seed;

[0025] e) Population optimization algorithm-crossover operator module; used to perform crossover operations on individuals in the population;

[0026] f) Swarm Optimization Algorithm - Selection Update Module; used to calculate the objective function of individuals in the population based on the results of the simulation module and update the reference set based on the probability.

[0027] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for dynamically adjusting and arranging internal isolation devices of a public transportation hub are implemented.

[0028] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for dynamically adjusting and arranging internal isolation devices of a public transportation hub.

[0029] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0030] 1. Introducing alienation forces into the social force model can more accurately describe pedestrian path selection behavior in epidemic scenarios than existing models, providing guidance for decision-making. In addition, due to the uneven temporal and spatial distribution of passenger flow in public transportation hubs, dynamically adjusting the placement of isolation devices can make better use of isolation devices and achieve the purpose of precise control of passenger flow compared to traditional placement methods.

[0031] 2. The method of the present invention achieves the goal of maintaining necessary social distance between pedestrians and reducing the risk of infection for passengers when taking public transportation by placing facilities in public transportation hubs that consider pedestrians' path selection in non-emergency situations from the perspective of the epidemic. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic plan view of a public transportation hub of the present invention.

[0033] Figure 2 This is the interface diagram of the simulation module of the present invention.

[0034] Figure 3 It is a schematic diagram of the method flow of the present invention.

[0035] Figure 4 A schematic structural diagram of the isolation device involved in the present invention. DETAILED DESCRIPTION

[0036] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0037] A dynamically adjusted internal isolation device for a public transportation hub and a method for arranging the same are provided in the present invention. Figure 3 , including the following steps:

[0038] Step 1: Obtain the building structure and passenger flow information in the public transportation hub and generate an initial passenger flow scene model, where:

[0039] The building structure information in the public transportation hub specifically refers to the waiting hall, entrance, and boarding gate, and does not include the facilities within the station; the pedestrian flow information includes the pedestrian number, pedestrian mass, pedestrian radius, expected speed, pedestrian position, and pedestrian acceleration information. The pedestrian flow information variable is randomly generated within a given numerical range.

[0040] Step 2: Chromosome encoding of the site isolation device is performed, and an initial population is generated based on a random principle.

[0041] The location of the isolation device is obtained by discretizing the horizontal plane of the building: Specifically, the plane of the public transportation hub is divided into grids of equal size, and the divided grids are numbered once. If there is a facility in the grid, x ij = 1 otherwise 0, and arranged in a list from small to large according to i, forming a representation of the solution; for example Figure 1 The relationship between the public transportation hub floor plan and the equipment placement shown can be encoded into individuals as shown in Table 1. The initial population is formed by initializing individuals by generating a random number between [0, 1] in each grid (if the random number is less than or equal to 0.5, it is set to 0, otherwise it is set to 1).

[0042] Table 1 Solution representation

[0043] 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0

[0044] Step 3: numerically simulate individuals according to the improved social force model, calculate the individual objective function value, and construct a reference set according to the optimal and decentralized principles;

[0045] The traditional social force model takes into account the self-driving force, the force between people, and the force between people and boundaries. The path choice of pedestrians is the result of the acceleration generated by the combined force. However, in the context of the epidemic, pedestrians will behave in a way that alienates people for the purpose of self-protection. This method takes this alienation phenomenon into account and introduces the alienation force f into the social force model. es :

[0046]

[0047] Among them, A i , B i is the strength and range of force, μ ij is the coefficient [-1,0] representing the degree of alienation, r ij represents the sum of the radii of pedestrian i and pedestrian j, d ij represents the distance between pedestrian i and pedestrian j, k is a constant coefficient, n ij represents the unit vector from pedestrian j to pedestrian i.

[0048] The result of step 2, i.e. the location information of the facility, is input into the simulation module to generate force from the boundary on pedestrians. The simulation-statistics submodule will calculate the pedestrian flow density per unit area within the simulation time. After the simulation is finished, the peak value of the unit flow density within the simulation time is output. The individuals with the minimum function value b1 are selected and put into the reference set, and then the individuals with the maximum dispersion b2 are selected and put into the reference set;

[0049] Step 4: Randomly group the individuals in the initial population into pairs (x, x') for crossover operation; the crossover operator can be divided into row crossover and column crossover of the solution matrix. In step 4, two crossover strategies are randomly used to obtain a new solution x new , and release the new release into the simulation module to obtain the individual objective function value;

[0050] Step 5: Accept the updated reference set according to probability;

[0051] In order to ensure the breadth of the search and avoid being limited to the local optimum during the iteration process, this method uses The probability of accepting inferior solutions in the reference set; where f(x new ) represents the average flow density under the new isolation device placement, f(x b ) represents the average crowd density under the current placement of isolation devices, and n is the number of iterations.

[0052] Step 6. Repeat the iteration until the preset maximum number of iterations is reached or the preset maximum number of iterations without updates is reached, stop the iteration, and output the saved optimal solution. The optimal solution at this time is the optimal public transportation hub isolation device placement plan obtained by optimization.

[0053] See Figure 4 The isolation device specifically includes an LED information bulletin board 1, an isolation device body 2, and a base 3. The height of the isolation device is 1.037m, the side length of the base is 43.7cm, and there are 4 fixed universal wheels under the base for easy movement. The LED information bulletin board can play epidemic information warnings to assist in crowd control.

[0054] The simulation module and the swarm optimization algorithm block of the present invention are both implemented in Python. Figure 2 ,The simulation scene and visualization are realized through the graphical user interface class, which contains the configuration of simulation visualization window, color and other visualization information. Pedestrians and crowds in the public transportation hub are realized by constructing "people" and "crowd" classes respectively. The "people" class contains pedestrian number, pedestrian quality, pedestrian radius, expected speed, current position, current speed and current acceleration attributes; "crowd" contains methods to control pedestrian movement. When the system simulation time ends or all pedestrians reach their destination, the simulation module terminates and is output by the simulation-statistics submodule.

[0055] The swarm optimization algorithm is implemented through the "swarm optimization" class, which includes three methods: initializing the swarm, hybridization, and updating the reference set; it is composed of three properties: swarm, maximum number of iterations, and longest iteration time; the individual is composed of two properties including the solution matrix and the objective function, and a method to copy an individual.

[0056] Finally, it should be pointed out that the above examples are only used to illustrate the calculation process of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above examples, a person skilled in the art should understand that the calculation process described in the above examples can still be modified, or some parameters can be replaced by equivalents, and these modifications or replacements do not make the essence of the corresponding calculation method deviate from the spirit and scope of the calculation method of the present invention.

[0057] The present invention is not limited to the embodiments described above. The above description of the specific embodiments is intended to describe and illustrate the technical solution of the present invention. The above specific embodiments are merely illustrative and not restrictive. Without departing from the scope of the present invention and the scope of protection of the claims, a person of ordinary skill in the art can also make many forms of specific changes under the guidance of the present invention, which all fall within the scope of protection of the present invention.

Claims

1. A method for dynamically adjusting and arranging internal isolation devices of a public transportation hub, characterized in that: The steps include: Step 1: Obtain the building structure and passenger flow information in the public transportation hub to generate an initial passenger flow scene model; Step 2: Encode the isolation devices in the public transportation hub, generate the solution space, and generate the initial group according to the random principle; Step 3: Introduce alienation force into the traditional social force model to construct an improved social force model, perform numerical simulation on the scenario corresponding to the individual according to the improved social force model, calculate the objective function of each individual in the group, and construct a reference set using the optimal criterion and the dispersion criterion, wherein the individual is an isolation device placement scheme in the initial group; alienation force f es It is expressed as: Among them, A i , B i is the strength and range of force, μ ij is the coefficient [-1,0] representing the degree of alienation, r ij represents the sum of the radii of pedestrian i and pedestrian j, d ij represents the distance between pedestrian i and pedestrian j, k is a constant coefficient, n ij represents the unit vector from pedestrian j to pedestrian i; Step 4: Use the crossover operator to perform crossover operations on individuals in the group; Step 5: Recalculate the individual objective function and update the reference set according to the probability; Step 6: Repeat the iteration until the termination condition is met, then the iteration stops and the optimal isolation device placement plan is output.

2. A method for dynamically adjusting and arranging internal isolation devices of a public transportation hub according to claim 1, characterized in that: Building structure information includes: public transportation hub waiting hall, entrance and boarding gate.

3. A method for dynamically adjusting and arranging internal isolation devices of a public transportation hub according to claim 1, characterized in that: The pedestrian flow information includes the pedestrian number, pedestrian mass, pedestrian radius, expected speed, pedestrian position and pedestrian acceleration information.

4. A method for dynamically adjusting and arranging internal isolation devices of a public transportation hub according to claim 1, characterized in that: In numerical simulation, the placement of isolation devices is obtained by discretizing the horizontal plane of the building; Specifically, the public transportation hub plane is divided into equal-sized grids, and the divided grids are numbered in sequence. If there is an isolation device in the grid, x i =1 otherwise 0, and arranged into a list from small to large according to i to form a representation of the solution.

5. The method for dynamically adjusting and arranging internal isolation devices of a public transportation hub according to claim 1, characterized in that: The crossover operator is to select any two individuals x and x' in the population to form a binary pair (x, x') to generate a new individual x new operation.

6. A method for dynamically adjusting and arranging internal isolation devices of a public transportation hub according to claim 1, characterized in that: The pedestrian activities in public transportation hubs are simulated by using an improved social force model, and the peak density of pedestrian flow per unit area in the numerical simulation is calculated as the individual fitness value.

7. A method for dynamically adjusting and arranging internal isolation devices of a public transportation hub according to claim 1, characterized in that: In the improved social force model, the forces acting on pedestrians include self-driving force, force between people, force between people and boundaries, and alienation force.

8. A system for dynamically adjusting and arranging internal isolation devices of a public transportation hub, based on the method for dynamically adjusting and arranging internal isolation devices of a public transportation hub according to claim 1, characterized in that: It includes simulation module, swarm optimization algorithm module and the following sub-modules: a) Simulation-initialization submodule: used to build a simulation scene of a public transportation hub and initialize pedestrians in the public transportation hub; b) Simulation-improvement of social force submodule; Used to build an improved social force model to simulate pedestrian walking behavior in public transportation hubs; c) Group optimization algorithm - statistical submodule; used to calculate the density of people flow per unit area within a given time and output the density peak value; d) Population optimization algorithm-initialization submodule; used to generate an initialization population according to a random seed; e) Population optimization algorithm-crossover operator module; used to perform crossover operations on individuals in the population; f) Swarm optimization algorithm - selection of update modules; It is used to calculate the objective function of individuals in the population based on the simulation module results and update the reference set based on the probability.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for dynamically adjusting and arranging internal isolation devices of a public transportation hub as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for dynamically adjusting and arranging internal isolation devices of a public transportation hub as described in any one of claims 1 to 7 are implemented.

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