Patent ID: 12222207

DESCRIPTION OF EMBODIMENT(S)

First Embodiment

<Configuration>

FIG.1is a block diagram showing an example of a configuration of a map matching apparatus1according to a first embodiment. The map matching apparatus1performs offline map matching described above. As shown inFIG.1, the map matching apparatus1includes a map information acquisition unit2, a movement information acquisition unit3, and a matching unit4.

The map information acquisition unit2acquires map information including link endpoint coordinates, which are the coordinates of the endpoints of each link, and a connection relationship of each link. The movement information acquisition unit3acquires movement information of a moving body on a predetermined route. In the following, the moving body will be described as being a vehicle.

The matching unit4identifies a link string, which is a string of links corresponding to the route, based on the map information which the map information acquisition unit2has acquired and the movement information which the movement information acquisition unit3has acquired. Specifically, the matching unit4generates a physical network, which is a road network, based on the movement information and the connection relationship among the links included in the map information, generates a hierarchical logical network in which the physical network is duplicated a plurality of times and superimposes the layers into hierarchy, and specifies a link string indicating the minimized cost in the hierarchical logical network.

FIG.2is a block diagram showing an application example of the map matching apparatus1shown inFIG.1, and shows an example of the configuration of an autonomous driving system. In the autonomous driving system shown inFIG.2, the map matching apparatus1specifies the route of the moving body acquired from an IVI9on the high-precision map and transmits the route to an ECU13. The ECU13controls to autonomously drive the moving body in accordance with to the route specified on the high-precision map. Hereinafter, each component of the autonomous driving system will be described. The autonomous driving system is a function included in Advanced Driver Assistance System (ADAS).

A high-definition locator5includes the map matching apparatus1, a receiving unit6, a high-precision map database (DB)7, and a transmission unit8.

The map matching apparatus1includes the map information acquisition unit2, the movement information acquisition unit3, and the matching unit4. The functions of the map information acquisition unit2, the movement information acquisition unit3, and the matching unit4are as described above.

The map information acquisition unit2acquires map information, which is a high-precision map, from the high-precision map database (DB)7. Specifically, the map information acquisition unit2is an Application Programming Interface (API) group for acquiring necessary information from the high-precision map DB7.

The movement information acquisition unit3acquires the movement information which the receiving unit6has received from the IVI9. The movement information includes a coordinate point string of positions on the route on which the moving body is to travel. Further, the movement information may include attribute information regarding the route. Examples of the route on which the moving body is to travel include a route of guide in progress or a route expected to be traveled in the future if it is not a route of guide in progress.

The matching unit4identifies a link string, which is a string of links corresponding to the route, based on the map information which the map information acquisition unit2has acquired and the movement information which the movement information acquisition unit3has acquired. If the map information corresponding to a part of a section of the route included in the movement information is not stored in the high-precision map DB7, the matching unit4does not specify the link string corresponding to the part of the section.

The receiving unit6receives the movement information on the route on which the moving body is to travel from the IVIS. The high-precision map DB7stores the high-precision map as a database. Specifically, the high-precision map DB7stores lane-level detailed shape information, information indicating the connection relationship between lanes, and lane-changeability information.

The transmission unit8adds road information (position, shape, attributes, etc.) and position information of the moving body and the like necessary for control by the ECU13to the link string the matching unit4has specified and transmits the link string to the ECU13. As the position information of the moving body, the position information measured by a high-precision positioning unit (not shown) provided in the high-definition locator5may be adoptable, and the high-definition locator5may predict the position of the moving body based on the movement information which the receiving unit6has received.

The IVI9includes an IVI map database (DB)10, a route search unit11, and a transmission unit12. The IVI9is, for example, a navigation system.

The IVI map DB10stores a regular map used in the navigation system as a database. The regular map does not include lane-level detailed shapes, only road-level schematic shapes. The schematic shape is less accurate than the high-precision map. Typically, it is said that a road-level schematic shape may contain an error of about 10 m. In addition, the latitude/longitude at branch points and the like in the regular map may differ from those in the high-precision map due to differences in maintenance specifications between the regular map and the high-precision map. Furthermore, the regular map does not always include newly opened roads in synchronization with high-precision maps; therefore, the assumption that differences are found in the contents of both maps lies.

The route search unit11determines the route to the destination at the road level as the shortest route issue based on the regular map stored in the IVI map DB10. That is, the route search unit11determines the route on which the moving body will travel in the future.

The transmission unit12transmits the movement information of the moving body in the route the route search unit11has searched to the high-precision locator5. If the destination is not set, the transmission unit12transmits the route predicted that the moving body will travel in the future to the high-definition locator5. The route search unit11may perform such a route prediction. Note that ADASIS-V2 or the like, which is a commonly-adopted standard, may be adopted for communication between the transmission unit12and the receiving unit6of the high-definition locator5.

The ECU13includes a receiving unit14, a recognition unit15, a determination unit16, and a controller17. The ECU13controls the autonomous operation of the moving body.

The receiving unit14receives information such as a link string specified on the high-precision map from the high-definition locator5. The recognition unit15recognizes the state of the moving body and the situation around the moving body and the like required for automatic driving based on the information received from the sensor provided on the moving body. The determination unit16determines how the movement of the moving body should be controlled based on the recognition result by the recognition unit15and the information which the receiving unit14has received. The controller17controls the movement of the moving body based on the determination result by the determination unit16and the information which the reception unit14has received.

<Operation>

FIG.3is a flowchart showing an operation example of the map matching apparatus1.

In Step S11, the map information acquisition unit2acquires the map information of high-precision from the high-precision map database (DB)7. In Step S12, the movement information acquisition unit3acquires the movement information which the receiving unit6has received from the IVI9. In Step S13, the matching unit4performs a map matching process.

FIG.4is a flowchart showing the details of the map matching process in Step S13ofFIG.3.

In Step S21, the matching unit4generates a hierarchical list based on the coordinate point strings and the attribute information included in the movement information which the movement information acquisition unit3has acquired. Hereinafter, a case where the movement information acquisition unit3acquires the movement information shown inFIG.5will be described.

InFIG.5, “Points 0, 1, 2, and 3” indicate a string of coordinate points at a plurality of positions on the route on which the moving body is to travel. Note, “Points 0, 1, 2, are 3” are also collectively referred to as “waypoints”. “VICS=100, 103, 105, 106, 108” represents the VICS number, and indicates the link attribute of the link connected to each Point 0, 1, 2, and 3. “Offset=0, 500, 900, 1200, 1500” represents the distance from Point 0. Further, unnumbered Point existing between Points 2 and 3 represents a point where the link attributes change, and is also referred to as an “attribute change point”.

The matching unit4generates a hierarchical list as shown inFIG.6based on the movement information shown inFIG.5. The hierarchical list shows a hierarchy in which movement information is arranged in the order of Offset and separated by the waypoints and the attribute change point.

In Step S22, the matching unit4generates a physical network based on the movement information and the high-precision map. The physical network is a road network on the high-precision map, which is a target when searching for a route on which the moving body is to travel on the high-precision map. The links and nodes consisting the physical network are referred to as “physical links” and “physical nodes,” respectively. The physical network has information about the physical links and the physical nodes, such as a link shape, the link attribute, the link number, and the parameters necessary for calculating the cost described later. The term “physical” is used here to clarify the contrast with the non-existent virtual “logical network”, “logical link”, and “logical node” described later.

Specifically, the matching unit4searches for a physical link existing near a waypoint or an attribute change point. Then, the matching unit4expands the physical link from the searched physical link to the next waypoint or the attribute change point. The matching unit4generates a physical network as shown inFIG.7by performing such a procedure for all waypoints and the attribute change point.

FIG.8is a diagram showing the movement information shown inFIG.5and the physical network shown inFIG.7together. The matching unit4searches for the physical link AB and the physical link HI existing near Point 0 which is a waypoint. Here, the “physical link AB” indicates that the link connects the physical node A and the physical node B, and the same applies to other physical links.

Then, the matching unit4expands each of the physical link AB and the physical link HI up to the next waypoint, Point 1. In the example ofFIG.8, the physical link BC and the physical link BJ are expanded from the physical link AB, and the physical link IO is expanded from the physical link HI. The matching unit4generates a physical network by performing such a procedure for all waypoints and the attribute change point.

In Step S23, the matching unit4generates a hierarchical logical network and sets the connection relationship between the layers. Specifically, the matching unit4duplicates the physical network generated in Step S22by the same number as the number of layers shown in the hierarchical list generated in Step S21. In order to clarify the contrast with the above-mentioned “physical network”, which is the network configured by duplicating the physical network a plurality of times and making them into hierarchy, is referred to as a “hierarchical logical network” (seeFIG.9described later).

Here, the links and nodes constituting the hierarchical logical network are referred to as “logical link” and “logical node”, respectively, in order to clarify the contrast with the above-mentioned “physical link” and “physical node”. The hierarchical logical network is made of duplications of the physical network; therefore, the physical link and the logical link having the same link attribute correspond to each other, and the physical node and the logical node having the same position coordinates correspond to each other. In the hierarchical logical network, the logical node of the layer k (layers 0, 1, . . . From the starting point; the same applies hereinafter) and the physical node X represent a “state where the position of the physical moving body is the position of the physical node X, and the passing state of each waypoint has passed up to the waypoint k and has not passed after the waypoint k+1”. Therefore, the movement of the logical node which is the physical node X and from the layer k to the layer k+1 corresponds to “determining that the waypoint k has been passed”. Here, from the viewpoint of the reproducibility of the route based on the movement history of the moving body, if the position of the physical node X is far away from the waypoint k, it is determined that the reproducibility of the route is low, and a large penalty is imposed on such a route. On the other hand, if the position of the physical node X is close to the waypoint k, it is determined that the reproducibility of the route is high, and a small penalty is imposed on such a route.

A start link in the hierarchical logical network is the logical link within a layer corresponding to the first waypoint and closest to the first waypoint. An end link in the hierarchical logical network is the logical link within a layer corresponding to the last waypoint and closest to the last waypoint. Specifically, the matching unit4determines that the logical link existing within a predetermined radius centered on the first waypoint is the start link, and the logical link existing within a predetermined radius centered on the last waypoint is the end link. The start link and the end link may include, in addition to the logical link existing within the predetermined radius, the logical links connected before and after thereof distanced by the predetermined distance from the logical link based on the connection relationship of the links.

In the above, although the case where the number of layers in the hierarchical logical network corresponds to the number of division sections obtained by dividing the route searched by the route search unit11of IVI9by the waypoints and the attribute change point has been described, this is not limited thereto. For example, the number of layers in the hierarchical logical network may correspond to the number of divided sections obtained by dividing the route searched by the route search unit11of IVI9by the road attribute included in the movement information. Examples of road attributes include a road type, a link type, the number of lanes, a road width, a speed limit, presence/absence of toll, a link number, a road name, a national road number, a prefectural road number, and the like. As described above, when the switching of the layers corresponds to the attribute change point, the logical node of the layer k and the physical link Y in the hierarchical logical network represents the “the state where the position of the physical moving body is the position of the physical link Y, and the road attribute in the movement history of the moving body stays within the kth section”. Therefore, it is determined that the movement of the logical node which is the physical link Y and from the layer k to the layer k+1 corresponds to “determining that the kth and k+1st attribute change points in the movement history of the moving body have been passed”. Here, from the viewpoint of the reproducibility of the route based on the movement history of the moving body, if the link attribute of the physical link Y is not consistent with the kth road attribute of the movement history of the moving body (when they are far away from each other), it is determined that the reproducibility of the route is low, and a large penalty is imposed on such a route. On the other hand, if the link attribute of the physical link Y is consistent with the kth road attribute of the movement history of the moving body (when they are close to each other), it is determined that the reproducibility of the route is high, and a small penalty is imposed on such a route. It should be noted that the layers in the hierarchical logical network may be associated with both each waypoint and each road attribute of the movement history of the moving body.

Next, the matching unit4sets an inter-layer link at appropriate positions between the layers of the hierarchical logical network. Specifically, the matching unit4sets the logical link connecting the same logical nodes in each adjacent layer as an inter-layer link.

FIG.9is a diagram showing an example of the connection relationship between each layer in the hierarchical logical network. InFIG.9, the logical link connecting the same logical nodes in each layer is an inter-layer link. The boundary of each layer in the hierarchical logical network corresponds to a waypoint or an attribute change point. In the example ofFIG.9, the boundary between Layer 0 and Layer 1 corresponds to Waypoint 1, and the boundary between Layer 2 and Layer 3 corresponds to the attribute change point. Inter-layer links are set according to the concepts shown in (A) and (B) below.

(A) When the boundary between layers corresponds to a waypoint, the matching unit4sets only the logical nodes that can be regarded as having a correspondence relationship by satisfying the conditions such as being within a predetermined distance from the waypoint as inter-layer links.

(B) When the boundary between layers corresponds to the attribute change point, the matching unit4unconditionally sets the inter-layer links for all the logical nodes.

In Step S24, the matching unit4sets the cost in the hierarchical logical network. Specifically, the matching unit4sets the cost for the inter-layer link set in Step S23and the logical link in each layer (hereinafter, also referred to as “intra-layer link”). The cost setting value is designed to be small when a route that is consistent with the movement history of the moving body or a route that is close to the moving history of the moving body is selected. Further, the cost setting value of is designed to be large when a route that is not consistent with the movement history of the moving body or a route that is far from the moving history of the moving body is selected. In the first embodiment, the above-mentioned “consistent with” or “not consistent with”, or “close to” or “far” is quantitatively determined based on the coordinates of the waypoint and the attribute information of the movement history, and the cost is set based on the result.

FIG.10is a diagram showing an example of the cost in the hierarchical logical network. The cost is set according to the concepts shown in (C), (D) and (E) below.

(C) Regarding the inter-layer cost, the matching unit4sets the cost according to the degree of consistency of the link attribute included in the movement information corresponding to each layer with the link attribute of the physical link corresponding to the logical link. When the degree of consistency is large, the cost is reduced, and when the degree of consistency is small, the cost is increased.

For example, focusing on Layer 0 inFIG.10, the link attribute (link attribute of the link connecting Point 0 and Point 1) included in the movement information corresponding to Layer 0 is “VICS=100”. Then, when the link attribute of the physical link AB corresponding to the logical link AB in the hierarchical logical network is “VICS=100”, the matching unit4sets the cost of the logical link AB to “0”. Further, the matching unit4sets the cost of the logical link other than the logical link AB to “100”. Here, the “logical link AB” indicates that the link connects the logical node A and the logical node B, and the same applies to other logical links.

In the above, although the case where the cost is set according to the degree of consistency of the link attribute has been described, the present invention is not limited thereto. For example, the matching unit4may set the cost of the logical link within each layer based on the traveling direction of the moving body at the branch point of each layer and at least one of the presence/absence of a branch of the physical link corresponding to the logical link and the traveling direction after the branch of the physical link corresponding to the logical link. In this case, the traveling direction of the moving body is included in the moving information.

(D) Regarding the cost of the inter-layer link when the boundary between the layers corresponds to the waypoint, the matching unit4sets the cost according to the degree of consistency between the coordinates of each waypoint and the coordinates of the physical link corresponding to the logical link. If the distance between the two coordinates is close, it is determined that the degree of coincidence is large and the cost is reduced, and if the distance between the two coordinates is far, it is determined that the degree of coincidence small and the cost is increased. The distance between the two coordinates may be the distance of a perpendicular line drawn from the coordinates of the waypoint to the physical link. If the perpendicular line cannot be drawn from the coordinates of the waypoint to the physical link, the distance of the straight line drawn from the coordinates of the waypoint to the end point closer to the physical link may be adopted.

In the above, although the case where the cost is set according to the degree of coincidence between the coordinates of the waypoint and the coordinates of the physical link has been described, the present invention is not limited thereto. For example, the matching unit4may set the cost according to the degree of consistency between the coordinates of the waypoint and the coordinates of the physical node.

(E) Regarding the cost of inter-layer link when the boundary between the layers corresponds to the attribute change points, the matching unit4sets all costs to “0”.

In Step S25, the matching unit4searches for a route in the hierarchical logical network. Specifically, the matching unit4applies the Dijkstra's algorithm or the like to search for the route that minimizes the cost in the cost set in Step S24. At this point, the route search is performed focusing on minimizing the cost in the hierarchical logical network without the physical network being taken into consideration.

FIG.11is a diagram showing the results of route search in the hierarchical logical network. As shown inFIG.11, the matching unit4searches for the route that minimizes the cost in the hierarchical logical network.FIG.12shows the result of reflecting the result of the route search on the physical network. As shown inFIG.12, the route, which consists of a plurality of links connecting physical node A, physical node B, physical node C, physical node D, physical node E, and physical node F, is the route having the highest degree of coincidence with the route consisting of the coordinate point string included in the movement information (that is, the route searched or estimated by the route search unit11of IVI9).

<Effect>

From the above, according to the first embodiment, the cost-minimized route on the logical network, with which the total cost set based on the above (C) to (E) is minimized, that is, the route which is expected to be closest to the movement information of the moving body is calculated. As a result, the route obtained with a map other than the high-precision map is made accurately matched on the high-precision map.

Specifically, the hierarchical logical network is generated based on a coordinate point string included in a route in which the moving body travels or is predicted to travel in the future and a high-precision map, and a route is obtained on the high-precision map using the hierarchical logical network. This allows the state of the physical node to a given coordinate point string to be applied to the shortest route issue in the form of a “layer”.

In the hierarchical logical network, an inter-layer link connecting the same logical nodes between the layers is set, and a cost is set for the inter-layer link. This allows setting the cost according to the positional relationship between the coordinate point string and the physical link.

In the hierarchical logical network, the shortest route search is performed using the cost of inter-layer link, and the route on a high-precision map is obtained. This allows obtaining a route that minimizes the cost of the entire route.

In the route search in the hierarchical logical network, the shortest route search may be performed using the costs of a plurality of parameters. Link attributes other than the link number may be used for the plurality of parameters, and each may be weighted. This allows obtaining a route in which a plurality of parameters are considered.

Second Embodiment

In the first embodiment, the case where the route on which the moving body is to travel in the future is matched on the high-precision map has been described. In the second embodiment, a case where a route the moving body traveled in the past is matched on the map will be described.

FIG.13is a block diagram showing an application example of a map matching apparatus1according to the second embodiment, and shows an example of a system configuration including a server18and an information device24.

The information device24is an in-vehicle device that outputs probe data, and includes a gyro sensor25, a Global Positioning System (GPS) receiver26, a positioning unit27, and a transmission unit28. The information device24is provided on the moving body.

The gyro sensor25detects the angular velocity of the moving body during traveling. The GPS receiver26calculates the position of the moving body based on the signal received from a GPS satellite.

The positioning unit27calculates a position of the moving body in a place where the GPS receiver26cannot receive a signal, such as in a tunnel, based on the angular velocity detected by the gyro sensor25and the position of the moving body calculated by the GPS receiver26. In places where the GPS receiver26can receive the signal, the position calculated by the GPS receiver may be used as it is, and the position of the moving body may be calculated based on the signal the GPS receiver26has received and the angular velocity the gyro sensor25has detected.

The transmission unit28transmits the position information of the moving body the positioning unit27has calculated and additional event information to a server18as movement information (probe data) via the Internet. Examples of the event information include information around the moving body acquired from a sensor (not shown) provided on the moving body, the state of the driver of the moving body, and the like.

The server18is a probe data analysis server that analyzes movement information (probe data) received from the information device24, and includes the map matching apparatus1, a receiving unit19, an event information storage20, a map DB21, and a matching history storage22, and a statistical processing unit23. Hereinafter, although the case where the map DB21stores the above-mentioned regular map will be described, the above-mentioned high-precision map may be stored.

The receiving unit19receives the movement information of the moving body from the information device24via the Internet. Of the movement information which the receiving unit19has received, the event information is recorded in the event information storage20and the position information of the moving body is acquired and held by the movement information acquisition unit3. When a plurality of mobile bodies provided with the information device24exist, the receiving unit19receives the moving information from each information device24.

The map matching apparatus1includes the map information acquisition unit2, the movement information acquisition unit3, and the matching unit4, similar to the map matching apparatus1shown inFIG.2. The map information acquisition unit2and the matching unit4have the same configuration and operation as those described in the first embodiment; therefore, detailed description thereof will be omitted here.

The movement information acquisition unit3acquires the position information of the moving body among the movement information which the receiving unit19has received and holds the position information in chronological order. Further, when the movement information acquisition unit3acquires the position information of a plurality of moving bodies, the movement information acquisition unit3holds the position information for each moving body in chronological order. In this manner, the movement information acquisition unit3acquires the coordinate point string of the position of the moving body in the past traveled route.

The event information storage20stores event information in chronological order among the movement information which the receiving unit19has received. When the receiving unit19receives the movement information of the plurality of moving bodies, the event information storage20stores the moving information for each moving body.

The matching history storage22stores the link string included in the route on which the moving body has traveled on the map, which is specified by the matching unit4of the map matching apparatus1. When the matching unit4specifies a link string for the plurality of moving bodies, the matching history storage22stores the link string for each moving body.

The statistical processing unit23links the link string stored in the matching history storage22and the event information stored in the event information storage20based on a common time (time stamp) and accurately identifies on which link on the map the event occurred. That is, the statistical processing unit23accurately identifies the position of the moving body on the map when an event occurs.

From the above, according to the second embodiment, the map matching apparatus1performs the same operation as that of the first embodiment, so that the route the moving body traveled in the past can be accurately matched on the map.

<Hardware Configuration>

Each function of the map information acquisition unit2, the movement information acquisition unit3, and the matching unit4in the map matching apparatus1described in the first and second embodiments is implemented by the processing circuit. That is, the map matching apparatus1includes a processing circuit acquiring the map information, acquiring the movement information of the moving body, and specifying a link string corresponding to a route on a map based on the map information and the movement information. For the processing circuit, dedicated hardware may be adopted, or a processor (also referred to as a Central Processing Unit (CPU), a central processing unit, a processing unit, an arithmetic unit, a microprocessor, a microcomputer, a Digital Signal Processor (DSP)) that executes a program stored in a memory may also be adopted.

When the dedicated hardware is applied to the processing circuit, as shown inFIG.14, a processing circuit29corresponds, for example, to a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an Application Specific Integrated Circuit (ASIC), or a Field-Programmable Gate Array (FPGA), or the combination thereof. While each function of the map information acquisition unit2, the movement information acquisition unit3, and the matching unit4, or may also be implemented by one processing circuit29, each function may be collectively implemented by one processing circuit29.

When the processing circuit29is applied to the processor30shown inFIG.15, each function of the map information acquisition unit2, the movement information acquisition unit3, and the matching unit4is implemented by software, firmware, or a combination of software and firmware. The software or firmware is written as a program and stored in a memory31. The processor30implements each function by reading and executing the program recorded in the memory31. That is, the map matching apparatus1includes the memory31for storing the program which, eventually, executes the steps of acquiring the map information, acquiring the movement information of the moving body, and specifying a link string corresponding to a route on the map based on the map information and the movement information. Further, it can be said that these programs are programs to execute the procedure and method of the map information acquisition unit2, the movement information acquisition unit3, and the matching unit4. Here, the memory may be, for example, a non-volatile or volatile semiconductor memory, such as a Random Access Memory (RAM), a Read Only Memory (ROM), a flash memory, an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), or the like, a magnetic disk, a flexible disk, an optical disk, a compact disk, a digital versatile disc (DVD) or the like, or any storage medium used in the future.

For each function of the map information acquisition unit2, the movement information acquisition unit3, and the matching unit4, part of functions thereof may be implemented by dedicated hardware and another part of the components is implemented by software or the like.

Accordingly, the processing circuit can implement the above each function by hardware, software, firmware, or a combination thereof.

<System Configuration>

Although the map matching apparatus described above is applicable to a high-definition locator as described in the first embodiment, or applicable to a probe data analysis server as described in the second embodiment, the application thereof not limited thereto. The map matching apparatus is applicable, for example, to an in-vehicle navigation device, that is, a satellite navigation device, or a Portable Navigation Device (PND) that is mountable on a vehicle, and these can be appropriately combined to construct a system. In this case, each function or each component of the map matching apparatus is distributed and arranged in each function for constructing the above system.

Further, software in the above embodiments may be incorporated into, for example, a server. A map matching method implemented by the server executing the software includes acquiring map information including link endpoint coordinates, which are coordinates of endpoints of a plurality of links, and a connection relationship of each of the links, acquiring movement information of a moving body on a predetermined route, identifying a link string, which is a string of the links corresponding to the route, based on the acquired map information and the acquired movement information, and specifying the link string includes generating a physical network, which is a road network, based on the connection relationship and the movement information, generating a hierarchical logical network in which the physical network is duplicated a plurality of times and configured into hierarchy specifying a route with a minimized cost in the hierarchical logical network as the link string.

As described above, by incorporating the software that executes the operation in the above embodiments into the server and operating the server, the same effect as that in the above embodiments can be obtained.

In the present disclosure, the embodiments can be combined, appropriately modified or omitted, without departing from the scope of the disclosure.

While the disclosure has been shown and described in detail, the foregoing description is in all aspects illustrative and not restrictive. It is therefore understood that numerous modifications and variations can be devised without departing from the scope of the disclosure.

EXPLANATION OF REFERENCE SIGNS

1map matching apparatus,2map information acquisition unit,3moving information acquisition unit,4matching unit,5high-definition locator,6receiving unit,7high-precision map,8transmission unit,9IVI,10IVI map DB,11route search unit,12transmission unit,13ECU,14receiving unit,15recognition unit,16determination unit,17controller,18server,19receiving unit,20event information storage,21map DB,22matching history storage,23statistical processing unit,24information device,25gyro sensor,26GPS receiver,27positioning unit,28transmission unit,29processing circuit, 30 processor,31memory.