Method for searching midpoint between vehicles and server carrying out the same

Abstract

The present invention relates to a method for searching for an optimal intermediate point between vehicles and a server providing the same. A method for searching for an intermediate point between vehicles according to one embodiment of the present invention may include: a step in which a server obtains a first location of a first vehicle and a second location of a second vehicle; a step in which the server determines a third location between the first location and the second location such that the driving time of the first vehicle and the driving time of the second vehicle correspond to each other, by considering weights assigned according to path conditions between the first location and the second location; and a step of transmitting path information to the third location satisfying the corresponding driving time to each of the first vehicle and the second vehicle.

Description

Technology Field

[0001] The present invention relates to a method for searching for an optimal midpoint between vehicles and a server providing the same. Background Technology

[0002] Methods for a vehicle to search for a route from its current location to a destination have not only been continuously researched through various algorithms to determine the optimal route based on various criteria such as travel time, driving distance, and driving convenience, but are also already widely used.

[0003] On the other hand, when two vehicles starting from different locations intend to meet at an arbitrary midpoint, it is common practice to select a point that is arithmetically similar in distance from both sides. However, if only distance is considered, travel times may vary depending on the route, potentially leading to a situation where one party must arrive first and wait for the other. Furthermore, even if travel times are similar based on the time of departure, there is a problem in responding to constantly changing road conditions.

[0004] The matters described above as background technology are intended only to enhance understanding of the background of the present invention and should not be construed as an acknowledgment that they constitute prior art already known to those skilled in the art. The problem to be solved

[0005] The present invention is intended to provide a method for searching for the optimal midpoint between vehicles.

[0006] The technical problems to be solved by the present invention are not limited to those mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art to which the present invention belongs from the description below. means of solving the problem

[0007] As a means for solving the above technical problem, a method for searching for an intermediate point between vehicles according to an embodiment of the present invention may include: a step in which a server obtains a first location of a first vehicle and a second location of a second vehicle; a step in which the server determines a third location between the first location and the second location such that the driving time of the first vehicle and the driving time of the second vehicle correspond to each other, by considering weights assigned according to path conditions between the first location and the second location; and a step of transmitting path information to the third location satisfying the corresponding driving time to each of the first vehicle and the second vehicle.

[0008] For example, the step of determining the third location may include: determining a plurality of nodes existing between the first location and the second location; determining a cost according to the weight for each of the plurality of sections connecting adjacent nodes among the plurality of nodes; and determining the third location by considering the total sum of the costs for each combination of the plurality of sections, the driving time of the first vehicle, and the driving time of the second vehicle.

[0009] For example, the step of determining the third location by considering the total sum of the costs and the time required may include the step of determining the third location by considering the sum of the costs of the path corresponding to the direction of travel from the first location and the sum of the costs of the path corresponding to the direction of travel from the second location.

[0010] For example, the plurality of nodes may include at least some of the nodes used when generating a candidate path from the location of the first vehicle to the location of the second vehicle, and at least some of the nodes used when generating a candidate path from the location of the second vehicle to the location of the first vehicle.

[0011] For example, the step of determining the third location by considering the total sum of the costs for each combination of the above-mentioned multiple sections can be performed using the Dijkstra algorithm.

[0012] For example, the above path conditions may include at least one of traffic information and road information.

[0013] For example, the above traffic information may include at least one of real-time congestion and accident occurrence information.

[0014] For example, the above road information may include at least one of the road type, whether it is an accident-prone area, and whether it is a construction zone.

[0015] For example, the step of determining the third position may be repeated at a predetermined period or according to changes in the path conditions.

[0016] Additionally, a server according to one embodiment may include a communication unit that exchanges data with a first vehicle and a second vehicle; and a control unit that determines a third location between the first location and the second location where the driving time of the first vehicle corresponds to the driving time of the second vehicle by considering a weight assigned according to a path condition between the first location of the first vehicle and the second location of the second vehicle received through the communication unit, and controls the transmission of path information to the third location satisfying the corresponding driving time to each of the first vehicle and the second vehicle through the communication unit.

[0017] For example, the control unit may determine a plurality of nodes existing between the first position and the second position, determine a cost according to the weight for each of the plurality of sections connecting adjacent nodes among the plurality of nodes, and determine the third position by considering the total sum of the costs for each combination of the plurality of sections, the driving time of the first vehicle, and the driving time of the second vehicle. Effects of the invention

[0018] According to at least one embodiment of the present invention, a server can determine an optimal intermediate point existing between a first location of a first vehicle and a second location of a second vehicle and provide it to each vehicle driver.

[0019] The midpoint determined here is not simply a midpoint based on equal distance, but may be an optimal midpoint for the driver that reflects information regarding traffic conditions or road conditions as well as the travel time.

[0020] In addition, in embodiments of the present invention, the server simultaneously considers whether the driving time of both vehicles corresponds to an intermediate point, so it can determine the optimal intermediate point more efficiently.

[0021] The effects obtainable from the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description below. Brief explanation of the drawing

[0022] FIG. 1 shows an example of an environment configuration for providing a method for searching intermediate points between vehicles applicable to embodiments. FIG. 2 shows an example of a process for searching for an intermediate point between vehicles according to one embodiment. FIG. 3 illustrates an example of a step for determining a node based on the current location of two vehicles according to one embodiment. FIG. 4 illustrates an example of a step of connecting adjacent nodes among a plurality of nodes according to one embodiment and determining a cost value according to a weight for each section. FIG. 5 shows an example of a step for determining an optimal intermediate point according to one embodiment. FIG. 6 illustrates an example of a process for searching for an optimal intermediate point based on real-time situational changes after vehicle movement according to one embodiment. FIG. 7 illustrates an example of a step for determining an optimal intermediate point that reflects real-time situational changes after vehicle movement according to one embodiment. Specific details for implementing the invention

[0023] Hereinafter, embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Identical or similar components regardless of drawing symbols will be assigned the same reference number, and redundant descriptions thereof will be omitted. The suffixes "module" and "part" used for components in the following description are assigned or used interchangeably solely for the ease of drafting the specification and do not inherently possess distinct meanings or roles. Furthermore, in describing embodiments disclosed in this specification, if it is determined that a detailed description of related prior art could obscure the essence of the embodiments disclosed in this specification, such detailed description will be omitted. Additionally, the attached drawings are intended only to facilitate understanding of the embodiments disclosed in this specification; the technical concept disclosed in this specification is not limited by the attached drawings, and it should be understood that they include all modifications, equivalents, and substitutions that fall within the spirit and technical scope of the present invention.

[0024] Terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but said components are not limited by said terms. These terms are used solely for the purpose of distinguishing one component from another.

[0025] When it is stated that one component is "connected" or "connected" to another component, it should be understood that while it may be directly connected or connected to that other component, there may also be other components in between. On the other hand, when it is stated that one component is "directly connected" or "directly connected" to another component, it should be understood that there are no other components in between.

[0026] A singular expression includes a plural expression unless the context clearly indicates otherwise.

[0027] In this specification, terms such as “comprising” or “having” are intended to indicate the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not excluding in advance the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0028] Furthermore, the terms "Unit" or "Control Unit" included in names such as "MCU" are merely terms widely used in naming controllers that control specific functions, and do not refer to generic function units. For example, each controller may include a communication device that communicates with other controllers or sensors to control the function it is responsible for, memory that stores an operating system, logic instructions, and input / output information, and one or more processors that perform judgments, calculations, and decisions necessary for controlling the responsible function.

[0029] In embodiments of the present invention, a method is proposed for searching for an optimal intermediate point by considering traffic conditions and road conditions, where the travel time from the current locations of both vehicles corresponds. Here, considering traffic conditions may mean considering various factors that cause traffic congestion, such as traffic congestion levels and the occurrence of traffic accidents. Additionally, considering road conditions may mean considering information regarding road conditions that affect vehicle driving, such as whether there is road construction or whether the road is damaged due to natural disasters. Therefore, the optimal intermediate point does not simply mean an intermediate point in terms of distance, but may mean an optimal intermediate point based on traffic conditions or road conditions.

[0030] FIG. 1 shows an example of an environment configuration for providing a method for searching intermediate points between vehicles applicable to embodiments of the present invention.

[0031] Referring to FIG. 1, an environment configuration that provides a method for searching for an intermediate point between vehicles may include a server (100) that determines an intermediate point and provides it, and vehicle terminal A (200A) and vehicle terminal B (200B) that request the server (100) to determine the intermediate point and the path to the intermediate point.

[0032] The server (100) may be a Connected Car Service (CCS) server that exchanges data with the AVNT (Audio / Video / Navigation) terminal of a vehicle and supports various functions and services. In embodiments of the present invention, the server (100) may receive information regarding the current location of the vehicle (200A, 200B) from the vehicle terminal (200A, 200B). When the server (100) finds an intermediate point between the two vehicles (200A, 200B), it may provide the intermediate point through the following process based on the information regarding the current location of the two vehicles (200A, 200B).

[0033] First, the server (100) may set up multiple nodes based on the current locations of the two vehicles (200A, 200B) received. Here, the multiple nodes may include a node that serves as a reference for multiple paths searched when generating candidate paths from the current location of vehicle A (200A) to the current location of vehicle B (200B), and a node that serves as a reference for multiple paths searched when generating candidate paths from the current location of vehicle B (200B) to the current location of vehicle A (200A). However, this is exemplary, and the method of determining multiple nodes is not limited thereto.

[0034] Afterward, the server (100) can determine a cost value according to weight for each section (e.g., one or more road links) that connects adjacent nodes among the determined multiple nodes.

[0035] Here, adjacent nodes may mean two nodes that can be connected directly via one or more road links without passing through other nodes.

[0036] Additionally, weights can be determined based on the driving distance per section, traffic conditions, and road conditions. For example, if a section has a long driving distance, the weight corresponding to the distance is applied at a higher value, which may increase the cost; however, if traffic congestion is low and a large weight relative to the driving distance is applied, the final cost may be lower. Alternatively, even if a section has a short driving distance, the cost of that section may increase due to the weighting applied to road conditions if the road is covered in mud caused by heavy rainfall.

[0037] When cost values ​​are determined according to weights for each section, the server (100) can determine the optimal intermediate point based on the current locations of Vehicle A (200A) and Vehicle B (200B) based on the cost values ​​for each section. The server (100) may use the Dijkstra algorithm as a means to determine the optimal intermediate point. A method of finding the optimal intermediate point using the Dijkstra algorithm may be to find an intermediate point where the sum of cost values ​​for each section from the current location of Vehicle A (200A) is the lowest and the sum of cost values ​​for each section from the current location of Vehicle B (200B) is the same. However, in the embodiments of the present invention, the server (100) may determine the optimal intermediate point as an intermediate point where the sum of cost values ​​for each section is low, and the driving time of Vehicle A (200A) and the driving time of Vehicle B (200B) correspond. Therefore, the optimal midpoint determined by the server (100) may not necessarily be the midpoint where the sum of the cost values ​​for each section is the lowest. In this case, different weights may be assigned to the difference in driving time between the two vehicles and the sum of the cost values. For example, if a greater weight is assigned to the driving time, the cost value may be slightly higher compared to other candidate midpoints when determining the midpoint, but the candidate midpoint with the most similar driving time between the two vehicles may be determined as the final candidate midpoint. Conversely, if a greater weight is assigned to the sum of the cost values, even if there is a slight difference in driving time between the two vehicles and one side arrives first and waits a little, the candidate midpoint with the lower sum of the cost values ​​may be determined as the final midpoint.

[0038] When the server (100) determines the optimal midpoint, it may provide the determined optimal midpoint to vehicle terminal A (200A) and vehicle terminal B (200B) along with the route applied to the determination of the midpoint. The provided optimal midpoint may be displayed on the display of each vehicle terminal (200A, 200B). That is, each vehicle terminal (200A, 200B) on which the navigation app is running may guide each driver to the route to the optimal midpoint received from the server (100) through the display. However, this is merely an example, and the method of guiding the route to the optimal midpoint is not limited thereto.

[0039] FIG. 2 shows an example of a process for searching for an intermediate point between vehicles according to one embodiment.

[0040] Referring to FIG. 2, first, the vehicle terminal (200A, 200B) can transmit information about the current location of its vehicle (200A, 200B) to the server (100), and the server (100) can determine the current location of the two vehicles (200A, 200B) based on the received information (S210).

[0041] The server (100) can determine multiple nodes existing between two locations based on the current locations of the two determined vehicles (200A, 200B) (S220). Subsequently, the server (100) can determine cost values ​​according to weights for each section connecting adjacent nodes among the determined multiple nodes (S230). Here, the weights can be determined based on the driving distance per section, traffic conditions, and road conditions. The server (100) can determine the optimal intermediate point where the driving distances of the two vehicles (200A, 200B) correspond, while considering the sum of the costs determined for each section (S240).

[0042] The situation may change in real time while the two vehicles (200A, 200B) are moving toward the optimal intermediate point (S250, Yes). If the situation changes in real time, the server (100) can receive information about the current location from each vehicle terminal (200A, 200B) after the two vehicles (200A, 200B) have moved and determine the optimal intermediate point anew. A change in the situation in real time may mean that the cost changes due to changes in traffic conditions or road conditions in each section after the two vehicles (200A, 200B) have moved. Alternatively, a case where vehicle movement is temporarily impossible due to a traffic accident occurring in some section of the route to the optimal intermediate point provided by the server (100), or where vehicle movement is difficult due to a natural disaster such as a landslide, may be considered a case where the situation changes in real time. In this case, the server (100) must determine the optimal intermediate point based on the route that is available again.

[0043] If there is no change in the real-time situation, the server (100) can determine whether the driving times of the two vehicles (200A, 200B) correspond (S260). Corresponding driving times may mean that even if the driving times of the two vehicles (200A, 200B) are not exactly the same, the difference is within 5 to 10 minutes. However, this is merely an example, and the criteria for correspondence can be arbitrarily set by the driver. If the driving times of the two vehicles (200A, 200B) do not correspond, the server (100) can determine a new optimal midpoint after receiving information about the current locations of the two vehicles (200A, 200B) again (S260, No). On the other hand, if the driving times of the two vehicles (200A, 200B) correspond, the server (100) can provide the already determined optimal midpoint to the two vehicle terminals (200A, 200B) (S260, Yes). The process of providing the optimal intermediate point as described above can be repeated at predetermined intervals.

[0044] FIGS. 3 to 7 illustrate the decision process of the server (100) at each step of the process of finding the intermediate point between vehicles in FIG. 2.

[0045] FIG. 3 illustrates an example of a step for determining a plurality of nodes based on the current location of two vehicles according to one embodiment.

[0046] Referring to FIG. 3, the current location of vehicle A (200A) and the current location of vehicle B (200B) may be determined based on information regarding the current location received from each vehicle terminal (200A, 200B). Multiple nodes (310, 320, 330, 340) existing between the current locations of each vehicle (200A, 200B) may be determined by the server (100) under certain criteria. Here, certain criteria may mean determining a node that serves as a reference for multiple paths found by searching for a path between the current location of vehicle A (200A) and the current location of vehicle B (200B) as a node necessary for determining the optimal intermediate point. This is exemplary and is not limited thereto.

[0047] FIG. 4 illustrates an example of a step of connecting adjacent nodes among a plurality of nodes according to one embodiment and determining a cost value according to a weight for each section.

[0048] Referring to Figure 4, the cost according to the weight for each section may vary depending on the direction. This is because the lanes differ depending on the direction for each section. For example, between two nodes, the cost may be high in one direction due to high traffic congestion, but it may be low in the opposite direction due to low traffic congestion.

[0049] FIG. 5 shows an example of a step for determining an optimal intermediate point according to one embodiment.

[0050] Referring to FIG. 5, it can be seen that, unlike FIG. 4, FIG. 5 shows only a single path between the two vehicles (200A, 200B) and the nodes connecting that path. Here, the single path may be the optimal path. Meanwhile, in the embodiments of the present invention, to determine the optimal path, the server (100) may use the Dijkstra algorithm. For example, the server (100) may first use the Dijkstra algorithm to determine the optimal path and intermediate point where the sum of the costs for each section is minimized, and simultaneously determine the optimal path and intermediate point corresponding to the driving time of the two vehicles (200A, 200B), and determine the overlapping intermediate point as the optimal intermediate point.

[0051] More specifically, the process of summing the cost values ​​for each section according to multiple paths derived with reference to FIG. 4 and determining the intermediate point derived in FIG. 5 based thereon is described as follows. First, assuming the intermediate point is between Node 1 (310) and Node 2 (320), if Vehicle A (200A) travels from its current location to the intermediate point along the path from Node 1 (310) to Node 2 (320), the range of the summed cost value may be 6 to 10. If Vehicle B (200B) travels from its current location to the intermediate point along the path from Node 2 (320) to Node 1 (310), the range of the summed cost value may be 3 to 4.

[0052] Assuming the midpoint between Node 2 (320) and Node 4 (340), if Vehicle A (200A) travels from its current location to the midpoint of the path from Node 4 (340) to Node 2 (320), the range of the summed cost value may be 2 to 3. If Vehicle B (200B) travels from its current location to the midpoint of the path from Node 2 (320) to Node 4 (340), the range of the summed cost value may be 3 to 7.

[0053] Assuming the midpoint between node 3 (330) and node 4 (340), if vehicle A (200A) travels from its current location to the midpoint of the path from node 4 (340) to node 3 (330), the range of the summed cost value may be 2 to 4. If vehicle B (200B) travels from its current location to the midpoint of the path from node 3 (330) to node 4 (340), the range of the summed cost value may be 4 to 7.

[0054] As described above, when there are three possible intermediate points, for the server (100) to determine the optimal intermediate point among the three intermediate points, the summed cost value must be low, and at the same time, the driving time of vehicle A (200A) and the driving time of vehicle B (200B) must correspond. First, if the intermediate point is assumed to be between node 1 (310) and node 2 (320), the summed cost value of the path each vehicle (200A, 200B) passes through may be higher than in other cases, so the intermediate point between node 1 (310) and node 2 (320) may not be the optimal intermediate point determined by the server (100).

[0055] When comparing the case where the midpoint is between Node 2 (320) and Node 4 (340) with the case where the midpoint is between Node 3 (330) and Node 4 (340), the range of the cost sum value of each path is similar, but the cost sum value may be lower when the midpoint is between Node 2 (320) and Node 4 (340). However, the midpoint (500) shown in FIG. 5 is the midpoint (500) between Node 3 (330) and Node 4 (340), which may be the midpoint determined by the server (100) by considering whether the driving time of Vehicle A (200A) corresponds to the driving time of Vehicle B (200B). Therefore, even if the sum of the costs of the routes used by vehicle A (200A) and vehicle B (200B) is not the lowest, if the driving times of vehicle A (200A) and vehicle B (200B) correspond, it can be a route with an optimal intermediate point.

[0056] This is just one example for finding an intermediate point, and there may be more or fewer possible cases for an intermediate point, and the server (100) can determine one of the intermediate points corresponding to each case as an intermediate point based on whether the sum of the costs for each section corresponds to the driving time of each vehicle (200A, 200B).

[0057] FIG. 6 illustrates an example of a process for searching for an optimal intermediate point based on real-time situational changes after vehicle movement according to one embodiment.

[0058] Referring to FIG. 6, it can be seen that the two vehicles (200A, 200B) have moved toward a pre-set optimal midpoint through the distance (601) traveled by vehicle A (200A) and the distance (602) traveled by vehicle B (200B). However, the difference from FIG. 4 is that node 5 (640) has been added and node 1 (310) has been deleted. The added node 5 (640) may be a node derived when multiple nodes (610, 620, 630, 640) are re-evaluated based on the current location after the two vehicles (200A, 200B) have moved. The deletion of node 1 (310) may mean that it was deleted because there is no section available for use due to real-time situational changes after the two vehicles (200A, 200B) have moved. For example, if vehicle movement becomes impossible in a section due to a traffic accident or natural disaster that occurred while the vehicle (200A, 200B) was moving, Node 1 (310) connected to that section may also lose its function as a branch point. Therefore, Node 1 (310) that has lost its function as a branch point can be deleted by the server (100) in real time.

[0059] Additionally, when comparing FIG. 6 with FIG. 4, it can be seen that the cost value according to the weight for each section has changed. This may mean that there has been a change in the traffic situation or road condition for each section after the two vehicles (200A, 200B) have moved. For example, before the two vehicles (200A, 200B) moved, a traffic accident occurred in one section, increasing the congestion of vehicles and thus increasing the cost; however, after the two vehicles (200A, 200B) moved, the response to the traffic accident was completed, the congestion of vehicles was alleviated again, and accordingly, the cost may decrease. The cost value for each section shown in FIG. 6 can be changed in real time by the server (100).

[0060] FIG. 7 illustrates an example of a step for determining an optimal intermediate point that reflects real-time situational changes after vehicle movement according to one embodiment.

[0061] Referring to FIG. 7, it can be seen that the optimal midpoint (700) has changed compared to FIG. 5. This may be the optimal midpoint (700) that reflects the situation in which the cost value according to the weight of each section changes as the situation changes in real time as shown in FIG. 6.

[0062] More specifically, based on the intermediate point (500) shown in FIG. 5 and the cost change in FIG. 6, the sum of the costs of the paths to be used by Vehicle A (200A) and Vehicle B (200B) is calculated as follows. First, when Vehicle A (200A) goes to the intermediate point (500) on the path from Node 4 (610) to Node 3 (630), the range of the summed cost value may be 3 to 10. When Vehicle B (200B) goes to the intermediate point (500) on the path from Node 3 (630) to Node 4 (610), the range of the summed cost value may be 5 to 11. It can be seen that the range of the summed cost value is higher than the range of the cost value based on the cost value shown in FIG. 4. This may be the result of the cost value changing in real time, such as when traffic congestion increases in each section or the degree of road damage increases due to the influence of natural disasters.

[0063] Meanwhile, based on the intermediate point (700) shown in FIG. 7, the total cost of the path that Vehicle A (200A) and Vehicle B (200B) will use is calculated as follows. First, when Vehicle A (200A) goes to the intermediate point (700) in the path that goes from Node 4 (610) to Node 2 (620), the range of the total cost value can be 3 to 5. When Vehicle B (200B) goes to the intermediate point (700) in the path that goes from Node 2 (620) to Node 4 (610), the range of the total cost value can be 1 to 3. When comparing this with the range of the total cost value calculated by the intermediate point (500) shown in FIG. 5, it can be confirmed that the intermediate point (700) shown in FIG. 7 is an intermediate point (700) that presents a path that reflects a lower total cost value compared to the intermediate point (500) shown in FIG. 5.

[0064] According to the embodiments of the present invention described so far, an optimal midpoint can be provided that takes into account traffic conditions and road conditions, rather than a midpoint in terms of distance from the current locations of the two vehicles (200A, 200B). In addition, since the server (100) can update weights by reflecting real-time situational changes, the present invention can provide the optimal midpoint to the driver in real time.

[0065] Meanwhile, the present invention described above can be implemented as computer-readable code on a medium on which a program is recorded. A computer-readable medium includes all types of recording devices in which data that can be read by a computer system is stored. Examples of computer-readable media include HDD (Hard Disk Drive), SSD (Solid State Disk), SSD (Silicon Disk Drive), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. Accordingly, the above detailed description should not be interpreted restrictively in all respects and should be considered exemplary. The scope of the present invention should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the present invention are included within the scope of the present invention.

Claims

Claim 1 A method for searching for an intermediate point between vehicles, comprising: a step in which a server obtains a first location of a first vehicle and a second location of a second vehicle; a step in which the server determines a third location between the first location and the second location such that the driving time of the first vehicle and the driving time of the second vehicle correspond to each other, by considering weights assigned according to path conditions between the first location and the second location; and a step of transmitting path information to the third location satisfying the corresponding driving time to each of the first vehicle and the second vehicle. Claim 2 A method for searching for an intermediate point between vehicles according to claim 1, wherein the step of determining the third location comprises: determining a plurality of nodes existing between the first location and the second location; determining a cost according to the weight for each of the plurality of sections connecting adjacent nodes among the plurality of nodes; and determining the third location by considering the total sum of the costs for each combination of the plurality of sections, the driving time of the first vehicle, and the driving time of the second vehicle. Claim 3 A method for searching for an intermediate point between vehicles according to claim 2, wherein the step of determining the third location by considering the total sum of the costs and the time required includes the step of determining the third location by considering the sum of the costs of the path corresponding to the direction of travel from the first location and the sum of the costs of the path corresponding to the direction of travel from the second location. Claim 4 A method for searching intermediate points between vehicles according to claim 2, wherein the plurality of nodes includes at least some of the nodes used when generating a candidate path from the location of the first vehicle to the location of the second vehicle and at least some of the nodes used when generating a candidate path from the location of the second vehicle to the location of the first vehicle. Claim 5 A method for searching for an intermediate point between vehicles according to claim 2, wherein the step of determining a third location by considering the sum of the costs for each combination of the plurality of sections is performed through the Dijkstra Algorithm. Claim 6 A method for searching for an intermediate point between vehicles according to claim 1, wherein the path condition comprises at least one of traffic information and road information. Claim 7 A method for searching for an intermediate point between vehicles according to claim 4, wherein the traffic information includes at least one of real-time congestion and accident occurrence information, and the road information includes at least one of road type, whether it is an accident-prone area, and whether it is a construction zone. Claim 8 A method for searching for an intermediate point between vehicles according to claim 1, wherein the step of determining the third position is performed repeatedly at a predetermined period or according to a change in the path conditions. Claim 9 A server comprising: a communication unit that exchanges data with a first vehicle and a second vehicle; and a control unit that determines a third location between the first location and the second location corresponding to the driving time of the first vehicle and the driving time of the second vehicle by considering a weight assigned according to a path condition between the first location of the first vehicle and the second location of the second vehicle received through the communication unit, and controls the transmission of path information to the third location satisfying the corresponding driving time to each of the first vehicle and the second vehicle through the communication unit. Claim 10 A server according to claim 9, wherein the control unit determines a plurality of nodes existing between the first position and the second position, determines a cost according to the weight for each of the plurality of sections connecting adjacent nodes among the plurality of nodes, and determines the third position by considering the total sum of the costs for each combination of the plurality of sections, the driving time of the first vehicle, and the driving time of the second vehicle.

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