CN116720644B - Pedestrian dynamic evacuation method and system based on social force model and path finding algorithm - Google Patents
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Abstract
The invention discloses a pedestrian dynamic evacuation method and system based on a social force model and a path finding algorithm, wherein the method comprises the following steps: acquiring emergency information and corresponding event parameters of a target area; determining obstacle information and space information in the target area according to the Navmash model of the target area and a collision body detection algorithm; determining a plurality of possible evacuation routes in the target area according to a social force model and a dynamic route finding algorithm, and the obstacle information and the space information; and determining an optimal evacuation route from the plurality of possible evacuation routes according to the neural network model and the event parameters. Therefore, the invention can determine a plurality of candidate routes through the social force model and the dynamic route finding algorithm, and then determine the optimal route through the neural network, thereby effectively improving the accuracy and the effectiveness of the final route, improving the evacuation efficiency and the evacuation effect of people and reducing casualties.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a pedestrian dynamic evacuation method and system based on a social force model and a road finding algorithm.
Background
With the improvement of the living standard of people and the development of urban facilities, security consciousness and related technologies are also gaining attention gradually. While various path search algorithms are proposed in the prior art to solve the pedestrian evacuation problem, there are still many limitations of these algorithms, for example, these algorithms do not consider adjusting the algorithms in combination with the event parameters of the actually occurring emergency, nor consider integrating the results of the various algorithms and utilizing the neural network algorithm to make decisions to improve the accuracy and effectiveness of the decisions. It can be seen that the prior art has defects and needs to be solved.
Disclosure of Invention
The invention aims to solve the technical problem of providing a pedestrian dynamic evacuation method and system based on a social force model and a road finding algorithm, which can effectively improve the accuracy and effectiveness of a final route, improve the efficiency and effect of crowd evacuation and reduce casualties.
In order to solve the technical problems, the first aspect of the invention discloses a pedestrian dynamic evacuation method based on a social force model and a path finding algorithm, which comprises the following steps:
acquiring emergency information and corresponding event parameters of a target area;
determining obstacle information and space information in the target area according to the Navmash model of the target area and a collision body detection algorithm;
determining a plurality of possible evacuation routes in the target area according to a social force model and a dynamic route finding algorithm, and the obstacle information and the space information;
and determining an optimal evacuation route from the plurality of possible evacuation routes according to the neural network model and the event parameters.
As an optional implementation manner, in the first aspect of the present invention, the event parameters include an event type, an event influence range and an event position.
As an optional implementation manner, in the first aspect of the present invention, the determining a plurality of possible evacuation routes in the target area according to the social force model and the dynamic routing algorithm, and the obstacle information and the spatial information includes:
acquiring a parameter interval of a social force model parameter and a parameter interval of a cost parameter corresponding to the target area;
determining a plurality of possible evacuation routes in the target area according to the parameter interval of the social force model parameter, a preset social force model algorithm, the obstacle information and the space information;
and determining a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic path finding algorithm, the obstacle information and the space information.
As an optional implementation manner, in the first aspect of the present invention, the social force model parameter includes at least one of a pedestrian tendency parameter, a pedestrian movement direction parameter, a pedestrian movement speed parameter, and a pedestrian following search range parameter.
As an optional implementation manner, in the first aspect of the present invention, the determining a plurality of possible evacuation routes in the target area according to the parameter interval of the social force model parameter, the preset social force model algorithm, and the obstacle information and the spatial information includes:
determining interval proportion parameters according to the equipment performance of the computing equipment; the interval proportion parameter is inversely proportional to the device performance;
according to the interval proportion parameters, taking points from parameter intervals of the social force model parameters to obtain a plurality of optimized social force model parameters;
and according to the multiple optimized social force model parameters, carrying out multiple calculation on the obstacle information and the space information based on a preset social force model algorithm to obtain multiple possible evacuation routes in the target area.
As an optional implementation manner, in the first aspect of the present invention, the determining a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic routing algorithm, the obstacle information and the spatial information includes:
according to the interval proportion parameters, taking points from parameter intervals of the cost parameters to obtain a plurality of optimal cost parameters;
and according to the multiple preferred cost parameters, carrying out multiple times of calculation on the obstacle information and the space information based on a dynamic path finding algorithm to obtain multiple possible evacuation routes in the target area.
As an optional implementation manner, in the first aspect of the present invention, the determining, according to a neural network model and the event parameters, an optimal evacuation route from the plurality of possible evacuation routes includes:
determining a plurality of route excellent degree prediction models with the event type and the event position in a history processing event record from a preset algorithm model library according to the event type and the event position; the route excellence degree prediction model is a neural network model obtained through training of a training data set comprising a plurality of training evacuation routes, corresponding route parameters and corresponding excellence degree marks;
for each possible evacuation route, inputting the possible evacuation route and route parameters into each route goodness prediction model to obtain a plurality of output goodness prediction parameters; the route parameters are social force model parameters or cost parameters corresponding to a calculation algorithm model corresponding to the route;
calculating the influence weight corresponding to the intersection degree parameter of the possible evacuation route and the event influence range; the impact weight is inversely proportional to the intersection degree parameter;
calculating the average value of all the excellent degree prediction parameters corresponding to the possible route and the product of the average value and the influence weight to obtain the excellent degree parameter corresponding to the possible route;
and determining the possible evacuation route with the highest degree of excellence parameter as the optimal evacuation route.
The second aspect of the invention discloses a pedestrian dynamic evacuation system based on a social force model and a routing algorithm, which comprises:
the acquisition module is used for acquiring the emergency information and the corresponding event parameters of the target area;
the first determining module is used for determining obstacle information and space information in the target area according to the Navmesh model of the target area and a collision body detection algorithm;
the second determining module is used for determining a plurality of possible evacuation routes in the target area according to the social force model, the dynamic path finding algorithm, the obstacle information and the space information;
and the third determining module is used for determining an optimal evacuation route from the plurality of possible evacuation routes according to the neural network model and the event parameters.
As an optional implementation manner, in the second aspect of the present invention, the event parameters include an event type, an event influence range and an event position.
As an optional implementation manner, in the second aspect of the present invention, the determining, by the second determining module, a specific manner of determining a plurality of possible evacuation routes in the target area according to a social force model and a dynamic routing algorithm, and the obstacle information and the spatial information includes:
acquiring a parameter interval of a social force model parameter and a parameter interval of a cost parameter corresponding to the target area;
determining a plurality of possible evacuation routes in the target area according to the parameter interval of the social force model parameter, a preset social force model algorithm, the obstacle information and the space information;
and determining a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic path finding algorithm, the obstacle information and the space information.
As an optional implementation manner, in the second aspect of the present invention, the social force model parameter includes at least one of a pedestrian tendency parameter, a pedestrian movement direction parameter, a pedestrian movement speed parameter, and a pedestrian following search range parameter.
As an optional implementation manner, in the second aspect of the present invention, the determining, by the second determining module, a specific manner of determining a plurality of possible evacuation routes in the target area according to the parameter interval of the social force model parameter, a preset social force model algorithm, and the obstacle information and the spatial information, includes:
determining interval proportion parameters according to the equipment performance of the computing equipment; the interval proportion parameter is inversely proportional to the device performance;
according to the interval proportion parameters, taking points from parameter intervals of the social force model parameters to obtain a plurality of optimized social force model parameters;
and according to the multiple optimized social force model parameters, carrying out multiple calculation on the obstacle information and the space information based on a preset social force model algorithm to obtain multiple possible evacuation routes in the target area.
As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the second determining module determines a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic routing algorithm, and the obstacle information and the spatial information includes:
according to the interval proportion parameters, taking points from parameter intervals of the cost parameters to obtain a plurality of optimal cost parameters;
and according to the multiple preferred cost parameters, carrying out multiple times of calculation on the obstacle information and the space information based on a dynamic path finding algorithm to obtain multiple possible evacuation routes in the target area.
As an optional implementation manner, in the second aspect of the present invention, the determining, by the third determining module, a specific manner of determining an optimal evacuation route from the plurality of possible evacuation routes according to a neural network model and the event parameters, includes:
determining a plurality of route excellent degree prediction models with the event type and the event position in a history processing event record from a preset algorithm model library according to the event type and the event position; the route excellence degree prediction model is a neural network model obtained through training of a training data set comprising a plurality of training evacuation routes, corresponding route parameters and corresponding excellence degree marks;
for each possible evacuation route, inputting the possible evacuation route and route parameters into each route goodness prediction model to obtain a plurality of output goodness prediction parameters; the route parameters are social force model parameters or cost parameters corresponding to a calculation algorithm model corresponding to the route;
calculating the influence weight corresponding to the intersection degree parameter of the possible evacuation route and the event influence range; the impact weight is inversely proportional to the intersection degree parameter;
calculating the average value of all the excellent degree prediction parameters corresponding to the possible route and the product of the average value and the influence weight to obtain the excellent degree parameter corresponding to the possible route;
and determining the possible evacuation route with the highest degree of excellence parameter as the optimal evacuation route.
The third aspect of the invention discloses another pedestrian dynamic evacuation system based on a social force model and a path finding algorithm, the system comprises:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program codes stored in the memory to execute part or all of the steps in the pedestrian dynamic evacuation method based on the social force model and the path finding algorithm disclosed in the first aspect of the invention.
A fourth aspect of the present invention discloses a computer storage medium storing computer instructions for performing part or all of the steps of the dynamic pedestrian evacuation method based on the social force model and the routing algorithm disclosed in the first aspect of the present invention when the computer instructions are invoked.
Compared with the prior art, the invention has the following beneficial effects:
the invention can determine a plurality of candidate routes through the social force model and the dynamic route finding algorithm, and then determine the optimal route through the neural network, thereby effectively improving the accuracy and the effectiveness of the final route, improving the evacuation efficiency and the evacuation effect of people and reducing casualties.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a pedestrian dynamic evacuation method based on a social force model and a road finding algorithm, which is disclosed by the embodiment of the invention;
fig. 2 is a schematic structural diagram of a pedestrian dynamic evacuation system based on a social force model and a routing algorithm according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another pedestrian dynamic evacuation system based on a social force model and a routing algorithm according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The invention discloses a pedestrian dynamic evacuation method and system based on a social force model and a path finding algorithm, wherein a plurality of candidate routes can be determined through the social force model and the dynamic path finding algorithm, and then an optimal route is determined through a neural network, so that the accuracy and the effectiveness of a final route can be effectively improved, the efficiency and the effect of crowd evacuation are improved, and casualties are reduced. The following will describe in detail.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart of a pedestrian dynamic evacuation method based on a social force model and a path finding algorithm according to an embodiment of the present invention. The method described in fig. 1 may be applied to a corresponding data processing device, a data processing terminal, and a data processing server, where the server may be a local server or a cloud server, and the embodiment of the present invention is not limited to the method shown in fig. 1, and the method for dynamically evacuating pedestrians based on a social force model and a routing algorithm may include the following operations:
101. and acquiring the emergency information and the corresponding event parameters of the target area.
Optionally, the event parameters include event type, event scope of influence, and event location. Optionally, the event influence range may be a possible influence range area corresponding to the emergency information, which is an influence circle with the event position as a center and the statistical data as a radius. Alternatively, the statistics may be calculated by an operator based on event information in the historical incident processing record, for example, by counting the furthest distance of the range of influence in a plurality of historical events of the same event type.
102. And determining obstacle information and space information in the target area according to the Navmash model of the target area and a collision body detection algorithm.
103. And determining a plurality of possible evacuation routes in the target area according to the social force model and the dynamic path finding algorithm, as well as the obstacle information and the space information.
104. And determining an optimal evacuation route from a plurality of possible evacuation routes according to the neural network model and the event parameters.
Therefore, the method described by implementing the embodiment of the invention can determine a plurality of candidate routes through a social force model and a dynamic route finding algorithm, and then determine the optimal route through a neural network, so that the accuracy and the effectiveness of the final route can be effectively improved, the evacuation efficiency and the evacuation effect of people are improved, and the casualties are reduced.
As an alternative embodiment, in the step, determining a plurality of possible evacuation routes in the target area according to the social force model and the dynamic routing algorithm, and the obstacle information and the spatial information includes:
acquiring a parameter interval of a social force model parameter and a parameter interval of a cost parameter corresponding to a target area;
determining a plurality of possible evacuation routes in a target area according to a parameter interval of social force model parameters, a preset social force model algorithm, obstacle information and space information;
and determining a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic path finding algorithm, the obstacle information and the space information.
Optionally, the social force model parameters include at least one of a pedestrian slave tendency parameter, a pedestrian movement direction parameter, a pedestrian movement speed parameter, and a pedestrian following search range parameter.
Optionally, the parameter interval of the social force model parameter and the parameter interval of the cost parameter corresponding to the target area may be determined by an operator through statistics or experiments in advance, and the parameter intervals are used for characterizing the characteristics and the cost of personnel evacuation of the target area in the history evacuation record. Alternatively, the operator may also use historical evacuation records of a plurality of other regions with similar regional characteristics for the target region to make statistics to obtain the parameter interval.
Therefore, through the embodiment, a plurality of possible evacuation routes in the target area can be determined based on the social force model and the dynamic route finding algorithm according to the parameter interval corresponding to the target area, so that after candidate possible routes are screened later, the accuracy and effectiveness of the final route can be effectively improved, the crowd evacuation efficiency and effect are improved, and casualties are reduced.
As an alternative embodiment, in the step, determining a plurality of possible evacuation routes in the target area according to the parameter interval of the social force model parameter, the preset social force model algorithm, and the obstacle information and the spatial information includes:
determining interval proportion parameters according to the equipment performance of the computing equipment; the interval proportion parameter is inversely proportional to the equipment performance;
according to the interval proportion parameters, taking points from parameter intervals of the social force model parameters to obtain a plurality of optimized social force model parameters;
and according to the multiple preferred social force model parameters, carrying out multiple calculation on the obstacle information and the space information based on a preset social force model algorithm to obtain multiple possible evacuation routes in the target area.
Alternatively, the device performance of the computing device may be obtained by statistics and analysis of device parameters of the computing device, and may also be predicted using a neural network algorithm.
Alternatively, the interval proportion parameter and the equipment performance can be in a corresponding relation through experiments or experience of operators.
Optionally, a plurality of preferred social force model parameters can be combined in a plurality of modes to obtain a plurality of parameter combinations, and then according to each parameter combination, obstacle information and space information are calculated based on a preset social force model algorithm to obtain a possible evacuation route.
Therefore, through the embodiment, the parameter interval can be selected to obtain a plurality of model parameters, and a plurality of possible evacuation routes in the target area are respectively determined based on the social force model, so that after candidate possible routes are screened subsequently, the accuracy and the effectiveness of a final route can be effectively improved, the evacuation efficiency and the evacuation effect of people are improved, and casualties are reduced.
As an alternative embodiment, in the step, determining a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic routing algorithm, the obstacle information and the spatial information includes:
according to the interval proportion parameters, taking points from parameter intervals of the cost parameters to obtain a plurality of optimal cost parameters;
and according to the multiple preferred cost parameters, carrying out multiple times of calculation on the obstacle information and the space information based on the dynamic path finding algorithm to obtain multiple possible evacuation routes in the target area.
Optionally, each price parameter is used for limiting the calculation degree of the dynamic routing algorithm, specifically, when the dynamic routing algorithm is limited by a specific cost parameter, the route calculated by the dynamic routing algorithm can be output as a possible evacuation route when the cost of the route calculated by the dynamic routing algorithm is higher than the specific cost parameter, and the route with smaller cost does not need to be calculated continuously.
Therefore, through the above embodiment, the parameter interval can be selected to obtain a plurality of cost parameters, and a plurality of possible evacuation routes in the target area are determined based on the dynamic route finding algorithm, so that after the candidate possible routes are screened subsequently, the accuracy and the effectiveness of the final route can be effectively improved, the efficiency and the effect of crowd evacuation are improved, and the casualties are reduced.
As an optional embodiment, in the step, determining, according to the neural network model and the event parameter, an optimal evacuation route from a plurality of possible evacuation routes includes:
determining a plurality of route excellent degree prediction models with event types and event positions in the historical processing event records from a preset algorithm model library according to the event types and the event positions; the route excellence degree prediction model is a neural network model obtained by training a training data set comprising a plurality of training evacuation routes, corresponding route parameters and the corresponding excellence degree marks;
for each possible evacuation route, inputting the possible evacuation route and route parameters into each route goodness prediction model to obtain a plurality of output goodness prediction parameters; the route parameters are social force model parameters or cost parameters corresponding to the calculation algorithm model corresponding to the route;
calculating the influence weight corresponding to the intersection degree parameter of the possible evacuation route and the event influence range; the impact weight is inversely proportional to the intersection degree parameter;
calculating the average value of all the excellent degree prediction parameters corresponding to the possible route and the product of the average value and the influence weight to obtain the excellent degree parameters corresponding to the possible route;
and determining the possible evacuation route with the highest excellent degree parameter as the optimal evacuation route.
Therefore, through the embodiment, the excellent degree prediction parameters and the influence weights can be calculated according to the neural network model and the event parameters so as to determine the optimal evacuation route from a plurality of possible evacuation routes, thereby effectively improving the accuracy and the effectiveness of the final route, improving the evacuation efficiency and the evacuation effect of people and reducing casualties.
Example two
Referring to fig. 2, fig. 2 is a schematic structural diagram of a pedestrian dynamic evacuation system based on a social force model and a routing algorithm according to an embodiment of the present invention. The system described in fig. 2 may be applied to a corresponding data processing device, a data processing terminal, and a data processing server, where the server may be a local server or a cloud server, and embodiments of the present invention are not limited. As shown in fig. 2, the system may include:
the acquiring module 201 is configured to acquire emergency information and corresponding event parameters of the target area.
Optionally, the event parameters include event type, event scope of influence, and event location. Optionally, the event influence range may be a possible influence range area corresponding to the emergency information, which is an influence circle with the event position as a center and the statistical data as a radius. Alternatively, the statistics may be calculated by an operator based on event information in the historical incident processing record, for example, by counting the furthest distance of the range of influence in a plurality of historical events of the same event type.
The first determining module 202 is configured to determine obstacle information and spatial information in the target area according to a Navmesh model of the target area and with a collision body detection algorithm.
A second determining module 203, configured to determine a plurality of possible evacuation routes in the target area according to the social force model and the dynamic routing algorithm, and the obstacle information and the spatial information.
A third determining module 204 is configured to determine an optimal evacuation route from a plurality of possible evacuation routes according to the neural network model and the event parameters.
Therefore, the system described by implementing the embodiment of the invention can determine a plurality of candidate routes through a social force model and a dynamic route finding algorithm, and then determine the optimal route through a neural network, so that the accuracy and the effectiveness of the final route can be effectively improved, the evacuation efficiency and the evacuation effect of people are improved, and the casualties are reduced.
As an alternative embodiment, the second determining module 203 determines a specific manner of a plurality of possible evacuation routes in the target area according to the social force model and the dynamic routing algorithm, as well as the obstacle information and the spatial information, including:
acquiring a parameter interval of a social force model parameter and a parameter interval of a cost parameter corresponding to a target area;
determining a plurality of possible evacuation routes in a target area according to a parameter interval of social force model parameters, a preset social force model algorithm, obstacle information and space information;
and determining a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic path finding algorithm, the obstacle information and the space information.
Optionally, the social force model parameters include at least one of a pedestrian slave tendency parameter, a pedestrian movement direction parameter, a pedestrian movement speed parameter, and a pedestrian following search range parameter.
Optionally, the parameter interval of the social force model parameter and the parameter interval of the cost parameter corresponding to the target area may be determined by an operator through statistics or experiments in advance, and the parameter intervals are used for characterizing the characteristics and the cost of personnel evacuation of the target area in the history evacuation record. Alternatively, the operator may also use historical evacuation records of a plurality of other regions with similar regional characteristics for the target region to make statistics to obtain the parameter interval.
Therefore, through the embodiment, a plurality of possible evacuation routes in the target area can be determined based on the social force model and the dynamic route finding algorithm according to the parameter interval corresponding to the target area, so that after candidate possible routes are screened later, the accuracy and effectiveness of the final route can be effectively improved, the crowd evacuation efficiency and effect are improved, and casualties are reduced.
As an alternative embodiment, the second determining module 203 determines specific manners of a plurality of possible evacuation routes in the target area according to the parameter interval of the social force model parameter, the preset social force model algorithm, and the obstacle information and the spatial information, including:
determining interval proportion parameters according to the equipment performance of the computing equipment; the interval proportion parameter is inversely proportional to the equipment performance;
according to the interval proportion parameters, taking points from parameter intervals of the social force model parameters to obtain a plurality of optimized social force model parameters;
and according to the multiple preferred social force model parameters, carrying out multiple calculation on the obstacle information and the space information based on a preset social force model algorithm to obtain multiple possible evacuation routes in the target area.
Alternatively, the device performance of the computing device may be obtained by statistics and analysis of device parameters of the computing device, and may also be predicted using a neural network algorithm.
Alternatively, the interval proportion parameter and the equipment performance can be in a corresponding relation through experiments or experience of operators.
Optionally, a plurality of preferred social force model parameters can be combined in a plurality of modes to obtain a plurality of parameter combinations, and then according to each parameter combination, obstacle information and space information are calculated based on a preset social force model algorithm to obtain a possible evacuation route.
Therefore, through the embodiment, the parameter interval can be selected to obtain a plurality of model parameters, and a plurality of possible evacuation routes in the target area are respectively determined based on the social force model, so that after candidate possible routes are screened subsequently, the accuracy and the effectiveness of a final route can be effectively improved, the evacuation efficiency and the evacuation effect of people are improved, and casualties are reduced.
As an alternative embodiment, the second determining module 203 determines specific manners of multiple possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic routing algorithm, the obstacle information and the spatial information, and includes:
according to the interval proportion parameters, taking points from parameter intervals of the cost parameters to obtain a plurality of optimal cost parameters;
and according to the multiple preferred cost parameters, carrying out multiple times of calculation on the obstacle information and the space information based on the dynamic path finding algorithm to obtain multiple possible evacuation routes in the target area.
Optionally, each price parameter is used for limiting the calculation degree of the dynamic routing algorithm, specifically, when the dynamic routing algorithm is limited by a specific cost parameter, the route calculated by the dynamic routing algorithm can be output as a possible evacuation route when the cost of the route calculated by the dynamic routing algorithm is higher than the specific cost parameter, and the route with smaller cost does not need to be calculated continuously.
Therefore, through the above embodiment, the parameter interval can be selected to obtain a plurality of cost parameters, and a plurality of possible evacuation routes in the target area are determined based on the dynamic route finding algorithm, so that after the candidate possible routes are screened subsequently, the accuracy and the effectiveness of the final route can be effectively improved, the efficiency and the effect of crowd evacuation are improved, and the casualties are reduced.
As an alternative embodiment, the third determining module 204 determines, according to the neural network model and the event parameters, a specific manner of determining the optimal evacuation route from the plurality of possible evacuation routes, including:
determining a plurality of route excellent degree prediction models with event types and event positions in the historical processing event records from a preset algorithm model library according to the event types and the event positions; the route excellence degree prediction model is a neural network model obtained by training a training data set comprising a plurality of training evacuation routes, corresponding route parameters and the corresponding excellence degree marks;
for each possible evacuation route, inputting the possible evacuation route and route parameters into each route goodness prediction model to obtain a plurality of output goodness prediction parameters; the route parameters are social force model parameters or cost parameters corresponding to the calculation algorithm model corresponding to the route;
calculating the influence weight corresponding to the intersection degree parameter of the possible evacuation route and the event influence range; the impact weight is inversely proportional to the intersection degree parameter;
calculating the average value of all the excellent degree prediction parameters corresponding to the possible route and the product of the average value and the influence weight to obtain the excellent degree parameters corresponding to the possible route;
and determining the possible evacuation route with the highest excellent degree parameter as the optimal evacuation route.
Therefore, through the embodiment, the excellent degree prediction parameters and the influence weights can be calculated according to the neural network model and the event parameters so as to determine the optimal evacuation route from a plurality of possible evacuation routes, thereby effectively improving the accuracy and the effectiveness of the final route, improving the evacuation efficiency and the evacuation effect of people and reducing casualties.
Example III
Referring to fig. 3, fig. 3 is a schematic structural diagram of another pedestrian dynamic evacuation system based on a social force model and a routing algorithm according to an embodiment of the present invention. As shown in fig. 3, the system may include:
a memory 301 storing executable program code;
a processor 302 coupled with the memory 301;
the processor 302 invokes executable program code stored in the memory 301 to perform some or all of the steps in the pedestrian dynamic evacuation method based on the social force model and the routing algorithm disclosed in the embodiment of the present invention.
Example IV
The embodiment of the invention discloses a computer storage medium which stores computer instructions for executing part or all of the steps in the pedestrian dynamic evacuation method based on the social force model and the path finding algorithm disclosed in the embodiment of the invention when the computer instructions are called.
The system embodiments described above are merely illustrative, in which the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.
Finally, it should be noted that: the embodiment of the invention discloses a pedestrian dynamic evacuation method and system based on a social force model and a path finding algorithm, which are disclosed by the embodiment of the invention only as a preferred embodiment of the invention, and are only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (6)
1. A pedestrian dynamic evacuation method based on a social force model and a road finding algorithm, which is characterized by comprising the following steps:
acquiring emergency information and corresponding event parameters of a target area; the event parameters comprise event types, event influence ranges and event positions;
determining obstacle information and space information in the target area according to the Navmash model of the target area and a collision body detection algorithm;
acquiring a parameter interval of a social force model parameter and a parameter interval of a cost parameter corresponding to the target area;
determining interval proportion parameters according to the equipment performance of the computing equipment; the interval proportion parameter is inversely proportional to the device performance;
according to the interval proportion parameters, taking points from parameter intervals of the social force model parameters to obtain a plurality of optimized social force model parameters;
according to the multiple preferred social force model parameters, carrying out multiple calculation on the obstacle information and the space information based on a preset social force model algorithm to obtain multiple possible evacuation routes in the target area;
determining a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic path finding algorithm, the obstacle information and the space information;
determining a plurality of route excellent degree prediction models with the event type and the event position in a history processing event record from a preset algorithm model library according to the event type and the event position; the route excellence degree prediction model is a neural network model obtained through training of a training data set comprising a plurality of training evacuation routes, corresponding route parameters and corresponding excellence degree marks;
for each possible evacuation route, inputting the possible evacuation route and route parameters into each route goodness prediction model to obtain a plurality of output goodness prediction parameters; the route parameters are social force model parameters or cost parameters corresponding to a calculation algorithm model corresponding to the route;
calculating the influence weight corresponding to the intersection degree parameter of the possible evacuation route and the event influence range; the impact weight is inversely proportional to the intersection degree parameter;
calculating the average value of all the excellent degree prediction parameters corresponding to the possible evacuation route and the product of the average value and the influence weight to obtain the excellent degree parameter corresponding to the possible evacuation route;
and determining the possible evacuation route with the highest degree of excellence parameter as the optimal evacuation route.
2. The method for dynamically evacuating pedestrians based on the social force model and the routing algorithm according to claim 1, wherein the social force model parameters comprise at least one of pedestrian tendency parameter, pedestrian moving direction parameter, pedestrian moving speed parameter and pedestrian following search range parameter.
3. The pedestrian dynamic evacuation method based on the social force model and the routing algorithm according to claim 1, wherein the determining a plurality of possible evacuation routes within the target area according to the parameter interval of the cost parameter, and the dynamic routing algorithm, and the obstacle information and the spatial information includes:
according to the interval proportion parameters, taking points from parameter intervals of the cost parameters to obtain a plurality of optimal cost parameters;
and according to the multiple preferred cost parameters, carrying out multiple times of calculation on the obstacle information and the space information based on a dynamic path finding algorithm to obtain multiple possible evacuation routes in the target area.
4. A pedestrian dynamic evacuation system based on a social force model and a routing algorithm, the system comprising:
the acquisition module is used for acquiring the emergency information and the corresponding event parameters of the target area;
the first determining module is used for determining obstacle information and space information in the target area according to the Navmesh model of the target area and a collision body detection algorithm; the event parameters comprise event types, event influence ranges and event positions;
the second determining module is configured to determine a plurality of possible evacuation routes in the target area according to the social force model and the dynamic routing algorithm, and the obstacle information and the spatial information, and specifically includes:
acquiring a parameter interval of a social force model parameter and a parameter interval of a cost parameter corresponding to the target area;
determining interval proportion parameters according to the equipment performance of the computing equipment; the interval proportion parameter is inversely proportional to the device performance;
according to the interval proportion parameters, taking points from parameter intervals of the social force model parameters to obtain a plurality of optimized social force model parameters;
according to the multiple preferred social force model parameters, carrying out multiple calculation on the obstacle information and the space information based on a preset social force model algorithm to obtain multiple possible evacuation routes in the target area;
determining a plurality of possible evacuation routes in the target area according to the parameter interval of the cost parameter, the dynamic path finding algorithm, the obstacle information and the space information;
the third determining module is configured to determine an optimal evacuation route from the plurality of possible evacuation routes according to the neural network model and the event parameter, and specifically includes:
determining a plurality of route excellent degree prediction models with the event type and the event position in a history processing event record from a preset algorithm model library according to the event type and the event position; the route excellence degree prediction model is a neural network model obtained through training of a training data set comprising a plurality of training evacuation routes, corresponding route parameters and corresponding excellence degree marks;
for each possible evacuation route, inputting the possible evacuation route and route parameters into each route goodness prediction model to obtain a plurality of output goodness prediction parameters; the route parameters are social force model parameters or cost parameters corresponding to a calculation algorithm model corresponding to the route;
calculating the influence weight corresponding to the intersection degree parameter of the possible evacuation route and the event influence range; the impact weight is inversely proportional to the intersection degree parameter;
calculating the average value of all the excellent degree prediction parameters corresponding to the possible evacuation route and the product of the average value and the influence weight to obtain the excellent degree parameter corresponding to the possible evacuation route;
and determining the possible evacuation route with the highest degree of excellence parameter as the optimal evacuation route.
5. A pedestrian dynamic evacuation system based on a social force model and a routing algorithm, the system comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the pedestrian dynamic evacuation method based on the social force model and the routing algorithm as claimed in any one of claims 1-3.
6. A computer storage medium storing computer instructions which, when invoked, are operable to perform a method of dynamic evacuation of pedestrians based on a social force model and a routing algorithm according to any one of claims 1 to 3.
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