JP6733277B2 - Image display method and image display device - Google Patents

Description

The present invention relates to an image display method and an image display device for a passenger moving body such as a vehicle.

BACKGROUND ART Conventionally, there is known a technique of detecting an object existing in the traveling direction of a vehicle and displaying an emphasized image of the detected object on a display screen of a head-up display (HUD) (see Patent Document 1).

However, in the technique described in Patent Document 1, the object existing in the traveling direction when the vehicle goes straight is highlighted, but no consideration is given to driving scenes other than straight driving. Particularly in driving scenes other than straight ahead, for example, where the traveling direction of the vehicle is changed, it is necessary to pay attention to a wide range other than the traveling direction.

JP 2001-23091 A

In view of the above problems, the present invention provides an image display method and an image display device for a riding vehicle, which allows the occupant to easily perceive the surroundings of the riding vehicle that the occupant should be careful of according to the driving scene. The purpose is to provide.

According to one aspect of the present invention, the surrounding situation of the riding mobile body is detected, and the attention area around the riding mobile body is detected based on the surrounding situation, and the emphasis point is determined for the attention area, There is provided an image display method and an image display device, which are characterized in that a virtual image showing a surrounding situation is generated so as to highlight the highlighted portion, and the virtual image is displayed on a display unit.

According to the present invention, it is possible to provide an image display method and an image display device for a riding vehicle, which allows the occupant to easily perceive the surroundings of the riding vehicle that the occupant should be aware of according to the driving scene. You can

It is a block diagram showing an example of an image display device concerning an embodiment of the present invention. FIG. 2A is a schematic diagram showing an example of a driving scene of the host vehicle according to the embodiment of the present invention, and FIG. 2B is related to the embodiment of the present invention corresponding to FIG. 2A. It is the schematic which shows an example of a display image. FIG. 3A is a schematic view showing an example of a driving scene of the host vehicle according to the embodiment of the present invention, and FIG. 3B is related to the embodiment of the present invention corresponding to FIG. 3A. It is the schematic which shows an example of a display image. FIG. 4A is a schematic diagram showing an example of the driving scene of the host vehicle according to the embodiment of the present invention, and FIG. 4B is related to the embodiment of the present invention corresponding to FIG. 4A. It is the schematic which shows an example of a display image. FIG. 5(a) is a schematic diagram showing an example of a driving scene of the host vehicle according to the embodiment of the present invention, and FIG. 5(b) shows an embodiment of the present invention corresponding to FIG. 5(a). It is the schematic which shows an example of a display image. FIG. 6A is a schematic diagram showing an example of the driving scene of the own vehicle according to the embodiment of the present invention, and FIG. 6B is related to the embodiment of the present invention corresponding to FIG. 6A. It is the schematic which shows an example of a display image. FIG. 7A is a schematic diagram showing an example of the driving scene of the own vehicle according to the embodiment of the present invention, and FIG. 7B is related to the embodiment of the present invention corresponding to FIG. 7A. It is the schematic which shows an example of a display image. It is a schematic diagram showing an example of a virtual viewpoint of a display picture concerning an embodiment of the present invention. FIG. 9A is a schematic diagram showing an example of the driving scene of the own vehicle according to the embodiment of the present invention, and FIG. 9B is related to the embodiment of the present invention corresponding to FIG. 9A. It is the schematic which shows an example of a display image. FIG. 10A is a schematic diagram showing an example of the driving scene of the host vehicle according to the embodiment of the present invention, and FIG. 10B is related to the embodiment of the present invention corresponding to FIG. 10A. It is the schematic which shows an example of a display image. FIG. 11A is a schematic view showing an example of a driving scene of the host vehicle according to the embodiment of the present invention, and FIG. 11B is related to the embodiment of the present invention corresponding to FIG. 11A. It is the schematic which shows an example of a display image. It is the schematic which shows an example of the driving scene of the own vehicle which concerns on embodiment of this invention. FIG. 13 is a schematic diagram showing an example of a display image according to the embodiment of the present invention corresponding to FIG. 12. It is the schematic which shows an example of the driving scene of the own vehicle which concerns on embodiment of this invention. FIG. 15 is a schematic diagram showing an example of a display image according to the embodiment of the present invention corresponding to FIG. 14. It is the schematic which shows an example of the driving scene of the own vehicle which concerns on embodiment of this invention. FIG. 17 is a schematic diagram showing an example of a display image according to the embodiment of the present invention corresponding to FIG. 16. 6 is a flowchart for explaining an example of an image display method according to the embodiment of the present invention. 9 is a flowchart for explaining another example of the image display method according to the embodiment of the present invention. It is a schematic diagram showing an example of the driving scene of the own vehicle concerning the 1st modification of an embodiment of the present invention. FIG. 21 is a schematic diagram showing an example of a display image according to a first modification of the embodiment of the present invention corresponding to FIG. 20. It is a schematic diagram showing an example of the driving scene of the own vehicle concerning the 2nd modification of an embodiment of the present invention. FIG. 23 is a schematic diagram showing an example of a display image according to a second modification of the embodiment of the present invention corresponding to FIG. 22. 24A to 24C are schematic diagrams showing an example of a display image according to the third modification of the embodiment of the present invention. 25A to 25C are schematic diagrams showing an example of a display image according to the fourth modified example of the embodiment of the present invention. It is a schematic diagram showing an example of a display picture concerning other embodiments of the present invention.

Embodiments of the present invention will be described below with reference to the drawings. In the following description of the drawings, the same or similar reference numerals are attached to the same or similar parts. However, it should be noted that the drawings are schematic and the relationship between the thickness and the plane dimension, the thickness ratio, and the like are different from the actual ones. Further, it is needless to say that the drawings include portions in which dimensional relationships and ratios are different from each other. Further, the embodiments described below exemplify an apparatus and a method for embodying the technical idea of the present invention, and the technical idea of the present invention is the material, shape, structure, and arrangement of components. Etc. are not limited to the following. Various changes can be added to the technical idea of the present invention within the technical scope defined by the claims described in the claims.

<Structure of image display device>
The image display device according to the embodiment of the present invention can be mounted on a passenger moving body such as a vehicle. In the following description of the embodiments of the present invention, the case of being mounted on a vehicle is illustrated. As shown in FIG. 1, the image display device according to the embodiment of the present invention includes a control device 1, a vehicle position acquisition unit 2, a surrounding condition detection unit 4, and a display unit 5.

The vehicle position acquisition unit 2 can be configured by, for example, a navigation device, a GPS receiver that receives GPS signals from the global positioning system (GPS), or the like. The vehicle position acquisition unit 2 acquires the current position of the vehicle on the map.

The surrounding condition detection unit 4 detects a surrounding condition of the own vehicle including a front condition, a rear condition, and a side condition of the own vehicle. The surroundings of the own vehicle that can be detected by the surroundings detection unit 4 include other vehicles, pedestrians, bicycles, signals, signs, pedestrian crossings, power poles, intersections, and white lines. As the ambient condition detection unit 4, for example, a laser radar, a millimeter wave radar, a standing wave radar, or a sensor using a camera such as a CCD camera can be used. The number, type, and arrangement position of the surrounding condition detection units 4 are not particularly limited, and a plurality of surrounding condition detection units 4 may be installed in front of, in the side of, or behind the vehicle.

A display such as a liquid crystal display can be used as the display unit 5. The display unit 5 is installed in a position such as an instrumental panel in the passenger compartment that is easily visible to an occupant.

The control device 1 can be configured by, for example, an electronic control unit (ECU) including a logical operation processing device 6, a caution area storage device 3, a data storage device 7, and the like. As the attention area storage device 3 and the data storage device 7, a semiconductor storage device, a magnetic storage device, an optical storage device, or the like can be used. The caution area storage device 3 and the data storage device 7 may be registers or the like provided in the logical operation processing device 6, or may include a cache memory or the like. The attention area storage device 3 and the data storage device 7 may be a secondary storage device or a virtual memory set in the secondary storage device or the like. The caution area storage device 3 stores a correspondence relationship between various driving scenes of the own vehicle and a caution area described later.

A central processing unit (CPU) or the like can be used as the logical operation processing device 6. The logical operation processing device 6 functionally includes a scene determination unit 10, a caution area detection unit 11, a moving object detection unit 12, an emphasized portion determination unit 13, and an image generation unit 14.

The scene determination unit 10 includes a current position on the map of the own vehicle acquired by the own vehicle position acquisition unit 2, a surrounding condition of the own vehicle detected by the surrounding condition detection unit 4, shift lever operation information, and a blinker switch. The driving scene of the vehicle is determined from the operation information and the like. Driving scenes that can be discriminated by the scene discriminating unit 10 include, for example, backward parking, parallel parking, narrowing in narrow roads, passing through narrow roads, lane change (merging), T-shaped roads, intersection left turn, and intersection right turn. ..

The attention area detection unit 11 refers to the correspondence relationship between the driving scene and the attention area stored in the attention area storage device 3, and determines the scene determination unit in the surrounding situation of the own vehicle detected by the surrounding situation detection unit 4. An attention area that the occupant should pay attention to according to the driving scene determined by 10 is detected.

Here, the “attention area” that can be detected by the attention area detection unit 11 means an area in which vehicles or people may intersect with each other depending on the road structure on the road. The attention area includes an area where the attention object exists, an area where the attention place exists, and an area where the degree of attention is higher than a predetermined threshold.

The objects of attention include, for example, other vehicles, pedestrians (especially traffic vulnerable people), animals including guide dogs, bicycles, signals, signs, pedestrian crossings, intersections, and obstacles such as snow. Other vehicles include, for example, oncoming vehicles, runaway vehicles, and emergency vehicles. The object of attention can be determined, for example, from the surroundings of the host vehicle detected by the surroundings detection unit 4.

The attention place includes, for example, the periphery of the own vehicle, an intersection, a pedestrian crossing, an interchange, and a confluence point. Note that there may be a place (object) that is common to the attention place and the attention object, such as a pedestrian crossing. The attention location can be determined, for example, from the current position of the own vehicle on the map acquired by the own vehicle position acquisition unit 2 or the surrounding conditions of the own vehicle detected by the surrounding condition detection unit 4.

The degree of caution means the degree of approach between a moving object existing around the host vehicle and the host vehicle. The degree of caution can be calculated from the distance and relative speed between the own vehicle and the moving object, which is obtained from the surrounding situation of the own vehicle detected by the surrounding situation detection unit 4, for example. For example, the degree of caution is calculated as the distance between the own vehicle and the moving object is shorter, and the degree of caution is calculated as the relative speed between the own vehicle and the moving object is higher. Furthermore, the higher the speed of the host vehicle, the higher the degree of caution may be calculated.

Here, an example of a method of calculating the degree of caution will be described. For example, the degree of caution can be calculated using the collision margin time (TTC) and the inter-vehicle time (THW). The collision margin time t _c is an index for predicting the time until the host vehicle collides with the preceding other vehicle on the assumption that the current relative speed is maintained, and the relative speed between the host vehicle and the other vehicle is calculated. It is calculated by the following equation (1), where v _{r is} the distance and x _r is the distance.
t _c =−x _r /v _r (1)

Also, following time t _h is an index representing the time to reach current preceding vehicle position at the current vehicle speed, the vehicle speed v _f, the distance between the vehicle and the other vehicle as x _r, less Equation (2) is obtained.
t _h =−x _r /v _f (2)

The attention level RP can be set as in the following Expression (3) by using the collision margin time t _c and the inter-vehicle time t _h obtained in the Expressions (1) and (2).
RP = 1/2 (α / t c + β / t h) ... (3)

Here, each of α and β is an arbitrary coefficient and can be appropriately set. The predetermined threshold value for comparison with the caution degree can be set as appropriate, and may be stored in advance in the data storage device 7 or the like of the control device 1.

The moving object detection unit 12 detects a moving object in the attention area detected by the attention area detection unit 11 using the surrounding situation of the own vehicle detected by the surrounding situation detection unit 4. Moving objects that can be detected by the moving object detection unit 12 include other vehicles, pedestrians, animals, and bicycles. The moving objects that can be detected by the moving object detection unit 12 include an object that is actually moving and an object that has stopped moving due to signal waiting or the like but may move.

The emphasis point determination unit 13 determines an emphasis point for the attention area detected by the attention area detection unit 11. The emphasis point determination unit 13 may determine, for example, the attention area itself as the emphasis point, or may determine the area surrounding the attention area as the emphasis point. Further, the emphasis point determination unit 13 may change the emphasis point and the emphasis method of the attention area according to the type of the attention area.

The emphasis point determination unit 13 may further determine the area of the moving object detected by the moving object detection unit 12, the direction of the moving object, the movable range of the moving object, etc. as the emphasis point. When the moving object is moving, the emphasizing portion determination unit 13 may change the emphasizing portion (range) or the emphasizing method of the moving object according to the relative moving speed of the moving object. For example, the emphasized part determination unit 13 may extend the emphasized part in the direction in which the moving object moves as the relative moving speed of the moving object increases.

The image generation unit 14 uses the surrounding situation detected by the surrounding situation detection unit 4 to display a virtual image (computer graphic (CG) image) so as to highlight the highlighted portion determined by the highlighted portion determination unit 13. To generate. The image generation unit 14 may emphasize the highlighted portion by, for example, increasing the brightness of the highlighted portion, coloring, blinking, or the like.

The image generation unit 14 can generate a virtual image such as a front image or a bird's-eye image viewed from various virtual viewpoint positions according to a driving scene or the like, and can appropriately adjust the scale, size, aspect ratio, etc. of the virtual image. is there. The image generation unit 14 generates an image signal for display so as to display the generated virtual image, transmits the image signal to the display unit 5, and controls the display unit 5.

Next, an example of the image display method according to the embodiment of the present invention will be described by citing various driving scenes. First, FIG. 2A shows a driving scene of “reverse parking”. The host vehicle 20 is about to park in the parking frame (parking space) S1 between the other vehicles 21, 22 behind the host vehicle 20. Based on the current position of the host vehicle 20 on the map acquired by the host vehicle position acquisition unit 2, the operation information of the shift lever, and the like, the scene determination unit 10 sets the driving scene shown in FIG. Is determined.

The attention area detection unit 11 refers to the correspondence relationship between the driving scene of "reverse parking" and the attention area stored in the attention area storage device 3 and refers to the rear area A1 including the inside of the turn of the host vehicle 20. Attention detected as a place. The attention area detection unit 11 further detects the other vehicles 21 and 22 as attention objects from the surrounding situation detected by the surrounding situation detection unit 4. The emphasis point determination unit 13 determines, for example, the attention area in which the area A1 detected by the attention area detection unit 11 and the other vehicles 21 and 22 exist as the emphasis points.

As shown in FIG. 2B, the image generation unit 14 generates a virtual image I1 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I1, the own vehicle M20 and the parking frame (parking frame (parking space) MS1) corresponding to the own vehicle 20 and the parking frame (parking space) S1 shown in FIG. 2A are virtually displayed.

Further, the area A1 and the areas MA1 and other vehicles M21 and M22 corresponding to the other vehicles 21 and 22 shown in FIG. 2A are highlighted. In FIG. 2B, for convenience, hatching indicates that the display is highlighted. For example, with respect to the area MA, the area MA may be surrounded by a frame line, or the area MA may be colored to be highlighted. The other vehicles 21 and 22 may be highlighted by surrounding the other vehicles 21 and 22 with a frame line or changing the color and the brightness in the other vehicles 21 and 22. In FIG. 2B, the own vehicle M20 and the other vehicles M21 and M22 simulate the shape of the actual vehicle, but they may be simple rectangles or icons.

Next, FIG. 3A shows a driving scene of “parallel parking”. The own vehicle 20 is about to park in the parking frame (parking space) S1 between the other vehicles 21 and 22 behind the own vehicle 20. Based on the current position of the own vehicle 20 on the map acquired by the own vehicle position acquisition unit 2, the operation information of the shift lever, and the like, the scene determination unit 10 performs “parallel parking” on the driving scene illustrated in FIG. Is determined.

The caution area detection unit 11 refers to the correspondence relationship between the "parallel parking" driving scene and the caution area stored in the caution area storage device 3, and wants to park in the direction approaching the other vehicles 21, 22. An arcuate area A2 including the end of the front corner located in the direction and an arcuate area A3 including the ground contact portion of the rear wheel in the direction to be parked are detected as attention points. The attention area detection unit 11 further detects the other vehicles 21 and 22 as attention objects based on the surrounding conditions and the like detected by the surrounding condition detection unit 4. The emphasis point determination unit 13 determines, for example, the attention area where the areas A2 and A3 and the other vehicles 21 and 22 exist as the emphasis points.

As shown in FIG. 3B, the image generation unit 14 generates a virtual image I2 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I2, the host vehicle M20 and the parking frame (parking space) MS1 corresponding to the host vehicle 20 and the parking frame (parking space) S1 shown in FIG. 3A are virtually displayed.

Further, areas A2, A3 and areas MA2, MA3 and other vehicles M21, M22 corresponding to the other vehicles 21, 22 shown in FIG. 3A are highlighted. In FIG. 3( b ), for convenience, it is indicated by hatching that they are highlighted. For example, with respect to the area MA, the area MA may be surrounded by a frame line, or the area MA may be colored to be highlighted. The other vehicles 21 and 22 may be highlighted by surrounding the other vehicles 21 and 22 with a frame line or changing the color and the brightness in the other vehicles 21 and 22.

Next, FIG. 4A shows a driving scene of "width reduction in a narrow road". As shown in FIG. 4(a), the host vehicle 20 is running near the guardrail 31 on the left side because the oncoming vehicle, the other vehicle 21, is approaching on a narrow road. The scene determination unit 10 determines a driving scene based on the current position on the map of the own vehicle 20 acquired by the own vehicle position acquisition unit 2, the surrounding situation detected by the surrounding situation detection unit 4, and the like. Alignment".

The attention area detection unit 11 refers to the correspondence relationship between the attention area and the driving scene of “width narrowing on a narrow road” stored in the attention area storage device 3, and refers to the left steering wheel side surface that approaches the own vehicle 20. An area A4 on the side surface of the vehicle body including the area is detected as a caution location. The attention area detection unit 11 further detects the other vehicle 21 and the guardrail 31 as attention objects based on the surrounding situation detected by the surrounding situation detection unit 4. The emphasis point determination unit 13 determines, for example, the attention area where the area A4, the other vehicle 21, and the guardrail 31 detected by the attention area detection unit 11 exist as the emphasis points.

As shown in FIG. 4B, the image generation unit 14 generates a virtual image I3 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I3, the host vehicle M20 corresponding to the host vehicle 20 shown in FIG. 4A is virtually displayed. Further, the area A4 shown in FIG. 4A, the area MA4 corresponding to the other vehicle 21 and the guardrail 31, and the other vehicle M21 are highlighted. In FIG. 4( b ), for convenience, it is indicated by hatching that they are highlighted.

Next, FIG. 5A shows a driving scene of “passing through a narrow road”. Before the other vehicle 21, which is an oncoming vehicle, approaches on the narrow road, the vehicle 20 draws an S-shape as shown by a dashed arrow in front of the vehicle 20, and tries to pass the other vehicle 22 in front. There is. The scene determination unit 10 determines a driving scene based on the current position on the map of the own vehicle 20 acquired by the own vehicle position acquisition unit 2, the surrounding situation detected by the surrounding situation detection unit 4, and the like. Pass through”.

The attention area detection unit 11 includes the front (the traveling direction) of the host vehicle 20 with reference to the correspondence between the attention area and the driving scene of “passing through a narrow road” stored in the attention area storage device 3. , The area A5 on the left and right side surfaces of the vehicle body is detected as the attention location. The attention area detection unit 11 further detects the other vehicles 21 and 22 as attention objects based on the surrounding conditions and the like detected by the surrounding condition detection unit 4. The emphasis point determination unit 13 determines, for example, the attention area in which the area A5 detected by the attention area detection unit 11 and the other vehicles 21 and 22 exist as the emphasis points.

As shown in FIG. 5B, the image generation unit 14 generates a virtual image I4 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I4, the host vehicle M20 corresponding to the host vehicle 20 shown in FIG. 5A is virtually displayed. Further, the area A5, the area MA5 corresponding to the other vehicles 21, 22 and the other vehicles M21, M22 shown in FIG. 5A are highlighted. In FIG. 5( b ), for convenience, hatching is added to indicate that they are highlighted.

Next, FIG. 6A shows another driving scene of “passing through a narrow road”. The host vehicle 20 is about to pass between the utility pole 32 and the other vehicle 21 on a narrow road. The scene determination unit 10 determines a driving scene based on the current position on the map of the own vehicle 20 acquired by the own vehicle position acquisition unit 2, the surrounding situation detected by the surrounding situation detection unit 4, and the like. Pass through”.

The attention area detection unit 11 includes the front (the traveling direction) of the host vehicle 20 with reference to the correspondence between the attention area and the driving scene of “passing through a narrow road” stored in the attention area storage device 3. , The area A6 on the left and right sides of the vehicle body is detected as the attention location. The attention area detection unit 11 further detects the other vehicle 21 and the telephone pole 32 as the attention target object based on the surrounding situation detected by the surrounding situation detection unit 4. The emphasis point determination unit 13 determines, for example, the attention area where the area A6 detected by the attention area detection unit 11, the other vehicle 21, and the telephone pole 32 exists as the emphasis point.

As shown in FIG. 6B, the image generation unit 14 generates a virtual image I5 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I5, the host vehicle M20 and the guardrail M31 corresponding to the host vehicle 20 and the guardrail 31 shown in FIG. 6A are virtually displayed. Further, the area A6 shown in FIG. 6A, the area MA6 corresponding to the other vehicle 21 and the electric pole 32, the other vehicle M21 and the electric pole 32 are highlighted. In FIG. 6( b ), for convenience, hatching is added to indicate that they are highlighted.

Next, FIG. 7A shows a driving scene of “lane change”. At the interchange, the host vehicle 20 is traveling in the lane L1 before the merging and is about to change to the lane L2 on the right side. The scene determination unit 10 changes the driving scene to “lane change” based on the current position on the map of the own vehicle 20 acquired by the own vehicle position acquisition unit 2, the surrounding situation detected by the surrounding situation detection unit 4, and the like. To determine.

The attention area detection unit 11 refers to the correspondence relationship between the “lane change” driving scene and the attention area stored in the attention area storage device 3 and refers to the rear side of the own vehicle 20 including right next to the lane L2 of the change destination. The area A7 is detected as the attention location. The area in front of the host vehicle 20 in the lane L2 to be changed is not detected as a caution location because there is no other vehicle. The attention area detection unit 11 further detects the other vehicle 21 as an attention target object based on the surrounding situation and the like detected by the surrounding situation detection unit 4.

The emphasis point determination unit 13 determines, for example, the area A7 detected by the attention area detection unit 11 and the attention area where the other vehicle 21 exists as the emphasis points. The emphasis point determination unit 13 further calculates the relative speed of the other vehicle 21 and determines the relative speed as the emphasis point.

As shown in FIG. 7B, the image generation unit 14 generates a virtual image I6 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I6, the host vehicle M20 and the lanes ML1 and ML2 corresponding to the host vehicle 20 and the lanes L1 and L2 shown in FIG. 7A are virtually displayed. Furthermore, the area A7 and the area MA7 and the other vehicle M21 corresponding to the area A7 and the other vehicle 21 shown in FIG. 7A are highlighted. In FIG. 7( b ), for convenience, it is shown that the lines are highlighted by hatching. Further, in the rear part of the other vehicle M21, the relative speed is highlighted backward with an arrow M21a. The arrow M21a indicates that the relative speed of the other vehicle M21 is high in the direction away from the own vehicle M20.

Note that, for example, as illustrated in FIG. 8, the viewpoint position P1 of the virtual image I5 in the driving scene of “passing through a narrow road” illustrated in FIG. 6A is captured from above and behind the host vehicle 20. And has an imaging range R1. On the other hand, the viewpoint position P2 of the virtual image I6 in the driving scene of “lane change” shown in FIG. 7A is set so as to be captured from above and behind the own vehicle 20 with respect to the viewpoint position P1. The image pickup range R2 is wider than the image pickup range R1 of P1. In this way, the viewpoint position of the virtual image can be appropriately adjusted according to the driving scene or the like.

Next, FIG. 9A shows another driving scene of “lane change”. At the interchange, the own vehicle 20 is traveling in the lane L1 before the merging, and is about to change lanes to the lane L2 on the right side as in FIG. 7A, and the other vehicle 21 is in front of the own vehicle 20. It differs from FIG. 7A in that it is traveling. The scene determination unit 10 changes the driving scene to “lane change” based on the current position on the map of the own vehicle 20 acquired by the own vehicle position acquisition unit 2, the surrounding situation detected by the surrounding situation detection unit 4, and the like. To determine.

The attention area detection unit 11 refers to the correspondence relation between the driving scene of “lane change” and the attention area stored in the attention area storage device 3 and refers to the front side of the own vehicle 20 including right next to the lane L2 to be changed. The area A8 is detected as the attention location. Note that a region located behind the host vehicle 20 in the lane L2 of the change destination is not detected as a caution location because there is no other vehicle. The attention area detection unit 11 further detects the other vehicle 21 as an attention target object based on the surrounding situation and the like detected by the surrounding situation detection unit 4.

The emphasis point determination unit 13 determines, for example, the area A8 detected by the attention area detection unit 11 and the attention area where the other vehicle 21 exists as the emphasis points. The emphasis point determination unit 13 further calculates the relative speed of the other vehicle 21 and determines the relative speed as the emphasis point.

As shown in FIG. 9B, the image generation unit 14 generates a virtual image I7 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I7, the own vehicle M20 and the lanes ML1 and ML2 corresponding to the own vehicle 20 and the lanes L1 and L2 shown in FIG. 9A are virtually displayed. Further, the area A8 and the other vehicle M21 corresponding to the other vehicle 21 and the other vehicle M21 shown in FIG. 9A are highlighted. In FIG. 9( b ), for convenience, it is shown that they are highlighted by hatching. Further, in the front portion of the other vehicle M21, the relative speed is highlighted forward by the arrow M21a. The arrow M21a indicates that the relative speed of the other vehicle M21 is high in the direction away from the own vehicle M20. The arrow M21a may be longer as the relative speed is higher.

Next, FIG. 10A shows still another driving scene of “lane change”. In the interchange, the own vehicle 20 is traveling in the lane L1 before the merging, and is about to change the lane to the lane L2 on the right side, which is the same as in FIGS. 7(a) and 9(a). 22 differs from FIGS. 7(a) and 9(a) in that the vehicle 22 travels in front of and behind the vehicle 20. The scene determination unit 10 changes the driving scene to “lane change” based on the current position on the map of the own vehicle 20 acquired by the own vehicle position acquisition unit 2, the surrounding situation detected by the surrounding situation detection unit 4, and the like. To determine.

The attention area detection unit 11 refers to the correspondence relationship between the driving scene of “lane change” and the attention area stored in the attention area storage device 3 and refers to the front and rear of the own vehicle 20 including right next to the lane L2 of the change destination. The area A9 in the direction is detected as the attention location. The attention area detection unit 11 further detects the other vehicles 21 and 22 as attention objects based on the surrounding conditions and the like detected by the surrounding condition detection unit 4.

The emphasis point determination unit 13 determines, for example, the attention area where the attention area detection unit 11 detects the area A9 and the other vehicles 21 and 22 as the emphasis points. The emphasis point determination unit 13 further calculates the relative speeds of the other vehicles 21 and 22, and determines the relative speeds as the emphasis points.

As shown in FIG. 10B, the image generation unit 14 generates a virtual image I8 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I8, the host vehicle M20 and the lanes ML1 and ML2 corresponding to the host vehicle 20 and the lanes L1 and L2 shown in FIG. 10A are virtually displayed. Further, the area A9 and the areas MA9 and the other vehicles M21 and M22 corresponding to the other vehicles 21 and 22 shown in FIG. 10A are highlighted. In FIG. 10( b ), for convenience, it is indicated by hatching that the image is highlighted.

Further, in the front part of the other vehicle M21 located behind the host vehicle M20, the relative speed is highlighted forward by the arrow M21a, indicating that the relative speed of the other vehicle M21 is high in the direction approaching the host vehicle M20. There is. Further, the relative speed is highlighted backward by the arrow M22a in the rear portion of the other vehicle M22 located in front of the own vehicle M20, indicating that the relative speed of the other vehicle M22 is high in the direction of approaching the own vehicle M20. There is. The arrows M21a and M22a may be made longer as the relative speed is higher.

Next, FIG. 11A shows a driving scene of “lane change” similar to FIG. 10A, but the attention area detection unit 11 detects the surrounding situation detected by the surrounding situation detection unit 4. Based on this, the surroundings of the vehicle 20 may be virtually divided into a plurality (12 in FIG. 11A) of regions RA, and the degree of caution may be calculated for each region RA. In FIG. 11A, a plurality of regions RA are set along the lane with the position of the host vehicle 20 as a reference. The shapes, positions, and numbers of the plurality of regions RA are not particularly limited, and can be appropriately set according to the driving scene and the like.

For example, when there are other vehicles 21, 22 in the area RA, the attention area detection unit 11 calculates the degree of attention from the relative distance and relative speed of the other vehicles 21, 22. The attention area detection unit 11 further determines whether the degree of attention is equal to or higher than a predetermined threshold value, and detects an area RA (for example, an area including the other vehicle 21) equal to or higher than the predetermined threshold value as a caution area. The emphasis point determination unit 13 determines, for example, the area RA including the other vehicle 21 detected by the attention area detection unit 11 as an emphasis point.

As shown in FIG. 11B, the image generation unit 14 generates a virtual image I8 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I8, the own vehicle 20, the other vehicles 21, 22 and the own vehicle M20 corresponding to the lanes L1, L2, the other vehicles M21, M22, and the lanes ML1, ML2 shown in FIG. 11A are virtually displayed. ing. Further, the area RB corresponding to the area RA including the other vehicle 21 shown in FIG. 11A is highlighted. In FIG. 11B, for convenience sake, hatching indicates that the display is highlighted.

Next, FIG. 12 shows a driving scene of “T-shaped road”. The host vehicle 20 is about to enter the front T-shaped road. At the T-shaped road, the sign 51 and the pedestrian crossings 41 and 42 are installed, and other vehicles 21 and 22 and bicycles 61 to 64 are present. The scene determination unit 10 determines the driving scene to be a “T-shaped road” based on the current position of the vehicle 20 on the map acquired by the vehicle position acquisition unit 2, the surrounding situation detected by the surrounding situation detection unit 4, and the like. Is determined.

The attention area detection unit 11 refers to the correspondence between the “T-shaped road” driving scene and the attention area stored in the attention area storage device 3, and refers to the surrounding situation or the like detected by the surrounding situation detection unit 4. Based on this, the areas A11 and A12 in both the left and right directions of the vehicle 20 and the semicircular area A10 located at the center of the intersection are detected as attention points. The attention area detection unit 11 further, based on the surrounding conditions and the like detected by the surrounding condition detection unit 4, other vehicles 21 and 22, bicycles 61 to 64, a sign 51, and a pedestrian crossing 41 that are traveling on the intersection road at the intersection. , 42 are detected as attention objects.

For example, the emphasis point determination unit 13 emphasizes the attention area where the areas A10 to A12, the other vehicles 21 and 22, the bicycles 61 to 64, the sign 51, and the pedestrian crossings 41 and 42 detected by the attention area detection unit 11 are present. To decide.

As illustrated in FIG. 13, the image generation unit 14 generates a virtual image I9 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I9, the host vehicle M20 corresponding to the host vehicle 20 shown in FIG. 12 is virtually displayed. Further, areas A10 to A12, other vehicles 21 and 22, bicycles 61 to 64, signs 51, areas MA10 to MA12 corresponding to the pedestrian crossings 41 and 42, other vehicles M21 and M22, and bicycles M61 to M64 shown in FIG. The sign M51 and the pedestrian crossings M41 and M42 are highlighted. In FIG. 13, for convenience, hatching is added to indicate that they are highlighted.

Next, FIG. 14 shows a driving scene of “turn left at an intersection”. At the intersection, a sign 51, a traffic light 53, and pedestrian crossings 41 and 42 are installed, and other vehicles 21 and 22, motorcycles 81 and 82, a pedestrian 71, and a bicycle 61 are present. The scene determination unit 10 determines that the driving scene is “turn left at intersection” based on the current position of the vehicle 20 on the map acquired by the vehicle position acquisition unit 2, the operation information of the direction indicator, and the like.

The attention area detection unit 11 refers to the correspondence relationship between the driving scene of “intersection left turn” stored in the attention area storage device 3 and the attention area, and based on the surrounding situation detected by the surrounding situation detection unit 4. An area A13 of an arc of about 3/4 that does not include the traveling direction (left turn) of the vehicle 20 with the intersection center C1 as a reference is detected as a caution location. The attention area detection unit 11 is further based on the surrounding situation detected by the surrounding situation detection unit 4 and the like, the other vehicles 21 and 22, the two-wheeled vehicles 81 and 82, the pedestrian 71, the bicycle 61, the sign 51, the traffic light 53, and the pedestrian crossing. 41 and 42 are detected as attention objects.

The emphasis point determination unit 13 is, for example, the region A13 detected by the attention region detection unit 11, other vehicles 21, 22, two-wheeled vehicles 81, 82, pedestrians 71, bicycles 61, signs 51, traffic lights 53, pedestrian crossings 41, 42. The attention area where is present is determined as the emphasis point.

As shown in FIG. 15, the image generation unit 14 generates a virtual image I10 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I10, the host vehicle M20 corresponding to the host vehicle 20 shown in FIG. 14 is virtually displayed. Further, the area A13 shown in FIG. 14, the other vehicles 21, 22, the two-wheeled vehicles 81, 82, the pedestrian 71, the bicycle 61, the sign 51, the traffic light 53, the area MA13 corresponding to the pedestrian crossings 41, 42, and the other vehicles M21, M22. , M81, M82, pedestrian M71, bicycle M61, sign M51, traffic light M53, pedestrian crossings M41, M42 are highlighted. In FIG. 15, for convenience, hatching is added to indicate that they are highlighted.

Next, FIG. 16 shows a driving scene of “turn right at an intersection”. Signs 51 and 52, traffic lights 53, and pedestrian crossings 41 and 42 are installed at the intersections, and other vehicles 21 to 23, two-wheeled vehicles 81 to 83, pedestrians 71 and 72, and bicycles 61 to 64 are present. The scene determination unit 10 determines that the driving scene is “turn right at the intersection” based on the current position of the vehicle 20 on the map acquired by the vehicle position acquisition unit 2, operation information of the direction indicator, and the like.

The attention area detection unit 11 refers to the correspondence relationship between the attention area and the driving scene of “turn right at the intersection” stored in the attention area storage device 3, and based on the surrounding situation and the like detected by the surrounding situation detection unit 4. Then, the area A14 of an arc of about 3/4 that does not include the traveling direction (right turn) of the host vehicle 20 with the center of the intersection as a reference is detected as the attention location. The attention area detection unit 11 further, based on the surrounding situation and the like detected by the surrounding situation detection unit 4, other vehicles 21-23, two-wheeled vehicles 81-83, pedestrians 71, 72, bicycles 61-64, signs 51, 52. , The traffic signal 53 and the pedestrian crossings 41 and 42 are detected as attention objects.

The emphasis point determination unit 13 may be, for example, the area A14 detected by the attention area detection unit 11, other vehicles 21 to 23, two-wheeled vehicles 81 to 83, pedestrians 71 and 72, bicycles 61 to 64, signs 51 and 52, and a traffic light 53. , The attention area in which the pedestrian crossings 41 and 42 exist is determined as the highlighted portion.

As shown in FIG. 17, the image generation unit 14 generates a virtual image I11 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I11, the host vehicle M20 corresponding to the host vehicle 20 shown in FIG. 16 is virtually displayed. Furthermore, the area MA14 corresponding to the area A14, the other vehicles 21 to 23, the two-wheeled vehicles 81 to 83, the pedestrians 71 and 72, the bicycles 61 to 64, the signs 51 and 52, the traffic light 53, and the crosswalks 41 and 42 shown in FIG. Other vehicles M21 to M23, two-wheeled vehicles M81 to M83, pedestrians M71 and M72, bicycles M61 to M64, signs M51 and M52, traffic lights M53, pedestrian crossings M41 and M42 are highlighted. In FIG. 17, for convenience, hatching is added to indicate that they are highlighted.

<Image display method>
Next, an example of an image display method for a riding vehicle according to the embodiment of the present invention will be described with reference to the flowchart in FIG. The series of processes in the flowchart of FIG. 18 can be repeatedly executed at a predetermined control cycle.

In step S1, the vehicle position acquisition unit 2 acquires the current position of the vehicle 20 on the map and inputs the acquired current position of the vehicle 20 on the map to the control device 1. The surrounding condition detection unit 4 detects the surrounding condition of the own vehicle 20 and inputs the detected surrounding condition of the own vehicle 20 to the control device 1.

In step S2, the scene determination unit 10 causes the current position on the map of the own vehicle 20 acquired by the own vehicle position acquisition unit 2, the surrounding situation detected by the surrounding situation detection unit 4, the operation information of the shift lever or the blinker switch. Based on the above, the driving scene of the vehicle 20 is determined.

In step S3, the attention area detection unit 11 refers to the correspondence relationship between the driving scene and the attention area stored in the attention area storage device 3, and refers to the attention area corresponding to the driving scene determined by the scene determination unit 10. To extract. Then, the attention area detection unit 11 detects, in the surrounding situation of the own vehicle detected by the surrounding situation detection unit 4, an area where the attention place exists, an area where the attention object exists, and an area where the attention degree is equal to or higher than a predetermined threshold value. The attention area including etc. is detected.

In step S4, the moving object detection unit 12 detects a moving object in the attention area detected by the attention area detection unit 11 based on the surrounding situation detected by the surrounding situation detection unit 4. In step S<b>5, the emphasized part determination unit 13 determines whether or not there is a moving object detected by the moving object detection unit 12. When it is determined that there is a moving object, the process proceeds to step S6, and the emphasis point determination unit 13 determines the moving object in the attention area as the emphasis point. The image generation unit 14 generates a virtual image in which a moving object in the attention area is highlighted. The display unit 5 displays the virtual image generated by the image generation unit 14.

In step S7, the image generation unit 14 determines whether or not the moving object has moved to the outside of the attention area based on the surrounding situation detected by the surrounding situation detection unit 4. When it is determined that the moving object has moved out of the attention area, the process proceeds to step S8. In step S8, the image generation unit 14 outputs to the display unit 5 a signal for stopping the highlighting of the moving object in the virtual image.

When it is determined in step S5 that there is no moving object detected by the moving object detection unit 12, the process proceeds to step S9. In step S<b>9, the emphasis point determination unit 13 determines an emphasis point for the attention area detected by the attention area detection unit 11. The image generation unit 14 generates a virtual image in which the attention area is highlighted and causes the display unit 5 to display the virtual image.

In step S10, the image generation unit 14 determines whether or not the own vehicle has passed the highlighted caution area based on the position of the own vehicle 20 obtained from the GPS or the like. When it is determined that the vehicle has passed through the attention area, the process proceeds to step S8, and the image generation unit 14 outputs to the display unit 5 a signal for stopping the highlighting of the attention area in the virtual image.

The image display program for a riding vehicle according to the embodiment of the present invention causes a computer constituting the control device 1 to execute the procedure of the image display method shown in FIG. That is, the driving support program according to the embodiment of the present invention, the procedure for detecting the surrounding situation of the riding vehicle, the procedure for detecting the attention area around the riding vehicle based on the surrounding situation, The computer configuring the control device 1 is caused to execute a procedure of determining an emphasized portion, a procedure of generating a virtual image displaying a surrounding situation so as to emphasize the emphasized portion, a procedure of displaying the virtual image on the display unit, and the like. The image display program according to the embodiment of the present invention can be stored in, for example, the data storage device 7.

Note that the image display method according to the embodiment of the present invention may be, for example, the procedure of the flowchart shown in FIG. After executing the procedure of steps S1 to S3 in the same manner as the flowchart shown in FIG. 18, the process proceeds to step S11, where the emphasized part determination unit 13 does not determine the presence or absence of the moving object detected by the moving object detection unit 12. The attention area detected by the attention area detection unit 11 may be determined as the emphasized portion. The image generation unit 14 generates a virtual image in which the attention area is highlighted. The display unit 5 displays the virtual image generated by the image generation unit 14.

After that, in step S12, as in step S10 of the flowchart shown in FIG. 18, the image generation unit 14 determines the highlighted caution area based on the position of the own vehicle 20 obtained from GPS or the like. It is determined whether or not has passed. When it is determined that the vehicle has passed through the attention area, the process proceeds to step S13, and like step S10 of the flowchart shown in FIG. 18, the image generation unit 14 stops the highlighting of the attention area in the virtual image. ..

Further, in the flowchart shown in FIG. 18, the case where the attention area or the moving object is selectively highlighted in step S6 and step S9 is illustrated, but the attention area and the moving object may be highlighted simultaneously.

As described above, according to the embodiment of the present invention, a driving scene is discriminated, and an area where vehicles or people may intersect with each other according to a road structure on a road is set as a caution area, A caution area corresponding to the driving scene is detected in a wide range around the vehicle 20, and the caution area is highlighted. As a result, it is possible to make the occupant perceive, in a wide range, an area that the occupant should pay attention to in addition to the traveling direction, depending on the driving scene.

In particular, when displaying the entire surroundings of the own vehicle 20 as a CG image as in the embodiment of the present invention, unnecessary information can be eliminated during driving in the real world by CG conversion while the occupant perceives the attention area. There may be a loss of useful information. On the other hand, according to the embodiment of the present invention, the occupant can easily perceive the attention area so as to compensate for the loss of information due to CG conversion.

Further, the surroundings of the own vehicle 20 are virtually divided into a plurality of regions RA, a caution degree is calculated for each of the plurality of regions RA, and a virtual image is generated so as to emphasize a region where the caution degree is equal to or higher than a predetermined threshold value. By doing so, it is possible to easily perceive the area to which the occupant should pay attention in units of a plurality of areas RA.

<First Modification>
As a first modified example of the embodiment of the present invention, a traveling direction that may intersect the own vehicle 20 of the attention target existing in the attention area is detected, and a virtual image in which the detected traveling direction is emphasized is generated. A case will be described.

FIG. 20 shows a driving scene of “turn left at an intersection”. At the intersections, signs 51 and 52 and pedestrian crossings 41 and 42 are installed, and other vehicles 21 to 23, two-wheeled vehicles 81 to 83, pedestrians 71 to 73, and bicycles 61 to 67 are present. The scene determination unit 10 determines that the driving scene is “turn left at intersection” based on the current position of the vehicle 20 on the map acquired by the vehicle position acquisition unit 2, the operation information of the direction indicator, and the like.

Based on the fact that the driving scene determined by the scene determination unit 10 is “turn left at the intersection”, the attention area detection unit 11 determines the other vehicles 21 to 23 and the two-wheeled vehicle 81 based on the surrounding situation detected by the surrounding situation detection unit 4. ˜83, pedestrians 71 to 73, bicycles 61 to 67, signs 51 and 52, and pedestrian crossings 41 and 42 are detected as attention objects. Note that, as in the case of the "turn left at intersection" driving scene shown in FIG. 14, the attention area detection unit 11 may further detect an arc area of about 3/4 of the center of the intersection as the attention location.

The highlighted portion determination unit 13 includes other vehicles 21 to 23, two-wheeled vehicles 81 to 83, pedestrians 71 to 73, bicycles 61 to 67, signs 51, 52, and pedestrian crossings 41, 42 detected by the attention area detection unit 11. The attention area to be selected is determined as the emphasis point. Among the attention objects detected by the attention area detection unit 11, the emphasis point determination unit 13 further includes other vehicles 21 to 23, two-wheeled vehicles 81 to 83, pedestrians 71 to 73, and bicycles 61 to 67, which are moving objects. A traveling direction that may intersect when the host vehicle 20 turns left is detected.

For example, the emphasized location determination unit 13 determines that the other vehicle 21 entering the intersection from the left side may go straight or turn left or right, but there is no possibility of crossing when the vehicle 20 turns left. The emphasized location determination unit 13 may go straight or turn left or right with respect to the other vehicle 22 and the two-wheeled vehicle 81 that enter the intersection from the oncoming lane side, but there is a possibility that the own vehicle 20 may intersect when turning left, the right turn direction. Is determined as the emphasis point.

The emphasis point determination unit 13 may make a straight or left-right turn with respect to the other vehicle 23 and the two-wheeled vehicle 83 that enter the intersection from the right side, but emphasize the straight-ahead direction that may intersect when the vehicle 20 makes a left turn. It is decided as the place. The emphasis point determination unit 13 determines, as an emphasis point, a straight traveling direction of the two-wheeled vehicle 82 behind the host vehicle 20 that may be caught when the host vehicle 20 turns left.

For the pedestrians 71, 72 and bicycles 61, 62, 64 near the pedestrian crossing 41 on the left side, the emphasis point determination unit 13 crosses the pedestrian crossing 41 where the vehicle 20 may intersect when turning left. Is determined as the emphasis point. For the pedestrian 73 and the bicycles 61, 65, 67 located far from the pedestrian crossing at the intersection, the emphasis point determination unit 13 sets the front of the own vehicle 20 that may intersect when the own vehicle 20 turns left. The crossing direction is determined as the emphasis point.

As shown in FIG. 21, the image generation unit 14 generates a virtual image I13 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I13, the other vehicles M21 to M23 corresponding to the other vehicles 21 to 23 shown in FIG. 20 are highlighted, and the arrows D22 and D23 indicating the traveling directions of the other vehicles M22 and M23 are also highlighted. ..

Further, the two-wheeled vehicles M81 to M83 corresponding to the two-wheeled vehicles 81 to 83 shown in FIG. 20 are highlighted, and the arrows D81 to D83 indicating the traveling directions of the two-wheeled vehicles M81 to M83 are also highlighted. Further, the pedestrians M71 to M73 and the bicycles M61 to M67 corresponding to the pedestrians 71 to 73 and the bicycles 61 to 67 shown in FIG. 20 are highlighted, and the traveling directions of the pedestrians M71 to M73 and the bicycles M61 to M67 are highlighted. Arrows D71 to D73 and D61 to D67 indicating the are also highlighted.

According to the first modification of the embodiment of the present invention, a virtual image in which a traveling direction that may intersect the own vehicle 20 of the attention target existing in the attention area is detected and the detected traveling direction is emphasized is displayed. By generating I13, it is possible to easily grasp the advancing direction in which the object of attention should be noted.

<Second Modification>
As a third modified example of the embodiment of the present invention, similarly to the first modified example, a traveling direction that may intersect with the own vehicle 20 of the attention object existing in the attention area is detected and detected. A case where a virtual image in which the traveling direction is emphasized is generated, but a case of turning right at an intersection will be described unlike the first modification.

FIG. 22 shows a driving scene of “turn right at an intersection”. The host vehicle 20 is about to turn right at an intersection without a traffic light. At the intersections, signs 51 and 52 and pedestrian crossings 41 and 42 are installed, and other vehicles 21 to 24, two-wheeled vehicles 81 to 84, pedestrians 71 and bicycles 61 to 63 are present. The scene determination unit 10 determines that the driving scene is “turn right at the intersection” based on the current position of the vehicle 20 on the map acquired by the vehicle position acquisition unit 2, operation information of the direction indicator, and the like.

Based on the fact that the driving scene determined by the scene determination unit 10 is “turn right at an intersection”, the attention area detection unit 11 determines the other vehicles 21 to 24 and the two-wheeled vehicle 81 based on the surrounding situation detected by the surrounding situation detection unit 4. ˜84, pedestrian 71, bicycles 61 to 63, signs 51 and 52, and pedestrian crossings 41 and 42 are detected as attention objects. Note that, as in the case of the driving scene of "turn left at intersection" shown in FIG. 16, the attention area detection unit 11 may further detect an area of an arc of about 3/4 of the center of the intersection as the attention location.

The emphasis point determination unit 13 is a caution that the other vehicles 21 to 24, the two-wheeled vehicles 81 to 84, the pedestrian 71, the bicycles 61 to 63, the signs 51 and 52, and the pedestrian crossings 41 and 42 detected by the attention area detection unit 11 exist. The area is determined as the emphasis point. The emphasis point determination unit 13 further turns right of the other vehicles 21 to 24, the motorcycles 81 to 84, the pedestrian 71, and the bicycles 61 to 63, which are moving objects, among the attention objects detected by the attention area detection unit 11. The direction of travel that may intersect at the time is determined as the emphasis point.

For example, the emphasis point determination unit 13 determines, for the other vehicle 21 and the two-wheeled vehicle 81 that enter the intersection from the left side, the straight traveling direction and the right turn direction that may intersect when the vehicle 20 turns right as the emphasis points. The emphasis point determination unit 13 determines, for the other vehicle 22 and the two-wheeled vehicle 82 entering the intersection from the opposite lane side, a straight traveling direction and a right turn direction that may intersect when the vehicle 20 makes a right turn as an emphasis point.

The emphasis point determination unit 13 determines, for the other vehicle 23 and the two-wheeled vehicle 84 entering the intersection from the right side, a straight traveling direction and a right turn direction that may intersect when the host vehicle 20 turns right as an emphasis point. The emphasis point determination unit 13 determines that there is no possibility that the other vehicle 24, which is separated from the intersection on the side of the host vehicle 20, will be crossed when the host vehicle 20 turns right. For the two-wheeled vehicle 83 behind the host vehicle 20, the emphasis point determination unit 13 determines, as the emphasis points, the straight traveling direction and the right turn direction that may be involved when the host vehicle 20 turns right.

As shown in FIG. 23, the image generation unit 14 generates a virtual image I14 in which the emphasized place determined by the emphasized place determination unit 13 is highlighted. In the virtual image I14, the other vehicles M21 to M24 corresponding to the other vehicles 21 to 24 shown in FIG. 22 are highlighted, and the arrows D21 to D23 indicating the traveling directions of the other vehicles M21 to M23 are also highlighted. ..

Further, the two-wheeled vehicles M81 to M84 corresponding to the two-wheeled vehicles 81 to 84 shown in FIG. 22 are highlighted, and the arrows D81 to D84 indicating the traveling directions of the two-wheeled vehicles M81 to M84 are also highlighted. Further, the pedestrian M71 and the bicycles M61 to M63 corresponding to the pedestrian 71 and the bicycles 61 to 63 shown in FIG. 22 are highlighted, and arrows D71 and D61 indicating the traveling directions of the pedestrian M71 and the bicycles M61 to M63 are displayed. ~D63 are also highlighted.

According to the second modification of the embodiment of the present invention, a virtual image in which a traveling direction that may intersect with the own vehicle 20 of the attention target existing in the attention region is detected and the detected traveling direction is emphasized is displayed. By generating I14, it is possible to easily grasp the advancing direction in which the object of attention should be noted.

<Third Modification>
As a third modified example of the embodiment of the present invention, a modified example of highlighted display when the driving scene is "passing through a narrow road" will be described. When the driving scene is “passing through a narrow road” and the own vehicle 20 overtakes the other vehicle 21 parked forward, as shown in FIG. 24A, the own vehicle is displayed in the virtual image I15. Parallel lines L11 and L12 that define the vehicle width W1 may be highlighted in front of M20. By highlighting the straight lines L11 and L12, the distance from the other vehicle M21 and the vehicle width W1 of the host vehicle M20 can be easily grasped.

Therefore, when the own vehicle 20 is turned as shown in FIG. 24(b) and the other vehicle M21 is overtaken as shown in FIG. 24(c), the other vehicles are indicated by the straight lines L11 and L12 in the virtual image I15. The distance from M21 can be easily grasped, and the other vehicle M21 can be safely overtaken.

<Fourth Modification>
As a fourth modified example of the embodiment of the present invention, a modified example of highlighted display when the driving scene is “passing through a narrow road” will be described. When the driving scene is “passing through a narrow road” and the own vehicle 20 passes through between the guardrail 31 and the other vehicle 21 as shown in FIG. 4A, as shown in FIG. The virtual image I16 in which the straight lines L11 and L12 defining the vehicle width W1 of the vehicle M20 are highlighted may be generated. By highlighting the straight lines L11 and L12, it is possible to easily understand the distance between the guardrail M31 and the other vehicle M21 which is an oncoming vehicle.

Further, when the driving scene is “passing through a narrow road”, and when the vehicle 20 passes between the utility pole 32 and the other vehicle 21 as shown in FIG. 6A, as shown in FIG. 25B. Alternatively, the virtual image I17 in which the straight lines L11 and L12 defining the vehicle width W1 of the host vehicle M20 are highlighted may be generated. By highlighting the straight lines L11 and L12, the distance between the utility pole M32 and the other vehicle M21 that is an oncoming vehicle can be easily grasped.

When the driving scene is “passing through a narrow road” and the host vehicle 20 makes a left turn, the curves L11 and L12 that define the trajectory of the host vehicle M20 are highlighted as shown in FIG. 25(c). The virtual image I18 may be generated. By highlighting the straight lines L11 and L12, the locus of turning left can be easily grasped.

(Other embodiments)
As described above, the present invention has been described by way of embodiments, but it should not be understood that the descriptions and drawings forming a part of this disclosure limit the present invention. From this disclosure, various alternative embodiments, examples and operational techniques will be apparent to those skilled in the art.

In the embodiment of the present invention, the case where the passenger moving body is a vehicle (automobile) has been illustrated, but the passenger moving body is not limited to the vehicle, and an occupant such as an aircraft such as an airplane or a helicopter, or a passenger such as a ship moves. It is also applicable to mobile units. For example, the attention area when the passenger moving body is an aircraft means an area where aircrafts in the sky may intersect each other, and the attention area can be highlighted like the embodiment of the present invention. In addition, the caution area when the passenger moving body is a ship means an area where ships on the sea may intersect with each other, and the caution area can be highlighted as in the embodiment of the present invention.

In the embodiment of the present invention, the case where the image generation unit 14 generates the bird's-eye view image as the virtual image has been exemplified, but as shown in FIG. 26, the front image I19 may be generated as the virtual image. In the front image I19, the other vehicle M21 is highlighted at the intersection. In addition to highlighting the pedestrian M71 itself, a circular area M71a surrounding the foot of the pedestrian M71 is also highlighted. The region M71a may extend in the direction in which the pedestrian M71 is facing (the direction in which the pedestrian M71 is highly movable) while surrounding the foot of the pedestrian M71. Further, an arrow D71 indicating the traveling direction of the pedestrian M71 is highlighted by the arrow. As described above, various variations can be adopted as the emphasis method for the attention area.

As described above, it goes without saying that the present invention includes various embodiments and the like not described here. Therefore, the technical scope of the present invention is defined only by the matters specifying the invention according to the scope of claims reasonable from the above description.

DESCRIPTION OF SYMBOLS 1... Control device 2... Own vehicle position acquisition unit 3... Attention area storage device 4... Surrounding condition detection unit 5... Display unit 6... Logical operation processing device 7... Data storage device 10... Scene determination unit 11... Attention area detection unit 12 ...Moving object detection unit 13...emphasized portion determination unit 14...image generation unit 20...own vehicle 21-24...other vehicle 31...guardrail 32...electric poles 41,42...pedestrian crossing 51,52...sign 53...signals 61-67. Bicycles 71-73... Pedestrians 81-84... Motorcycles

Claims (6)

Detecting the surroundings of the riding vehicle,
Detecting the attention area around the riding vehicle in the ambient condition based on the ambient condition ;
Determining an emphasis point for the attention area,
Generating a virtual image showing the surrounding situation so as to highlight the highlighted portion,
Displaying the virtual image on a display unit,
The step of determining the emphasized part includes
Determine the presence or absence of moving objects in the attention area,
When it is determined that the moving object is present, the moving object is determined as the emphasized location, and when it is determined that the moving object is not present, the attention area is determined as the emphasized location , whereby the moving object or An image display method characterized in that the attention area is selectively highlighted . The image display method according to claim 1, wherein the attention area is an area where vehicles or people may intersect with each other depending on a road structure on the road. The step of determining the emphasized part includes
The image display method according to claim 1 or 2, wherein a region surrounding a foot of a pedestrian as the moving object is determined as the emphasized portion. The step of determining the emphasized part includes
Detecting a moving object in the detected attention area,
The image display method according to claim 1, wherein the moving direction of the detected moving object is determined as the emphasized portion. The step of detecting the attention area includes
Determine the driving scene of the passenger vehicle,
The image display method according to any one of claims 1 to 4, wherein the attention area is detected according to the determined driving scene. A surrounding condition detection unit that detects the surrounding condition of the passenger moving body,
A caution area detection unit that detects a caution area around the riding vehicle in the surrounding situation based on the surrounding situation ,
An emphasis point determination unit that determines an emphasis point for the attention area,
An image generation unit that generates a virtual image showing the surrounding condition so as to highlight the highlighted portion,
A display unit for displaying the virtual image,
The emphasis point determination unit,
Determine the presence or absence of moving objects in the attention area,
When it is determined that the moving object is present, the moving object is determined as the emphasized location, and when it is determined that the moving object is not present, the attention area is determined as the emphasized location , whereby the moving object or An image display device, wherein the attention area is selectively highlighted .

Images