Route guiding device and method based on topological map

Abstract

The invention relates to a route guiding device and method based on a topological map. The topological map-based route guidance apparatus may include: a topological map generated from a guidance map image based on optical character recognition (OCR) and image processing; a destination determiner configured to determine a position selected by a user in the topological map as a destination; a starting point determiner configured to determine a current position of a user as a starting point, the current position of the user being detected by comparing characters recognized from a surrounding image provided by the user with position information of the topological map; and a route generator configured to generate a final route from the starting point to the destination based on the degree of congestion and the degree of preference.

Description

[0001] Cross-references to related applications

[0002] This application claims priority and benefit to Korean Patent Application No. 10-2024-0079640, filed on June 19, 2024, with the Korean Intellectual Property Office, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This invention relates to a route guidance device and a route guidance method based on a topology map. More specifically, this invention relates to a route guidance device and a route guidance method based on a topology map that guides a user to the optimal route on the topology map. Background Technology

[0004] Traditional route-finding technologies can provide the fastest route for users or robots. However, in some cases, simply providing a fast route is not important to the user.

[0005] Traditional route-finding technologies fail to consider user safety, event intent, and other factors when controlling the density of people in each space. For example, traditional route-finding technologies cannot ensure that people gather in meaningful spaces during events or exhibitions. If too many people are gathered in a space, traditional route-finding technologies cannot provide directions to help people avoid crowded areas, taking safety into account. The subject matter described in this background section is intended to facilitate an understanding of the background of the invention and may therefore include topics not yet known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a route guidance device and a route guidance method based on a topology map, which can guide situation-customized routes by utilizing a topology map to which various information fragments can be added, taking into account the congestion level of the passage and the route preference of the administrator.

[0007] A route guidance device based on a topology map may include a topology map, generated from a guidance map image based on optical character recognition (OCR) and image processing. The device may also include a destination determiner configured to identify a location selected by the user in the topology map as the destination. The device may further include a origin determiner configured to identify the user's current location as the origin, detected by comparing characters recognized from surrounding images provided by the user with location information in the topology map. The device may also include a route generator configured to generate a final route from the origin to the destination based on congestion levels and preference levels.

[0008] The topology map can include a plurality of nodes disposed in a travel lane on the map and respectively storing location information. The topology map can include edges connecting the nodes.

[0009] The start point determiner can be configured to estimate a specific node on the topology map having location information matching a character recognized in the surrounding image as the current location of the user.

[0010] The route generator can be configured to use the detected route as a final route and stop the route generation when a route passing through the start point and the destination is detected from the pre-stored routes.

[0011] The route generator can calculate a congestion degree based on a real-time number of people obtained through a closed-circuit television (CCTV) of the travel lane and an area of the lane. The congestion degree is calculated for each edge.

[0012] The route generator can be configured to calculate the congestion degree of each edge through Equation 1.

[0013] [Equation 1]

[0014]

[0015] The optimal number of people for the lane is a value predetermined based on the area of the lane.

[0016] When the preference degree value preset by the administrator is low, the preference degree is considered to be high, and the preference degree can be set for each edge.

[0017] The route generator can be configured to generate a route including a plurality of edges having a low congestion degree and a high preference degree as a final route.

[0018] The route generator can be configured to determine a route having a shortest distance between the start point and the destination as a final route. When there are a plurality of candidate routes having the same distance between the start point and the destination, a candidate route having a low congestion degree and a high preference degree among the plurality of candidate routes is determined as a final route.

[0019] The route generator can be configured to determine a cost of each candidate route through Equation 2 and determine a candidate route having a lowest cost as a final route.

[0020] [Equation 2]

[0021] Cost(edge id) = distance(node1, node2) x edge congestion degree x administrator factor

[0022] Node 1 is a first side node of a route determining edge, node 2 is a second side node of the route determining edge, distance(node 1, node 2) is a distance between the first side node and the second side node, edge congestion degree is a congestion degree of each edge, and administrator factor is a route preference degree value of the administrator for each edge.

[0023] The route guidance method based on the topology map can include providing a topology map generated based on OCR and image processing from a guide map image. The method can further include determining a location selected by a user in the topology map as a destination. The method can further include determining a current location of the user as a starting point, which is detected by comparing characters recognized from a surrounding image provided by the user with location information of the topology map. The method can further include generating a final route from the starting point to the destination based on the congestion degree and the preference degree.

[0024] The topology map can include a plurality of nodes disposed in a travel lane on a map and respectively storing location information. The topology map can include edges connecting the nodes.

[0025] Determining the starting point can include estimating a specific node on the topology map having location information matching characters recognized in the surrounding image as the current location of the user.

[0026] Generating the final route can include using a detected route as the final route and stopping route generation when a route passing through the starting point and the destination is detected from the pre-stored routes.

[0027] Generating the final route can include calculating the congestion degree based on a real-time number of people obtained through a closed-circuit television of the travel lane and an area of the lane. Generating the final route can include calculating the congestion degree of each edge.

[0028] Generating the final route can further include calculating the congestion degree of each edge through Equation 1.

[0029] [Equation 1]

[0030]

[0031] The optimal number of people for the lane is a value predetermined based on an area of the lane.

[0032] When the preference degree value preset by the administrator is low, the preference degree is considered to be high, and the preference degree can be set for each edge.

[0033] Generating the final route can further include generating a route including a plurality of edges having a low congestion degree and a high preference degree as the final route.

[0034] The generating of the final route can include determining a route having the shortest distance between the start point and the destination as the final route. When there are a plurality of candidate routes having the same distance between the start point and the destination, a candidate route having a low congestion degree and a high preference degree among the plurality of candidate routes is determined as the final route.

[0035] The generating of the final route can further include determining a cost of each candidate route by Equation 2, and determining a candidate route having the lowest cost as the final route.

[0036] [Equation 2]

[0037] Cost(edge id) = Distance(node 1, node 2) x Edge Congestion Degree x Admin Factor

[0038] Node 1 is a first side node of an edge for which a route is determined, node 2 is a second side node of the edge for which the route is determined, Distance(node 1, node 2) is a distance between the first side node and the second side node, Edge Congestion Degree is a congestion degree of each edge, and Admin Factor is a route preference degree value of each edge by an administrator.

[0039] The topology map-based route guidance device and the topology map-based route guidance method according to the embodiments can guide a situation-based customized route by considering a congestion degree of a passage and a route preference degree of an administrator, by using a topology map to which various pieces of information can be added. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 A topology map system according to an embodiment of the present application is schematically shown.

[0041] Figure 2 is a block diagram of a topology map-based route guidance device according to an embodiment of the present application.

[0042] Figure 3 is a flowchart of a topology map-based route guidance method according to an embodiment of the present application.

[0043] Figure 4 is a schematic diagram for explaining a topology map-based route guidance method according to an embodiment of the present application. Figure 3

[0044] Figure 5 is a flowchart of a topology map-based route guidance method according to an embodiment of the present application.

[0045] Figure 6 and Figure 7 is a schematic diagram for explaining a topology map-based route guidance method according to an embodiment of the present application.

[0046] Figure 8 ​is a schematic diagram for explaining a computing device according to an embodiment of the present application. DETAILED DESCRIPTION

[0047] Embodiments of the present application will be described more fully hereinafter with reference to the accompanying drawings, in which embodiments of the application will be shown. Like reference numerals can be used to refer to like elements throughout. As this description proceeds, an embodiment will be described as being implemented in one or more specific implementations and with reference to one or more specific drawing figures. It is to be understood that the embodiments are presented by way of example only, and that other embodiments can be implemented.

[0048] In addition, unless explicitly described to the contrary, the word "comprise" and variations such as "comprises" or "comprising" will be understood to imply the inclusion of stated elements but not the exclusion of any other elements. The terms "first", "second", and the like, as can be used herein, are meant to be illustrative and are not intended to be limiting. The terms are used to distinguish one element from another.

[0049] In addition, in the present application, terms such as "unit", "component", or "part", "device", and "module" refer to a unit that processes at least one function or operation, which can be implemented by hardware, software, or a combination of hardware and software. When a controller, module, component, device, element, unit, part, "device", etc. of the present application is described as having a purpose or performing an operation, function, etc., in this document, the controller, module, component, device, element, unit, part, "device", etc. should be considered as being "configured to" satisfy the purpose or perform the operation or function. Each controller, module, component, device, element, unit, part, "device", etc. can be embodied as a separate part of a device or included in a processor and a memory, for example, a non-volatile computer readable medium, as a whole.

[0050] Hereinafter, embodiments of the present application will be described with reference to the accompanying drawings.

[0051] Figure 1 A topological map system according to an embodiment of the present application is schematically shown.

[0052] The topological map system can generate a topological map 110 through a topological map generation device TMM.

[0053] When a user provides a photo of characters around the user or an image 20a around the user through an application or the like, the topological map system can recognize characters through an optical character recognition (OCR) module 30, can find matching characters through an OCR filter 40, and can estimate a current position PL of the user on the topological map 110 based on these through a position finding module 50.

[0054] When the user inputs the destination selection 20b, the topological map system can provide a topological map-based route guidance map 70 through the route guidance device 100 based on the estimated current location PL of the user.

[0055] In Figure 1 The topological map generation device TMM can generate a topological map 110 from a simple guidance map image 10.

[0056] The topological map generation device TMM can create a topological map TM capable of position search and route service search by utilizing a simple guidance map.

[0057] The topological map generation device TMM can operate offline and on a server. The greatest difference from existing precise map creation is that a map capable of providing a position estimation and a route search service for people can be created without collecting sensor data at a service site.

[0058] The topological map generation device TMM can be configured to perform a process of creating nodes and edges and a process of inputting location information. The topological map generation device TMM includes an automatic mode and a manual mode in each of the two processes.

[0059] In the automatic mode, the topological map generation device TMM can recognize characters from the guidance map 10 by utilizing the OCR module 30, can extract a polygon to automatically create nodes and edges by utilizing an image processing technique, and can store location information in the created topological map 110 by utilizing the recognition result of the OCR module 30.

[0060] In the manual mode, the topological map generation device TMM can provide an interface for generating and / or modifying the topological map 110 to a user.

[0061] The topological map generation device TMM can store location information in nodes of the topological map 110. For example, the topological map generation device TMM can store location information of a location, a word list, an image around a word, etc. in the nodes of the topological map 110.

[0062] The topological map generation device TMM can store a distance between nodes, information of connected nodes, etc. in edges of the topological map 110.

[0063] In an embodiment, the topological map 110 can store location information in a word dictionary WD. The word dictionary WD can store words matching the location information stored in the nodes in Korean and English.

[0064] In Figure 1In this context, the topology map-based route guidance device 100 can leverage the advantages of adding various information fragments to the topology map 110 and quickly applying changes to provide a route guidance method customized based on congestion levels and preferences.

[0065] In other words, the route guidance device 100 based on the topology map can use the user's current location determined by the location lookup module 50 as the starting point to find the shortest route to the user's selected destination in the dictionary WD of the topology map 110.

[0066] In the process of finding the shortest route, the route guidance device 100 based on the topology map can reflect the congestion level of the roads the user travels and the route preference of the administrator.

[0067] The route guidance device 100 based on topology maps can provide route finding or route guidance services with various intentions by taking advantage of the advantages of topology maps.

[0068] By reflecting the number of people and the area of ​​the passageway obtained from closed-circuit television (CCTV) into the topology map 110, the route guidance device 100 based on the topology map can guide the route so that people do not gather in one place (reflecting the degree of congestion).

[0069] When there is a space that event organizers or exhibition artists want people to gather in, the topological map-based route guidance device 100 can guide people through the space by providing route guidance (reflecting the degree of preference).

[0070] When a user enters multiple destinations they wish to visit, the topology-based route guidance device 100 can provide route guidance services, enabling the user to access all destinations most efficiently.

[0071] By leveraging the scalability of space (another advantage of the topology map 110), the topology map-based route guidance device 100 can provide route finding services at low cost over a wide area.

[0072] Figure 2 This is a block diagram of a route guidance device based on a topology map according to an embodiment of the present invention.

[0073] refer to Figure 2 The route guidance device 100 based on the topology map may include: a topology map 110, a destination determiner 120, a starting point determiner 130, and a route generator 140.

[0074] It can be based on the guide map image 10 (see Figure 1 ), via the topology map generation device TMM (see Figure 1A topology map 110 is generated based on OCR and image processing. The topology map 110 may include nodes storing location information and may include edges connecting the nodes. Nodes can be estimated based on the user's location, and edges can be configured along the user's movement path.

[0075] The destination determiner 120 can determine the location selected by the user on the topology map 110 as the destination. In other words, when the user enters the location information of the destination on the topology map 110, the destination determiner 120 can determine it as the destination.

[0076] The starting point determiner 130 can determine the starting point by taking the user-provided image 20a around the user (see...) Figure 1 The characters identified in the map are compared with location information stored in the topology map to determine the current location (PL) of the detected user. Figure 1 (This is determined as the starting point.)

[0077] Location information can be stored for each node in the topology map. This location information can be stored in the topology map's dictionary (WD). The location information can include words matching the location, and words can be configured using Korean and English characters.

[0078] The starting point determiner 130 can estimate the user's current location by identifying a specific node on the topology map that has location information that matches the recognized characters in the image around the user.

[0079] The starting point determiner 130 can be accessed via OCR filter 40 (see...). Figure 1 ) Filter out the results from OCR module 30 (see Figure 1 The identified characters are used to determine the final character. The starting point determiner 130 can identify the node on the topology map 110 that has location information that matches the final character as the user's current location, and can determine the user's current location as the starting point.

[0080] The route generator 140 can take into account congestion levels and preference levels to generate the final route from the origin to the destination.

[0081] When a route passing through a start point and a destination is detected from the pre-stored routes, the route generator 140 can use the detected route as the final route and can stop route generation.

[0082] The route generator 140 can calculate the level of congestion based on the real-time number of people and the area of ​​the passageway obtained from CCTV footage of the passageway through which the user travels. Congestion level can be calculated for each edge.

[0083] Route generator 140 can calculate the congestion level of each edge using Equation 1.

[0084] [Equation 1]

[0085]

[0086] Here, the optimal number of people in the passage is based on a predetermined value for the passage area.

[0087] When the administrator's preset preference level is low, the preference level is considered high. The preference level can be set for each edge.

[0088] The route generator 140 can generate a final route from multiple edges that include low congestion and high preference.

[0089] The route generator 140 can determine the route with the shortest distance between the origin and the destination as the final route.

[0090] When there are multiple candidate routes with the same distance between the origin and destination, the route generator 140 can determine the candidate route with low congestion and high preference as the final route.

[0091] The route generator 140 can determine the cost of each candidate route using Equation 2, and can determine the candidate route with the lowest cost as the final route.

[0092] [Equation 2]

[0093] Cost (edge ​​ID) = Distance (vertex 1, vertex 2) × Edge congestion level × Administrator factor

[0094] Here, node 1 is the first side node of the edge that determines the route, node 2 is the second side node of the edge that determines the route, distance (node ​​1, node 2) is the distance between the first side node and the second side node, edge congestion is the congestion level of each edge, and administrator factor is the route preference value of the administrator for each edge.

[0095] One of the first or second side nodes of the edge that determines the route can be the starting point, and the other can be the destination.

[0096] Figure 3 This is a flowchart of a route guidance method based on a topology map according to an embodiment of the present invention. The route guidance method based on a topology map can be implemented using a route guidance device 100 based on a topology map (see...). Figure 1 ) to execute.

[0097] exist Figure 3 In step S100, the route guidance device 100 based on the topology map can provide a topology map generated from a guidance map image based on OCR and image processing.

[0098] A topology map can include multiple nodes positioned along the user's path, each storing its own location information. The topology map can also include edges connecting the nodes.

[0099] In step S200, the route guidance device 100 based on the topology map can determine the location selected by the user in the topology map as the destination.

[0100] In step S300, the route guidance device 100 based on the topology map can determine the current location of the detected user as the starting point by comparing the characters identified from the user-provided image of the user's surroundings with the location information of the topology map.

[0101] The topology-based route guidance device 100 can estimate the user's current location by identifying specific nodes on the topology map that have location information that matches characters recognized in the user's surrounding image.

[0102] In step S400, the route guidance device 100 based on the topology map can generate the final route from the origin to the destination by taking into account the degree of congestion and the degree of preference.

[0103] When a route passing through the origin and destination exists in the pre-stored routes, the route guidance device 100 based on the topology map can use the corresponding route as the final route and can stop route generation.

[0104] The topology-based route guidance device 100 can determine the route with the shortest distance between the origin and the destination as the final route. When there are multiple candidate routes with the same distance between the origin and the destination, the topology-based route guidance device 100 can determine the candidate route with low congestion and high preference among the multiple candidate routes as the final route.

[0105] Figure 4 It is used to explain the basis Figure 3 A schematic diagram of the route guidance method based on topology maps in the implementation scheme.

[0106] exist Figure 4 In this context, based on a route guidance method using a topological map, an image 20a of the user's surroundings can be provided as user input 20a. Users can take photos and upload pictures of signs, markers, etc., around them to provide photos of the surrounding characters as user input 20a.

[0107] Subsequently, based on user input 20a, it can be implemented using the OCR module 30 (see... Figure 1 Character recognition and character position detection are performed to generate OCR result image 20b. OCR result image 20b can identify all characters and character positions included in the photo surrounding the user.

[0108] Subsequently, through OCR filter 40 (see...) Figure 1 The OCR filter image 20c can be generated by extracting only the necessary characters from the OCR result image 20b and filtering out the other characters. The OCR filter result image 20c can include only the final characters that match the characters stored in the topology map (or the dictionary of the topology map), and exclude the unnecessary characters in the OCR result image 20b.

[0109] Subsequently, the location lookup module 50 (see...) Figure 1 The current position PL of the user on the topology map 110 can be calculated based on the OCR filter result image 20c. The current position PL can be determined as the user's starting point.

[0110] The final detected user current location PL can be detected as a specific node on the topology map that stores location information that matches the characters in the OCR result image 20b.

[0111] Furthermore, based on the topology-based route guidance method, a topology-based route guidance map 70 can be provided from the origin to the destination.

[0112] The route guidance map 70 based on the topology map can provide users with the final route RT on the topology map by reflecting the degree of congestion of passages where people gather and the degree of preference of the administrator.

[0113] Figure 5 This is a flowchart of a route guidance method based on a topology map according to an embodiment of the present invention.

[0114] The route guidance device 100 based on the topology map can use the current location estimated by the location lookup module as the starting point to find the shortest route to the destination selected by the user in the topology map.

[0115] When route guidance is initiated in step S510 based on a user request, in steps S520 and S530, the route guidance device 100 based on the topology map can determine whether the user's current location has been estimated and whether the destination has been determined.

[0116] In other words, the route guidance device 100 based on the topology map can function once the current location and destination are determined.

[0117] In the topology-based route guidance device 100, since the starting point is determined based on OCR location lookup and the destination is determined based on the topology map, there may be multiple starting points and multiple destinations. The optimal route can be found using information obtained from CCTV via a control server.

[0118] Furthermore, the route guidance device 100 based on topology maps can find routes from multiple topology maps.

[0119] When the user's current location has been estimated (step S520 is "Yes") and when the destination has been determined (step S530 is "Yes"), in step S540, the route guidance device 100 based on the topology map can determine whether it is a single destination.

[0120] When a starting point and a destination are set and there is more than one destination (step S540 is "No"), in step S550, the route guidance device 100 based on the topology map can begin to find the route to the destination.

[0121] When the input image of the user's surroundings is one and there are multiple locations on the map extracted from the image, various starting point nodes may appear.

[0122] The route guidance device 100 based on the topology map can find multiple routes in the topology map while avoiding duplication.

[0123] In step S551, before finding the route from the starting node estimated as the current location to the destination node, the route guidance device 100 based on the topology map can list the nodes estimated as the current location in ascending order of distance to the destination.

[0124] The route guidance device 100 based on the topology map can use the A* algorithm (commonly known as the A* algorithm) to find the route from the starting node estimated as the current location to the destination node.

[0125] When determining the cost in the A* algorithm, various factors can be input. The algorithm of this invention can consider the distance between the starting node and the destination node, the number of people detected by CCTV, and the channel area estimated by CCTV, and calculate the cost according to Equation 2.

[0126] [Equation 2]

[0127] Cost (edge ​​ID) = Distance (vertex 1, vertex 2) × Edge congestion level × Administrator factor

[0128] Here, node 1 is the first side node of the edge that determines the route, node 2 is the second side node of the edge that determines the route, distance (node ​​1, node 2) is the distance between the first side node and the second side node, edge congestion is the congestion level of each edge, and administrator factor is the route preference value of the administrator for each edge.

[0129] One of the first or second side nodes of the edge determining the route can be the starting point, and the other can be the destination. In other words, through Equation 2, the route guidance device 100 based on the topology map can determine the cost of each of the multiple candidate routes from the starting point to the destination, and can determine the candidate route with the lowest cost as the final route.

[0130] In step S552, the route guidance device 100 based on the topology map can determine whether the starting point and the destination are in the same topology map.

[0131] When the origin and destination do not exist in the same topology map (step S552 is "No"), in step S553, the route guidance device 100 based on the topology map can determine whether topology maps containing the origin and destination can be combined. When topology maps containing the origin and destination can be combined (step S553 is "Yes"), in step S554, the route guidance device 100 based on the topology map can combine them into a single topology map including the origin and destination.

[0132] For example, when the origin and destination are located in different layers or have different spatial names in the same layer, the topology-based route guidance device 100 can create topology maps separately.

[0133] For example, when the names of steps or doors used for elevator access are consistent across different topology maps, the topology map-based route guidance device 100 can provide the same service by combining them into a single topology map.

[0134] When a user enters multiple destinations, the route guidance device 100 based on a topology map can generate the optimal route by utilizing the TSP algorithm.

[0135] Following step S554, or when it is a single destination (step S540 is "Yes"), in step S555, the route guidance device 100 based on the topology map can determine whether the previous route has already passed the starting node estimated as the current location. When the previous route has already passed the starting node (step S555 is "Yes"), this means that the optimal route has been found and there is no need to find a new route.

[0136] In other words, a new route needs to be found in step S556 to reduce computational costs only if the previous route did not pass through the starting node (step S555 is "No"). The route guidance device 100 based on the topology map can search for routes in the topology map. The destination can also include multiple destination nodes depending on its size.

[0137] The route guidance device 100 based on a topology map can calculate the degree of congestion based on the real-time number of people and the area of ​​the passageway obtained from CCTV footage of the passageway through which the user travels. The degree of congestion can be calculated for each edge.

[0138] The route guidance device 100 based on the topology map can detect the number of people via CCTV in step S10, and can calculate the congestion level of each edge via Equation 1 in step S20.

[0139] [Equation 1]

[0140]

[0141] Here, the optimal number of people in the passage is based on a predetermined value for the passage area.

[0142] When the administrator's preset preference level value is low, it is considered that the preference level is high, and the preference level can be set for each edge.

[0143] The route guidance device 100 based on the topology map can generate a final route from multiple edges that include low congestion and high preference.

[0144] In steps S556 and S557, the route guidance device 100 based on the topology map can determine the route with the shortest distance between the starting point and the destination as the final route. Specifically, in step S557, the route guidance device 100 based on the topology map can determine whether there exists a route with the shortest distance between the starting point and the destination.

[0145] In steps S556 and S557, when there are multiple candidate routes with the same distance between the origin and destination, the route guidance device 100 based on the topology map can determine the candidate route with low congestion and high preference among the multiple candidate routes as the final route.

[0146] Therefore, when a route with the shortest distance between the origin and destination exists (step S557 is "Yes"), in step S558, the route guidance device 100 based on the topology map can store this route. The route guidance device 100 based on the topology map can search for routes to all possible destination nodes, and then in step S559, the shortest route can be added to the recommended routes. In step S560, the route guidance device 100 based on the topology map can add route information.

[0147] In step S50, after confirming all starting point nodes included in the starting point, the route guidance device 100 based on the topology map can visually notify the user of all the calculated recommended routes through the topology map.

[0148] When many destinations are entered, the route guidance device 100 based on the topology map can generate the best route in step S570 by using the TSP algorithm, and can recommend the generated best route to the user in step S580.

[0149] Figure 6 and Figure 7 This is an example diagram used to explain the route guidance method based on a topology map according to an embodiment of the present invention.

[0150] Figure 6 This is an example diagram used to explain route guidance based on the congestion level calculated using Equation 1.

[0151] [Equation 1]

[0152]

[0153] Here, the optimal number of people in the passage is based on a predetermined value for the passage area.

[0154] As a premise of example diagram EX1, route 1 and route 2 can have the same distance.

[0155] Route 1 can pass through Route 2 can be through The route.

[0156] The information for edge 1 and edge 2 detected by CCTV is as follows.

[0157] Side 1: Distance 20, optimal number of people: 5

[0158] Side 2: Distance 20, optimal number of people: 5

[0159] In scenario 1, the number of people detected by CCTV in channel 1 can be 1, while the number of people detected by CCTV in channel 2 can be 5. The route guidance device 100 based on the topology map can ultimately select route 1 (reason: the congestion level of edge 1 is less than the congestion level of edge 2).

[0160] [Equation 2]

[0161] Cost (edge ​​ID) = Distance (vertex 1, vertex 2) × Edge congestion level × Administrator factor

[0162] Here, node 1 is the first side node of the edge that determines the route, node 2 is the second side node of the edge that determines the route, distance (node ​​1, node 2) is the distance between the first side node and the second side node, edge congestion is the congestion level of each edge, and administrator factor is the route preference value of the administrator for each edge.

[0163] The route guidance device 100 based on the topology map can recommend route 1 as the final route to the user based on the cost calculated according to Equation 2 as follows.

[0164] Cost (edge ​​1) = Distance (node ​​2, node 4) × (1 + 1 / 5) × 1 = 24

[0165] Cost (edge ​​2) = Distance (node ​​3, node 5) × (1 + 5 / 5) × 1 = 40

[0166] In scenario 2, the number of people detected by CCTV in channel 1 can be 4, while the number of people detected by CCTV in channel 2 can be 2. The route guidance device 100 based on the topology map can ultimately select route 2 (reason: the congestion level of edge 1 is greater than that of edge 2).

[0167] In other words, the route guidance device 100 based on the topology map can recommend route 2 as the final route to the user based on the cost calculated according to Equation 2 as follows.

[0168] Cost (edge ​​1) = Distance (node ​​2, node 4) × (1 + 4 / 5) × 1 = 36

[0169] Cost (edge ​​2) = Distance (node ​​3, node 5) × (1 + 2 / 5) × 1 = 28

[0170] Figure 7 This is an example diagram used to explain route finding using administrator factors (degree of preference).

[0171] The administrator factor can be a preference level value predetermined by the administrator.

[0172] exist Figure 7 In the example graph EX2, the administrator factor can be set to minimum: 1.0, maximum: 2.0, and default: 1.5.

[0173] In other words, an administrator can assign values ​​closer to 1.0 to edges that more users want to traverse, and values ​​closer to 2.0 to edges that fewer users want to traverse. Therefore, an administrator can guide service users along the administrator's intended routes. For example, an administrator can guide roads so that more people can gather in a specific activity space.

[0174] In example diagram EX2, it can be assumed that route 1 and route 2 are the same distance.

[0175] Route 1:

[0176] Route 2:

[0177] The information for edge 1 and edge 2 can be assumed as follows.

[0178] Side 1 Distance 30, optimal number of people: 15, number of people detected: 5, edge 2 Distance 30, optimal number of people: 15, number of people detected: 5. Case 1 can represent the situation where people want to take route 1 through edge 2.

[0179] The administrator can set the administrator factor of edge 1 to 2.0 and the administrator factor of edge 2 to 1.0.

[0180] Therefore, the route guidance device 100 based on the topology map can select route 1 (reason: cost (edge ​​2) < cost (edge ​​1).

[0181] In other words, the route guidance device 100 based on the topology map can recommend route 1 as the final route to the user based on the cost calculated according to Equation 2 as follows.

[0182] Cost (edge ​​1) = Distance (node ​​2, node 3) × 5 / 15 × 2.0 = 20

[0183] Cost (edge ​​2) = Distance (node ​​4, node 5) × 5 / 15 × 1.0 = 10

[0184] Case 2 can represent the situation where people want to take route 2 through edge 1.

[0185] Administrator factor of edge 1: 1.0

[0186] Administrator factor of edge 2: 2.0

[0187] The route guidance device 100 based on the topology map can select route 2 as the recommended route (reason: cost (edge ​​2) > cost (edge ​​1)).

[0188] In other words, the route guidance device 100 based on the topology map can recommend route 2 as the final route to the user based on the cost calculated according to Equation 2 as follows.

[0189] Cost (edge ​​1) = Distance (node ​​2, node 3) × 5 / 15 × 1.0 = 10

[0190] Cost (edge ​​2) = Distance (node ​​4, node 5) × 5 / 15 × 2.0 = 20

[0191] Figure 8 This is a diagram used to explain a computing device according to an embodiment of the present invention.

[0192] refer to Figure 8 The route guidance device and method based on the topology map according to the implementation plan can be implemented using a computing device 900.

[0193] The computing device 900 may include at least one processor 910, a memory 930, a user interface input device 940, a user interface output device 950, and a storage device 960, all communicating via a bus 920. The computing device 900 may also include a network interface 970 electrically connected to a network 90. ​​The network interface 970 can send or receive signals with other objects via the network 90.

[0194] Processor 910 can be implemented in various types, such as a microcontroller unit (MCU), application processor (AP), central processing unit (CPU), graphics processing unit (GPU), neural processing unit (NPU), etc. Processor 910 can be any type of semiconductor device capable of executing instructions stored in memory 930 or storage device 960. Processor 910 can be configured to implement the above-mentioned... Figures 1 to 7 The functions and methods described herein.

[0195] The memory 930 and storage device 960 may include various types of volatile or non-volatile storage media. For example, the memory may include read-only memory (ROM) 931 and random access memory (RAM) 932. In this embodiment, the memory 930 may be located inside or outside the processor 910, and the memory 930 may be connected to the processor 910 in various known ways.

[0196] In some implementations, at least some configurations or functions of the topology map-based route guidance device and the topology map-based route guidance method according to the implementation can be implemented as a program or software executable by the computing device 900, and the program or software can be stored in a computer-readable medium.

[0197] In some implementations, at least some configurations or functions of the topology map-based route guidance device and the topology map-based route guidance method according to the implementation can be implemented by utilizing the hardware or circuitry of the computing device 900, or can be implemented as separate hardware or circuitry that can be electrically connected to the computing device 900.

[0198] Although the invention has been described in conjunction with embodiments, it should be understood that the invention is not limited to the disclosed embodiments. Rather, the invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A route guidance device based on a topological map, comprising: The topology map is generated based on optical character recognition and image processing, and from a guide map image. A destination determiner, configured to determine the location selected by the user in the topology map as the destination; A starting point determiner is configured to determine the user's current location as the starting point, which is detected by comparing characters identified from surrounding images provided by the user with location information from a topological map; as well as A route generator configured to generate the final route from origin to destination based on congestion levels and preference levels.

2. The route guidance device based on a topology map according to claim 1, wherein, The topology map includes: Multiple nodes are positioned along the travel path on the map and each stores its location information; and An edge, which connects the nodes.

3. The route guidance device based on a topology map according to claim 2, wherein, The starting point determiner is configured to estimate the user's current location by identifying specific nodes on the topology map that have location information that matches characters identified in the surrounding images.

4. The route guidance device based on a topology map according to claim 3, wherein, The route generator is configured to use the detected route as the final route and stop route generation when a route passing through the origin and destination is detected from the pre-stored routes.

5. The route guidance device based on a topology map according to claim 3, wherein: The route generator is configured to calculate the congestion level based on the real-time number of people and the area of ​​the passageway obtained by CCTV through the travel channel; and to calculate the congestion level for each edge.

6. The route guidance device based on a topology map according to claim 5, wherein, The route generator is configured to calculate the congestion level of each edge using Equation 1; Equation 1 The optimal number of people in a passageway is based on a predetermined value for the passageway area.

7. The route guidance device based on a topology map according to claim 6, wherein, When the administrator's preset preference level value is low, the preference level is considered high, and a preference level is set for each edge.

8. The route guidance device based on a topology map according to claim 7, wherein, The route generator is configured to generate the final route from multiple edges that include low congestion and high preference.

9. The route guidance device based on a topological map according to claim 1, wherein, The route generator is configured to determine the route with the shortest distance between the origin and the destination as the final route; When there are multiple candidate routes with the same distance between the origin and destination, the candidate route with low congestion and high preference is determined as the final route.

10. The route guidance device based on a topological map according to claim 9, wherein, The route generator is configured to: determine the cost of each candidate route using Equation 2, and determine the candidate route with the lowest cost as the final route; Equation 2 Cost (edge ​​ID) = Distance (vertex 1, vertex 2) × Edge congestion level × Administrator factor In this context, node 1 is the first-side node of the edge that determines the route, node 2 is the second-side node of the edge that determines the route, distance (node ​​1, node 2) is the distance between the first-side node and the second-side node, edge congestion level is the congestion level of each edge, and administrator factor is the administrator's route preference value for each edge.

11. A route guidance method based on a topological map, comprising: Provides a topology map generated from a guide map image based on optical character recognition and image processing. The location selected by the user on the topology map is designated as the destination; The user's current location is determined as the starting point, which is detected by comparing characters identified from the surrounding images provided by the user with the location information of the topological map; The final route from the origin to the destination is generated based on the level of congestion and preference.

12. The route guidance method based on a topology map according to claim 11, wherein, The topology map includes: Multiple nodes are positioned along the travel path on the map and each stores its location information; and An edge is a node that connects to another edge.

13. The route guidance method based on a topological map according to claim 12, wherein, Determining the starting point involves estimating the user's current location by identifying specific nodes on the topological map that have location information that matches characters identified in the surrounding images.

14. The route guidance method based on a topology map according to claim 13, wherein, The process of generating the final route includes: when a route passing through the origin and destination is detected from the pre-stored routes, the detected route is used as the final route and route generation is stopped.

15. The route guidance method based on a topology map according to claim 13, wherein, The final route generation includes: The degree of congestion is calculated based on the real-time number of people and the area of ​​the passageway obtained through closed-circuit television. Calculate the congestion level of each edge.

16. The route guidance method based on a topology map according to claim 15, wherein, Generating the final route further includes: calculating the congestion level of each edge using Equation 1. Equation 1 The optimal number of people in a passageway is based on a predetermined value for the passageway area.

17. The route guidance method based on a topology map according to claim 16, wherein, When the administrator's preset preference level value is low, the preference level is considered high, and a preference level is set for each edge.

18. The route guidance method based on a topology map according to claim 17, wherein, The process of generating the final route further includes generating a route that includes multiple edges with low congestion and high preference as the final route.

19. The route guidance method based on a topology map according to claim 11, wherein, Generating the final route involves determining the route with the shortest distance between the origin and the destination as the final route. When there are multiple candidate routes with the same distance between the origin and destination, the candidate route with low congestion and high preference is determined as the final route.

20. The route guidance method based on a topology map according to claim 19, wherein, The process of generating the final route further includes: determining the cost of each candidate route using Equation 2, and identifying the candidate route with the lowest cost as the final route; Equation 2 Cost (edge ​​ID) = Distance (vertex 1, vertex 2) × Edge congestion level × Administrator factor In this context, node 1 is the first-side node of the edge that determines the route, node 2 is the second-side node of the edge that determines the route, distance (node ​​1, node 2) is the distance between the first-side node and the second-side node, edge congestion level is the congestion level of each edge, and administrator factor is the administrator's route preference value for each edge.

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