JP2014153192A - Travel guide system, travel guide method, and computer program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a travel guide system, a travel guide method, and a computer program which reduce the processing load as well as the processing time of image processing when detecting a marker object from a captured image.SOLUTION: When a guide intersection exists in the front of a vehicle in the traveling direction, a periphery of the guide intersection included in a guide route is imaged by a front camera 19 mounted in the vehicle to acquire information which specifies a state around the guide intersection. A detection exclusion area is set to the captured image captured by the front camera 19 on the basis of the acquired information, and an area except the detection exclusion area in the captured image captured by the front camera 19 is preferentially subjected to image processing to detect a marker object which is taken as a marker for guiding the vehicle about the guide intersection in the captured image. When the marker object is detected, the marker object is used to guide the vehicle about the guide intersection.

Description

  The present invention relates to a travel guidance system, a travel guidance method, and a computer program that guide a vehicle using a mark.

  2. Description of the Related Art In recent years, a navigation device is often mounted on a vehicle that provides vehicle travel guidance so that a driver can easily arrive at a desired destination. Here, the navigation device detects the current position of the vehicle by a GPS receiver or the like, acquires map data corresponding to the current position through a recording medium such as a DVD-ROM or HDD or a network, and displays it on a liquid crystal monitor. It is a device that can do. Further, such a navigation device has a route search function for searching for an optimum route from the departure place to the destination when a desired destination is input. Then, the guidance route set based on the search result is displayed on the display screen, and when approaching an intersection (hereinafter referred to as a guidance intersection) for guidance such as a right or left turn, a voice or a display screen is used. By performing the guidance, the user is surely guided to a desired destination. In recent years, some mobile phones, smartphones, PDAs (Personal Digital Assistants), personal computers, and the like have functions similar to those of the navigation device. Furthermore, it is also possible to perform the above guidance for pedestrians and two-wheeled vehicles as well as vehicles.

  Here, when performing guidance such as turning left or right at the guidance intersection, it is important to allow the user to accurately identify the guidance intersection. Therefore, conventionally, guidance has been performed using landmark objects (for example, store signboards) that serve as landmarks of guidance intersections. Further, when performing guidance using a landmark object, it is important that the landmark object is visible to the user when performing guidance. Therefore, for example, in Japanese Patent No. 3399506, when a vehicle approaches a guidance intersection, the direction of the guidance intersection is captured by a camera mounted on the vehicle, and image processing is performed on the captured image so that the user can visually recognize the intersection. A technique for detecting a landmark object and guiding a guidance intersection using the detected landmark object is described.

Japanese Patent No. 3399506 (page 6-7, FIG. 11)

  However, in the technique described in Patent Document 1, since the landmark object is detected by uniformly performing image processing on the entire range of the captured image captured by the camera, the landmark is clearly determined from the surrounding situation of the guidance intersection. Image processing is performed on a range in which an object cannot be detected in the same manner as other ranges. As a result, the processing load of the image processing increases, the processing time also becomes longer, the guidance timing is delayed, or the guide object that does not use the mark object despite the presence of the mark object visible to the user exists. Was happening.

  The present invention has been made to solve the above-described conventional problems, and when detecting a landmark object from a captured image, image processing is preferentially performed on the captured image in consideration of the surrounding situation of the guidance intersection. It is an object of the present invention to provide a travel guidance system, a travel guidance method, and a computer program that reduce the processing load of image processing and reduce the processing time by setting an area for performing the above.

In order to achieve the above object, the travel guidance system (1) according to claim 1 of the present application includes a guide route setting means (13) for setting a guide route and an imaging device (19) mounted on a vehicle. Obtained by an imaging means (13) that images the surroundings of the included guidance intersection (61), peripheral information acquisition means (13) that acquires information specifying the surrounding situation of the guidance intersection, and the peripheral information acquisition means Based on the information, an area setting unit (13) for setting a detection exclusion area (66 to 68) for the captured image captured by the imaging unit, and the detection among the captured images captured by the imaging unit Eyes that detect landmark objects (63 to 65) that serve as landmarks when performing guidance of the guidance intersection from the captured image by performing image processing with priority on areas other than the exclusion areas. Object detection means (13), and intersection guidance means (13) for guiding the guidance intersection using the mark object when the mark object detection means detects the mark object. It is characterized by having.
Note that the “guidance intersection” corresponds to an intersection that is a target for performing guidance such as a right / left turn instruction when performing guidance of movement of the moving object according to the guidance route.
Further, the “marking object” is a structure installed on the ground surface that can serve as a user's mark, and corresponds to, for example, a store signboard.

  Further, the travel guidance system (1) according to claim 2 is the travel guidance system according to claim 1, wherein the peripheral situation acquired by the peripheral information acquisition means (13) is the guidance intersection (61). The area setting means (13) sets the detection exclusion areas (66 to 68) based on the vehicle congestion situation and the road shape of the road on which the vehicle travels. It is characterized by that.

  Further, the travel guidance system (1) according to claim 3 is the travel guidance system according to claim 2, wherein the area setting means (13) is a road of the road on which the vehicle is congested and the vehicle travels. Based on the shape, an area in which the field of view is predicted to be blocked by another vehicle in the captured image captured by the imaging unit is set as the detection exclusion area (66 to 68).

  Further, the travel guidance system (1) according to claim 4 is the travel guidance system according to claim 1, wherein the peripheral situation acquired by the peripheral information acquisition means (13) is the guidance intersection (61). ) Around the pedestrian, and the area setting means (13) sets the detection exclusion area (66 to 68) based on the pedestrian congestion and the road shape of the road on which the vehicle travels. It is characterized by setting.

  Further, the travel guidance system (1) according to claim 5 is the travel guidance system according to claim 4, wherein the area setting means (13) includes the pedestrian congestion situation and a road on which the vehicle travels. Based on the road shape, an area in which the field of view is predicted to be blocked by a pedestrian in the captured image captured by the imaging means (19) is set as the detection exclusion area (66 to 68). And

  A travel guidance system (1) according to claim 6 is the travel guidance system according to any one of claims 1 to 5, wherein the travel guidance system (1) includes an object located around the guidance intersection (61). A landmark candidate information acquisition means (13) for acquiring height information where a landmark object candidate that is a candidate for the landmark object to be detected by the landmark object detection means (13) is installed; and the peripheral information Reference value setting means (13) for setting a height reference value based on the information acquired by the acquisition means, and the mark object detection means includes the reference object among the mark object candidates. The mark object candidate having a height equal to or higher than the value is preferentially detected, and the mark object object is selected from the detected mark object candidates.

  The travel guidance system (1) according to claim 7 is the travel guidance system according to claim 6, wherein the peripheral situation acquired by the peripheral information acquisition means (13) is the guidance intersection (61). ), The reference value setting means (13) blocks the landmark object candidate by the other vehicles (52, 54) when the vehicle congestion state is equal to or greater than a predetermined threshold. The lowest height predicted not to be set is set as the reference value.

  Further, the travel guidance system (1) according to claim 8 is the travel guidance system according to claim 6, wherein the peripheral situation acquired by the peripheral information acquisition means (13) is the vicinity of the guidance intersection. The reference value setting means (13) does not block the landmark object candidate by the pedestrians (56, 58) when the pedestrian congestion state is a predetermined threshold value or more. The lowest predicted height is set as the reference value.

  A travel guidance system (1) according to claim 9 is the travel guidance system according to any one of claims 1 to 8, wherein the landmark object detection means (13) causes the landmark object to be detected. When not detected, it has an intersection distance guidance means (13) for guiding the guidance intersection using the distance to the guidance intersection (61).

  According to a tenth aspect of the present invention, there is provided a travel guidance method for imaging a periphery of a guidance intersection (61) included in the guidance route by a guidance route setting step for setting a guidance route and an imaging device (19) mounted on the vehicle. Detecting a captured image captured by the imaging unit based on an imaging step, a peripheral information acquisition step for acquiring information specifying the surrounding situation of the guidance intersection, and information acquired by the peripheral information acquisition step An area setting step for setting an exclusion area (66 to 68), and performing image processing with priority given to an area excluding the detection exclusion area among the captured images captured by the imaging unit, thereby allowing the captured image to A mark object detection step for detecting a mark object (63 to 65) as a mark when guiding a guidance intersection, and the mark object detection When the mark object is detected by step, characterized by having a, and intersection guidance step of guiding the guidance intersection using the landmarks object.

  Furthermore, a computer program according to an eleventh aspect provides a computer with a guide route setting function for setting a guide route, and a periphery of a guide intersection (61) included in the guide route by an imaging device (19) mounted on the vehicle. Based on the information acquired by the imaging function for imaging, the peripheral information acquisition function for acquiring information for specifying the surrounding situation of the guidance intersection, and the information acquired by the peripheral information acquisition function, the captured image captured by the imaging unit An area setting function for setting detection exclusion areas (66 to 68), and performing image processing with priority given to areas other than the detection exclusion area among the captured images captured by the imaging unit, thereby obtaining the captured image. A mark object detection function for detecting a mark object (63 to 65) as a mark when performing guidance at the guidance intersection, and the mark object detection function. When the mark object is detected by the function, characterized in that to execute, and intersection guidance function for guiding the guidance intersection using the landmarks object.

  According to the travel guidance system according to claim 1 having the above-described configuration, when detecting a landmark object from a captured image, image processing is preferentially performed on the captured image in consideration of the surrounding situation of the guidance intersection. By setting the area, it is possible to reduce the processing load of image processing and shorten the processing time. As a result, it is possible to prevent the timing of guidance from being delayed or the situation where guidance without using the landmark object is performed despite the presence of the landmark object visible to the user.

  According to the travel guidance system of the second aspect, the detection exclusion area is set based on the vehicle congestion situation around the guidance intersection and the road shape of the road on which the vehicle travels. In the captured image, it is possible to appropriately identify an area where the field of view is predicted to be blocked by a vehicle ahead or another vehicle traveling in the oncoming lane, and set it as a detection exclusion area.

  According to the travel guidance system of the third aspect, the other vehicle in the picked-up image picked up by the image pickup means based on the vehicle congestion situation around the guidance intersection and the road shape of the road on which the vehicle travels. Since the area where the field of view is predicted to be blocked is set as the detection exclusion area, it is possible to prevent unnecessary image processing from being performed on areas where the mark target object is unlikely to be detected, and to reduce the processing load of image processing In addition, the processing time can be shortened.

  According to the travel guidance system of the fourth aspect, the detection exclusion area is set based on the pedestrian congestion around the guidance intersection and the road shape of the road on which the vehicle travels. In the captured image, it is possible to appropriately identify an area where the field of view is predicted to be blocked by a pedestrian walking along the side of the roadway and set it as a detection exclusion area.

  According to the travel guidance system according to claim 5, the pedestrian in the captured image captured by the imaging means based on the pedestrian congestion around the guidance intersection and the road shape of the road on which the vehicle travels. Since the area where the field of view is predicted to be blocked is set as the detection exclusion area, unnecessary image processing is prevented from being performed on the area where the mark target object is unlikely to be detected, and the processing load of the image processing is reduced. In addition to the reduction, the processing time can also be shortened.

  In addition, according to the travel guidance system of claim 6, the height information where the landmark object candidate, which is a candidate for the landmark object, is installed among the objects located around the guidance intersection is acquired. Among the candidate objects, a candidate mark object having a height equal to or higher than the reference value is preferentially detected, and the mark object is selected from the detected mark object candidates, so that it is detected from the captured image. By selecting detection targets in order from the most probable landmark object candidates, it is possible to prevent unnecessary image processing from being performed, reduce the processing load of image processing, and shorten the processing time. .

  Further, according to the travel guidance system of claim 7, when the vehicle congestion around the guidance intersection is equal to or greater than the threshold, the vehicle has a height equal to or higher than the lowest height that is predicted not to be shielded by other vehicles. Since the landmark object candidates are preferentially detected as targets, it is possible to prevent unnecessary image processing from being performed by sequentially selecting the landmark object candidates that are likely to be detected from the captured image. It is possible to reduce the processing load of the process and also reduce the processing time.

  According to the travel guidance system of claim 8, when the pedestrian congestion around the guidance intersection is greater than or equal to the threshold value, the height equal to or higher than the lowest height predicted not to be shielded by the pedestrian. Since the mark object candidate that has a priority is set as the detection target, unnecessary image processing is prevented from being performed by sequentially setting the detection target candidates from the mark object candidates that are likely to be detected from the captured image. It is possible to reduce the processing load of image processing and shorten the processing time.

  According to the travel guidance system of claim 9, when the landmark object is not detected, the guidance intersection is guided using the distance to the guidance intersection, so the landmark object cannot be detected. Even in such a case, it is possible to appropriately guide the vehicle traveling on the guidance intersection without using the landmark object.

  Further, according to the travel guidance method of the tenth aspect, when the landmark object is detected from the captured image, the area where the image processing is preferentially performed on the captured image in consideration of the surrounding situation of the guidance intersection. By setting, it is possible to reduce the processing load of image processing and shorten the processing time. As a result, it is possible to prevent the timing of guidance from being delayed or the situation where guidance without using the landmark object is performed despite the presence of the landmark object visible to the user.

  Furthermore, according to the computer program according to claim 11, when the landmark object is detected from the captured image, an area for preferentially performing image processing on the captured image is set in consideration of the surrounding situation of the guidance intersection. As a result, the processing load of the image processing can be reduced and the processing time can be shortened. As a result, it is possible to prevent the timing of guidance from being delayed or the situation where guidance without using the landmark object is performed despite the presence of the landmark object visible to the user.

It is the block diagram which showed the navigation apparatus which concerns on this embodiment. It is the figure which showed an example of the landmark information memorize | stored in map information DB. It is a flowchart of the intersection guidance processing program concerning this embodiment. It is a figure explaining the setting method of the detection priority in case a vehicle is in the congestion state around a guidance intersection. It is a figure explaining the setting method of the detection priority in case a pedestrian is in the congestion state around a guidance intersection. It is the figure which showed the picked-up image which imaged the periphery of the guidance intersection with the front camera. It is a figure explaining the setting method of the detection exclusion area when a pedestrian is in the congestion state around the guidance intersection. It is a figure explaining the setting method of the detection exclusion area when the vehicle is in a congested state around the guidance intersection. It is a figure explaining the setting method of the detection exclusion area when a vehicle and a pedestrian are in the congestion state around the guidance intersection. It is a flowchart of the sub process program of the shielding determination process by the other vehicle which concerns on this embodiment. It is a flowchart of the sub process program of the shielding determination process by the person concerning this embodiment.

  DETAILED DESCRIPTION Hereinafter, a travel guidance system according to the present invention will be described in detail with reference to the drawings based on an embodiment in which the navigation apparatus is embodied. First, a schematic configuration of the navigation device 1 according to the present embodiment will be described with reference to FIG. FIG. 1 is a block diagram showing a navigation device 1 according to this embodiment.

  As shown in FIG. 1, the navigation device 1 according to the present embodiment includes a current position detection unit 11 that detects a current position of a vehicle on which the navigation device 1 is mounted, a data recording unit 12 that records various data, A navigation ECU 13 that performs various arithmetic processes based on the input information, an operation unit 14 that receives operations from the user, and a liquid crystal display 15 that displays a map around the vehicle and facility information related to the facility to the user. Communicating between a speaker 16 that outputs voice guidance regarding route guidance, a DVD drive 17 that reads a DVD as a storage medium, and an information center such as a probe center or a VICS (registered trademark: Vehicle Information and Communication System) center And a communication module 18 for performing. In addition, a front camera 19 is connected to the navigation device 1.

Below, each component which comprises the navigation apparatus 1 is demonstrated in order.
The current position detection unit 11 includes a GPS 21, a vehicle speed sensor 22, a steering sensor 23, a gyro sensor 24, and the like, and can detect the current vehicle position, direction, vehicle traveling speed, current time, and the like. . Here, in particular, the vehicle speed sensor 22 is a sensor for detecting a moving distance and a vehicle speed of the vehicle, generates a pulse according to the rotation of the driving wheel of the vehicle, and outputs a pulse signal to the navigation ECU 13. And navigation ECU13 calculates the rotational speed and moving distance of a driving wheel by counting the generated pulse. Note that the navigation device 1 does not have to include all the four types of sensors, and the navigation device 1 may include only one or more types of sensors.

  The data recording unit 12 is also a hard disk (not shown) as an external storage device and a recording medium, and a driver for reading the map information DB 31 and a predetermined program recorded on the hard disk and writing predetermined data on the hard disk And a recording head (not shown). The data recording unit 12 may be configured by a memory card, an optical disk such as a CD or a DVD, instead of the hard disk. Further, the map information DB 31 may be stored in an external server, and the navigation device 1 may be configured to acquire by communication.

  Here, the map information DB 31 includes, for example, link data 32 relating to roads (links), node data 33 relating to node points, intersection data 34 relating to each intersection, point data relating to points such as facilities, and map display data for displaying a map. The storage means stores search data for searching for routes, search data for searching for points, and the like.

  Here, as the link data 32, for example, a link ID for identifying the link, end node information for specifying a node located at the end of the link, the road type of the road constituting the link, the number of lanes, the road The width, travel classification for each lane, and the like are stored. It is also stored whether the link is a section with particularly many pedestrians. The node data 33 stores a node ID for identifying the node, position coordinates of the node, connection destination node information for specifying a connection destination node to which the node is connected through a link, and the like. Further, as the intersection data 34, relevant node information for identifying the node forming the intersection, connection link information for identifying a link connected to the intersection (hereinafter referred to as a connection link), and a mark object located around the intersection The landmark information 35 etc. regarding the object candidate is stored.

  The landmark object candidate is a candidate for an object (such as a store signboard) that can be a landmark when guiding a guidance intersection. Here, as a landmark object candidate, for example, a specific facility (for example, a convenience store, a gas station, a fast food) that is located within a predetermined range (for example, within a radius of 100 m) from an intersection and that can provide a sign that can be identified from a distance. Corresponding to the store sign. The landmark information 35 stores the type (name) of the landmark object candidate, the position coordinates, and the installation height of the landmark object candidate for each intersection in the whole country. In addition, when there are a plurality of landmark object candidates for one intersection, the type (name), position coordinates, and installation height of the landmark object candidate are stored for each of the plurality of landmark object candidates. Yes. Note that “the installation height of the landmark object candidate” is a height H from the ground surface to the lower end of the landmark object candidate as shown in FIG. The position coordinates may be the position coordinates of the facility when the landmark object candidate is a signboard of the facility.

Here, FIG. 2 is a diagram showing an example of the mark information 35 stored in the map information DB 31. As shown in FIG. 2, the landmark information 35 includes an intersection ID for identifying an intersection, a type (name) of a landmark object candidate located around the intersection ID, a position coordinate, and an installation height of the landmark object candidate. It is stored in association.
For example, at the intersection with the intersection ID “10001”, there are four objects as landmark object candidates, and each landmark object candidate is a “convenience store ○ installed at a height of 8 m from the ground surface at (X1, Y1). “Signboard of ○”, “Signboard of petrol station XX” installed at a height of 10m from the ground surface at (X2, Y2), and “Fast Food ○” installed at a height of 6m from the ground surface at (X3, Y3) “X signboard” and “X ○ bookstore signboard” installed at a height of 2 m from the ground surface at (X4, Y4). Similarly, information related to landmark object candidates at other intersections is also stored.

  The landmark information 35 stores, for each type of landmark object candidate, a voice phrase for allowing the user to identify the landmark object candidate among voice phrases used for voice guidance at the guidance intersection. For example, “Convenience Store XX” is stored as a speech phrase for allowing the user to identify the landmark target candidate of “Convenience Store XX Signboard”, and the landmark target candidate of “Gas Station XX Signboard” is selected by the user. “Gasoline station xx” is stored as a voice phrase to be specified. Similarly, other landmark object candidates are also stored. The mark information 35 may be stored in an external server and acquired by the navigation device 1 through communication.

  On the other hand, the navigation ECU (Electronic Control Unit) 13 is an electronic control unit that controls the entire navigation device 1. The CPU 41 as an arithmetic device and a control device, and a working memory when the CPU 41 performs various arithmetic processes. Read out from the ROM 43 and the ROM 43 in which the RAM 42 that stores the route data when the route is searched, the control program, the intersection guidance processing program (FIG. 3) described later, and the like are recorded. An internal storage device such as a flash memory 44 for storing the program is provided. The navigation ECU 13 constitutes various means as processing algorithms. For example, the guide route setting means sets a guide route. The imaging means images the vicinity of the guidance intersection included in the guidance route by the front camera 19 mounted on the vehicle. The surrounding information acquisition means acquires information for specifying the surrounding situation of the guidance intersection. The area setting unit sets a detection exclusion area for the captured image captured by the front camera 19 based on the information acquired by the peripheral information acquisition unit. The mark object detection means is a mark when guiding a guidance intersection from a captured image by performing image processing with priority given to areas other than the detection exclusion area among the captured images captured by the front camera 19. A mark object is detected. The intersection guidance means guides the guidance intersection using the mark object when the mark object detection means detects the mark object. The landmark candidate information acquisition means acquires height information where a landmark object candidate that is a candidate for the landmark object is installed among the objects located around the guidance intersection. The reference value setting means sets the height reference value based on the information acquired by the peripheral information acquisition means. The intersection distance guidance means guides the guidance intersection using the distance to the guidance intersection when no landmark object is detected by the landmark object detection means.

  The operation unit 14 is operated when inputting a departure point as a travel start point and a destination as a travel end point, and includes a plurality of operation switches (not shown) such as various keys and buttons. Then, the navigation ECU 13 performs control to execute various corresponding operations based on switch signals output by pressing the switches. The operation unit 14 can also be configured by a touch panel provided on the front surface of the liquid crystal display 15. Moreover, it can also be comprised with a microphone and a speech recognition apparatus.

  The liquid crystal display 15 also includes a map image including a road, traffic information, operation guidance, operation menu, key guidance, a planned travel route from the departure point to the destination, guidance information along the planned travel route, news, weather Forecast, time, mail, TV program, etc. are displayed. In particular, in this embodiment, when the guidance intersection approaches within a predetermined distance (for example, 300 m) ahead of the traveling direction of the vehicle, an enlarged view near the guidance intersection and the traveling direction at the guidance intersection of the vehicle are displayed.

  Further, the speaker 16 outputs voice guidance for guiding traveling along the planned traveling route and traffic information guidance based on an instruction from the navigation ECU 13. In particular, in this embodiment, at the timing when the guidance intersection reaches a predetermined distance ahead of the vehicle in the traveling direction (for example, three times of 700 m, 300 m, and 100 m), output of voice guidance for guiding traveling along the guidance route is started. To do. Further, in the navigation device 1 according to the present embodiment, when there is an appropriate target object (for example, a store signboard) at the guidance intersection in front of the traveling direction of the host vehicle, the target mark object is used. Output voice guidance. For example, “Soon after XX (store name) is going to the right” is output.

  The DVD drive 17 is a drive that can read data recorded on a recording medium such as a DVD or a CD. Based on the read data, music and video are reproduced, the map information DB 31 is updated, and the like.

  The communication module 18 is a communication device for receiving traffic information composed of information such as traffic jam information, regulation information, and traffic accident information transmitted from a traffic information center, for example, a VICS center or a probe center. For example, a mobile phone or DCM is applicable. In the present embodiment, the navigation ECU 13 communicates with an external server via the communication module 18 so that, in addition to the traffic information, a baseball game, a fireworks display, a festival, a concert, and the like performed around the current position. Also get event information about various events held in.

The front camera 19 is constituted by a camera using a solid-state image sensor such as a CCD, for example, and is installed above the front bumper of the vehicle and installed with the optical axis direction downward from the horizontal by a predetermined angle. And the front camera 19 images the surrounding environment around a guidance intersection, when a vehicle approaches a guidance intersection. Moreover, navigation ECU13 detects the kind and position of the marker object candidate located in the periphery of a guidance intersection by performing image processing with respect to the captured image. In addition, when performing image processing on the captured image, the navigation ECU 13 sets a range in which image processing is preferentially performed on the captured image based on traffic information, event information, and the like acquired via the communication module 18. . Details of the image processing will be described later.
Then, the navigation ECU 13 selects a mark object for guiding the guidance intersection based on the detected mark object candidate.

  Next, an intersection guidance processing program executed by the navigation ECU 13 in the navigation device 1 having the above configuration will be described with reference to FIG. FIG. 3 is a flowchart of the intersection guidance processing program according to the present embodiment. Here, the intersection guidance processing program is a program that is executed at predetermined intervals after the ACC of the vehicle is turned on, and guides the guidance intersection in front of the traveling direction of the vehicle. The programs shown in the flowcharts of FIGS. 3, 10, and 11 below are stored in the RAM 42 and the ROM 43 provided in the navigation device 1, and are executed by the CPU 41.

  First, in the intersection guidance processing program, in step (hereinafter abbreviated as S) 1, the CPU 41 determines whether route guidance based on the guidance route set in the navigation device 1 is being performed. Here, the guidance route is a recommended route from the departure point (for example, the current position of the host vehicle) to the destination selected by the user, and is set based on the result of the route search process. The route search process is performed by a known Dijkstra method or the like using link data 32, node data 33, traffic information acquired from the VICS center, or the like stored in the map information DB 31.

  And when it determines with the route guidance based on the guidance route set in the navigation apparatus 1 being performed (S1: YES), it transfers to S2. On the other hand, when it is determined that route guidance based on the guidance route set in the navigation device 1 is not performed (S1: NO), the intersection guidance processing program is terminated.

  In S <b> 2, the CPU 41 acquires the current position and direction of the vehicle based on the detection result of the current position detection unit 11. A map matching process for specifying the current position of the vehicle on the map data is also performed. Furthermore, it is desirable to specify the current position of the vehicle in detail using high-precision location technology. In addition, when the vehicle travels on a road composed of a plurality of lanes, it is desirable to specify the lane in which the vehicle travels. Here, the high-accuracy location technology detects the white line and road surface paint information captured from the camera behind the vehicle by image recognition, and further compares the white line and road surface paint information with a previously stored map information DB, thereby driving the vehicle. This is a technology that makes it possible to detect lanes and highly accurate vehicle positions. The details of the high-accuracy location technology are already known and will be omitted.

  Next, in S <b> 3, the CPU 41 acquires a guide route set in the navigation device 1.

  Subsequently, in S4, the CPU 41 determines whether or not the vehicle is positioned a predetermined distance before the guidance utterance point at the guidance intersection based on the current position and direction of the vehicle obtained in S1 and the guidance route obtained in S2. judge. Note that the guidance intersection is an intersection to which guidance such as a right / left turn instruction is given when the navigation device 1 provides guidance for traveling according to the guidance route set in the navigation device 1 as described above. The guidance utterance point at the guidance intersection is a point at which the guidance voice is uttered at the guidance intersection. For example, the guidance utterance point is 700 m before, 300 m before, and 100 m before the guidance intersection. Further, the predetermined distance of S4 is the vehicle during the time required for detection and selection of the mark object used for guidance at the guidance intersection (specifically, the time required for performing the processing of S5 to S14 described later). The distance is longer than the distance traveled. Although it depends on the current vehicle speed of the vehicle, it is set to 50 m, for example.

  If it is determined that the vehicle is positioned a predetermined distance before the guidance utterance point at the guidance intersection (S4: YES), the process proceeds to S5. On the other hand, when it is determined that the vehicle is not located a predetermined distance before the guidance utterance point of the guidance intersection (S4: NO), the intersection guidance processing program is terminated.

  In S <b> 5, the CPU 41 executes a shielding determination process (FIG. 10) by another vehicle described later. In the shielding determination process by other vehicles, the degree of possibility that the field of view of the front camera 19 is obstructed by other vehicles located around the vehicle based on traffic information or the like as will be described later (hereinafter referred to as vehicle shielding degree S). It is a process which determines.

  Next, in S6, the CPU 41 executes a shielding determination process (FIG. 11) by a person described later. In addition, the shielding determination process by a person is a degree of possibility that the field of view of the front camera 19 is blocked by a person (pedestrian) located in the vicinity of the vehicle based on event information or the like as will be described later (hereinafter, a person shielding degree T It is a process to determine.

  Subsequently, in S <b> 7, the CPU 41 obtains information on landmark object candidates in the vicinity of the guidance intersection in front of the traveling direction of the vehicle from the map information DB 31. Specifically, the CPU 41 first specifies an intersection ID of a guidance intersection that is ahead in the vehicle traveling direction. Then, from the landmark information 35 (FIG. 2) stored in the map information DB 31, the type (name) of the landmark object candidate associated with the identified intersection ID, the position information, and the installation height of the landmark object candidate. Is obtained by reading each of them.

  Thereafter, in S8, the CPU 41 determines whether or not the vehicle shielding degree S calculated in S5 is equal to or greater than a predetermined threshold. The threshold value of S8 is a threshold value for determining whether or not there is a high possibility that the field of view of the front camera 19 is blocked by another vehicle around the guidance intersection. The threshold value is stored in a storage unit such as the RAM 42.

  Then, when it is determined that the vehicle shielding degree S is equal to or greater than the predetermined threshold (S8: YES), that is, it is determined that there is a high possibility that the field of view of the front camera 19 is blocked by another vehicle around the guidance intersection. In this case, the process proceeds to S9. On the other hand, when it is determined that the vehicle shielding degree S is less than the predetermined threshold (S8: NO), that is, when it is determined that the possibility of the front camera 19 being blocked by another vehicle is low, The process proceeds to S10.

  In S9, the CPU 41 sets a height less than the first reference value for the mark object candidate having a height equal to or higher than the first reference value among the mark object candidates in the vicinity of the guidance intersection ahead of the traveling direction of the vehicle. The detection priority is set higher than the landmark object candidate that the mark object candidate has. In S14, which will be described later, when a landmark object candidate is detected from a captured image captured by the front camera 19, the landmark object candidate set with a high priority detection level in S9 is preferentially set as a detection target.

  Further, the first reference value is the lowest height at which the landmark object candidate is predicted not to be shielded by other vehicles traveling around the guidance intersection, for example, 4 m. That is, even if another vehicle exists between the host vehicle and the mark object, the detection priority is set high for the mark object candidate located at a height where there is no possibility of being blocked by the other vehicle. . As a specific example, a case where there is a guidance intersection of ID “10001” shown in FIG. 2 ahead of the traveling direction of the vehicle will be described. As shown in FIG. "Is set to a low detection priority because there is a risk of being blocked by another vehicle 52 located between the host vehicle and the signboard 51. On the other hand, “Convenience Store Sign 53” installed at a height of 8 m from the ground surface has a high detection priority because there is no possibility of being blocked by another vehicle 54 located between the own vehicle and the sign 53. The

  Next, in S10, the CPU 41 determines whether or not the human shielding degree T calculated in S6 is equal to or greater than a predetermined threshold value. Note that the threshold value of S10 is a threshold value for determining whether or not there is a high possibility that the field of view of the front camera 19 is blocked by a person around the guidance intersection. The threshold value is stored in a storage unit such as the RAM 42.

  Then, when it is determined that the person blocking degree T is equal to or greater than the predetermined threshold (S10: YES), that is, when it is determined that there is a high possibility that the field of view of the front camera 19 is blocked by a person around the guidance intersection. To S11. On the other hand, when it is determined that the human shielding degree T is less than the predetermined threshold (S10: NO), that is, when it is determined that the possibility that the front camera 19 is blocked by the person is low, The process proceeds to S12.

  In S <b> 11, the CPU 41 sets a height less than the second reference value for the mark object candidate having a height equal to or higher than the second reference value among the mark object candidates in the vicinity of the guidance intersection ahead of the traveling direction of the vehicle. The detection priority is set higher than the landmark object candidate that the mark object candidate has. In S14, which will be described later, when a landmark object candidate is detected from a captured image captured by the front camera 19, the landmark object candidate whose priority detection level is set high in S11 is preferentially set as a detection target.

  Further, the first reference value is the lowest height at which the landmark object candidate is predicted not to be shielded by a person walking around the guidance intersection, for example, 2 m. That is, even if there is a person between the host vehicle and the mark object, the detection priority is set high for the mark object candidate located at a height where there is no possibility of being blocked by the person. As a specific example, a case where there is a guidance intersection of ID “10002” shown in FIG. 2 ahead of the traveling direction of the vehicle will be described. As shown in FIG. ”Is set to a low detection priority because there is a risk of being blocked by the person 56 positioned between the vehicle and the signboard 55. On the other hand, the “convenience store signboard 57” installed at a height of 6 m from the ground surface has a high detection priority because there is no risk of being blocked by a person 58 located between the vehicle and the signboard 57. .

  When the vehicle shielding degree S is equal to or lower than the threshold value and the human shielding level T is also equal to or lower than the threshold value, the landmark object candidate having a height equal to or higher than the first reference value is set to the highest detection priority. A mark object candidate having a height less than the first reference value and having a height greater than or equal to the second reference value is set to the next highest detection priority, and the mark object candidate having a height less than the second reference value is most detected. Set low priority.

  Next, in S12, CPU41 acquires the road shape of the road where a vehicle drive | works from map information DB31. Specifically, there are the number of road lanes, road width, presence of oncoming lanes, turning radius, and the like.

  Thereafter, in S13, the CPU 41 determines the front camera 19 based on the vehicle shielding degree S calculated in S5, the person shielding degree T calculated in S6, and the road shape of the road on which the vehicle travels obtained in S12. A detection exclusion area is set for the captured image captured by the above. In S14, which will be described later, when the landmark object candidate is detected from the captured image captured by the front camera 19, image processing is performed by giving priority to the area excluding the detection exclusion area set in S11. A landmark object candidate is detected from the captured image. Note that the CPU 41 sets an area in the captured image captured by the front camera 19 that is predicted to be blocked by another vehicle or a person (pedestrian) as a detection exclusion area.

Hereinafter, the setting method of the detection exclusion area in S13 will be described below with a specific example.
Here, FIG. 6 is a captured image 62 obtained by imaging the periphery of the guidance intersection 61 with the front camera 19 at a predetermined timing when the guidance intersection 61 is in front of the traveling direction of the host vehicle traveling on the one-lane road. . As shown in FIG. 6, three signboards 63 to 65 having different installation positions and heights exist as landmark object candidates around the guidance intersection 61.

Then, based on the vehicle shielding degree S and the human shielding degree T, the detection exclusion area is set in any of the following modes (A) to (D).
(A) When the vehicle shielding degree S is less than the first reference value and the person shielding degree T is less than the second reference value, the area where the field of view is blocked by a pedestrian or another vehicle in the captured image 62 is Predict that there will be no detection exclusion area. As a result, any of the signboards 63 to 65 is detected in the image processing of S14 described later.
(B) When the vehicle shielding degree S is less than the first reference value and the person shielding degree T is greater than or equal to the second reference value, the field of view is viewed by a pedestrian walking on the sidewalk beside the road in the captured image 62. It is predicted that there is an area to be blocked, and as shown in FIG. 7, within a certain range from the left and right edges of the road on which the vehicle travels (a range where the field of view is predicted to be blocked by many pedestrians on the sidewalk) Detection exclusion areas 66 and 67 are set. As a result, the signboards 63 and 65 excluding the signboard 64 included in the detection exclusion area 66 are preferentially detected in the image processing of S14 described later. However, the detection exclusion areas 66 and 67 are not set when the vehicle travels on a road where a pedestrian such as an automobile-only road cannot exist. In addition, when the sidewalk exists only on one side (for example, the left side with respect to the vehicle), a detection exclusion area (for example, only the detection exclusion area 66) is set only on the side where the sidewalk exists.
(C) When the vehicle shielding degree S is equal to or higher than the first reference value and the human shielding degree T is less than the second reference value, the field of view is displayed by the forward vehicle traveling in front of the own lane in the captured image 62. It is predicted that there is an area to be blocked, and the detection exclusion area 68 is set in a range including the front in the traveling direction of the own lane (a range in which the field of view is predicted to be blocked by many forward vehicles) as shown in FIG. As a result, in the image processing of S14 described later, the signboard 65 excluding the signboards 63 and 64 included in the detection exclusion area 68 is preferentially detected.
(D) When the vehicle shielding degree S is greater than or equal to the first reference value and the person shielding degree T is also greater than or equal to the second reference value, the field of view is viewed by a pedestrian walking on the sidewalk beside the road in the captured image 62. It is predicted that there is an area to be blocked, and an area in which the field of view is blocked by a forward vehicle traveling in front of the own lane, and all detection exclusion areas 66 set in (B) and (C) as shown in FIG. , 67 and 68 are set. As a result, in the image processing of S14 described later, the signboard 65 excluding the signboards 63 and 64 included in the detection exclusion areas 66, 67, and 68 is preferentially detected. In addition, as shown in FIG. 9, when the detection exclusion area set in (B) and the detection exclusion area set in (C) overlap, detection that does not overlap more than the overlapping detection exclusion area as described later The target object candidate is detected with priority on the excluded area. Therefore, the signboard 63 is preferentially detected between the signboard 63 and the signboard 64.
The detection exclusion areas 66, 67, and 68 are set based on the road shape of the road on which the host vehicle is traveling. For example, when the road on which the vehicle is traveling is curved, the detection exclusion areas 66, 67, and 68 are set according to the curve shape.

  Thereafter, in S <b> 14, the CPU 41 detects a landmark object candidate included in the captured image by performing image processing on the captured image obtained by capturing the vicinity of the guidance intersection ahead of the traveling direction with the front camera 19. Details of the process of S14 will be described below.

  First, the CPU 41 records, as a data record, a captured image most recently captured by the front camera 19 and a template for image recognition corresponding to the landmark object candidate to be detected (the landmark object candidate for which information has been acquired in S7). Read from a storage medium such as the unit 12. Note that a template for image recognition is prepared in advance for each type of landmark object (for example, “Convenience Store XX Sign”, “Gas Station xx Sign”, etc.). Next, the CPU 41 executes image recognition processing by template matching on the captured image based on the captured image captured by the front camera 19 and the read template. And the mark target object candidate of the process target contained in a captured image is detected.

  When the detection priority order is set for the landmark object candidate in S9 and S11, first, only the image recognition template corresponding to the landmark object candidate with the highest detection order is read, and template matching is performed. Perform image recognition processing. As a result, when the landmark object candidate cannot be detected, an image recognition template corresponding to the landmark object candidate having the next highest detection order is read out. Similarly, image processing is performed as detection targets in order from the mark target candidate having the highest detection order. When a detection exclusion area is set in S13, image processing is performed on an area of the captured image excluding the detection exclusion area. When the landmark object candidate cannot be detected, the image processing is performed on the detection exclusion area as a target. In addition, when a plurality of detection exclusion areas overlap as shown in FIG. 9, first, image processing is performed on an area excluding the detection exclusion area. Then, when a landmark object candidate cannot be detected, image processing is performed on a detection exclusion area that does not overlap. If the landmark object candidate still cannot be detected, image processing is performed for the overlapping detection exclusion area. Since image recognition processing by template matching is already known, detailed description is omitted.

  Further, when only one mark object candidate is detected in S14, the CPU 41 selects the detected mark object candidate as a mark object used for guidance of the guidance intersection. On the other hand, when a plurality of landmark object candidates are detected in S14, the most suitable landmark object candidate among the detected landmark object candidates is selected as the landmark object to be used for guidance at the guidance intersection. To do. For example, a landmark object candidate that is on the near side of the guidance intersection and is on the exit direction side of the vehicle at the guidance intersection or a landmark object candidate that is closest to the intersection center is preferentially selected. It should be noted that a selection priority may be set in advance for each landmark object candidate in the landmark information 35 (FIG. 2).

  Thereafter, in S15, the CPU 41 determines whether or not the vehicle has reached the guidance utterance point at the guidance intersection based on the current position of the vehicle detected by the GPS 21 or the like. The guidance utterance points at the guidance intersection are, for example, 700 m before, 300 m before, and 100 m before the guidance intersection.

  And when it determines with the vehicle having arrived at the guidance speech point of a guidance intersection (S15: YES), it transfers to S16. On the other hand, when it is determined that the vehicle has not reached the guidance utterance point at the guidance intersection (S15: NO), the system waits until the vehicle reaches the guidance utterance point at the guidance intersection.

In S16, the CPU 41 performs guidance related to the guidance intersection using the landmark object candidate selected as the landmark object at the guidance intersection in S14. Specifically, guidance for specifying the exit direction of the guidance intersection of the vehicle (that is, guidance for identifying the exit road from which the vehicle exits the guidance intersection) is performed. For example, when the vehicle is approaching a guidance intersection where a right turn guidance is provided and “Convenience Store XX Sign” is selected as the target object of the guidance intersection, the user will be marked “Convenience Store XX Sign”. Instructs to turn right at the intersection. Specifically, voice guidance “300m ahead, convenience store ○ is right” is output from the speaker 16. Further, when the guidance intersection approaches within a predetermined distance (for example, 300 m) of the vehicle, an enlarged view of the vicinity of the guidance intersection including the mark object and the traveling direction at the guidance intersection of the vehicle are displayed on the liquid crystal display 15.
As a result, it becomes possible for the user to accurately specify the guidance intersection and the road from which the vehicle exits from the guidance intersection.

  If no landmark object candidate is detected in S14, the CPU 41 guides the guidance intersection using the distance to the guidance intersection. For example, voice guidance “300 m ahead is in the right direction” is output from the speaker 16.

  Next, the sub-process of the shielding determination process performed by the other vehicle executed in S5 will be described with reference to FIG. FIG. 10 is a flowchart of a sub-processing program for shielding determination processing by another vehicle.

  First, in S21, the CPU 41 obtains traffic jam information around a guidance intersection from a traffic information center such as a VICS center.

  Next, in S22, the CPU 41 determines whether the congestion level of the road around the guidance intersection (specifically, the road connected to the guidance intersection) is “congested” or more based on the congestion information acquired in S21. Determine whether or not. It is assumed that the degree of congestion is specified as one of “congested”, “congested”, and “empty” in descending order of the degree of congestion.

  If it is determined that the degree of congestion on the road around the guidance intersection is “congested” or higher (S22: YES), the process proceeds to S23. On the other hand, when it is determined that the degree of traffic congestion on the road around the guidance intersection is in an “empty” state (S22: NO), the process proceeds to S24.

  In S23, the CPU 41 reads the vehicle shielding degree S from the RAM 42 or the like, and adds “1” when the traffic congestion degree is “congested” and adds “2” when the traffic congestion degree is “congestion”. Then, it is stored again in the RAM 42 or the like. The vehicle shielding degree S is set to “0” in the initial state.

  Thereafter, in S24, the CPU 41 detects other vehicles included in the captured image by performing image processing on the captured image most recently captured by the front camera 19. In addition, template matching etc. are used for the detection of other vehicles.

  Next, in S25, the CPU 41 determines whether or not another vehicle is detected in the captured image as a result of the image processing in S24. In addition, it is good also as conditions on detecting more than predetermined number (for example, 3 units).

  And when it determines with the other vehicle having been detected in the captured image (S25: YES), it transfers to S26. On the other hand, when it is determined that no other vehicle is detected in the captured image (S25: NO), the process proceeds to S6.

  In S26, the CPU 41 reads the vehicle shielding degree S from the RAM 42 or the like, adds “1”, and stores it again in the RAM 42 or the like. Thereafter, the process proceeds to S6. In addition, it is good also as a structure which performs only one of the process of said S21-S23, and the process of S24-S26.

  Next, the sub-process of the occlusion determination process performed by a person in S6 will be described with reference to FIG. FIG. 11 is a flowchart of a sub-processing program for the occlusion determination process by a person.

  First, in S31, the CPU 41 communicates with an external server through the communication module 18, thereby event information relating to holding various events such as a baseball game, a fireworks display, a festival, and a concert that are held around the current position. To get.

  Next, in S32, the CPU 41 determines whether or not pedestrians around the guidance intersection are congested based on the event information acquired in S32. Specifically, the event is held within a predetermined distance (for example, within 1 km) of the guidance intersection, and the current time is within a predetermined time before and after the start time and end time of the event (for example, within 1 hour before and after). In this case, it is determined that the pedestrians around the guidance intersection are congested.

  And when it determines with the pedestrian around a guidance intersection being in a congestion state (S32: YES), it transfers to S33. On the other hand, when it is determined that the pedestrians around the guidance intersection are not congested (S32: NO), the process proceeds to S34.

  In S <b> 33, the CPU 41 reads out the human shielding degree T from the RAM 42 or the like, adds “1”, and stores it again in the RAM 42 or the like. Incidentally, the person blocking degree T is set to “0” in the initial state.

  Next, in S34, the CPU 41 acquires map information around the guidance intersection from the map information DB 31. In S34, information about whether or not the link connected to the guidance intersection is a section with particularly many pedestrians is acquired.

  Subsequently, in S35, based on the map information acquired in S34, the CPU 41 determines whether or not the link connected to the guidance intersection corresponds to a section with particularly many pedestrians.

  And when it determines with the link connected to a guidance intersection corresponding to a section with many pedestrians (S35: YES), it transfers to S36. On the other hand, when it is determined that the link connected to the guidance intersection does not correspond to a section having a large number of pedestrians (S35: NO), the process proceeds to S37.

  In S <b> 36, the CPU 41 reads out the human shielding degree T from the RAM 42 or the like, adds “1”, and stores it again in the RAM 42 or the like. Incidentally, the person blocking degree T is set to “0” in the initial state.

  Next, in S <b> 37, the CPU 41 detects a person included in the captured image by performing image processing on the captured image most recently captured by the front camera 19. In addition, template matching etc. are used for a person detection.

  Subsequently, in S38, the CPU 41 determines whether or not a person is detected in the captured image as a result of the image processing in S37. In addition, it is good also as conditions on having detected more than predetermined number of persons (for example, 5 persons).

  When it is determined that a person is detected in the captured image (S38: YES), the process proceeds to S39. On the other hand, when it is determined that no person is detected in the captured image (S38: NO), the process proceeds to S7.

  In S39, the CPU 41 reads out the human shielding degree T from the RAM 42 and the like, adds “1”, and stores it again in the RAM 42 and the like. Thereafter, the process proceeds to S7. Note that only one or two of the processes of S31 to S33, S34 to S36, and S37 to S39 may be executed.

As described above in detail, according to the navigation device 1 according to the present embodiment, the travel guidance method using the navigation device 1 and the computer program executed by the navigation device 1, there is a guidance intersection ahead of the traveling direction of the vehicle. In addition, the periphery of the guidance intersection included in the guidance route is imaged by the front camera 19 mounted on the vehicle, and information specifying the surrounding situation of the guidance intersection is acquired (S21, S24, S31, S34, S37). Based on the obtained information, a detection exclusion area is set for the captured image captured by the front camera 19 (S13), and the area excluding the detection exclusion area among the captured images captured by the front camera 19 is given priority. By performing image processing, the mark object to be used as a mark when guiding a guidance intersection from a captured image is displayed. (S14) When the landmark object is detected, the guidance intersection is guided using the landmark object (S16). Therefore, when the landmark object is detected from the captured image, the surrounding situation of the guidance intersection By setting an area where image processing is preferentially performed on the captured image in consideration of the above, it is possible to reduce the processing load of the image processing and shorten the processing time. As a result, it is possible to prevent the timing of guidance from being delayed or the situation where guidance without using the landmark object is performed despite the presence of the landmark object visible to the user.
In addition, since the detection exclusion area is set based on the congestion situation of the vehicle around the guidance intersection and the road shape of the road on which the vehicle travels, the vehicle travels in the forward vehicle or the oncoming lane in the captured image captured by the imaging unit. It is possible to appropriately specify an area where the field of view is predicted to be blocked by another vehicle and set it as a detection exclusion area. Further, it is possible to prevent unnecessary image processing from being performed on an area where the mark target object is unlikely to be detected, thereby reducing the processing load of the image processing and shortening the processing time.
In addition, since the detection exclusion area is set based on the pedestrian congestion situation around the guidance intersection and the road shape of the road on which the vehicle travels, in the captured image captured by the imaging unit, walking walking on the side of the road It is possible to appropriately specify an area where the field of view is predicted to be blocked by a person and set it as a detection exclusion area. Further, it is possible to prevent unnecessary image processing from being performed on an area where the mark target object is unlikely to be detected, thereby reducing the processing load of the image processing and shortening the processing time.
In addition, it obtains the height information where the landmark object candidates that are candidates for the landmark object among the objects located in the vicinity of the guidance intersection are obtained, and the height of the landmark object candidate is higher than the reference value. Since the target landmark object candidate is preferentially detected and the landmark target object is selected from the detected landmark object candidates, the landmark target candidates that are likely to be detected from the captured image are detected in order from the candidate landmark object candidates. By doing so, it is possible to prevent unnecessary image processing from being performed, reduce the processing load of image processing, and shorten the processing time.
Also, when the vehicle congestion around the guidance intersection is greater than or equal to the threshold value, the landmark object candidate having a height equal to or higher than the lowest height that is predicted not to be blocked by other vehicles is preferentially detected. In addition, it is possible to prevent unnecessary image processing from being performed, and to reduce the processing load of the image processing by setting the detection target in order from the mark target candidate that is highly likely to be detected from the captured image. It can be shortened.
In addition, when the pedestrian congestion situation around the guidance intersection is equal to or greater than the threshold, a landmark object candidate having a height equal to or higher than the lowest height that is predicted not to be blocked by the pedestrian is preferentially detected. Therefore, by making the detection target in order from the mark object candidate that is likely to be detected from the captured image, unnecessary image processing is prevented, the processing load of the image processing is reduced, and the processing time is reduced. Can also be shortened.
Further, when the landmark object is not detected, the guidance intersection is guided using the distance to the guidance intersection, so even if the landmark object cannot be detected, the landmark object is not used. It is possible to properly guide the vehicle traveling at the guidance intersection.

Note that the present invention is not limited to the above-described embodiment, and various improvements and modifications can be made without departing from the scope of the present invention.
For example, in this embodiment, the detection exclusion area and the detection priority order are set based on the congestion situation of vehicles and pedestrians around the guidance intersection (S9, S11, S13). It is good also as setting a detection exclusion area based on (for example, the congestion condition of a two-wheeled vehicle).

  Further, in the present embodiment, first, image processing is performed on an area excluding the detection exclusion area in the captured image captured by the front camera 19, and when the landmark object candidate cannot be detected, the detection exclusion area is detected. However, if a landmark object candidate cannot be detected when image processing is performed on an area excluding the detection exclusion area, guidance without using the landmark object (for example, a guidance intersection) The guidance intersection may be guided by the guidance using the distance up to.

  In this embodiment, image recognition processing by template matching is performed as image processing for detecting a landmark object candidate from a captured image. However, the landmark object candidate is detected by other image processing (for example, feature point detection). It is good also as a structure to detect.

  In addition to the navigation device, the present invention can be applied to a device having a function of performing route guidance based on a guidance route. For example, the present invention can be applied to a mobile terminal such as a mobile phone or a smartphone, a personal computer, a tablet terminal (hereinafter referred to as a mobile terminal or the like). However, it is set as the structure connected to onboard equipment so that the captured image of the front camera 19 can be acquired. Further, the present invention can be applied to a system including a server and a mobile terminal. In that case, each step of the above-described intersection guidance processing program (FIGS. 3, 10, and 11) may be configured to be performed by either the server or the mobile terminal.

1 Navigation device 13 Navigation ECU
35 Mark information 41 CPU
42 RAM
43 ROM
61 Guide intersection 62 Captured image 63-65 Signboard 66-68 Detection exclusion area

Claims (11)

A guide route setting means for setting a guide route;
Imaging means for imaging the vicinity of a guidance intersection included in the guidance route by an imaging device mounted on a vehicle;
Surrounding information acquisition means for acquiring information for specifying the surrounding situation of the guidance intersection;
An area setting unit that sets a detection exclusion area for a captured image captured by the imaging unit, based on the information acquired by the peripheral information acquisition unit;
By performing image processing with priority on the area excluding the detection exclusion area among the captured images captured by the imaging unit, a landmark object to be a landmark when guiding the guidance intersection from the captured image is selected. Mark object detection means for detecting;
An intersection guide means for guiding the guide intersection using the mark object when the mark object is detected by the mark object detection means. The surrounding situation acquired by the surrounding information acquisition means is a vehicle congestion situation around the guidance intersection,
The travel guidance system according to claim 1, wherein the area setting unit sets the detection exclusion area based on the congestion state of the vehicle and a road shape of a road on which the vehicle travels. The area setting means includes
Based on the congestion situation of the vehicle and the road shape of the road on which the vehicle travels, an area that is predicted to be blocked by other vehicles in the captured image captured by the imaging unit is set as the detection exclusion area The travel guidance system according to claim 2, wherein: The surrounding situation acquired by the surrounding information acquisition means is a pedestrian congestion situation around the guidance intersection,
The travel guidance system according to claim 1, wherein the area setting means sets the detection exclusion area based on the pedestrian congestion situation and a road shape of a road on which the vehicle travels. The area setting means includes
Based on the pedestrian congestion situation and the road shape of the road on which the vehicle travels, an area that is predicted to be blocked by a pedestrian in the captured image captured by the imaging unit is defined as the detection exclusion area. The travel guidance system according to claim 4, wherein the travel guidance system is set. Mark candidate information acquisition for acquiring height information where a mark object candidate, which is a candidate for the mark object to be detected by the mark object detection means, among objects located around the guidance intersection is acquired. Means,
Reference value setting means for setting a reference value of height based on the information acquired by the peripheral information acquisition means,
The landmark object detection means preferentially sets the landmark object candidate having a height equal to or higher than the reference value among the landmark object candidates, and selects the landmark object candidate from the detected landmark object candidates. The travel guidance system according to any one of claims 1 to 5, wherein a landmark object is selected. The surrounding situation acquired by the surrounding information acquisition means is a vehicle congestion situation around the guidance intersection,
The reference value setting means sets, as the reference value, the lowest height at which the candidate landmark object is predicted not to be shielded by another vehicle when the vehicle congestion state is equal to or greater than a predetermined threshold. The travel guidance system according to claim 6. The surrounding situation acquired by the surrounding information acquisition means is a pedestrian congestion situation around the guidance intersection,
The reference value setting means sets, as the reference value, the lowest height at which the landmark object candidate is predicted not to be shielded by a pedestrian when the pedestrian congestion state is equal to or greater than a predetermined threshold. The travel guidance system according to claim 6, wherein   2. An intersection distance guide means for guiding the guidance intersection using the distance to the guidance intersection when the landmark object detection means does not detect the landmark object. The travel guidance system according to claim 8. A guide route setting step for setting a guide route;
An imaging step of imaging the vicinity of a guidance intersection included in the guidance route by an imaging device mounted on a vehicle;
Surrounding information acquisition step for acquiring information for specifying the surrounding situation of the guidance intersection;
An area setting step for setting a detection exclusion area for a captured image captured by the imaging unit based on the information acquired by the peripheral information acquisition step;
By performing image processing with priority on the area excluding the detection exclusion area among the captured images captured by the imaging unit, a landmark object to be a landmark when guiding the guidance intersection from the captured image is selected. A landmark object detection step to detect,
An intersection guidance step for guiding the guidance intersection using the landmark object when the landmark object is detected by the landmark object detection step. On the computer,
A guide route setting function for setting a guide route,
An imaging function for imaging the vicinity of a guidance intersection included in the guidance route by an imaging device mounted on a vehicle;
Surrounding information acquisition function for acquiring information for specifying the surrounding situation of the guidance intersection;
An area setting function for setting a detection exclusion area for a captured image captured by the imaging unit, based on information acquired by the peripheral information acquisition function;
By performing image processing with priority on the area excluding the detection exclusion area among the captured images captured by the imaging unit, a landmark object to be a landmark when guiding the guidance intersection from the captured image is selected. A landmark object detection function to detect,
An intersection guidance function for guiding the guidance intersection using the landmark object when the landmark object is detected by the landmark object detection function;
A computer program for executing

Images