Fire rescue path planning method and system based on big data

Abstract

The present invention relates to the technical field of big data analysis and planning, and in particular to a method and system for fire rescue path planning based on big data, the method comprising obtaining a three-dimensional road network map of a pre-demarcated fire rescue area, mapping to obtain road network topology data; obtaining three-dimensional parameters of the road network in the three-dimensional road network map; obtaining a first planned path to a second planned path according to the road network topology data and a pre-set equal division coefficient; and obtaining a first planned path to a second planned path based on the road network topology data and a pre-set equal division coefficient. Y Plan the path; read the first smoke density to the N Smoke density; calculate the first planning path to the Y Plan the rescue target value of the path, and get the first rescue target value to the Y Rescue target value; change the first rescue target value to the Y The planned path corresponding to the maximum value of the rescue target value is used as the optimal planned path for fire rescue. The present invention realizes flexible and efficient pre-planning of fire rescue paths by considering two methods: rescue by taking a rescue vehicle and rescue by walking personnel, and based on the parameters of buildings and roads in the fire rescue area.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis and planning, and in particular to a fire rescue path planning method and system based on big data. Background Art

[0002] With the acceleration of urbanization, the building density and population density are increasing, and the frequency and complexity of fires are also increasing. As an important part of the emergency rescue system, the flexibility and efficiency of fire rescue path planning directly affect the success of the rescue operation. The existing fire rescue path planning mainly considers the following aspects: first, traffic congestion; second, path topology. However, this path planning method has the following defects: first, traffic congestion data can only be obtained in real time, and it is difficult to predict in advance. The planning of fire rescue paths often needs to be prepared in time after the fire occurs and before the rescue personnel set off. Therefore, it is not feasible to use traffic congestion data for fire rescue path planning; second, the existing fire rescue path planning method does not consider the impact of smoke concentration in the disaster relief area after the fire occurs on fire rescue. For example, after the fire occurs, due to the influence of wind direction, there may be a situation where the smoke concentration of a certain section is much greater than that of other sections. In this case, it is necessary to consider the impact of smoke concentration on rescue path planning; third, the existing fire rescue path planning method does not consider the collaborative planning of the combination of rescue vehicles and rescue personnel on foot, which makes it difficult to achieve the optimal planning path selection. Based on the above three reasons, the existing fire rescue path planning methods are difficult to meet the needs of flexible and efficient planning of rescue paths in complex urban environments.

[0003] In order to overcome the drawbacks of existing technical solutions, it is necessary to start with the integration of multi-dimensional data in the fire rescue area, analyze and process the multi-dimensional data through big data algorithms, and consider the collaborative planning of two methods: rescue vehicles and rescue personnel on foot. This will enable advance planning of fire rescue routes based on big data and improve the flexibility and efficiency of planned routes. Summary of the invention

[0004] (1) Technical issues to be resolved

[0005] The purpose of the present invention is to provide a fire rescue path planning method and system based on big data, so as to realize the advance planning of fire rescue paths by combining both rescue vehicles and rescue personnel on foot, and to improve the flexibility and efficiency of the planned path.

[0006] (2) Technical solution

[0007] To achieve the above object, the present invention provides a fire rescue path planning method based on big data, the method comprising the following steps:

[0008] S1, obtaining a three-dimensional road network map of a pre-defined fire rescue area, and mapping to obtain road network topology data; the road network topology data includes road network topology elements and connection relationships between road network topology elements; the road network topology elements include a first branch node to a second branch node; N Branch node, first driving link to the M Driving link, departure node, destination node; N Indicates the number of branch nodes, M Indicates the number of driving links; obtains the three-dimensional parameters of the road network in the three-dimensional road network map.

[0009] S2, according to the road network topology data, traverse the driving links from the starting node to the target node to obtain associated driving links; combine the associated driving links to obtain the first driving path to the first driving path R Driving path; R Indicates the number of driving lanes.

[0010] S3, connect the first driving path to the R The driving lanes are divided into equal parts according to the pre-set coefficients D Divide equally and get the first equal division decision point to the Y Equally divided decision points; Y is the number of equally divided decision points; the equally divided decision points are connected with the first driving path to the R The driving path combination obtains the first planned path to the Y Plan the path; read the pre-installed N The smoke density measured by the smoke density detector of the branch node is used to obtain the smoke density from the first smoke density to the second smoke density. N Smoke density.

[0011] S4, according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Rescue target value; change the first rescue target value to the Y The planned path corresponding to the maximum value of the rescue target value is used as the optimal planned path for fire rescue; the equal division decision points corresponding to the optimal planned path for fire rescue are extracted and recorded as the optimal equal division decision points; in the optimal planned path for fire rescue, the section between the starting node and the optimal equal division decision point adopts the driving mode of taking the rescue vehicle, and the section between the optimal equal division decision point and the target node adopts the rescue personnel on foot.

[0012] Furthermore, the method for obtaining three-dimensional parameters of a road network in a three-dimensional road network map includes:

[0013] The heights of buildings on both sides of the road in the three-dimensional road network map are extracted to obtain a building height sequence; the road widths in the three-dimensional road network map are extracted to obtain a road width sequence.

[0014] The building height sequence, road width sequence and road network topology data are combined to obtain the three-dimensional parameters of the road network.

[0015] Further, the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Methods for rescuing target values ​​include:

[0016] S31, set flag variable .

[0017] S32, according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Plan path speed function.

[0018] S33, according to Planning path concentration function and The planning path speed function is calculated to obtain the Rescue target value ; said The calculation formula of rescue target value is:

[0019] ;

[0020] in, is the first target coefficient set in advance, is a preset second target coefficient; For the The path distance between any position on the planned path and the starting node, in meters; Indicates The path length of the planned path, in meters; Indicates Planning path concentration function, in milligrams per cubic meter; Indicates Planned path speed function, in meters per second.

[0021] S34, increase the value of the flag variable by 1, and repeat steps S32 to S34 in sequence until the value of the flag variable is greater than Y .

[0022] Further, the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Methods for planning path velocity functions include:

[0023] The first The planned path is mapped to the horizontal axis on the two-dimensional coordinate plane, and the first Distance horizontal axis; from the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Plan the path concentration function; calculate the The path distance between the decision point and the starting node is divided equally to obtain the first Driving distance .

[0024] Filter the road width sequence with Planning path related data, get the first width sequence; Width sequence and The distance is associated with the horizontal axis, and the mapping is obtained Width sequence and The functional relationship is recorded as Road Width Function ; Filter the building height sequence with the first Planning path related data, get the first Height sequence; Height sequence and The distance is associated with the horizontal axis, and the mapping is obtained Height sequence and The functional relationship is recorded as Height function According to Road Width Function , No. Height function The first speed function is calculated by the path speed conversion formula with the preset rescuer speed function and rescue vehicle speed function. Plan the path speed function; the path speed conversion formula is:

[0025] ;

[0026] in, represents the rescue vehicle speed function, represents the rescuer speed function, represents the first speed parameter, represents the second speed parameter, Indicates the third speed parameter.

[0027] Further, the method according to the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Methods for planning path concentration functions include:

[0028] Search the first branch node to the N In the branch node Plan the branch nodes that overlap the path and renumber them to get the first associated node to the associated node; Indicates The number of branch nodes that overlap in the planning path; Associate the node with the first branch node to the N The mapping relationship of the branch nodes is obtained from the first associated concentration to the Associated concentration.

[0029] Using the first association node to the The associated node will The planned path is divided into path segments; calculate separately The length of the path segment is obtained The length of the first path segment of the planned path to the Planning the path Path segment length; the concentration distribution conversion formula is used to calculate the first Planning path concentration function; the concentration distribution conversion formula is:

[0030] ;

[0031] in, represents the first associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to An integer between .

[0032] Based on the same inventive concept, on the other hand, the present invention also provides a fire rescue path planning system based on big data, the system comprising:

[0033] The data reading module is used to obtain a three-dimensional road network map of a pre-defined fire rescue area and map it to obtain road network topology data; the road network topology data includes road network topology elements and connection relationships between road network topology elements; the road network topology elements include a first branch node to a second branch node; N Branch node, first driving link to the M Driving link, departure node, destination node; N Indicates the number of branch nodes, M Indicates the number of driving links; obtains the three-dimensional parameters of the road network in the three-dimensional road network map.

[0034] The path traversal module is connected to the data reading module and is used to traverse the driving links from the starting node to the target node according to the road network topology data to obtain associated driving links; combine the associated driving links to obtain the first driving path to the target node; R Driving path; R Indicates the number of driving lanes.

[0035] A path segmentation module is connected to the path traversal module and is used to divide the first driving path into the first R The driving lanes are divided into equal parts according to the pre-set coefficients D Divide into equal parts and get the first equal division decision point to the Y Equally divided decision points; Y is the number of equally divided decision points; the equally divided decision points are connected with the first driving path to the R The driving path combination obtains the first planned path to the Y Plan the path; read the pre-installed N The smoke density measured by the smoke density detector of the branch node is used to obtain the smoke density from the first smoke density to the second smoke density. N Smoke density.

[0036] The optimization calculation module is connected to the path segmentation module and is used to calculate the number of paths according to the three-dimensional parameters of the road network, the first smoke density and the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Rescue target value; change the first rescue target value to the Y The planned path corresponding to the maximum value of the rescue target value is used as the optimal planned path for fire rescue; the equal division decision points corresponding to the optimal planned path for fire rescue are extracted and recorded as the optimal equal division decision points; in the optimal planned path for fire rescue, the section between the starting node and the optimal equal division decision point adopts the driving mode of taking the rescue vehicle, and the section between the optimal equal division decision point and the target node adopts the rescue personnel on foot.

[0037] Furthermore, the data reading module includes:

[0038] The data extraction module is used to extract the heights of buildings on both sides of the road in the three-dimensional road network map to obtain a building height sequence; and to extract the road widths in the three-dimensional road network map to obtain a road width sequence.

[0039] The data combination module is connected to the data extraction module and is used to combine the building height sequence, the road width sequence and the road network topology data to obtain the three-dimensional parameters of the road network.

[0040] Furthermore, the optimization calculation module includes:

[0041] Initialization module, used to set flag variables .

[0042] The function generation module is connected to the initialization module and is used to generate the function according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Plan path speed function.

[0043] The rescue target value calculation module is connected to the function generation module and is used to calculate the rescue target value according to the first Planning path concentration function and The planning path speed function is calculated to obtain the Rescue target value ; said The calculation formula of rescue target value is:

[0044] ;

[0045] in, is the first target coefficient set in advance, is a preset second target coefficient; For the The path distance between any position on the planned path and the starting node, in meters; Indicates The path length of the planned path, in meters; Indicates Planning path concentration function, in milligrams per cubic meter; Indicates Planned path speed function, in meters per second.

[0046] The loop calculation module is connected to the rescue target value calculation module, and is used to increase the value of the flag variable by 1, and repeatedly execute the initialization module, the function generation module, the rescue target value calculation module, and the loop calculation module until the value of the flag variable is greater than Y .

[0047] Furthermore, the function generation module includes:

[0048] Mapping module, used to convert The planned path is mapped to the horizontal axis on the two-dimensional coordinate plane, and the first Distance horizontal axis; from the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Plan the path concentration function; calculate the The path distance between the decision point and the starting node is divided equally to obtain the first Driving distance .

[0049] The path speed conversion module is connected to the mapping module and is used to select the path speed in the road width sequence. Planning path related data, get the first width sequence; Width sequence and The distance is associated with the horizontal axis, and the mapping is obtained Width sequence and The functional relationship is recorded as Road Width Function ; Filter the building height sequence with the first Planning path related data, get the first Height sequence; Height sequence and The distance is associated with the horizontal axis, and the mapping is obtained Height sequence and The functional relationship is recorded as Height function According to Road Width Function , No. Height function The first speed function is calculated by the path speed conversion formula with the preset rescuer speed function and rescue vehicle speed function. Plan the path speed function; the path speed conversion formula is:

[0050] ;

[0051] in, represents the rescue vehicle speed function, represents the rescuer speed function, represents the first speed parameter, represents the second speed parameter, Indicates the third speed parameter.

[0052] Furthermore, the mapping module includes:

[0053] Concentration association module, used to search from the first branch node to the N In the branch node Plan the branch nodes that overlap the path and renumber them to get the first associated node to the associated node; Indicates The number of branch nodes that overlap in the planning path; Associate the node with the first branch node to the N The mapping relationship of the branch nodes is obtained from the first associated concentration to the Associated concentration.

[0054] The concentration distribution conversion module is connected to the concentration association module and is used to convert the first association node to the second association node. The associated node will The planned path is divided into path segments; calculate separately The length of the path segment is obtained The length of the first path segment of the planned path to the Planning the path Path segment length; the concentration distribution conversion formula is used to calculate the first Planning path concentration function; the concentration distribution conversion formula is:

[0055] ;

[0056] in, represents the first associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to An integer between .

[0057] (3) Beneficial effects

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. By introducing the variable of equally divided decision points, R The driving route is divided into equal parts, and the equal division decision points are used as dividing points to divide and optimize the driving mode of taking rescue vehicles and the rescue mode of using rescue personnel on foot, thereby realizing the coordinated planning of both the rescue mode of taking rescue vehicles and the rescue mode of using rescue personnel on foot in the fire rescue route planning.

[0060] 2. According to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y The rescue target value of the planning path is calculated, so that the influence of multi-dimensional data such as building height, road width and smoke concentration on the rescue path is comprehensively considered in the fire rescue path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a flowchart of a fire rescue path planning method based on big data according to Embodiment 1 of the present invention;

[0062] Figure 2 This is a schematic diagram of a fire rescue area in Example 1 of the present invention;

[0063] Figure 3 Schematic diagram of the module composition of the fire rescue path planning system based on big data according to Embodiment 2 of the present invention. Detailed implementation manners

[0064] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0065] Before giving examples, it is necessary to elaborate on the application scenarios of the concept of the present invention. The present invention is applied to the prior planning of fire rescue paths that simultaneously consider two methods of taking rescue vehicles and rescue personnel walking on foot.

[0066] Embodiment 1: As Figure 1 shown, this embodiment provides a fire rescue path planning method based on big data. The method includes the following steps:

[0067] S1. Obtain a three-dimensional road network map of a pre-defined fire rescue area, and map it to obtain road network topology data; the road network topology data includes road network topology elements and the connection relationships between the road network topology elements; the road network topology elements include the first branch node to the N th branch node, the first driving link to the M th driving link, a starting node, and a target node; where N represents the number of branch nodes, M represents the number of driving links; obtain road network three-dimensional parameters in the three-dimensional road network map.

[0068] Exemplarily, as Figure 2 shown, taking a typical "day"-shaped fire rescue area as an example, the road network topology elements include a first branch node, a second branch node, the first driving link to the fifth driving link, a starting node, and a target node. Among them, the number of branch nodes , and the number of driving links . A branch node represents a node connected to no less than 3 driving links. A driving link represents a connecting branch between two nodes among the first branch node to the N th branch node, the starting node, and the target node. The numbers of the branch nodes and driving links can be set artificially.

[0069] S2. According to the road network topology data, traverse the driving links from the starting node to the target node to obtain associated driving links; combine the associated driving links to obtain the first driving path to the R th driving path; where RIndicates the number of driving lanes.

[0070] Exemplarily, the associated driving links represent a group of non-repetitive driving links from the starting node to the target node that are connected end to end, and the associated driving links are combined to obtain the first driving path to the fourth driving path. For example, the first driving path represents the combination of the first driving link and the fourth driving link, the second driving path represents the combination of the first driving link, the third driving link and the fifth driving link, the third driving path represents the combination of the second driving link, the third driving link and the fourth driving link, and the fourth driving path represents the combination of the second driving link and the fifth driving link.

[0071] S3, connect the first driving path to the R The driving lanes are divided into equal parts according to the pre-set coefficients D Divide equally and get the first equal division decision point to the Y Equally divided decision points; Y is the number of equally divided decision points; the equally divided decision points are connected with the first driving path to the R The driving path combination obtains the first planned path to the Y Plan the path; read the pre-installed N The smoke density measured by the smoke density detector of the branch node is used to obtain the smoke density from the first smoke density to the second smoke density. N Smoke density.

[0072] For example, the pre-set equal division coefficient D= 10, so the first to fourth driving paths are divided into 10 equal parts. Number of equally divided decision points , thus the first equal division decision point to the 36th equal division decision point are obtained, and then the first planned path to the 36th planned path are obtained. Taking the first planned path and the second planned path as examples, the first planned path indicates that the rescue vehicle is used to travel along the first driving path from the starting node to the first equal division decision point, and then the rescue personnel are used to travel along the first driving path from the first equal division decision point to the target node. The second planned path indicates that the rescue vehicle is used to travel along the first driving path from the starting node to the second equal division decision point, and then the rescue personnel are used to travel along the first driving path from the second equal division decision point to the target node.

[0073] S4, according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Rescue target value; change the first rescue target value to the YThe planned path corresponding to the maximum value of the rescue target value is used as the optimal planned path for fire rescue; the equal division decision points corresponding to the optimal planned path for fire rescue are extracted and recorded as the optimal equal division decision points; in the optimal planned path for fire rescue, the section between the starting node and the optimal equal division decision point adopts the driving mode of taking the rescue vehicle, and the section between the optimal equal division decision point and the target node adopts the rescue personnel on foot.

[0074] For example, the planned path corresponding to the maximum value among the first rescue target value to the 36th rescue target value is calculated to be the 8th planned path, so the equal division decision point corresponding to the 8th planned path is extracted and recorded as the optimal equal division decision point. In the 8th planned path, the road section between the starting node and the optimal equal division decision point adopts the driving mode of taking the rescue vehicle, and the road section between the optimal equal division decision point and the target node adopts the rescue mode of the rescue personnel on foot.

[0075] Furthermore, the method for obtaining three-dimensional parameters of a road network in a three-dimensional road network map includes:

[0076] The heights of buildings on both sides of the road in the three-dimensional road network map are extracted to obtain a building height sequence; the road widths in the three-dimensional road network map are extracted to obtain a road width sequence.

[0077] The building height sequence, road width sequence and road network topology data are combined to obtain the three-dimensional parameters of the road network.

[0078] For example, since the road width and the height of the buildings on both sides of the road will affect the speed of firefighting and rescue, it is necessary to extract the height of the buildings on both sides of the road and the road width data as the basis for path planning. According to statistics, the urban population activity density and the building height are positively correlated. Therefore, in the planning state data analysis, since it is impossible to obtain real-time traffic congestion data, it is an effective technical means to use the height of the buildings on both sides of the road to measure the urban population activity density, and then indirectly reflect the speed of firefighting and rescue. The impact of road width on the speed of firefighting and rescue is more direct. The wider the road, the faster the speed of firefighting and rescue tends to be. It is worth noting that the road width in the present invention refers to the road width that can be occupied by rescue vehicles or personnel under normal traffic conditions, excluding the width of the opposite lane. The sampling interval of the building height sequence and the road width sequence can be set manually, and is set to 10 meters in this embodiment.

[0079] Further, the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Methods for rescuing target values ​​include:

[0080] S31, set flag variable .

[0081] S32, according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Plan path speed function.

[0082] S33, according to Planning path concentration function and The planning path speed function is calculated to obtain the Rescue target value ; said The calculation formula of rescue target value is:

[0083] ;

[0084] in, is the first target coefficient set in advance, is a preset second target coefficient; For the The path distance between any position on the planned path and the starting node, in meters; Indicates The path length of the planned path, in meters; Indicates Planning path concentration function, in milligrams per cubic meter; Indicates Planned path speed function, in meters per second.

[0085] S34, increase the value of the flag variable by 1, and repeat steps S32 to S34 in sequence until the value of the flag variable is greater than Y .

[0086] For example, , It can be set according to the relative importance of rescue efficiency and rescue path obstacles to the technicians. , .

[0087] Further, the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Methods for planning path velocity functions include:

[0088] The first The planned path is mapped to the horizontal axis on the two-dimensional coordinate plane, and the first Distance horizontal axis; from the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Plan the path concentration function; calculate the The path distance between the decision point and the starting node is divided equally to obtain the first Driving distance .

[0089] Filter the road width sequence with Planning path related data, get the first width sequence; Width sequence and The distance is associated with the horizontal axis, and the mapping is obtained Width sequence and The functional relationship is recorded as Road Width Function ; Filter the building height sequence with the first Planning path related data, get the first Height sequence; Height sequence and The distance is associated with the horizontal axis, and the mapping is obtained Height sequence and The functional relationship is recorded as Height function According to Road Width Function , No. Height function The first speed function is calculated by the path speed conversion formula with the preset rescuer speed function and rescue vehicle speed function. Plan the path speed function; the path speed conversion formula is:

[0090] ;

[0091] in, represents the rescue vehicle speed function, represents the rescuer speed function, represents the first speed parameter, represents the second speed parameter, Indicates the third speed parameter.

[0092] For example, on the first planned path, the lane width of the road section with a path distance of 0 to 380 meters from the departure node is 10 meters, and the lane width of the road section with a path distance of 380 to 790 meters from the departure node is 12 meters, so the first road width function is obtained: The expression is:

[0093]

[0094] Similarly, we get the first height function The expression is:

[0095]

[0096] Similarly, according to the first smoke density to the second smoke density, the concentration distribution algorithm is used to calculate .

[0097] The rescuer speed function and the rescue vehicle speed function need to be set in advance. The setting method can be to fit the historical data obtained by measurement and correct them according to the relevant standards of fire rescue vehicle driving.

[0098] Since the path length of the first planned path is 790 meters, the path distance between the first bisection decision point and the starting node is 79 meters, .

[0099] According to the above formula, we can get , similarly we can get to .

[0100] Further, the method according to the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Methods for planning path concentration functions include:

[0101] Search the first branch node to the N In the branch node Plan the branch nodes that overlap the path and renumber them to get the first associated node to the associated node; Indicates The number of branch nodes that overlap in the planning path; Associate the node with the first branch node to the N The mapping relationship of the branch nodes is obtained from the first associated concentration to the Associated concentration.

[0102] Using the first association node to the The associated node will The planned path is divided into path segments; calculate separately The length of the path segment is obtained The length of the first path segment of the planned path to the Planning the path Path segment length; the concentration distribution conversion formula is used to calculate the first Planning path concentration function; the concentration distribution conversion formula is:

[0103] ;

[0104] in, represents the first associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to An integer between .

[0105] For example, since the first planned path coincides with one branch node, Calculated by the concentration distribution conversion formula , The expression is:

[0106]

[0107] Similarly, we can also obtain to .

[0108] Embodiment 2: Based on the same inventive concept, Figure 3 As shown, this embodiment also provides a fire rescue path planning system based on big data, and the system includes:

[0109] The data reading module is used to obtain a three-dimensional road network map of a pre-defined fire rescue area and map it to obtain road network topology data; the road network topology data includes road network topology elements and connection relationships between road network topology elements; the road network topology elements include a first branch node to a second branch node; N Branch node, first driving link to the M Driving link, departure node, destination node; N Indicates the number of branch nodes, M Indicates the number of driving links; obtains the three-dimensional parameters of the road network in the three-dimensional road network map.

[0110] The path traversal module is connected to the data reading module and is used to traverse the driving links from the starting node to the target node according to the road network topology data to obtain associated driving links; combine the associated driving links to obtain the first driving path to the target node; R Driving path; R Indicates the number of driving lanes.

[0111] A path segmentation module is connected to the path traversal module and is used to divide the first driving path into the first R The driving lanes are divided into equal parts according to the pre-set coefficients D Divide equally and get the first equal division decision point to the Y Equally divided decision points; Y is the number of equally divided decision points; the equally divided decision points are connected with the first driving path to the R The driving path combination obtains the first planned path to the Y Plan the path; read the pre-installed N The smoke density measured by the smoke density detector of the branch node is used to obtain the smoke density from the first smoke density to the second smoke density. N Smoke density.

[0112] The optimization calculation module is connected to the path segmentation module and is used to calculate the number of paths according to the three-dimensional parameters of the road network, the first smoke density and the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Rescue target value; change the first rescue target value to the Y The planned path corresponding to the maximum value of the rescue target value is used as the optimal planned path for fire rescue; the equal division decision points corresponding to the optimal planned path for fire rescue are extracted and recorded as the optimal equal division decision points; in the optimal planned path for fire rescue, the section between the starting node and the optimal equal division decision point adopts the driving mode of taking the rescue vehicle, and the section between the optimal equal division decision point and the target node adopts the rescue personnel on foot.

[0113] Furthermore, the data reading module includes:

[0114] The data extraction module is used to extract the heights of buildings on both sides of the road in the three-dimensional road network map to obtain a building height sequence; and to extract the road widths in the three-dimensional road network map to obtain a road width sequence.

[0115] The data combination module is connected to the data extraction module and is used to combine the building height sequence, the road width sequence and the road network topology data to obtain the three-dimensional parameters of the road network.

[0116] Furthermore, the optimization calculation module includes:

[0117] Initialization module, used to set flag variables .

[0118] The function generation module is connected to the initialization module and is used to generate the function according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Plan path speed function.

[0119] The rescue target value calculation module is connected to the function generation module and is used to calculate the rescue target value according to the first Planning path concentration function and The planning path speed function is calculated to obtain the Rescue target value ; said The calculation formula of rescue target value is:

[0120] ;

[0121] in, is the first target coefficient set in advance, is a preset second target coefficient; For the The path distance between any position on the planned path and the starting node, in meters; Indicates The path length of the planned path, in meters; Indicates Planning path concentration function, in milligrams per cubic meter; Indicates Planned path speed function, in meters per second.

[0122] The loop calculation module is connected to the rescue target value calculation module, and is used to increase the value of the flag variable by 1, and repeatedly execute the initialization module, the function generation module, the rescue target value calculation module, and the loop calculation module until the value of the flag variable is greater than Y .

[0123] Furthermore, the function generation module includes:

[0124] Mapping module, used to convert The planned path is mapped to the horizontal axis on the two-dimensional coordinate plane, and the first Distance horizontal axis; from the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Plan the path concentration function; calculate the The path distance between the decision point and the starting node is divided equally to obtain the first Driving distance .

[0125] The path speed conversion module is connected to the mapping module and is used to select the path speed in the road width sequence. Planning path related data, get the first width sequence; Width sequence and The distance is associated with the horizontal axis, and the mapping is obtained Width sequence and The functional relationship is recorded as Road Width Function ; Filter the building height sequence with the first Planning path related data, get the first Height sequence; Height sequence and The distance is associated with the horizontal axis, and the mapping is obtained Height sequence and The functional relationship is recorded as Height function According to Road Width Function , No. Height function The first speed function is calculated by the path speed conversion formula with the preset rescuer speed function and rescue vehicle speed function. Plan the path speed function; the path speed conversion formula is:

[0126] ;

[0127] in, represents the rescue vehicle speed function, represents the rescuer speed function, represents the first speed parameter, represents the second speed parameter, Indicates the third speed parameter.

[0128] Furthermore, the mapping module includes:

[0129] Concentration association module, used to search from the first branch node to the N In the branch node Plan the branch nodes that overlap the path and renumber them to get the first associated node to the associated node; Indicates The number of branch nodes that overlap in the planning path; Associate the node with the first branch node to the N The mapping relationship of the branch nodes is obtained from the first associated concentration to the Associated concentration.

[0130] The concentration distribution conversion module is connected to the concentration association module and is used to convert the first association node to the second association node. The associated node will The planned path is divided into path segments; calculate separately The length of the path segment is obtained The length of the first path segment of the planned path to the Planning the path Path segment length; the concentration distribution conversion formula is used to calculate the first Planning path concentration function; the concentration distribution conversion formula is:

[0131] ;

[0132] in, represents the first associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to An integer between .

[0133] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0134] Finally, it should be noted that: Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A fire rescue path planning method based on big data, characterized in that: The method comprises the following steps: S1, obtaining a three-dimensional road network map of a pre-defined fire rescue area, and mapping to obtain road network topology data; the road network topology data includes road network topology elements and connection relationships between road network topology elements; the road network topology elements include a first branch node to a second branch node; N Branch node, first driving link to the M Driving link, departure node, destination node; N Indicates the number of branch nodes, M Indicates the number of driving links; obtains the three-dimensional parameters of the road network in the three-dimensional road network diagram; S2, according to the road network topology data, traverse the driving links from the starting node to the target node to obtain associated driving links; combine the associated driving links to obtain the first driving path to the first driving path R Driving path; R Indicates the number of driving lanes; S3, connect the first driving path to the R The driving lanes are divided into equal parts according to the pre-set coefficients D Divide equally and get the first equal division decision point to the Y Equally divided decision points; Y is the number of equally divided decision points; the equally divided decision points are connected with the first driving path to the R The driving path combination obtains the first planned path to the Y Plan the path; read the pre-installed N The smoke density measured by the smoke density detector of the branch node is used to obtain the smoke density from the first smoke density to the second smoke density. N Smoke density; S4, according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Rescue target value; change the first rescue target value to the Y The planned path corresponding to the maximum value of the rescue target value is used as the optimal planned path for fire rescue; the equal division decision points corresponding to the optimal planned path for fire rescue are extracted and recorded as the optimal equal division decision points; in the optimal planned path for fire rescue, the section between the starting node and the optimal equal division decision point adopts the driving mode of taking the rescue vehicle, and the section between the optimal equal division decision point and the target node adopts the rescue personnel on foot.

2. The fire rescue path planning method based on big data according to claim 1, characterized in that: The method for obtaining three-dimensional parameters of a road network in a three-dimensional road network map comprises: Extract the heights of buildings on both sides of the road in the three-dimensional road network map to obtain a building height sequence; extract the road widths in the three-dimensional road network map to obtain a road width sequence; The building height sequence, road width sequence and road network topology data are combined to obtain the three-dimensional parameters of the road network.

3. The fire rescue path planning method based on big data as claimed in claim 2, characterized in that: The method according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Methods for rescuing target values ​​include: S31, set flag variable ; S32, according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Planning path speed function; S33, according to Planning path concentration function and The planning path speed function is calculated to obtain the Rescue target value ; said The calculation formula of rescue target value is: ； in, is the first target coefficient set in advance, is a preset second target coefficient; For the The path distance between any position on the planned path and the starting node, in meters; Indicates The path length of the planned path, in meters; Indicates Planning path concentration function, in milligrams per cubic meter; Indicates Planned path speed function, in meters per second; S34, increase the value of the flag variable by 1, and repeat steps S32 to S34 in sequence until the value of the flag variable is greater than Y .

4. The fire rescue path planning method based on big data as claimed in claim 3, characterized in that: The method according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Methods for planning path velocity functions include: The first The planned path is mapped to the horizontal axis on the two-dimensional coordinate plane, and the first Distance horizontal axis; from the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Plan the path concentration function; calculate the The path distance between the decision point and the starting node is divided equally to obtain the first Driving distance ; Filter the road width sequence with Planning path related data, get the first width sequence; Width sequence and The distance is associated with the horizontal axis, and the mapping is obtained Width sequence and The functional relationship is recorded as Road Width Function ; Filter the building height sequence with the first Planning path related data, get the first Height sequence; Height sequence and The distance is associated with the horizontal axis, and the mapping is obtained Height sequence and The functional relationship is recorded as Height function According to Road Width Function , No. Height function The first speed function is calculated by the path speed conversion formula with the preset rescuer speed function and rescue vehicle speed function. Plan the path speed function; the path speed conversion formula is: ； in, represents the rescue vehicle speed function, represents the rescuer speed function, represents the first speed parameter, represents the second speed parameter, Indicates the third speed parameter.

5. The fire rescue path planning method based on big data as claimed in claim 4, characterized in that: The method according to the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Methods for planning path concentration functions include: Search the first branch node to the N In the branch node Plan the branch nodes that overlap the path and renumber them to get the first associated node to the associated node; Indicates The number of branch nodes that overlap in the planning path; Associate the node with the first branch node to the N The mapping relationship of the branch nodes is obtained from the first associated concentration to the associated concentration; Using the first association node to the The associated node will The planned path is divided into path segments; calculate separately The length of the path segment is obtained The length of the first path segment of the planned path to the Planning the path Path segment length; the concentration distribution conversion formula is used to calculate the first Planning path concentration function; the concentration distribution conversion formula is: ； in, represents the first associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to An integer between .

6. The fire rescue path planning system based on big data is characterized by: The system comprises: The data reading module is used to obtain a three-dimensional road network map of a pre-defined fire rescue area and map it to obtain road network topology data; the road network topology data includes road network topology elements and connection relationships between road network topology elements; the road network topology elements include a first branch node to a second branch node; N Branch node, first driving link to the M Driving link, departure node, destination node; N Indicates the number of branch nodes, M Indicates the number of driving links; obtains the three-dimensional parameters of the road network in the three-dimensional road network diagram; The path traversal module is connected to the data reading module and is used to traverse the driving links from the starting node to the target node according to the road network topology data to obtain associated driving links; combine the associated driving links to obtain the first driving path to the target node; R Driving path; R Indicates the number of driving lanes; A path segmentation module is connected to the path traversal module and is used to divide the first driving path into the first R The driving lanes are divided into equal parts according to the pre-set coefficients D Divide equally and get the first equal division decision point to the Y Equally divided decision points; Y is the number of equally divided decision points; the equally divided decision points are connected with the first driving path to the R The driving path combination obtains the first planned path to the Y Plan the path; read the pre-installed N The smoke density measured by the smoke density detector of the branch node is used to obtain the smoke density from the first smoke density to the second smoke density. N Smoke density; The optimization calculation module is connected to the path segmentation module and is used to calculate the number of paths according to the three-dimensional parameters of the road network, the first smoke density and the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function are used to calculate the first planned path to the first planned path. Y Plan the rescue target value of the path, and get the first rescue target value to the Y Rescue target value; change the first rescue target value to the Y The planned path corresponding to the maximum value of the rescue target value is used as the optimal planned path for fire rescue; the equal division decision points corresponding to the optimal planned path for fire rescue are extracted and recorded as the optimal equal division decision points; in the optimal planned path for fire rescue, the section between the starting node and the optimal equal division decision point adopts the driving mode of taking the rescue vehicle, and the section between the optimal equal division decision point and the target node adopts the rescue personnel on foot.

7. The fire rescue path planning system based on big data according to claim 6, characterized in that: The data reading module comprises: The data extraction module is used to extract the heights of buildings on both sides of the road in the three-dimensional road network map to obtain a building height sequence; extract the road widths in the three-dimensional road network map to obtain a road width sequence; The data combination module is connected to the data extraction module and is used to combine the building height sequence, the road width sequence and the road network topology data to obtain the three-dimensional parameters of the road network.

8. The fire rescue path planning system based on big data according to claim 7, characterized in that: The optimization calculation module comprises: Initialization module, used to set flag variables ; The function generation module is connected to the initialization module and is used to generate the function according to the three-dimensional parameters of the road network, the first smoke density to the N The smoke concentration, the pre-set rescuer speed function and the rescue vehicle speed function will be The planned path is mapped onto the two-dimensional coordinate plane, and the Planning path concentration function and Planning path speed function; The rescue target value calculation module is connected to the function generation module and is used to calculate the rescue target value according to the first Planning path concentration function and The planning path speed function is calculated to obtain the Rescue target value ; said The calculation formula of rescue target value is: ； in, is the first target coefficient set in advance, is a preset second target coefficient; For the The path distance between any position on the planned path and the starting node, in meters; Indicates The path length of the planned path, in meters; Indicates Planning path concentration function, in milligrams per cubic meter; Indicates Planned path speed function, in meters per second; The loop calculation module is connected to the rescue target value calculation module, and is used to increase the value of the flag variable by 1, and repeatedly execute the initialization module, the function generation module, the rescue target value calculation module, and the loop calculation module until the value of the flag variable is greater than Y .

9. The fire rescue path planning system based on big data as claimed in claim 8, characterized in that: The function generation module comprises: Mapping module, used to convert The planned path is mapped to the horizontal axis on the two-dimensional coordinate plane, and the first Distance horizontal axis; from the first smoke density to the N The smoke concentration is calculated using the concentration distribution algorithm. Plan the path concentration function; calculate the The path distance between the decision point and the starting node is divided equally to obtain the first Driving distance ; The path speed conversion module is connected to the mapping module and is used to select the path speed in the road width sequence. Planning path related data, get the first width sequence; Width sequence and The distance is associated with the horizontal axis, and the mapping is obtained Width sequence and The functional relationship is recorded as Road Width Function ; Filter the building height sequence with the first Planning path related data, get the first Height sequence; Height sequence and The distance is associated with the horizontal axis, and the mapping is obtained Height sequence and The functional relationship is recorded as Height function According to Road Width Function , No. Height function The first speed function is calculated by the path speed conversion formula with the preset rescuer speed function and rescue vehicle speed function. Plan the path speed function; the path speed conversion formula is: ； in, represents the rescue vehicle speed function, represents the rescuer speed function, represents the first speed parameter, represents the second speed parameter, Indicates the third speed parameter.

10. The fire rescue path planning system based on big data according to claim 9, characterized in that: The mapping module comprises: Concentration association module, used to search from the first branch node to the N In the branch node Plan the branch nodes that overlap the path and renumber them to get the first associated node to the associated node; Indicates The number of branch nodes that overlap in the planning path; Associate the node with the first branch node to the N The mapping relationship of the branch nodes is obtained from the first associated concentration to the associated concentration; The concentration distribution conversion module is connected to the concentration association module and is used to convert the first association node to the second association node. The associated node will The planned path is divided into path segments; calculate separately The length of the path segment is obtained The length of the first path segment of the planned path to the Planning the path Path segment length; the concentration distribution conversion formula is used to calculate the first Planning path concentration function; the concentration distribution conversion formula is: ； in, represents the first associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates The associated concentration, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, Indicates Planning the path Path segment length, The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to Integers between The value range is 1 to An integer between .

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