JP6540415B2 - Route setting method and navigation apparatus - Google Patents

Description

  The present invention relates to a route setting method and a navigation apparatus for setting a guidance route from a departure place to a destination using travel history data of a host vehicle.

  There is known a navigation device for calculating a route giving priority to a cognitive road, which is a road on which the vehicle has traveled in the past, when performing route guidance from a departure place to a destination (see, for example, Patent Document 1) .

JP, 2014-10061, A

By the way, in the conventional device, a plurality of candidate routes which are candidates for guidance routes to be presented to the user are calculated, and a road included in the calculated candidate route corresponds to a cognitive road or a non-cognitive road (no travel experience Determine if it corresponds to a road). Then, the candidate route with the shortest distance of the non-cognitive road is presented to the user as a cognitive road.
Here, when calculating a candidate route, first, route cost is used as a standard without considering things such as cognitive roads and non-cognitive roads. In other words, although the candidate route may include the cognitive road as a result, the cognitive road is not positively included. Therefore, there is a problem that the candidate route may not include the cognitive road.

  The present invention has been made in view of the above problems, and provides a route setting method and a navigation device capable of setting a route which surely includes a cognitive road when setting a guidance route from a departure place to a destination. The purpose is to

In order to achieve the above object, the present invention provides a memory storing map data and travel history data of the host vehicle on the map data, and an operation unit for setting a guidance route based on the map data and travel history data And a route setting method in the navigation device.
First, the setting of the departure place and the destination of the vehicle is received. Next, among the intersections on the cognitive road with travel experience extracted based on the travel history data, the intersection present at the closest position from the departure point is selected as the first candidate intersection. Subsequently, among the intersections on the recognition road, the intersection present at the closest position to the destination is selected as a second candidate intersection.
Then, a road including at least a part of a cognitive road from the first candidate intersection to the second candidate intersection is set as a guidance route , and the first candidate intersection and the second candidate intersection have a predetermined central angle centered on the departure point , And a sector-shaped area formed in a direction from the departure place to the destination, and the area boundary is selected from the intersection on the recognition road in the area passing through the departure place and the destination .

  Therefore, in the route setting method of the present invention, the guidance route from the departure point to the destination point includes a road passing the first candidate intersection and the second candidate intersection existing on a cognitive road experienced by the host vehicle. Can. Therefore, when setting a guidance route, it is possible to set a route that surely includes a cognitive road.

FIG. 1 is an overall system diagram showing a configuration of a navigation device of Example 1; 7 is a flowchart showing the flow of a route setting process implemented in the first embodiment. It is explanatory drawing which shows the processing image at the time of setting the departure place and the destination on map data. It is an explanatory view showing the processing image at the time of reading a cognitive road at the time of first run. It is explanatory drawing which shows the processing image at the time of reading a cognitive road at the time of 2nd driving | running | working. It is explanatory drawing which shows the processing image at the time of setting a candidate intersection selection area | region at the time of 1st driving | running | working. It is explanatory drawing which shows the processing image at the time of setting a candidate intersection selection area | region at the time of 2nd driving | running | working. It is explanatory drawing which shows the processing image at the time of selecting a 1st candidate intersection at the time of 1st driving | running | working. It is explanatory drawing which shows the processing image at the time of selecting a 1st candidate intersection at the time of 2nd driving | running | working. It is an explanatory view showing the processing image at the time of choosing the 2nd candidate intersection at the time of first run. It is explanatory drawing which shows the processing image at the time of selecting a 2nd candidate intersection at the time of 2nd driving | running | working. It is an explanatory view showing the processing image at the time of extracting a guidance road at the time of first run. It is explanatory drawing which shows the processing image at the time of extracting a guidance road at the time of 2nd driving | running | working. It is explanatory drawing which shows the processing image at the time of setting an intermediate route at the time of 1st driving | running | working. It is explanatory drawing which shows the processing image at the time of setting an intermediate route at the time of 2nd driving | running | working. It is explanatory drawing which shows the processing image at the time of setting a 1st connection path | route at the time of 1st driving | running | working. It is explanatory drawing which shows the processing image at the time of setting a 1st connection path | route at the time of 2nd driving | running | working. It is explanatory drawing which shows the processing image at the time of setting a 2nd connection path | route at the time of 1st driving | running | working. It is explanatory drawing which shows the processing image at the time of setting a 2nd connection path | route at the time of 2nd driving | running | working. It is explanatory drawing which shows the processing image at the time of displaying the guide route set at the time of 1st driving | running | working on a display. It is explanatory drawing which shows the processing image at the time of displaying the guide route set at the time of 2nd driving | running | working on a display. It is an explanatory view showing the processing image at the time of displaying the guidance course set up after the 3rd time on a display.

  Hereinafter, an embodiment for realizing a route setting method and a navigation device of the present invention will be described based on a first embodiment shown in the drawings.

Example 1
First, the configuration of the navigation device of the first embodiment will be described by being divided into "overall system configuration" and "route setting processing configuration".

[Whole system configuration]
FIG. 1 is an overall system diagram showing the configuration of the navigation device of the first embodiment. Hereinafter, the entire system configuration will be described based on FIG.

  The navigation apparatus 1 according to the first embodiment is a car navigation system mounted on a vehicle (not shown), and as shown in FIG. 1, an arithmetic unit 10, a memory 20, a touch panel 30, a display 40, and a communication unit. And 50.

  The calculation unit 10 includes a route setting unit 11 that calculates a guidance route based on data stored in the memory 20 and collective intelligence information obtained from the probe data server 100 via the communication unit 50. . The path setting unit 11 includes a CPU (central processing unit), a ROM (read only memory), a RAM (random access memory), and the like, and the CPU executes a program stored in the ROM using the RAM as a working area. It is constituted by doing.

The memory 20 is configured using a readable / writable DRAM, an SRAM, a flash memory, a recording medium such as a hard disk, and the like, and the arithmetic unit 10 controls reading and writing of data. Further, the memory 20 stores map data and travel history data of the host vehicle.
The "map data" is road map information, and a predetermined road number is stored in association with each road. Further, depending on the road, a predetermined road number is stored in association with each section of the road.
The "travel history data" is information of a road on which the host vehicle has traveled once or more in the past, and the road number on which the host vehicle has traveled corresponds to the time when the host vehicle traveled and the number of travels. It is attached and memorized.

  The touch panel 30 is a data input unit provided on the surface of the display 40. The user of the navigation device 1 operates the touch panel 30 to input a departure place or a destination of the vehicle into the route setting unit 11.

  The display 40 is configured of a liquid crystal panel or the like provided on an instrument panel in a vehicle compartment. The display 40 appropriately displays the map data stored in the memory 20, the guidance route set by the route setting unit 11, and the like.

The communication unit 50 is a communication unit that performs wireless communication with the probe data server 100 installed outside. The calculation unit 10 transmits an information acquisition request to the probe data server 100 via the communication unit 50. The arithmetic unit 10 also receives collective intelligence information generated based on probe data from the probe data server 100 via the communication unit 50.
In the probe data server 100, probe data including travel locus data (position information indicated by latitude and longitude and time information associated with the position information) is acquired from a large number of vehicles 101. Then, the acquired traveling locus data is matched with the map data to generate locus information, and the locus information is stored as collective intelligence information.

[Route setting processing configuration]
FIG. 2 shows the flow of the route setting process performed in the first embodiment. Hereinafter, each step of FIG. 2 showing an example of a route setting processing configuration will be described.

In step S1, the departure place O (shown by a circular icon in FIG. 3) of the host vehicle is set, and the process proceeds to step S2.
Here, the setting of the departure place O is performed based on the position information acquired from the GPS signal mounted on the vehicle if it is the current location of the own vehicle. In addition, when the user arbitrarily sets, the touch panel 30 is operated to input. In addition, in FIG. 3, the process image at the time of setting the departure place O and the destination D on map data is shown.

In step S2, following the setting of the departure place O in step S1, a destination D (shown by a flag icon in FIG. 3) of the vehicle is set, and the process proceeds to step S3.
Here, the setting of the destination D is input by operating the touch panel 30.

In step S3, following the setting of the destination D in step S2, in the past, the vehicle has traveled once or less from the departure place O set in step S1 to the destination D set in step S2. Determine if there is. In the case of YES (one run experience or less), the process proceeds to step S4. In the case of NO (with two or more trips), the process proceeds to step S15.
Here, the determination of the number of traveling experiences is performed based on the traveling history data stored in the memory 20.

In step S4, based on the traveling history data stored in the memory 20, following the judgment of one or less traveling experiences in step S3, the cognitive road N with which the vehicle has traveled (see FIGS. 4A and 4B). Read in) to proceed to step S5.
All roads other than the cognitive road N are non-cognitive roads that the vehicle has not traveled. Also, at the time of the first running, the read recognition road N is as shown in FIG. 4A. At the time of the 2nd run, the previous run experience is reflected and the recognition road N read in becomes as shown in FIG. 4B.

  In step S5, following reading of the recognition road N in step S4, whether or not the vehicle has traveled in the past from the departure place O set in step S1 to the destination D set in step S2 To judge. In the case of YES (no travel experience), the process proceeds to step S6. In the case of NO (one run experience), the process proceeds to step S7.

In step S6, following the determination of no travel experience in step S5, the candidate intersection selection area A (the area surrounded by a broken line in FIG. 5) is set to the first range, and the process proceeds to step S8.
Here, the “candidate intersection selection area” is an area for selecting “first candidate intersection” and “second candidate intersection” described later. The candidate intersection selection area A is set in a direction from the departure place O to the destination D as shown in FIG. Further, the candidate intersection selection area A is a predetermined angle area (an area in which the central angle θ about the departure point O changes) which is centered on the departure point O and gradually spreads toward the destination point D. Have.
The “first range” is a range in which the setting range of this angle range is relatively narrow. In the first embodiment, as shown in FIG. 5, it has a fan-shaped shape with a starting point O as a center, a straight distance from the starting point O to a destination D as a radius, and a central angle θ as a right angle (90 °). Let the region be the “first range”.

In step S7, following the determination that there is one travel experience in step S5, the candidate intersection selection area A (the area surrounded by a broken line in FIG. 6) is set to the second range, and the process proceeds to step S8.
Here, the “second range” is a range set so that the setting range of the angle area is larger than the “first range”. That is, in the “second range”, the central angle θ centering on the departure place O is larger than the “first range”. As a result, the setting range of the candidate intersection selection area A set in the “second range” becomes larger than that of the candidate intersection selection area A set in the “first range”. In the first embodiment, as shown in FIG. 6, a circular shaped area having a straight line connecting the departure place O and the destination D as a "second range".

In step S8, following the setting of the candidate intersection selection area A in step S6 or step S7, from the known intersection existing in the candidate intersection selection area A, the intersection closest to the departure place O is the first candidate intersection α (see FIG. 7A or FIG. 7B), and the process proceeds to step S9.
Here, the "known intersection" is an intersection on the recognition road N where the host vehicle has traveled in the past, and is an intersection to which the host vehicle has passed.
Further, the first candidate intersection α is at the position shown in FIG. 7A when the candidate intersection selection area A is set to the “first range”, and when the candidate intersection selection area A is set to the “second range”. Is the position shown in FIG. 7B. That is, depending on the size of the setting range of the cognitive road N and the candidate intersection selection area A, the position of the first candidate intersection α may change.

In step S9, following the selection of the first candidate intersection α in step S8, from the known intersection existing in the candidate intersection selection area A set in step S6 or step S7, the intersection closest to the destination D is selected second It selects as a candidate intersection (refer FIG. 8A or FIG. 8B), and follows it to step S10.
The second candidate intersection β is at the position shown in FIG. 8A when the candidate intersection selection area A is set to the “first range”, and when the candidate intersection selection area A is set to the “second range”. Is the position shown in FIG. 8B. That is, depending on the size of the setting range of the recognition road N and the candidate intersection selection area A, the position of the second candidate intersection β may change.

In step S10, following the selection of the second candidate intersection β in step S9, the guidance road from the first candidate intersection α selected in step S8 to the second candidate intersection β selected in step S9 It is extracted as “Y (indicated by hatching in FIGS. 9A and 9B)”, and the process proceeds to step S11.
Here, the “guided road” is a road passing through the first candidate intersection α and the second candidate intersection β and connecting the first candidate intersection α and the second candidate intersection β, and the entire length is constituted by the cognitive road The shortest route in the route.

In step S11, following extraction of the guiding road Y in step S10, an intermediate route M from the first candidate intersection α to the second candidate intersection β is set so as to include at least a part of the guiding road Y, step S12 Go to
Here, when setting the intermediate route M, as in the example shown in FIG. 10A, if the total length of the shortest route from the first candidate intersection α to the second candidate intersection β is configured by the guidance road Y, the intermediate route M and the guidance road Y are the same. That is, the total length of the intermediate route M is formed by the guide road Y.
Also, as shown in FIG. 10B, when the total length of the guidance road Y indicated by the hatching is longer than the total length of the shortest route S from the first candidate intersection α to the second candidate intersection β, that is, travel on the guidance road Y When moving from the first candidate intersection α to the second candidate intersection β results in a detour, the bypass road B for shortening the distance of the intermediate route M is extracted. Then, in consideration of the distance difference between the route combining the guidance road Y and the bypass road B and the shortest route S, the ratio of the bypass road B to the intermediate route M, etc., a part of the guidance road Y and the bypass road B To set an intermediate route M in combination. That is, the intermediate route M is a route that passes the induction road Y as much as possible (the ratio of the bypass road B is low), and the distance difference with the shortest route S is small. The bypass road B is a non-cognitive road where there is no travel experience of the host vehicle. Therefore, when there are a plurality of candidates for the bypass road B, a road judged to be optimal is preferentially selected based on the collective intelligence information generated based on the probe data.

In step S12, following the setting of the intermediate route M in step S11, a first connection route K1 (see FIG. 11A or 11B) from the departure point O to the first candidate intersection α is set, and the process proceeds to step S13.
Here, as shown in FIG. 11A, in the first connection route K1, if there is only a non-cognitive road where the host vehicle has not traveled between the departure point O and the first connection route K1, the probe data is A road judged to be optimum is selected and set based on the collective intelligence generated based on the above. Moreover, as shown to FIG. 11B, when including the cognitive road N with the travel experience of the own vehicle between the departure place O and the 1st connection route K1, the 1st connection route including the said cognitive road N Set K1.

In step S13, following the setting of the first connection route K1 in step S12, a second connection route K2 (see FIG. 12A or 12B) from the second candidate intersection β to the destination D is set, and the process proceeds to step S14. .
Here, as shown in FIG. 12A, in the second connection route K2, if there is only a non-cognitive road where the host vehicle has not traveled between the second candidate intersection β and the destination D, the probe data is A road judged to be optimum is selected and set based on the collective intelligence generated based on the above. Further, as shown in FIG. 12B, when the cognitive road N having the traveling experience of the vehicle is included between the second candidate intersection β and the destination D, the second connection route including the cognitive road N Set K2.

In step S14, following the setting of the second connection route K2 in step S13, a guidance route X from the origin O to the destination D consisting of the intermediate route M, the first connection route K1, and the second connection route K2 Are displayed on the display 40 in association with the map data, and the process proceeds to the end.
FIG. 13A shows a display image on the display 40 in the case where there is no travel experience from the departure place O to the destination D. Moreover, in FIG. 13B, the display image in the display 40 in, when there is one travel experience from the departure place O to the destination D is shown.

  In step S15, following the determination that there is two or more running experiences in step S3, collective intelligence information (probe collective intelligence) generated based on probe data is read from the probe data server 100, and the process proceeds to step S16.

In step S16, following the reading of the probe set knowledge in step S15, the probe set knowledge in which the total length of the guidance route from the departure place O set in step S1 to the destination D set in step S2 is read. The road which is determined to be optimal is selected and set on the basis of and the process proceeds to step S17.
That is, if traveling experience is performed twice or more, a route that seems to be optimal is searched using probe collective intelligence regardless of whether it is a cognitive road or not. Also, “the route considered to be optimum” is a route that meets an arbitrarily set criterion (for example, a shortest time route, a frequently used route, and the like).

In step S17, following the setting of the guide route in step S16, the set guide route is displayed on the display 40 in association with the map data, and the process proceeds to the end.
In addition, in FIG. 14, the display image in the display 40 in, when there are two or more travel experience from the departure place O to the destination D is shown.

Next, the operation will be described.
First, “a general navigation device configuration and problems” will be described, and then, the operation of the route setting method and the navigation device according to the first embodiment will be described as “initial operation route setting operation”, and “second operation route setting”. The operation will be described by being divided into the “operation for setting the third and subsequent traveling routes”.

[Configuration and Issues of General Navigation Device]
Generally, when searching for a route in a navigation device, an optimum route that matches the set conditions is searched based on conditions such as distance, time, cost (charge), presence of toll roads, and the like. On the other hand, it has been found that, for the user (driver), driving a road that has not been driven in the past has a high driving load. Therefore, when a route is searched based on distance, time, etc., a route that the user has never traveled is set, and the driving load of the user can not be reduced.

On the other hand, after searching for a plurality of routes (candidate routes) corresponding to each of the plurality of conditions, the distance of a road (non-cognitive road) which the vehicle has never traveled for each candidate route is calculated. It is conceivable to select and present a route with the smallest distance of non-cognitive roads included in the candidate route. At this time, a route passing through the cognitive road will be selected as much as possible.
However, even in this case, the presence of a cognitive road (non-cognitive road) is not considered when searching for a plurality of candidate routes. Therefore, even if a cognitive road exists near the searched candidate route, a route for selecting the cognitive road is not set. That is, since a candidate route is searched and then matching with a cognitive road (non-cognitive road), even if any candidate route is selected, it eventually becomes equivalent to a route searched by a general navigation device, It did not become a route that prioritized the cognitive road.

[Route setting action at the time of the first run
In the case of searching for a guidance route in a vehicle equipped with the navigation device 1 of the first embodiment, in the flowchart shown in FIG. 2, the process proceeds from step S1 to step S2, and the departure place O and the destination D are set. Then, the process proceeds to step S3, and it is determined whether the travel experience from the departure place O to the destination D set by the user is equal to or less than one.
In the case where the vehicle has not traveled once in the past (without travel experience) and travels for the first time this time, the process proceeds to step S4, and a cognitive road is read from the memory 20.

  Then, proceeding from step S5 to step S6, the candidate intersection selection area A is set to the "first range" shown in FIG. When the candidate intersection selection area A is set, the process proceeds to step S8, and the intersection closest to the departure point O is the first candidate from the known intersections present in the candidate intersection selection area A set to the “first range”. The intersection point α is selected.

  When the first candidate intersection α is selected, the process proceeds to step S9, and the intersection closest to the destination D is the second candidate intersection from the known intersections present in the candidate intersection selection area A set in the “first range”. Selected as β.

Then, when the first candidate intersection α and the second candidate intersection β are selected, the process proceeds from step S10 to step S11, and a guidance road Y which is a cognitive road connecting the second candidate intersection β is extracted from the first candidate intersection α Ru. Then, an intermediate route M from the first candidate intersection α to the second candidate intersection β is set so as to include a part of the guide road Y.
Here, on the intermediate route M during the first run of the first embodiment, the guidance road Y, which is a cognitive road connecting the first candidate intersection α to the second candidate intersection β, is from the first candidate intersection α to the second candidate intersection β It is the shortest route to That is, the total length of the intermediate route M is formed by the guide road Y. As a result, from the first candidate intersection α to the second candidate intersection β, a cognitive road which has been traveled by the vehicle is guided in all steps.

  Thereafter, the process proceeds from step S12 to step S13, and a first connection route K1 from the departure place O to the first candidate intersection α and a second connection route K2 from the second candidate intersection β to the destination D are set. . Then, the process proceeds to step S14, and as shown in FIG. 13A, the guidance route from the departure place O to the destination D consisting of the intermediate route M, the first connection route K1 and the second connection route K2 is map data , And displayed on the display 40.

  As described above, in the route setting method and the navigation device 1 according to the first embodiment, the guidance route displayed on the display 40 is a route passing the first candidate intersection α and the second candidate intersection β on the cognitive road. Therefore, when setting a guidance route, it is possible to set a route that surely includes a cognitive road. And, it is possible to guide the route which can reduce the driving load of the user (driver).

  Further, in the first embodiment, the first candidate intersection α is selected from known intersections in the candidate intersection selection area A set in the direction from the departure place O toward the destination D. Therefore, the first candidate intersection α is an intersection existing on the destination D side with respect to the departure place O, and when the user goes to the destination D, the traveling direction when running out from the departure place O is restricted. Can maintain a sense of direction against As a result, it is possible to guide a route that is easy to understand globally.

  In particular, in the first embodiment, when there is no travel experience from the departure place O to the destination D, the candidate intersection selection area A is set to a relatively narrow “first area” of the angle area. Therefore, the selection area of the first candidate intersection α is limited, and the first candidate intersection α can be selected from known intersections that further match the direction toward the destination D. As a result, it is possible to provide a path that is easier to sense.

  Further, in the first embodiment, the second candidate intersection β is also selected from known intersections present in the candidate intersection selection area A set in the “first range”, similarly to the first candidate intersection α. Therefore, when the second candidate intersection β is an intersection existing on the departure place O side with respect to the destination D and the user goes to the destination D, the sense of direction for the destination D can be maintained. As a result, it is possible to guide a route that is easy to understand globally.

  Furthermore, in the first embodiment, when setting the first connection route K1 from the departure place O to the first candidate intersection α and the second connection route K2 from the second candidate intersection β to the destination D, If there is only a non-cognitive road without travel experience, a road judged to be optimal is selected and set based on the collective intelligence information generated based on the probe data.

[The route setting action at the time of 2nd run]
When there is one travel experience from the departure place O to the destination D set by the user (in the case of the second travel), the first travel time after progressing from step S1 → step S2 → step S3 Similarly, the process proceeds to step S4, and the recognition road N is read.

  Then, proceeding from step S5 to step S7, the candidate intersection selection area A is set to the “second range” shown in FIG. When the candidate intersection selection area A is set, the process proceeds to step S8, and the intersection closest to the departure point O is the first candidate from the known intersections present in the candidate intersection selection area A set to the “second range”. The intersection point α is selected. Then, the process proceeds to step S9, and an intersection closest to the destination D is selected as a second candidate intersection β from known intersections present in the candidate intersection selection area A set in the “second range”.

Here, the “second range”, which is the setting area of the candidate intersection selection area A, is the angle area thereof, as compared to the “first range” set when traveling from the departure place O to the destination D is the first time. The setting range of has become large.
Therefore, when traveling from the departure place O to the destination D is the second time, the candidate intersection selection area A in the vicinity of the departure place O can be widened. That is, the restriction on the traveling direction from the departure point O can be made relatively loose.
As a result, it is possible to select the first candidate intersection α and the second candidate intersection β from more known intersections, and for example, select a route that can shorten the traveling distance or shorten the time than the first run. Can be made possible.

Then, when the first candidate intersection α and the second candidate intersection β are selected, the process proceeds from step S10 to step S11, and a guidance road Y which is a cognitive road connecting the second candidate intersection β is extracted from the first candidate intersection α Ru. Then, an intermediate route M from the first candidate intersection α to the second candidate intersection β is set so as to include a part of the guide road Y.
Thereafter, the process proceeds from step S12 to step S13 to step S14, and when the first connection route K1 and the second connection route K2 are set, the induction route X including the intermediate route M and the first and second connection routes K1 and K2 Are presented on the display 40.

Here, at the time of the 2nd run of Example 1, guidance road Y which is cognitive road N which connects the 2nd candidate intersection beta from the 1st candidate intersection alpha is longer than the shortest route S.
Therefore, the bypass road B which can achieve shortening of this middle route M is extracted rather than the case where the full length of middle route M is constituted by induction road Y. Then, by combining the bypass road B and a part of the guidance road Y, and including the part of the guidance road Y and the bypass road B for shortening the middle path M in the middle path M, the middle path M can be set to be a route including the induced road Y but having a small difference in distance from the shortest route S.

[The route setting operation at the time of the third and subsequent driving]
If there are two or more travel experiences from the departure place O to the destination D set by the user (when traveling for the third and subsequent times), the process proceeds to step S1 → step S2 → step S3 and then to step S15. Then, the probe set knowledge is read from the probe data server 100.

Then, the process proceeds from step S16 to step S17, and the total length of the guidance route X from the departure place O to the destination D is set by selecting and setting the road judged to be optimum based on the read probe set knowledge. The guidance route X thus determined is displayed on the display 40.
Thereby, as shown in FIG. 14, the guidance route X from the departure place O to the destination D is displayed in association with the map data.

  As described above, in the first embodiment, regardless of the presence or absence of the recognition road N, the guidance route X from the departure place O to the destination D is set based on the probe collective knowledge. Therefore, it is possible to set a route determined to be optimal in consideration of the trends of other vehicles.

Next, the effects will be described.
In the route searching method and the navigation device of the first embodiment, the following effects can be obtained.

(1) A memory 20 storing map data and travel history data of the vehicle on the map data, and an operation unit 10 for setting a guidance route X based on the map data and the travel history data It is a route setting method in the navigation device 1, and
Accept the setting of the departure place O and the destination D of the own vehicle,
Among the intersections on the cognitive road N with travel experience extracted based on the travel history data, the intersection present at a position closest to the departure place O is set as a first candidate intersection α.
Among the intersections on the recognition road N, the intersection existing at the closest position to the destination D is set as a second candidate intersection β,
A road passing through the first candidate intersection α and the second candidate intersection β is set as the guidance route X.
Thereby, when setting the guidance route X from the departure place O to the destination D, it is possible to set a route that surely includes the cognitive road N.

(2) The first candidate intersection α is selected from intersections on the recognition road N in the candidate intersection selection area A set in the direction from the departure place O toward the destination D.
As a result, in addition to the effect of (1), the traveling direction when running out from the departure place O can be restricted, and a sense of direction with respect to the destination D can be maintained.

(3) The second candidate intersection β is selected from intersections on the cognitive road N within a predetermined range of candidate intersection selection area A which is centered on the departure place O and gradually spreads toward the destination D And
When the travel experience from the departure place O to the destination D is high, the setting range of the candidate intersection selection area A is made larger than when the travel experience is low.
Thereby, in addition to the effect of (1), when the number of travels is small, the second candidate intersection β can be selected from known intersections that match the direction toward the destination D, and the guidance route X is grasped by sense It can be an easy route. In addition, when travel experience is high, the selection range of the second candidate intersection β can be expanded, and a more appropriate route can be set.

(4) When setting up the guidance route X, the intermediate route M from the first candidate intersection α to the second candidate intersection β includes a non-cognitive road (bypass road B) that shortens the distance or travel time And
Thereby, in addition to the effect of any one of (1) to (3), it is possible to make the guide route X a route with a small difference in distance from the shortest route S while including the guide road Y with experience of traveling.

(5) The selection of the non-cognitive road without the driving experience of the vehicle contained in the guidance route X is performed based on the collective intelligence information obtained from the probe data.
Thereby, in addition to the effect in any one of (1) to (4), when selecting a non-cognitive road, it becomes possible to set a route that is determined to be optimal in consideration of the trends of other vehicles.

(6) When the traveling experience from the departure place O to the destination D is performed multiple times, all routes of the guidance route X from the departure place O to the destination D are set based on the collective intelligence information And
Thereby, in addition to the effect of any one of (1) to (5), when there are travel experiences from the departure place O to the destination D multiple times, all routes of the guidance route X regardless of the cognitive road N of the own vehicle In the above, it is possible to set a route that is determined to be optimal in consideration of the trends of other vehicles.

(7) A memory 20 storing map data and travel history data of the vehicle on the map data, and an operation unit 10 for setting a guidance route X based on the map data and the travel history data The navigation device 1 is
The arithmetic unit 10 is
Accept the setting of the departure place O and the destination D of the own vehicle,
Among the intersections on the cognitive road N with travel experience extracted based on the travel history data, the intersection present at a position closest to the departure place O is set as a first candidate intersection α.
Among the intersections on the recognition road N, the intersection existing at the closest position to the destination D is set as a second candidate intersection β,
The route setting unit 11 is configured to set a road passing the first candidate intersection α and the second candidate intersection β as the guidance route X.
Thereby, when setting the guidance route X from the departure place O to the destination D, it is possible to set a route that surely includes the cognitive road N.

  As mentioned above, although the route setting method and the navigation apparatus of the present invention have been described based on the first embodiment, the specific configuration is not limited to the first embodiment, and each claim in the claims Modifications and additions to the design are permitted without departing from the scope of the invention.

  In Example 1, when there is no travel experience from the departure place O to the destination D (at the time of the first run), the candidate intersection selection area A is set to the “first range”, and the departure place O to the destination D An example was shown in which the candidate intersection selection area A is set to the "second range" when there is one travel experience (at the second travel time). However, the setting range of the angle area of the candidate intersection selection area A may be enlarged not only when the travel experience from the departure point O to the destination D is high but also when the travel experience is low. That is, for example, the candidate intersection selection area A may be set as the “first range” until the third traveling time, and as the “second range” after the fourth traveling time.

In addition, in the first embodiment, a fan-shaped region having the origin O as a center, the straight distance from the origin O to the destination D as a radius, and the central angle θ as a right angle (90 °) (see FIG. 5) An example is shown in which a circular area (see FIG. 6) having a diameter of a straight line connecting the departure place O and the destination D as the “first range” and the “second range”.
However, the present invention is not limited to this. For example, a region of an isosceles triangle shape or a trapezoid shape whose height is a straight line connecting the departure place O and the destination D may be set as the “first range”. A second region may be a square region centered on a straight line connecting with the ground D, or an elliptically shaped region having a major axis the straight line connecting the starting place O and the destination D.
Furthermore, the starting point O and the destination D may not be included in the candidate intersection selection area A.

Furthermore, in the first embodiment, when selecting the first candidate intersection α, the candidate intersection selection area A is first set, but the present invention is not limited to this. Although selecting one of the first candidate intersections α from the intersections on the recognition road N in the candidate intersection selection area A can shorten the selection time of the first candidate intersection α, the first candidate without setting the candidate intersection selection area A The intersection point α may be selected.
Further, the selection range of the second candidate intersection β is not necessarily limited.

  In the first embodiment, when the travel experience from the departure place O to the destination D is less than one, the guidance route including the cognitive road is surely set, and the travel experience from the departure place O to the destination D When there are two times (when traveling from the third time onwards), an example is shown in which the guidance route is set from the probe set knowledge information. However, it is not limited to this. For example, even if there are two or more travel experiences from the departure point O to the destination D, if a predetermined time or more has passed since the previous travel, set up a guidance route that includes the cognitive road reliably It is also good.

  Also, in the first embodiment, the first connection route K1 is set because the departure place O and the first candidate intersection α are separated, and the destination D and the second candidate intersection β are separated from each other. An example of setting the connection route K2 has been shown. However, in the case where the departure point O and the first candidate intersection α match (including not only a perfect match but also a near match), it is not necessary to set the first connection route K1. In addition, when the destination D and the second candidate intersection point β match (including not only perfect match but also substantially match), it is not necessary to set the second connection route K2.

1 Navigation Device 10 Arithmetic Unit 11 Route Setting Unit 20 Memory 30 Touch Panel 40 Display 50 Communication Unit 100 Probe Data Server

Claims (6)

A route setting method in a navigation device, comprising: a memory storing map data and travel history data of the host vehicle on the map data; and an operation unit for setting a guidance route based on the map data and the travel history data And
Accept the setting of the departure place and destination of the vehicle.
Among the intersections on the cognitive road with travel experience extracted based on the travel history data of the own vehicle, the intersection present at the closest position from the departure point is set as a first candidate intersection,
Among the intersections on the recognition road, the intersection existing at the closest position to the destination is set as a second candidate intersection,
A road including at least a part of a cognitive road from the first candidate intersection to the second candidate intersection is set as a guidance route ,
The first candidate intersection and the second candidate intersection are fan-shaped regions having a predetermined central angle centered on the departure point and formed in a direction from the departure point toward the destination. The route setting method characterized in that the area boundary is selected from the intersection on the recognition road in the area passing through the departure place and the destination . In the route setting method described in claim 1 ,
The route setting method , wherein the guidance route is set to a route with a small difference from the shortest route from the first candidate intersection to the second candidate intersection . In the route setting method described in claim 1 or claim 2 ,
When setting the guidance route, the intermediate route from the first candidate intersection to the second candidate intersection includes a non-cognitive road with no travel experience of the vehicle that shortens the distance or the travel time. Setting method. In the route setting method according to any one of claims 1 to 3 ,
A route setting method characterized in that selection of a non-cognitive road having no travel experience of the vehicle contained in the guidance route is performed based on collective intelligence information obtained from probe data. In the route setting method described in claim 4 ,
A route setting method comprising: setting the entire route of the guidance route from the departure place to the destination based on the collective intelligence when there is a plurality of travel experiences from the departure place to the destination. A navigation apparatus, comprising: a memory storing map data and travel history data of the host vehicle on the map data; and a calculation unit for setting a guidance route based on the map data and the travel history data,
The arithmetic unit is
Accept the setting of the departure place and destination of the vehicle.
Among the intersections on the cognitive road with travel experience extracted based on the travel history data, the intersection present at a position closest to the departure place is set as a first candidate intersection,
Among the intersections on the recognition road, the intersection existing at the closest position to the destination is set as a second candidate intersection,
A road including at least a part of a cognitive road from the first candidate intersection to the second candidate intersection is set as a guidance route, and the first candidate intersection and the second candidate intersection are predetermined around the departure place. A sector-shaped area having a central angle and formed in a direction from the departure place to the destination, the intersection of the area boundary on the cognitive road in the area passing through the departure place and the destination A navigation apparatus, comprising: a route setting unit for selecting from the following .