CN114661055A - Emergency logistics vehicle optimal path planning method, device, equipment and storage medium - Google Patents
Emergency logistics vehicle optimal path planning method, device, equipment and storage medium Download PDFInfo
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- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
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Abstract
The invention relates to a path planning technology and discloses an optimal path planning method for an emergency logistics vehicle, which comprises the following steps: taking the road node, the current position and the target position as segmentation nodes to segment all the roads to obtain a plurality of road segments; acquiring all road damage information in the region and road damage point information identified by a satellite, which are manually fed back in a preset time interval; screening all road sections by using all road damage point information to obtain a target road section set; planning a path from the current position to the target position according to the road sections in the target road section set to obtain a target planned path; and issuing the target planning path to the emergency logistics vehicle. The invention also provides an emergency logistics vehicle optimal path planning recommendation device, equipment and a storage medium. The method and the system can improve the accuracy of the optimal path planning of the emergency logistics vehicle.
Description
Technical Field
The invention relates to a path planning technology, in particular to an optimal path planning method, device, equipment and storage medium for an emergency logistics vehicle.
Background
After an emergency occurs, a disaster site usually needs a large amount of emergency materials. Because the road network near the disaster site is usually destroyed, great difficulty is brought to the transportation of materials, and therefore path planning must be carried out for emergency logistics vehicles, and the timeliness of material distribution is improved.
However, the existing path planning method can only perform optimal path planning according to the damage condition of the road in the emergency logistics vehicle passing area reported by the manual history, and the damage condition of the road cannot be updated and matched in time, so that the accuracy of the optimal path planning of the emergency logistics vehicle is poor.
Disclosure of Invention
The invention provides an emergency logistics vehicle optimal path planning method and device, electronic equipment and a storage medium, and mainly aims to improve the accuracy of emergency logistics vehicle optimal path planning.
Acquiring road nodes of all roads between the current position of an emergency logistics vehicle in a preset area and a preset target position, wherein the distance between the current position and the target position is larger than a preset distance threshold;
taking the road node, the current position and the target position as segmentation nodes to segment all the roads to obtain a plurality of road segments;
acquiring all road damage information in the region fed back manually in a preset time interval, wherein the road damage information comprises: a first road damage point coordinate and a damage level of the first road damage point coordinate;
acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage level of the second road damage point coordinate;
screening all road sections according to the first road damage point coordinates, the second road damage point coordinates, the damage levels and a preset damage level threshold value to obtain a target road section set;
planning a path from the current position to the target position according to the road sections in the target road section set to obtain a target planned path;
and issuing the target planning path to the emergency logistics vehicle.
Optionally, the identifying the road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage level of the second road damage point coordinate includes:
performing image preprocessing operation on the satellite image to obtain a target satellite image, wherein the image preprocessing operation comprises the following steps: one or more of geometric correction processing, image enhancement processing and image optimization processing of vector registration processing;
utilizing a region extraction network in a preset road damage identification model to mark a road damage region in the target satellite image;
mapping the longitude and latitude information of the area to the target satellite image to obtain longitude and latitude coordinates of each pixel point in the target satellite image, and determining the longitude and latitude coordinates of a central pixel point in the road damage area as coordinates of the second road damage point;
carrying out convolution pooling on the marked road damage area by utilizing a convolution neural network in the road damage identification model to obtain damage characteristic data;
performing probability calculation of preset damage levels on the damage characteristic data by using a softmax activation function to obtain identification probabilities of different damage levels;
and determining the damage grade with the highest identification probability as the damage grade of the second road damage point coordinate corresponding to the road damage area.
Optionally, the screening all the road segments according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold to obtain a target road segment set, includes:
marking the road section corresponding to the road damage point coordinate by using the damage level of the first road damage point coordinate;
marking the road section corresponding to the road damage point coordinate by using the damage level of the second road damage point coordinate;
determining the maximum damage level of the road section mark as the final damage level of the road section;
and removing the road sections with the final damage levels larger than a preset damage level threshold value from all the road sections to obtain the target road section set.
Optionally, the planning a path from the current location to the target location according to the road segments in the target road segment set to obtain a target planned path includes:
determining the current position as an initial road node and determining the target position as a target road node;
starting from the starting road node, sequentially connecting adjacent road nodes along the direction from the starting road node to the target road node until the adjacent road nodes are connected to the target road node to obtain a node map;
judging whether a road section between any two adjacent road nodes in the node map exists in the target road section set or not, and updating the node map according to a judgment result to obtain a target node map;
determining a path from each current position to the target position in the target node graph as an initial planned path;
and calculating the passing time of the initial planned path, and determining the initial planned path with the shortest passing time in all the initial planned paths as the target planned path.
Optionally, the updating the node map according to the determination result to obtain the target node map includes:
when the judgment result is that the node graph exists, determining the node graph as the target node graph;
and when the judgment result is that the target node map does not exist, removing the connection of two corresponding adjacent road nodes in the node map to obtain the target node map.
Optionally, the calculating the transit time of the initial planned path includes:
acquiring the distances and speed limiting speeds of all road sections in the initial planned path;
calculating the section passing time of each road section in the initial planned path according to the distance and the speed limiting speed;
and calculating the road section passing time of all road sections corresponding to the initial planned path to obtain the passing time.
Optionally, the planning a path from the current location to the target location according to the road segments in the target road segment set to obtain a target planned path includes:
and continuously searching continuous road sections in the target road section set by using a preset path planning algorithm from the road section where the current position is located until the road where the terminal point is located is found, and combining all continuous road sections according to the continuous sequence to obtain the target planning path.
In order to solve the above problem, the present invention further provides an emergency logistics vehicle optimal path planning device, which includes:
the road section dividing module is used for acquiring road nodes of all roads between the current position of the emergency logistics vehicle in a preset area and a preset target position, wherein the distance between the current position and the target position is greater than a preset distance threshold; taking the road node, the current position and the target position as segmentation nodes to segment all the roads to obtain a plurality of road segments;
the road section screening module is used for acquiring all road damage information in the region, fed back manually in a preset time interval, wherein the road damage information comprises: a first road damage point coordinate and a damage level of the first road damage point coordinate; acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage grade of the second road damage point coordinate; screening all road sections according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road section set;
the path planning module is used for planning a path from the current position to the target position according to the road sections in the target road section set to obtain a target planned path; and issuing the target planning path to the emergency logistics vehicle.
In order to solve the above problem, the present invention also provides an electronic device, including:
a memory storing at least one computer program; and
and the processor executes the computer program stored in the memory to realize the optimal path planning method for the emergency logistics vehicle.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is executed by a processor in an electronic device to implement the emergency logistics vehicle optimal path planning method described above.
The embodiment of the invention obtains all road damage information in the region manually fed back in a preset time interval, wherein the road damage information comprises the following steps: a first road damage point coordinate and a damage level of the first road damage point coordinate; acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage grade of the second road damage point coordinate; screening all road sections according to the first road damage point coordinates, the second road damage point coordinates, the damage levels and a preset damage level threshold value to obtain a target road section set; the optimal path of the emergency logistics vehicle is planned from two levels of dynamic identification and path planning of the road damage information, the path planning is more comprehensive, meanwhile, the road damage information identified by the satellite image is used for supplementing the road damage information manually reported, the damaged road screening is more comprehensive and accurate, and the accuracy of the optimal path planning of the emergency logistics vehicle is further improved; therefore, the method, the device, the electronic equipment and the readable storage medium for planning the optimal path of the emergency logistics vehicle, which are provided by the embodiment of the invention, improve the accuracy of planning the optimal path of the emergency logistics vehicle.
Drawings
Fig. 1 is a schematic flow chart of an emergency logistics vehicle optimal path planning method according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of an emergency logistics vehicle optimal path planning apparatus according to an embodiment of the present invention;
fig. 3 is a schematic internal structural diagram of an electronic device for implementing an emergency logistics vehicle optimal path planning method according to an embodiment of the present invention;
the implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the invention provides an optimal path planning method for an emergency logistics vehicle. The execution subject of the emergency logistics vehicle optimal path planning method includes, but is not limited to, at least one of electronic devices such as a server and a terminal, which can be configured to execute the method provided by the embodiment of the application. In other words, the emergency logistics vehicle optimal path planning method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The server includes but is not limited to: the cloud server can be an independent server, or can be a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, Network service, cloud communication, middleware service, domain name service, security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Referring to fig. 1, a schematic flow diagram of an emergency logistics vehicle optimal path planning method according to an embodiment of the present invention is shown, in the embodiment of the present invention, the emergency logistics vehicle optimal path planning method includes:
s1, acquiring road nodes of all roads between the current position of the emergency logistics vehicle in the preset area and a preset target position, wherein the distance between the current position and the target position is larger than a preset distance threshold;
in the embodiment of the invention, the preset area is an administrative area allowing emergency logistics vehicles to run, the emergency logistics vehicles are vehicles for transporting emergency materials, the current position is the current position coordinate of the emergency logistics vehicle, the target position is the position coordinate of a planned destination of the emergency logistics vehicle, and the road nodes are the starting points and the intersection points of roads in the area, wherein the roads are roads which are designed in the area and can be used for the emergency logistics vehicles of the same type to run.
Further, in order to ensure that path planning can be more efficient, and avoid wasting computing resources by planning when the distance between the current position and the target position is too close, the embodiment of the present invention needs to ensure that the distance between the current position and the target position is greater than a preset distance threshold. The distance threshold in the embodiment of the present invention is set according to daily practice, and the embodiment of the present invention is not particularly limited.
S2, segmenting all roads by taking the road nodes, the current position and the target position as segmentation nodes to obtain a plurality of road segments;
in order to better perform path planning and effectively avoid the damaged road sections, the road nodes, the current position and the target position are used as segmentation nodes to segment all the roads to obtain a plurality of road sections.
For example: a, B, C three road nodes are totally arranged in the road A, the connecting direction of the three road nodes is A-B-C, then the road node is used as a segmentation node to segment the road A, and a road section A-B and a road section B-C are obtained.
S3, acquiring all road damage information in the region fed back manually in a preset time interval, wherein the road damage information comprises: a first road damage point coordinate and a damage level of the first road damage point coordinate;
in the embodiment of the present invention, in order to ensure that the road damage information has referential property, the time required to be fed back is limited, so that in the embodiment of the present invention, all the road damage information in the region fed back manually in a preset time interval is obtained, wherein the road damage information includes: the first road damage point coordinate and the corresponding damage level. Optionally, in the embodiment of the present invention, the preset time interval is a time period that is set in advance and can ensure the road damage information referential, for example, the preset time interval may be a time period within three days from the current time, and the embodiment of the present invention does not limit the preset time period.
Further, in this embodiment of the present invention, the damage level is a parameter value used to measure a degree of damage, and optionally, the damage level in this embodiment of the present invention includes: the system comprises a first stage, a second stage and a third stage, wherein the first stage represents that the system is basically intact, the second stage represents that partial damage can be passed conditionally, and the third stage represents that damage cannot be passed.
S4, acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage level of the second road damage point coordinate;
in the embodiment of the invention, in order to ensure that all road sections during path planning are passable, and some road sections cannot be manually patrolled and reported in time, and thus the damage information of the road sections is lost, and in order to more comprehensively detect the road damage information in the area, the current satellite image of the area is obtained, and the road damage point in the area is identified according to the satellite image. The satellite image is a satellite remote sensing image of the current high resolution of the region.
Specifically, in the embodiment of the present invention, identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage level of the second road damage point coordinate includes:
performing image preprocessing operation on the satellite image to obtain a target satellite image, wherein the image preprocessing operation comprises the following steps: one or more of geometric correction processing, image enhancement processing and vector registration processing;
utilizing a region extraction network in a preset road damage identification model to mark a road damage region in the target satellite image;
specifically, in the embodiment of the present invention, the regional extraction Network is an RPN (Region pro-social Network).
Mapping the longitude and latitude information of the area to the target satellite image to obtain longitude and latitude coordinates of each pixel point in the target satellite image, and determining the longitude and latitude coordinates of a central pixel point in the road damage area as coordinates of the second road damage point;
carrying out convolution pooling on the marked road damage area by utilizing a convolution neural network in the road damage identification model to obtain damage characteristic data;
performing probability calculation of preset damage levels on the damage characteristic data by using a softmax activation function to obtain identification probabilities of different damage levels;
and determining the damage grade with the highest identification probability as the damage grade of the second road damage point coordinate corresponding to the road damage area.
For example: the preset damage levels are a first level, a second level and a third level, the recognition probability of the first level is 0.6, the recognition probability of the second level is 0.65, and the recognition probability of the third level is 0.8, so that the third level is determined as the damage level of the second road damage point coordinate corresponding to the road damage area.
S5, screening all road sections according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road section set;
in order to screen out the road sections which cannot pass through, all the road sections are screened according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road section set.
In detail, in the embodiment of the present invention, the screening all the road segments according to the first road damage point coordinate, the second road damage point coordinate, the damage level, and a preset damage level threshold to obtain a target road segment set includes:
marking the road section corresponding to the road damage point coordinate by using the damage level of the first road damage point coordinate;
marking the road section corresponding to the road damage point coordinate by using the damage level of the second road damage point coordinate;
determining the maximum damage level of the road section mark as the final damage level of the road section;
and removing the road sections marked in all the road sections, wherein the final damage levels are greater than a preset damage level threshold value, so as to obtain a target road section set.
S6, planning a path from the current position to the target position according to the road sections in the target road section set to obtain a target planned path;
in the embodiment of the present invention, planning a path from the current location to the target location according to the road segments in the target road segment set to obtain a target planned path, including:
a node conversion step: determining the current position as an initial road node and determining the target position as a target road node;
and a node graph construction step: starting from the starting road node, sequentially connecting adjacent road nodes along the direction from the starting road node to the target road node until the adjacent road nodes are connected to the target road node to obtain a node map;
further, the node map building step in the embodiment of the present invention may be further replaced by the following step:
and starting from the starting road node, sequentially connecting road nodes closest to the current node along the direction from the starting road node to the target road node until the road nodes are connected to the target road node, and obtaining a node map.
In the embodiment of the present invention, the distance from the current node is an euclidean distance in a direction from the starting road node to the target road node, and needs to be greater than or equal to zero.
And a node map updating step: judging whether a road section between any two adjacent road nodes in the node map exists in the target road section set or not, and updating the node map according to a judgment result to obtain a target node map;
a path construction step: determining a path from each current position to the target position in the target node graph as an initial planned path;
path screening: and calculating the passing time of the initial planned path, and determining the initial planned path with the shortest passing time in all the initial planned paths as the target planned path.
Further, in the embodiment of the present invention, updating the node map according to the determination result to obtain a target node map includes:
when the judgment result is that the node graph exists, determining the node graph as the target node graph;
and when the judgment result is that the target node map does not exist, removing the connection of two corresponding adjacent road nodes in the node map to obtain the target node map.
Further, calculating the transit time of the initial planned path in the embodiment of the present invention includes:
acquiring the distances and speed limiting speeds of all road sections in the initial planned path;
calculating the section passing time of each road section in the initial planned path according to the distance and the speed limiting speed;
optionally, in the embodiment of the present invention, a road segment passing time of each road segment in the initial planned path is calculated by using the following formula:
wherein s isiIs the distance, v, of the road section iiIs the speed-limiting speed, t, of said road section iiA section transit time of the road section i, aiThe road traffic coefficient is preset.
And calculating the passage time of all road sections corresponding to the initial planned path to obtain the passage time.
Optionally, in the embodiment of the present invention, the passing time of all road segments corresponding to the initial planned path is added to obtain the passing time.
Further, in another embodiment of the present invention, starting from the road segment where the current position is located, a preset path planning algorithm is used to continuously search for a continuous road segment in the target road segment set until a road where the end point is located is found, and all continuous road segments are combined according to a continuous sequence to obtain the target planned path. Optionally, the path planning algorithm in the embodiment of the present invention includes, but is not limited to, an a-star algorithm and an ant colony algorithm, and the embodiment of the present invention does not set a range limit on the path planning algorithm.
And S7, issuing the target planning path to the emergency logistics vehicle.
Optionally, the target planning path is sent to the vehicle-mounted terminal of the emergency logistics vehicle in the embodiment of the invention.
In another embodiment of the invention, the target planning path is sent to the terminal equipment of the driver of the emergency logistics vehicle. The terminal devices include but are not limited to: intelligent terminal equipment such as cell-phone, flat board.
In the embodiment of the invention, the optimal path of the emergency logistics vehicle is planned from two levels of dynamic identification and path planning of the road damage information,
the embodiment of the invention obtains all road damage information in the region manually fed back in a preset time interval, wherein the road damage information comprises the following steps: a first road damage point coordinate and a damage level of the first road damage point coordinate; acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage grade of the second road damage point coordinate; screening all road sections according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road section set; the optimal path of the emergency logistics vehicle is planned from the two aspects of dynamic identification of the road damage information and path planning, the path planning is more comprehensive, meanwhile, the road damage information identified by the satellite image is used for supplementing the road damage information manually reported, the damaged road screening is more comprehensive and accurate, and the accuracy of the optimal path planning of the emergency logistics vehicle is further improved.
Fig. 2 is a functional block diagram of the optimal path planning device for emergency logistics vehicles according to the present invention.
The emergency logistics vehicle optimal path planning device 100 can be installed in electronic equipment. According to the realized functions, the device for planning the optimal path of the emergency logistics vehicle may include a road section segmentation module 101, a road section screening module 102, and a path planning module 103, which may also be referred to as a unit, and refers to a series of computer program segments that can be executed by a processor of the electronic device and can perform fixed functions, and the computer program segments are stored in a memory of the electronic device.
In the present embodiment, the functions of the respective modules/units are as follows:
the road segment segmentation module 101 is configured to acquire road nodes of all roads between a current position of an emergency logistics vehicle in a preset area and a preset target position, where a distance between the current position and the target position is greater than a preset distance threshold; taking the road node, the current position and the target position as segmentation nodes to segment all the roads to obtain a plurality of road segments;
the road section screening module 102 is configured to acquire all road damage information in the area, which is manually fed back in a preset time interval, where the road damage information includes: a first road damage point coordinate and a damage level of the first road damage point coordinate; acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage grade of the second road damage point coordinate; screening all road sections according to the first road damage point coordinates, the second road damage point coordinates, the damage levels and a preset damage level threshold value to obtain a target road section set;
the path planning module 103 is configured to plan a path from the current position to the target position according to the road segments in the target road segment set, so as to obtain a target planned path; and issuing the target planning path to the emergency logistics vehicle.
In detail, when the modules in the emergency logistics vehicle optimal path planning apparatus 100 according to the embodiment of the present invention are used, the same technical means as the emergency logistics vehicle optimal path planning method described in fig. 1 above are adopted, and the same technical effects can be produced, which is not described herein again.
Fig. 3 is a schematic structural diagram of an electronic device for implementing the emergency logistics vehicle optimal path planning method according to the present invention.
The electronic device may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may further include a computer program, such as an emergency logistics vehicle optimal path planning program, stored in the memory 11 and operable on the processor 10.
The memory 11 includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only to store application software installed in the electronic device and various types of data, such as codes of an emergency logistics vehicle optimal path planning program, etc., but also to temporarily store data that has been output or will be output.
The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the whole electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (such as an emergency logistics vehicle optimal path planning program) stored in the memory 11 and calling data stored in the memory 11.
The communication bus 12 may be a PerIPheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The communication bus 12 is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like. For ease of illustration, only one thick line is shown, but this is not intended to represent only one bus or type of bus.
Fig. 3 shows only an electronic device having components, and those skilled in the art will appreciate that the structure shown in fig. 3 does not constitute a limitation of the electronic device, and may include fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management and the like are realized through the power management device. The power source may also include any component of one or more dc or ac power sources, recharging devices, power failure classification circuits, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
Optionally, the communication interface 13 may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices.
Optionally, the communication interface 13 may further include a user interface, which may be a Display (Display), an input unit (such as a Keyboard), and optionally, a standard wired interface and a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The emergency logistics vehicle optimal path planning program stored in the memory 11 of the electronic device is a combination of a plurality of computer programs, and when running in the processor 10, can realize that:
acquiring road nodes of all roads between the current position of an emergency logistics vehicle in a preset area and a preset target position, wherein the distance between the current position and the target position is greater than a preset distance threshold value;
taking the road node, the current position and the target position as segmentation nodes to segment all the roads to obtain a plurality of road segments;
acquiring all road damage information in the region fed back manually in a preset time interval, wherein the road damage information comprises: a first road damage point coordinate and a damage level of the first road damage point coordinate;
acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage grade of the second road damage point coordinate;
screening all road sections according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road section set;
planning a path from the current position to the target position according to the road sections in the target road section set to obtain a target planned path;
and issuing the target planning path to the emergency logistics vehicle.
Specifically, the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the computer program, which is not described herein again.
Further, the electronic device integrated module/unit, if implemented in the form of a software functional unit and sold or used as a stand-alone travel product, may be stored in a computer readable storage medium. The computer readable medium may be non-volatile or volatile. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
Embodiments of the present invention may also provide a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program may implement:
acquiring road nodes of all roads between the current position of an emergency logistics vehicle in a preset area and a preset target position, wherein the distance between the current position and the target position is greater than a preset distance threshold value;
taking the road node, the current position and the target position as segmentation nodes to segment all the roads to obtain a plurality of road segments;
acquiring all road damage information in the region fed back manually in a preset time interval, wherein the road damage information comprises: a first road damage point coordinate and a damage level of the first road damage point coordinate;
acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage grade of the second road damage point coordinate;
screening all road sections according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road section set;
planning a path from the current position to the target position according to the road sections in the target road section set to obtain a target planned path;
and issuing the target planning path to the emergency logistics vehicle.
Further, the computer usable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it will be obvious that the term "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. An optimal path planning method for an emergency logistics vehicle is characterized by comprising the following steps:
acquiring road nodes of all roads between the current position of an emergency logistics vehicle in a preset area and a preset target position, wherein the distance between the current position and the target position is greater than a preset distance threshold value;
taking the road node, the current position and the target position as segmentation nodes to segment all the roads to obtain a plurality of road segments;
acquiring all road damage information in the region fed back manually in a preset time interval, wherein the road damage information comprises: a first road damage point coordinate and a damage level of the first road damage point coordinate;
acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage level of the second road damage point coordinate;
screening all road sections according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road section set;
planning a path from the current position to the target position according to the road sections in the target road section set to obtain a target planned path;
and issuing the target planning path to the emergency logistics vehicle.
2. The method for planning an optimal path for an emergency logistics vehicle according to claim 1, wherein the step of identifying the road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage level of the second road damage point coordinate comprises the steps of:
performing image preprocessing operation on the satellite image to obtain a target satellite image, wherein the image preprocessing operation comprises the following steps: one or more of geometric correction processing, image enhancement processing and image optimization processing of vector registration processing;
utilizing a region extraction network in a preset road damage identification model to mark a road damage region in the target satellite image;
mapping the longitude and latitude information of the area to the target satellite image to obtain longitude and latitude coordinates of each pixel point in the target satellite image, and determining the longitude and latitude coordinates of a central pixel point in the road damage area as coordinates of the second road damage point;
carrying out convolution pooling on the marked road damage area by utilizing a convolution neural network in the road damage identification model to obtain damage characteristic data;
performing probability calculation of preset damage levels on the damage characteristic data by using a softmax activation function to obtain recognition probabilities of different damage levels;
and determining the damage grade with the highest identification probability as the damage grade of the second road damage point coordinate corresponding to the road damage area.
3. The method for planning an optimal path of an emergency logistics vehicle according to claim 1, wherein the step of screening all road segments according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road segment set comprises:
marking the road section corresponding to the road damage point coordinate by using the damage level of the first road damage point coordinate;
marking the road section corresponding to the road damage point coordinate by using the damage level of the second road damage point coordinate;
determining the maximum damage level of the road section mark as the final damage level of the road section;
and removing the road sections with the final damage levels larger than a preset damage level threshold value from all the road sections to obtain the target road section set.
4. The method as claimed in claim 3, wherein the step of planning the path from the current location to the target location according to the road segments in the target road segment set to obtain a target planned path comprises:
determining the current position as an initial road node and determining the target position as a target road node;
starting from the starting road node, sequentially connecting adjacent road nodes along the direction from the starting road node to the target road node until the adjacent road nodes are connected to the target road node to obtain a node map;
judging whether a road section between any two adjacent road nodes in the node map exists in the target road section set or not, and updating the node map according to a judgment result to obtain a target node map;
determining a path from each current position to the target position in the target node graph as an initial planned path;
and calculating the passing time of the initial planned path, and determining the initial planned path with the shortest passing time in all the initial planned paths as the target planned path.
5. The method for planning the optimal path of the emergency logistics vehicle of claim 4, wherein the updating the node map according to the judgment result to obtain the target node map comprises:
when the judgment result is that the node graph exists, determining the node graph as the target node graph;
and when the judgment result is that the target node map does not exist, removing the connection of two corresponding adjacent road nodes in the node map to obtain the target node map.
6. The method for planning the optimal path of the emergency logistics vehicle of claim 4, wherein the calculating the transit time of the initial planned path comprises:
acquiring the distances and speed limiting speeds of all road sections in the initial planned path;
calculating the section passing time of each road section in the initial planned path according to the distance and the speed limiting speed;
and calculating the passage time of all road sections corresponding to the initial planned path to obtain the passage time.
7. The method for planning the optimal path of the emergency logistics vehicle according to any one of claims 1 to 6, wherein the step of planning the path from the current position to the target position according to the road segments in the target road segment set to obtain a target planned path comprises:
and continuously searching continuous road sections in the target road section set by using a preset path planning algorithm from the road section where the current position is located until the road where the destination is located is found, and combining all continuous road sections according to the sequence of connection to obtain the target planning path.
8. An emergency logistics vehicle optimal path planning device is characterized by comprising:
the road section segmentation module is used for acquiring road nodes of all roads between the current position of the emergency logistics vehicle in a preset area and a preset target position, wherein the distance between the current position and the target position is greater than a preset distance threshold; taking the road node, the current position and the target position as segmentation nodes to segment all the roads to obtain a plurality of road segments;
the road section screening module is used for acquiring all road damage information in the region, fed back manually in a preset time interval, wherein the road damage information comprises: a first road damage point coordinate and a damage level of the first road damage point coordinate; acquiring a current satellite image of the area, and identifying a road damage point in the area according to the satellite image to obtain a second road damage point coordinate and a damage grade of the second road damage point coordinate; screening all road sections according to the first road damage point coordinate, the second road damage point coordinate, the damage level and a preset damage level threshold value to obtain a target road section set;
the path planning module is used for planning a path from the current position to the target position according to the road sections in the target road section set to obtain a target planned path; and issuing the target planning path to the emergency logistics vehicle.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the emergency logistics vehicle optimal path planning method of any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the emergency logistics vehicle optimal path planning method of any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115440074A (en) * | 2022-08-24 | 2022-12-06 | 中国人民解放军军事科学院战争研究院 | Emergency road recommendation method based on M/M/1/N queuing |
| CN117405124A (en) * | 2023-12-13 | 2024-01-16 | 融科联创(天津)信息技术有限公司 | Path planning method and system based on big data |
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- 2022-05-10 CN CN202210504102.1A patent/CN114661055A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115440074A (en) * | 2022-08-24 | 2022-12-06 | 中国人民解放军军事科学院战争研究院 | Emergency road recommendation method based on M/M/1/N queuing |
| CN115440074B (en) * | 2022-08-24 | 2024-04-16 | 中国人民解放军军事科学院战争研究院 | Emergency road recommendation method based on M/M/1/N queuing |
| CN117405124A (en) * | 2023-12-13 | 2024-01-16 | 融科联创(天津)信息技术有限公司 | Path planning method and system based on big data |
| CN117405124B (en) * | 2023-12-13 | 2024-02-27 | 融科联创(天津)信息技术有限公司 | Path planning method and system based on big data |
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