JP2017058289A - Route setting method and navigation device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a route setting method capable of setting a route certainly including a recognized road when a guide route from a departure place to a destination is set.SOLUTION: Setting of a departure place O and a destination D is accepted. Of intersections on a recognized road N on which a travel has been performed and that is extracted on the basis of travel history data of an own vehicle stored in a memory 20, the intersection existing at the nearest position to the departure place O is set as a first candidate intersection α, and the intersection existing at the nearest position to the destination D is set as a second candidate intersection β. The road passing the first candidate intersection α and second candidate intersection β is set as a guide route X from the departure place O to the destination D.SELECTED DRAWING: Figure 2

Description

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

  When performing route guidance from a departure place to a destination, a navigation device is known that calculates a route that prioritizes a recognized road, which is a road on which the vehicle has traveled in the past (see, for example, Patent Document 1). .

JP 2014-10061 A

By the way, in the conventional apparatus, a plurality of candidate routes that are candidates for the guide route to be presented to the user are calculated, and whether the road included in the calculated candidate route corresponds to a cognitive road or a non-cognitive road (having no traveling experience). To determine whether it corresponds to (road). Then, the candidate route with the shortest distance of the non-recognized road is presented to the user as the recognized road.
Here, when calculating the candidate route, the route cost is first used as a reference without considering the recognition road or the non-recognition road. That is, as a result, the recognition road may be included in the candidate route, but the recognition road is not actively included. For this reason, there existed a problem that a recognition road may not be included in a candidate route.

  The present invention has been made paying attention to the above problem, and provides a route setting method and a navigation device capable of reliably setting a route including a recognition road when setting a guide route from a departure place to a destination. The purpose is to do.

In order to achieve the above object, the present invention includes a map data and a memory that stores travel history data of the host vehicle on the map data, and a calculation unit that sets a guide route based on the map data and the travel history data. The route setting method in the navigation device having.
First, the setting of the departure place and the destination of the own vehicle is received. Next, an intersection existing at a position closest to the departure place is selected as the first candidate intersection among the intersections on the cognitive road with the traveling experience extracted based on the traveling history data. Subsequently, of the intersections on the recognition road, an intersection that is closest to the destination is selected as the second candidate intersection.
Then, a road passing through the first candidate intersection and the second candidate intersection is set as a guidance route from the departure place to the destination.

  Therefore, in the route setting method of the present invention, the guidance route from the departure point to the destination includes a road that passes through the first candidate intersection and the second candidate intersection that exist on the recognition road that the vehicle has experienced traveling. Can do. Therefore, when setting the guidance route, it is possible to set a route that reliably includes the recognition road.

1 is an overall system diagram illustrating a configuration of a navigation device according to a first embodiment. 4 is a flowchart illustrating a flow of route setting processing performed 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 explanatory drawing which shows the process image at the time of reading the recognition road at the time of the first run. It is explanatory drawing which shows the process image at the time of reading the recognition road at the time of the 2nd driving | running | working. It is explanatory drawing which shows the process image at the time of setting a candidate intersection selection area | region at the time of the first run. It is explanatory drawing which shows the process image at the time of setting a candidate intersection selection area | region at the time of the 2nd driving | running | working. It is explanatory drawing which shows the process image at the time of selecting the 1st candidate intersection at the time of the first run. It is explanatory drawing which shows the process image at the time of selecting the 1st candidate intersection at the time of the 2nd driving | running | working. It is explanatory drawing which shows the process image at the time of selecting the 2nd candidate intersection at the time of the first run. It is explanatory drawing which shows the process image at the time of selecting the 2nd candidate intersection at the time of the 2nd driving | running | working. It is explanatory drawing which shows the process image at the time of extracting a guidance road at the time of the first run. It is explanatory drawing which shows the process image at the time of extracting a guidance road at the time of the 2nd driving | running | working. It is explanatory drawing which shows the process image at the time of setting an intermediate route at the time of the first run. It is explanatory drawing which shows the process image at the time of setting an intermediate | middle route at the time of the 2nd driving | running | working. It is explanatory drawing which shows the process image at the time of setting a 1st connection path | route at the time of the first run. It is explanatory drawing which shows the process image at the time of setting a 1st connection path | route at the time of the 2nd driving | running | working. It is explanatory drawing which shows the process image at the time of setting a 2nd connection path | route at the time of the first run. It is explanatory drawing which shows the process 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 process image at the time of displaying the guidance route set at the time of the first run on a display. It is explanatory drawing which shows the process image at the time of displaying the guidance path | route set at the time of the 2nd driving | running | working on a display. It is explanatory drawing which shows the process image at the time of displaying the guidance path | route set after the 3rd time on a display.

  Hereinafter, a mode 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 according to the first embodiment will be described by dividing it into “entire system configuration” and “route setting processing configuration”.

[Overall system configuration]
FIG. 1 is an overall system diagram illustrating the configuration of the navigation device according to the first embodiment. The overall system configuration will be described below with reference to FIG.

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

  The calculation unit 10 includes a route setting unit 11 that calculates a guide route based on data stored in the memory 20 and collective intelligence information acquired 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), etc., and the CPU executes a program stored in the ROM using the RAM as a working area. It is composed by doing.

The memory 20 is configured using a readable / writable DRAM, SRAM, flash memory, recording medium such as a hard disk, and the like. The memory 20 stores map data and travel history data of the host vehicle.
“Map data” is road map information, and a predetermined road number is associated with each road and stored. Further, depending on the road, a predetermined road number is stored in association with each section of the road.
“Traveling history data” is information on the road on which the host vehicle has traveled at least once in the past. The road number on which the host vehicle has traveled corresponds to the time and number of times the host vehicle has traveled. Attached and memorized.

  The touch panel 30 is data input means provided on the surface of the display 40. The user of the navigation device 1 operates the touch panel 30 to input the departure point and destination of the host vehicle to the route setting unit 11.

  The display 40 is constituted by a liquid crystal panel or the like provided on an instrument panel in the vehicle interior. 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. Further, the calculation unit 10 receives collective intelligence information generated based on the probe data from the probe data server 100 via the communication unit 50.
Note that the probe data server 100 acquires probe data consisting of travel locus data (position information indicated by latitude and longitude and time information associated with the position information) from a large number of vehicles 101. Then, the acquired traveling locus data is matched with map data to generate locus information, and this locus information is stored as collective intelligence information.

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

In step S1, the departure point O (indicated by a round icon in FIG. 3) of the host vehicle is set, and the process proceeds to step S2.
Here, if the departure location O is the current location of the host vehicle, the departure location O is set based on position information acquired from a GPS signal mounted on the vehicle. Further, when the user arbitrarily sets, the touch panel 30 is operated to input. FIG. 3 shows a processing image when the departure point O and the destination D are set on the map data.

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

In step S3, following the setting of the destination D in step S2, the vehicle has traveled once or less in the past from the departure point O set in step S1 to the destination D set in step S2. Judge whether there is. If YES (less than one driving experience), the process proceeds to step S4. In the case of NO (having two or more driving experiences), the process proceeds to step S15.
Here, the determination of the number of travel experiences is performed based on the travel history data stored in the memory 20.

In step S4, following the determination that the driving experience is less than once in step S3, based on the driving history data stored in the memory 20, the cognitive road N on which the host vehicle has traveled (in FIGS. 4A and 4B). Read in color) and proceed to step S5.
Note that roads other than the recognition road N are all non-recognition roads on which the vehicle has not traveled. In addition, when the vehicle travels for the first time, the read recognition road N is as shown in FIG. 4A. At the time of the second run, the previous running experience is reflected, and the read recognition road N is as shown in FIG. 4B.

  In step S5, following the reading of the recognition road N in step S4, whether or not the host vehicle has traveled in the past from the departure point O set in step S1 to the destination D set in step S2. Judging. If YES (no driving experience), the process proceeds to step S6. If NO (there is one driving experience), the process proceeds to step S7.

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

In step S7, following the determination that there is one driving experience in step S5, the candidate intersection selection area A (area surrounded by a broken line in FIG. 6) is set as 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 region is larger than the “first range”. That is, in the “second range”, the central angle θ centered on the departure point O is larger than the “first range”. Thereby, the candidate intersection selection area A set to the “second range” has a larger setting range than the candidate intersection selection area A set to the “first range”. In the first embodiment, as shown in FIG. 6, a circular area having a diameter of a straight line connecting the starting point O and the destination D is defined as a “second range”.

In step S8, following the setting of the candidate intersection selection area A in step S6 or step S7, the intersection closest to the departure point O from the known intersection existing in the candidate intersection selection area A is set as the first candidate intersection α (FIG. 7A or 7B) and proceed 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 where the host vehicle has passed.
The first candidate intersection α is the position shown in FIG. 7A when the candidate intersection selection area A is set to “first range”, and when the candidate intersection selection area A is set to “second range”. Is the position shown in FIG. 7B. That is, the position of the first candidate intersection α may change depending on the size of the setting range of the recognition road N and the candidate intersection selection area A.

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

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

In step S11, following the extraction of the guidance road Y in step S10, the 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 guidance road Y, and step S12. Proceed to
Here, the intermediate route M is set when the total length of the shortest route from the first candidate intersection α to the second candidate intersection β is constituted by the guide road Y as in the example shown in FIG. 10A. M and the guide road Y are the same. That is, the entire length of the intermediate route M is constituted by the guide road Y.
In addition, as shown in FIG. 10B, when the total length of the guide road Y indicated by diagonal lines 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, the vehicle travels on the guide road Y. Thus, when the vehicle travels from the first candidate intersection α to the second candidate intersection β, a bypass road B that shortens the distance of the intermediate route M is extracted. Then, considering the distance difference between the route combining the guide road Y and the bypass road B and the shortest route S, the ratio of the bypass road B in the intermediate route M, etc., a part of the guide road Y and the bypass road B An intermediate route M combining the above is set. That is, the intermediate route M is a route that passes through the guide road Y as much as possible (the ratio of the bypass road B is low) and has a small distance difference from the shortest route S. Note that the bypass road B is a non-cognitive road with no traveling experience of the host vehicle. Therefore, when there are a plurality of candidates for the bypass road B, the road that is determined 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, if there is only a non-cognitive road in which the host vehicle has no travel experience between the starting point O and the first connection route K1, the first connection route K1 is included in the probe data. The road determined to be optimal based on the collective intelligence information generated based on the selection is selected and set. In addition, as illustrated in FIG. 11B, when a recognition road N with traveling experience of the host vehicle is included between the departure point O and the first connection route K1, the first connection route including the recognition road N is included. 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 FIG. 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, if there is only a non-cognitive road in which the host vehicle has no travel experience between the second candidate intersection β and the destination D, the second connection route K2 is included in the probe data. The road determined to be optimal based on the collective intelligence information generated based on the selection is selected and set. In addition, as shown in FIG. 12B, when a recognized road N with traveling experience of the host vehicle is included between the second candidate intersection β and the destination D, the second connection route including the recognized road N Set K2.

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

  In step S15, following the determination that there are two or more travel experiences in step S3, the collective intelligence information (probe collective intelligence) generated based on the 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 collective intelligence in step S15, the total length of the guide route from the starting point O set in step S1 to the destination D set in step S2 is read. Based on this, the road determined to be optimal is selected and set, and the process proceeds to step S17.
That is, if the driving experience is two times or more, a route that seems to be optimal is searched using probe collective intelligence regardless of whether the road is a cognitive road or not. In addition, the “route that seems to be optimal” is a route that matches an arbitrarily set standard (for example, a route with the shortest time, a route with high use frequency, etc.).

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.
FIG. 14 shows a display image on the display 40 in the case where there are two or more traveling experiences from the departure point O to the destination D.

Next, the operation will be described.
First, “general navigation device configuration and problems” will be described, and then the route setting method and the navigation device of the first embodiment will be described as “first-time travel route setting effect”, “second-time travel route setting”. The description will be divided into “operation” and “route setting operation during travel after the third time”.

[General navigation device configuration and issues]
In general, when searching for a route in a navigation device, an optimum route that matches a set condition is searched based on conditions such as distance, time, cost (fee), and presence / absence of a toll road. On the other hand, for a user (driver), driving on a road that has never traveled in the past is known to have 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 on the user cannot 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) where the vehicle has not traveled is calculated for each candidate route, It is conceivable to select and present a route with the shortest distance of the non-cognitive road included in the candidate route. At this time, a route passing through the cognitive road as much as possible is selected.
However, even in this case, the existence of a cognitive road (non-cognitive road) is not considered when searching for a plurality of candidate routes. Therefore, even if a recognized road exists near the searched candidate route, a route for selecting the recognized road is not set. In other words, since the candidate route is searched and matched with the cognitive road (non-cognitive road), no matter which candidate route is selected, it becomes the same as the route searched by a general navigation device in the end. The route did not prioritize the cognitive road.

[Route setting action during the first run]
When searching for a guidance route in a vehicle equipped with the navigation device 1 according to the first embodiment, the process proceeds from step S1 to step S2 in the flowchart shown in FIG. 2, and the departure point O and the destination D are set. And it progresses to step S3 and it is judged whether the driving | running experience from the departure place O to the destination D set by the user is 1 time or less.
If the vehicle has never traveled in the past (no travel experience) and this time is the first travel, the process proceeds to step S4, and the recognition road is read from the memory 20.

  Then, the process proceeds from step S5 to step S6, and the candidate intersection selection area A is set to the “first range” shown in FIG. If 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 existing in the candidate intersection selection area A set in the “first range”. Selected as intersection α.

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

When the first candidate intersection α and the second candidate intersection β are selected, the process proceeds from step S10 to step S11, and the guidance road Y, which is a recognition road connecting the second candidate intersection α and the second candidate intersection β, is extracted. The 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, in the intermediate route M at the time of the first run of the first embodiment, the guide road Y that is a recognition road connecting the first candidate intersection α to the second candidate intersection β is changed from the first candidate intersection α to the second candidate intersection β. It becomes the shortest route to. That is, the entire length of the intermediate route M is constituted by the guide road Y. As a result, between the first candidate intersection α and the second candidate intersection β, a cognitive road that has traveled by the host 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 point 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 starting point O to the destination D, which is composed of the intermediate route M, the first connection route K1, and the second connection route K2, is represented by map data. Are displayed on the display 40 in association with each other.

  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 that passes through the first candidate intersection α and the second candidate intersection β on the cognitive road. Therefore, when setting the guidance route, it is possible to set a route that reliably includes the recognition road. Then, a route that can reduce the driving burden on the user (driver) can be guided.

  In the first embodiment, the first candidate intersection α is selected from the known intersections in the candidate intersection selection area A set in the direction from the departure point O toward the destination D. Therefore, the first candidate intersection α is an intersection existing on the side of the destination D with respect to the departure point O. When the user goes to the destination D, the traveling direction when starting from the departure point O is limited, and the destination D Can maintain a sense of direction. As a result, a route that is easy to understand globally can be guided.

  In particular, in the first embodiment, when there is no travel experience from the departure point O to the destination D, the candidate intersection selection area A is set to a “first range” having a relatively narrow 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 match the direction toward the destination D. As a result, it is possible to provide a route that is easier to grasp sensuously.

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

  Furthermore, in the first embodiment, when setting the first connection route K1 from the departure point 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 having no traveling experience, a road determined to be optimal based on collective intelligence information generated based on probe data is selected and set.

[Route setting action during the second run]
When there is one driving experience from the starting point O to the destination D set by the user (in the case of the second driving), the process proceeds from step S1 to step S2 to step S3, and then the first driving. Similarly, the process proceeds to step S4, and the recognition road N is read.

  Then, the process proceeds from step S5 to step S7, and 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 existing in the candidate intersection selection area A set in the “second range”. Selected as intersection α. Then, the process proceeds to step S9, and the intersection closest to the destination D is selected as the second candidate intersection β from the known intersections existing in the candidate intersection selection area A set to the “second range”.

Here, the “second range” that is the setting area of the candidate intersection selection area A is an angular area compared to the “first range” that is set when traveling from the departure point O to the destination D for the first time. The setting range of is larger.
Therefore, when traveling from the departure point O to the destination D is the second time, the candidate intersection selection area A in the vicinity of the departure point O can be widened. That is, the restriction on the direction of travel from the departure point O can be relatively relaxed.
As a result, the first candidate intersection α and the second candidate intersection β can be selected from a larger number of known intersections. For example, a route selection that can shorten the travel distance or shorten the time compared to the first travel is possible. Can be made possible.

When the first candidate intersection α and the second candidate intersection β are selected, the process proceeds from step S10 to step S11, and the guidance road Y, which is a recognition road connecting the second candidate intersection α and the second candidate intersection β, is extracted. The 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 path K1 and the second connection path K2 are set, the guide path X consisting of the intermediate path M and the first and second connection paths K1 and K2 Is presented on the display 40.

Here, at the time of the second run of the first embodiment, the guide road Y, which is the recognition road N connecting the first candidate intersection α to the second candidate intersection β, is longer than the shortest route S.
Therefore, the bypass road B that can shorten the intermediate route M is extracted compared to the case where the entire length of the intermediate route M is configured by the guide road Y. Then, by combining the bypass road B and a part of the guide road Y, the intermediate route M includes a part of the guide road Y and the bypass road B that shortens the intermediate route M, so that the intermediate route M can be set so as to be a route including the guide road Y but having a small distance difference from the shortest route S.

[Route setting action during the third and subsequent runs]
If the user has traveled from the starting point O to the destination D twice or more (in the case of traveling after the third time), the process proceeds from step S1 to step S2 to step S3 and then to step S15. The probe collective intelligence 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 starting point O to the destination D is selected and set based on the road determined to be optimal based on the read probe collective intelligence. The guided route X is displayed on the display 40.
Thereby, as shown in FIG. 14, the guidance route X from the departure point O to the destination D is displayed in association with the map data.

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

Next, the effect will be described.
In the route search method and the navigation device of the first embodiment, the effects listed below can be obtained.

(1) It has a memory 20 that stores map data and travel history data of the host vehicle on the map data, and a calculation unit 10 that sets a guide route X based on the map data and the travel history data. A route setting method in the navigation device 1,
Accepting the setting of the starting point O and the destination D of the vehicle,
Of the intersections on the recognition road N with driving experience extracted based on the travel history data, set the intersection that is closest to the departure point O as the first candidate intersection α,
Of the intersections on the recognition road N, the intersection that is closest to the destination D is set as the second candidate intersection β,
A road passing through the first candidate intersection α and the second candidate intersection β is set as a guide route X.
Thereby, when setting the guidance route X from the departure point O to the destination D, it is possible to set a route that reliably includes the recognition road N.

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

(3) The second candidate intersection β is selected from the intersections on the recognition road N in the candidate intersection selection area A within a predetermined range that is centered on the departure point O and gradually expands toward the destination D. And
A configuration in which the setting range of the candidate intersection selection area A is made larger when there is more traveling experience from the starting point O to the destination D than when there is less traveling experience.
As a result, in addition to the effect of (1), when the number of runs 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 can be grasped sensuously. Easy to route Moreover, when there is much traveling experience, the selection range of the second candidate intersection β can be expanded, and a more appropriate route can be set.

(4) When setting the guide 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 reduces the distance or travel time. It was.
As a result, in addition to any one of the effects (1) to (3), the guidance route X can be a route with a small distance difference from the shortest route S while including the guidance road Y with experience of traveling.

(5) The non-cognitive road that is not included in the guidance route X and has no driving experience is selected based on collective intelligence information obtained from the probe data.
As a result, in addition to any one of the effects (1) to (4), when selecting a non-recognizable road, it is possible to set a route that is determined to be optimal in consideration of the trends of other vehicles.

(6) A configuration in which all routes of the guide route X from the departure point O to the destination D are set based on the collective intelligence information when there are a plurality of traveling experiences from the departure point O to the destination D. It was.
Thus, in addition to any of the effects (1) to (5), when there are a plurality of driving experiences from the departure point O to the destination D, all routes of the guidance route X regardless of the recognition road N of the own vehicle Thus, it is possible to set a route that is determined to be optimal in consideration of the trends of other vehicles.

(7) It has a memory 20 that stores map data and travel history data of the host vehicle on the map data, and a calculation unit 10 that sets a guide route X based on the map data and the travel history data. A navigation device 1 comprising:
The arithmetic unit 10
Accepting the setting of the starting point O and the destination D of the vehicle,
Of the intersections on the recognition road N with driving experience extracted based on the travel history data, set the intersection that is closest to the departure point O as the first candidate intersection α,
Of the intersections on the recognition road N, the intersection that is closest to the destination D is set as the second candidate intersection β,
The route setting unit 11 sets a road passing through the first candidate intersection α and the second candidate intersection β as a guide route X.
Thereby, when setting the guidance route X from the departure point O to the destination D, it is possible to set a route that reliably includes the recognition 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 it relates to each claim of the claims. Design changes and additions are allowed without departing from the spirit of the invention.

  In the first embodiment, when there is no travel experience from the departure point O to the destination D (during the first travel), the candidate intersection selection area A is set to the “first range” and the distance from the departure point O to the destination D is set. An example is shown in which the candidate intersection selection area A is set to the “second range” when there is one driving experience (during the second driving). However, the present invention is not limited to this, and the setting range of the angle area of the candidate intersection selection area A may be made larger when traveling experience from the departure point O to the destination D is greater than when traveling experience is small. That is, for example, the candidate intersection selection area A may be a “first range” until the third run, and may be a “second range” after the fourth run.

Further, in the first embodiment, a sector-shaped region having a starting point O as a center, a straight line distance from the starting point O to the destination D as a radius, and a central angle θ as a right angle (90 °) (see FIG. 5). ) Is a “first range”, and a circular area (see FIG. 6) having a diameter of a straight line connecting the starting point O and the destination D is shown as a “second range”.
However, the present invention is not limited to this. For example, an isosceles triangular or trapezoidal area having a height that is a straight line connecting the starting point O and the destination D may be set as the “first range”, or the starting point O and the destination A square-shaped area centering on a straight line connecting the ground D or an elliptical area having a long diameter on a straight line connecting the starting point O and the destination D may be set as the “second range”.
Further, the departure point O and the destination D may not be included in the candidate intersection selection area A.

Furthermore, in this Example 1, when selecting the 1st candidate intersection alpha, the candidate intersection selection area | region A is set first, but it is not restricted to this. Although selecting the first candidate intersection α from the intersections on the recognition road N in the candidate intersection selection area A can reduce the selection time of the first candidate intersection α, the first candidate without setting the candidate intersection selection area A An intersection α may be selected.
Also, the selection range is not necessarily limited for the second candidate intersection β.

  Further, in the first embodiment, when the travel experience from the departure point O to the destination D is less than one time, a guidance route that reliably includes the recognition road is set, and the travel experience from the departure point O to the destination D is established. When there is two times (during the third and subsequent runs), an example is shown in which a guide route is set from the probe collective intelligence information. However, the present invention is not limited to this. For example, even if you have traveled from the starting point O to the destination D more than twice, if a predetermined time has passed since the last time you traveled, set a guide route that reliably includes the recognition road. Also good.

  In the first embodiment, the first connection route K1 is set because the departure point O and the first candidate intersection α are separated from each other, and the second connection point K2 is established because the destination D and the second candidate intersection β are separated from each other. An example of setting the connection path K2 has been shown. However, when the departure point O and the first candidate intersection α match (not only completely match but also substantially match), it is not necessary to set the first connection route K1. Further, when the destination D and the second candidate intersection β match (not only completely match but also substantially match), it is not necessary to set the second connection route K2.

DESCRIPTION OF SYMBOLS 1 Navigation apparatus 10 Calculation part 11 Path | route setting part 20 Memory 30 Touch panel 40 Display 50 Communication part 100 Probe data server

Claims (7)

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 a calculation unit that sets a guide route based on the map data and the travel history data. Because
Accepting the setting of the departure and destination of the vehicle,
Of the intersections on the cognitive road with traveling experience extracted based on the travel history data of the host vehicle, set the intersection that is present at the closest position from the departure place as the first candidate intersection,
Of the intersections on the cognitive road, set the intersection that is closest to the destination as the second candidate intersection,
A route setting method, wherein a road passing through the first candidate intersection and the second candidate intersection is set as a guidance route. In the route setting method according to claim 1,
The route setting method, wherein the first candidate intersection is selected from intersections on a recognition road in a candidate intersection selection area set in a direction from the departure point to the destination. In the route setting method according to claim 1,
The second candidate intersection is selected from the intersections on the cognitive road within a predetermined range of candidate intersection selection areas of a predetermined range that is centered on the departure location and gradually expands toward the destination,
A route setting method characterized in that the setting range of the candidate intersection selection area is increased when there is more traveling experience from the departure place to the destination than when there is less traveling experience. In the route setting method according to any one of claims 1 to 3,
When setting up the guidance route, the intermediate route from the first candidate intersection to the second candidate intersection includes a non-cognitive road with no driving experience of the host vehicle that reduces the distance or travel time. Setting method. In the route setting method according to any one of claims 1 to 4,
The route setting method characterized in that selection of a non-cognitive road with no traveling experience of the host vehicle included in the guidance route is performed based on collective intelligence information obtained from probe data. In the route setting method according to claim 5,
A route setting method, wherein when there are a plurality of traveling experiences from the departure place to the destination, all routes of the guidance route from the departure place to the destination are set based on the collective intelligence information. A navigation device having map data and a memory that stores travel history data of the host vehicle on the map data, and a calculation unit that sets a guide route based on the map data and the travel history data,
The computing unit is
Accepting the setting of the departure and destination of the vehicle,
Of the intersections on the cognitive road with driving experience extracted based on the travel history data, set the intersection that is closest to the starting point as the first candidate intersection,
Of the intersections on the cognitive road, set the intersection that is closest to the destination as the second candidate intersection,
A navigation device, comprising: a route setting unit that sets a road passing through the first candidate intersection and the second candidate intersection as a guidance route.