JP5651491B2 - Image display system, image display apparatus, and image display method - Google Patents

Description

  The present invention relates to a technique for displaying a predicted course of a vehicle.

  In recent years, in a display device mounted on a vehicle, a technique for superimposing and displaying an index indicating a predicted course of the vehicle on an outside image obtained by photographing the periphery of the vehicle with a camera provided in the vehicle has been developed. The user of the vehicle moves the vehicle to the user's target space by operating the steering wheel of the vehicle and adjusting the accelerator opening, using the indicator displayed on the display device as a guide for the traveling direction of the vehicle. . Note that there is Patent Document 1 as a material for explaining the technology related to the present invention.

JP 2008-83990 A

  However, the predicted course of the vehicle displayed on the display device causes an error in the predicted course as the vehicle travels, although the display position on the outside image is changed according to the steering angle of the steering wheel of the vehicle. Factors were not considered. Therefore, when the user moves the vehicle based on the predicted course displayed on the display device, the vehicle may move to a position different from the position intended by the user.

  This invention is made | formed in view of the said subject, and it aims at providing the user the predicted course which shows the position where a vehicle may move.

In order to solve the above-mentioned problem, the invention of claim 1 is an image display system mounted on a vehicle, wherein the vehicle receives a vehicle outside image acquired by an imaging unit that captures the periphery of the vehicle, and the vehicle An obtaining means for obtaining a steering angle of the vehicle, a first deriving means for deriving a predicted course where the vehicle is predicted to travel based on the steering angle, and a degree of a factor causing an error in the predicted course. Detection means; and second derivation means for deriving a maximum error course having a maximum error with respect to the predicted course based on a calculation process of a road surface friction coefficient related to the degree of the factor and a parameter of the speed of the vehicle ; ranges comprised between the maximum error path and the predicted path, Bei and display means for displaying by superimposing an index indicating the broad in scope as the distance away from the vehicle to the exterior image That.

  According to a second aspect of the present invention, in the image display system according to the first aspect, the detecting means detects the slipperiness of the road surface on which the vehicle travels and the speed of the vehicle as the degree of the factor.

  According to a third aspect of the present invention, in the image display system according to the first or second aspect, the detection means detects a design tolerance of the vehicle as the degree of the factor.

Also, when the invention of claim 4, in the image display system according to claim 2, wherein the display means, the range that is constituted by the said maximum error path and the predicted path in response to the speed of the vehicle is changed In addition, an index indicating a range constituted by the predicted course and the maximum error course both before and after the change is displayed.

According to a fifth aspect of the present invention, there is provided an image processing apparatus mounted on a vehicle, wherein a receiving unit that receives an outside image acquired by an imaging unit that captures the periphery of the vehicle and a steering angle of the vehicle are acquired. An obtaining means; a first deriving means for deriving a predicted course where the vehicle is predicted to travel based on the steering angle; a detecting means for detecting a degree of a factor causing an error in the predicted course; and the factor the road surface friction coefficient regarding the degree of, and, based on the calculation of the speed parameter of the vehicle, a second derivation means for deriving the maximum error path having the largest error relative to the predicted route, and the predicted route the Transmitting means for transmitting to the display device an index indicating a range which is a range constituted by a maximum error path and becomes wider as the distance from the vehicle increases .

The invention of claim 6 is an image display method of an image display system mounted on a vehicle, wherein (a) a step of receiving an image outside the vehicle acquired by an imaging unit that captures the periphery of the vehicle; ) Obtaining a steering angle of the vehicle; (c) deriving a predicted course where the vehicle is predicted to travel based on the steering angle; and (d) a factor causing an error in the predicted course. And (e) a maximum error path having a maximum error with respect to the predicted path based on a calculation process of a road surface friction coefficient relating to the degree of the factor and a parameter of the speed of the vehicle. A step of deriving, and (f) a step of superimposing and displaying on the outside image an index indicating a range which is a range constituted by the predicted course and the maximum error course and becomes wider as the distance from the vehicle increases. And equipped with .
The invention according to claim 7 is an image display system mounted on a vehicle, wherein a receiving unit that receives an outside image acquired by an imaging unit that captures the periphery of the vehicle and a steering angle of the vehicle are acquired. An obtaining means; a first deriving means for deriving a predicted course where the vehicle is predicted to travel based on the steering angle; a detecting means for detecting a degree of a factor causing an error in the predicted course; and the factor A third deriving unit for deriving a range in which the error of the predicted course occurs based on the degree of the display, a display unit for displaying an index indicating the range in which the error of the predicted course occurs in a manner superimposed on the outside image, The detection means detects the speed of the vehicle as the degree of the factor, and the display means changes the range in which the error in the predicted course changes according to the speed of the vehicle before the change. And change Displaying an indication that the range in which an error occurs in the predicted course of both the.
According to an eighth aspect of the present invention, in the image display system according to the seventh aspect, the detection means detects the slipperiness of the road surface on which the vehicle travels as the degree of the factor.

  According to the first to sixth aspects of the present invention, the index indicating the range in which the predicted course error occurs is superimposed and displayed on the outside image so that the position where the vehicle may pass as the vehicle travels is displayed. Can be recognized.

  In particular, according to the invention of claim 2, the detecting means detects the slipperiness of the road surface on which the vehicle travels and the speed of the vehicle as factors, and is derived based on external factors of the vehicle. The user can recognize a position where the vehicle may pass as the vehicle travels.

  In particular, according to the invention of claim 3, the detecting means detects the design tolerance of the vehicle as the degree of the factor, so that the vehicle passes along with the progress of the vehicle derived based on the factor inside the vehicle. Possible positions can be recognized by the user.

  Further, according to the invention of claim 4, when the range in which the predicted path error occurs is changed according to the speed of the vehicle, the display means generates an error in the predicted path both before and after the change. By displaying the index indicating the range, the user can recognize the range in which the error in the predicted course that changes according to the speed of the vehicle occurs.

FIG. 1 is a block diagram of an image display system. FIG. 2 is a diagram illustrating a position where the in-vehicle camera is arranged in the vehicle. FIG. 3 is a diagram for explaining a method of generating a composite image. FIG. 4 is a diagram illustrating an example in which a composite image obtained by overlooking a vehicle image is displayed on the display. FIG. 5 is a diagram illustrating an example in which a composite image obtained by overlooking a vehicle image is displayed on the display. FIG. 6 is a diagram illustrating an index including a predicted course displayed behind the vehicle image. FIG. 7 is a diagram illustrating a predicted course range of an index displayed behind the vehicle image. FIG. 8 is a diagram illustrating an example in which a composite image obtained by overlooking a vehicle image is displayed on the display. FIG. 9 is a diagram illustrating an example in which a composite image obtained by overlooking a vehicle image is displayed on the display. FIG. 10 is a diagram in which an image taken by the back camera is processed by the image generation unit and displayed on the display. FIG. 11 is a process flowchart of the image processing apparatus according to the first embodiment. FIG. 12 is a diagram illustrating an index including a predicted course range displayed behind the vehicle image. FIG. 13 is a process flowchart of the image processing apparatus according to the second embodiment. FIG. 14 is a diagram illustrating an index including a predicted course range displayed behind the vehicle image.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<1. First Embodiment>
<1-1. System configuration>
FIG. 1 is a block diagram of the image display system 120. The image display system 120 is mounted on a vehicle (in this embodiment, an automobile), generates an image by photographing the periphery of the vehicle, and uses the generated image as a navigation device 20 in the vehicle interior. It has a function of outputting to a display device. By using this image display system 120, a user (typically a driver) of the image display system 120 can grasp the state around the vehicle in almost real time.

  As shown in FIG. 1, an image display system 120 includes an image processing device 100 that generates a peripheral image indicating the periphery of a vehicle and outputs image information to a display device such as a navigation device 20, and a camera that captures the periphery of the vehicle. And a photographing unit 5 having the above.

  The navigation device 20 provides navigation guidance to the user, and includes a display 21 such as a liquid crystal provided with a touch panel function, an operation unit 22 that is operated by the user, and a control unit 23 that controls the entire device. Yes. The navigation device 20 is installed on an instrument panel or the like of the vehicle so that the screen of the display 21 is visible from the user. Various instructions from the user are received by the operation unit 22 and the display 21 as a touch panel. The control unit 23 is a computer including a CPU, a RAM, a ROM, and the like, and various functions including a navigation function are realized by the CPU performing arithmetic processing according to a predetermined program.

  The navigation apparatus 20 is communicably connected to the image processing apparatus 100, and can transmit and receive various control signals to and from the image processing apparatus 100 and receive peripheral images generated by the image processing apparatus 100. . An image based on the function of the navigation device 20 alone is normally displayed on the display 21 under the control of the control unit 23, but the periphery showing the state of the periphery of the vehicle generated by the image processing device 100 under a predetermined condition An image and a bird's-eye view of the vehicle 9 and the surrounding area of the vehicle 9 are displayed. Moreover, the bird's-eye view image displayed on the display 21 shows the peripheral area almost in real time. Thereby, the navigation device 20 also functions as a display device that receives and displays a peripheral image generated by the image processing device 100.

  The image processing apparatus 100 is an ECU (Electronic Control Unit) whose main body 10 has a function of generating a peripheral image, and is arranged at a predetermined position of the vehicle. The image processing apparatus 100 includes an imaging unit 5 that captures the periphery of the vehicle. The image generation unit 5 generates a composite image viewed from a virtual viewpoint based on a captured image obtained by capturing the periphery of the vehicle. Functions as a device. The plurality of in-vehicle cameras 51, 52, and 53 provided in these photographing units 5 are arranged at appropriate positions on a vehicle different from the main body unit 10, but will be described in detail later.

  The main body 10 of the image processing apparatus 100 includes a control unit 1 that controls the entire apparatus, an image generation unit 3 that generates a peripheral image for display by processing a captured image acquired by the imaging unit 5, and a navigation device 20. And a navigation communication unit 42 that communicates with each other.

  Various instructions from the user received by the operation unit 22 or the display 21 of the navigation device 20 are received by the navigation communication unit 42 as control signals and input to the control unit 1.

  The image generation unit 3 is configured as a hardware circuit capable of various image processing, and includes an image reception unit 31, an image superimposition unit 33, and an image transmission unit 34 as main functions.

The image receiving unit 31 receives a plurality of captured images acquired by the plurality of in-vehicle cameras 51, 52, and 53 of the imaging unit 5 that captures the periphery of the vehicle 9.
The image composition unit 32 generates a composite image viewed from an arbitrary virtual viewpoint around the vehicle, based on the plurality of captured images acquired by the plurality of in-vehicle cameras 51, 52, and 53 of the photographing unit 5. A method by which the composite image generation unit 32 generates a composite image viewed from a virtual viewpoint will be described later.

  The image superimposing unit 33 performs a process of superimposing the predicted course predicted by the vehicle 9 to travel on the image captured by the imaging unit 5. The predicted course indicates a position through which the vehicle 9 travels and is derived by a predicted course deriving unit 13 of the control unit 1 described later. The images on which the predicted course is superimposed are an image taken by one camera (for example, the back camera 52) of the photographing unit 5, an image synthesized by the image synthesizing unit 32, and the like. Hereinafter, such an image obtained by photographing the periphery of the vehicle 9 with a single camera and a composite image obtained by combining images obtained by photographing the periphery of the vehicle 9 with a plurality of cameras are also referred to as an outside image.

  The image transmission unit 34 outputs the image outside the vehicle generated by the image generation unit 3 to the navigation device 20.

  The control unit 1 is a computer including a CPU, a RAM, a ROM, and the like, and various control functions are realized by the CPU performing arithmetic processing according to a predetermined program. The image control unit 11, the steering angle acquisition unit 12, the predicted course derivation unit 13, and the factor detection unit 14 shown in the drawing show some of the functions of the control unit 1 realized in this way. .

  The image control unit 11 controls image processing executed by the image generation unit 3. For example, the image control unit 11 instructs various parameters necessary for generating a composite image generated by the image combining unit 32.

  The steering angle acquisition unit 12 acquires information on the steering angle of the steering wheel of the vehicle 9 operated by the user from the steering angle sensor 83.

  The predicted course deriving unit 13 derives a predicted course where the vehicle 9 is expected to travel based on the steering angle of the steering wheel acquired by the steering angle acquiring unit 12. More specifically, the turning radius of the vehicle 9 is derived from information on the steering angle of the steering wheel, and a trajectory for which the rear wheels of the vehicle 9 are predicted to travel is calculated based on the turning radius.

  Further, the predicted course deriving unit 13 derives a range in which the predicted course error occurs based on the degree of the factor causing the predicted path error detected by the factor detecting unit 14 described later. That is, when the predicted course of the vehicle 9 derived based on the steering angle of the steering wheel causes an error due to the influence of the traveling environment of the vehicle 9, the predicted path of the vehicle 9 including the error in the calculation of the predicted course is calculated. The predicted course deriving unit 13 derives.

  Here, the traveling environment of the vehicle 9 is, for example, a road surface friction coefficient indicating the slipperiness of the road surface on which the vehicle 9 travels, and the speed of the vehicle 9. The predicted course deriving unit 13 is based on the ideal predicted path that does not take into account the error derived by the predicted course deriving unit 13 based only on the steering angle of the steering wheel, and the degree of factors that cause the steering angle of the steering wheel and the error. The distance from the predicted course in consideration of the maximum error derived from is derived as a range in which the predicted course error occurs. Then, an index indicating a range in which the predicted course error occurs is displayed on the display 21. Note that, regarding the derivation of the range in which the predicted course error occurs, the predicted course derivation unit 13 performs a calculation process using the road surface friction coefficient and the speed of the vehicle 9 as parameters. In addition, range data 4b, which is table data indicating a correspondence relationship for deriving a range in which a predicted course error occurs, is recorded in the nonvolatile memory 40, and the predicted course of the predicted course is determined according to the road surface friction coefficient and the speed of the vehicle 9. The predicted course deriving unit 13 may derive a range in which an error occurs.

  The factor detection unit 14 detects the degree of a factor that causes an error in the predicted course of the vehicle 9. Here, the factor causing the error in the predicted course is the traveling environment of the vehicle 9 as described above. One of the traveling environments is a road surface friction coefficient indicating the slipperiness of the road surface on which the vehicle 9 travels. This road surface friction coefficient is detected by the brake ECU 84. Another driving environment is the speed of the vehicle 9. This speed is detected by the vehicle speed sensor 86. The road surface friction coefficient and the speed are detected by the factor detection unit 14 as the degree of the factor causing an error in the predicted course.

  The main body 10 of the image processing apparatus 100 further includes a nonvolatile memory 40 and a signal input unit 41, which are connected to the control unit 1.

  The nonvolatile memory 40 is configured by a flash memory or the like that can maintain stored contents even when the power is turned off. The nonvolatile memory 40 stores vehicle type data 4a. The vehicle type data 4a is data corresponding to the type of vehicle required when the image composition unit 32 generates a composite image.

  Further, the range data 4b is recorded in the nonvolatile memory 40. The range data 4b is data that is read when the predicted course deriving unit 13 derives a range in which the predicted path error occurs. That is, the table data indicating the correspondence relationship for deriving the range where the predicted course error occurs is recorded in the nonvolatile memory as the range data 4b.

  Moreover, the signal input part 41 inputs the signal from the various apparatuses provided in the vehicle. A signal from the outside of the image display system 120 is input to the control unit 1 via the signal input unit 41. Specifically, signals indicating various information are input to the control unit 1 from the shift sensor 81, the gyro sensor 82, the steering angle sensor 83, the brake ECU 84, the suspension ECU 85, the vehicle speed sensor 86, and the like.

  From the shift sensor 81, the operation position of the shift lever of the transmission of the vehicle 9, ie, “P (parking)”, “D (forward)”, “N (neutral)”, “R (reverse)”, etc. The shift position is input. From the vehicle speed sensor 86, the traveling speed (km / h) of the vehicle 9 at that time is input.

  From the gyro sensor 82, a signal of an inclination change speed (angular speed) of the vehicle 9 is input. The control unit 1 derives a change in the inclination of the vehicle 9 based on an input signal from the gyro sensor 82.

  The steering angle sensor 83 inputs the operation direction of the steering wheel operated by the user to the control unit 1. Specifically, the steering angle sensor 83 inputs the rotation direction, rotation angle, and rotation speed of the steering wheel operated by the user to the control unit 1 via the signal input unit 41. The signal from the steering angle sensor 83 is also input to a control unit that controls the vehicle body. Based on the input signal of the steering angle sensor 83 and the signal input from the vehicle speed sensor 86 to the control unit that controls the vehicle body, the steering angle and the steering speed of the front wheels that steer the vehicle 9 are calculated. The vehicle 9 is controlled based on the value.

  The brake ECU 84 determines the friction of the road surface on which the vehicle 9 travels based on the braking distance derived by multiplying the wheel circumference of the vehicle 9 by the wheel rotation speed and the wheel speed corresponding to the speed of the vehicle 9. Deriving coefficients.

  The suspension ECU 85 detects the degree of unevenness of the road surface on which the vehicle 9 travels. The factor detection unit 14 detects the information on the degree of unevenness of the road surface as one of the factors causing an error in the predicted course.

  The vehicle speed sensor 86 outputs the speed at which the wheel rotates when the vehicle 9 moves to the control unit 1 as a vehicle speed signal.

<1-2. Shooting Department>
Next, the photographing unit 5 of the image processing apparatus 100 will be described in detail. The photographing unit 5 is electrically connected to the control unit 1 and operates based on a signal from the control unit 1.

  The imaging unit 5 includes a front camera 51, a back camera 52, a left side camera 53, and a right side camera 54 that are in-vehicle cameras. Each of these vehicle-mounted cameras 51, 52, 53, and 54 includes an image sensor such as a CCD or a CMOS and electronically acquires an image.

  FIG. 2 is a diagram illustrating positions where the in-vehicle cameras 51, 52, 53, 54 are arranged on the vehicle 9. In the following description, the three-dimensional XYZ orthogonal coordinates shown in the figure are used as appropriate when indicating the direction and direction. The XYZ axes are fixed relative to the vehicle 9. Here, the X-axis direction is along the left-right direction of the vehicle 9, the Y-axis direction is along the straight traveling direction (front-rear direction) of the vehicle 9, and the Z-axis direction is along the vertical direction. For convenience, the + X side is the right side of the vehicle 9, the + Y side is the rear side of the vehicle 9, and the + Z side is the upper side.

  The front camera 51 is provided in the vicinity of the license plate mounting position at the front end of the vehicle 9, and its optical axis 51 a is directed substantially along the straight direction of the vehicle 9 (on the −Y side in the Y-axis direction in plan view). Yes. The back camera 52 is provided in the vicinity of the license plate mounting position at the rear end of the vehicle 9, and its optical axis 52 a is directed in the reverse direction of the vehicle 9 in the straight traveling direction (+ Y side in the Y-axis direction in plan view). Yes. The left side camera 53 is provided on each of the left door mirrors 93, and its optical axis 53a is directed to the outside along the left direction of the vehicle 9 (+ X axis direction in plan view). Further, the right side camera 54 is provided on each of the right door mirrors 94, and its optical axis 54a is directed to the outside along the right direction of the vehicle 9 (the −X axis direction in plan view). Note that the mounting position of the front camera 51 and the back camera 52 is preferably approximately the center in the left and right, but may be slightly shifted in the left and right directions from the center in the left and right.

  As the lenses of these in-vehicle cameras 51, 52, 53, and 54, fish-eye lenses and the like are employed, and the in-vehicle cameras 51, 52, 53, and 54 have an angle of view α of 180 degrees or more. For this reason, by using the four in-vehicle cameras 51, 52, 53, and 54, it is possible to capture the entire periphery of the vehicle 9.

<1-3. Image conversion processing>
Next, a description will be given of a method in which the image composition unit 32 of the image generation unit 3 generates a composite image that shows how the periphery of the vehicle 9 is viewed from an arbitrary virtual viewpoint based on a plurality of photographed images obtained by the photographing unit 5. To do. When generating the composite image, the vehicle type data 4a stored in advance in the nonvolatile memory 40 is used. FIG. 3 is a diagram for explaining a method of generating a composite image.

  When the front camera 51, the back camera 52, the left side camera 53, and the right side camera 54 of the photographing unit 5 are simultaneously photographed, four images respectively indicating the front, rear, left side, and right side of the vehicle 9 are shown. Captured images P1 to P4 are acquired. That is, the four captured images P1 to P4 acquired by the imaging unit 5 include information indicating the entire periphery of the vehicle 9 at the time of shooting.

  Next, each pixel of the four captured images P1 to P4 is projected onto a three-dimensional curved surface SP in a virtual three-dimensional space. The three-dimensional curved surface SP has, for example, a substantially hemispherical shape (a bowl shape), and a center portion (a bottom portion of the bowl) is determined as a position where the vehicle 9 exists. The correspondence between the positions of the pixels included in the captured images P1 to P4 and the positions of the pixels of the solid curved surface SP is determined in advance. For this reason, the value of each pixel of the solid curved surface SP can be determined based on this correspondence and the value of each pixel included in the captured images P1 to P4.

  The correspondence between the positions of the pixels of the captured images P1 to P4 and the positions of the pixels of the three-dimensional curved surface SP is determined by the arrangement of the four in-vehicle cameras 51, 52, and 53 in the vehicle 9 (the distance between each other, the height above the ground, the optical axis). Angle). For this reason, the table data indicating this correspondence is included in the vehicle type data 4 a stored in the nonvolatile memory 40.

  Further, polygon data indicating the shape and size of the vehicle body included in the vehicle type data 4a is used, and a vehicle image that is a polygon model indicating the three-dimensional shape of the vehicle 9 is virtually provided. The configured vehicle image is arranged in a substantially hemispherical central portion determined as the position of the vehicle 9 in the three-dimensional space where the three-dimensional curved surface SP is set.

  Further, the virtual viewpoint VP is set by the control unit 1 for the three-dimensional space where the solid curved surface SP exists. The virtual viewpoint VP is defined by the viewpoint position and the visual field direction, and is set to an arbitrary visual field position corresponding to the periphery of the vehicle 9 in this three-dimensional space toward an arbitrary visual field direction.

  Then, according to the set virtual viewpoint VP, a necessary area on the three-dimensional curved surface SP is cut out as an image. The relationship between the virtual viewpoint VP and a necessary area in the three-dimensional curved surface SP is determined in advance, and is stored in advance in the nonvolatile memory 40 or the like as table data. On the other hand, rendering is performed on the vehicle image composed of polygons according to the set virtual viewpoint VP, and the resulting two-dimensional vehicle image is superimposed on the cut out image. Thereby, the composite image which shows a mode that the vehicle 9 and the periphery of the vehicle 9 were seen from arbitrary virtual viewpoints will be produced | generated.

  For example, when the virtual viewpoint VP1 in which the viewpoint position is a position just above the center of the position of the vehicle 9 and the visual field direction is a direction immediately below the vehicle 9 is set, the vehicle 9 ( Actually, a composite image CP1 showing the vehicle image) and the surroundings of the vehicle 9 is generated. Further, as shown in the figure, when the virtual viewpoint VP2 in which the viewpoint position is the left rear of the position of the vehicle 9 and the visual field direction is substantially in front of the vehicle 9 is set, the entire periphery from the left rear of the vehicle 9 is set. As seen, a composite image CP <b> 2 is generated that shows the vehicle 9 (actually a vehicle image) and the surroundings of the vehicle 9.

  In the case of actually generating a composite image, it is not necessary to determine the values of all the pixels of the three-dimensional curved surface SP, and only the values of the pixels in the area necessary corresponding to the set virtual viewpoint VP are photographed. By determining based on the images P1 to P4, the processing speed can be improved.

<1-4 display image>
In the following, an example is shown in which the predicted course derived by the predicted course deriving unit 13 is displayed superimposed on the outside image. FIG. 4 is a diagram illustrating an example in which composite images CQ1 and CQ2 overlooking the vehicle image 90 are displayed on the display 21. In the composite image CQ1, the vehicle image 90 is located approximately at the center of the composite image, and a space SA41 area exists between the vehicle image 19 and the vehicle image 29, which are images of other vehicles. The vehicle image 90 is an image of the vehicle 9 including the image display system 120. In the following, a state until the user operates the vehicle 9 and moves the vehicle 9 to an area corresponding to the space SA41 will be described using each composite image displayed on the display 21.

  A composite image CQ2 illustrated in FIG. 4 illustrates a state in which the vehicle 9 has advanced (moved in the −Y direction) from a position corresponding to the vehicle image 90 of the composite image CQ1. In addition, when the user of the vehicle 9 sets the position of the shift lever to “R (reverse)”, a shift position signal is input from the shift sensor 81 to the control unit 1. Then, the steering angle acquisition unit 12 acquires the steering angle of the steering wheel based on a signal from the steering angle sensor 83, and an index MA3 that is a predicted course of the vehicle 9 is superimposed and displayed on the composite image CQ2 behind the vehicle image 90. To do. Since the steering angle of the steering wheel is in a substantially neutral position, the predicted course indicated by the index MA3 extends in the direction in which the vehicle 9 goes straight backward (+ Y direction).

  FIG. 5 is a diagram illustrating an example in which composite images CQ3 and CQ4 overlooking the vehicle image 90 are displayed on the display 21. The composite image CQ3 shows a state where the vehicle 9 has moved backward from the position corresponding to the position of the vehicle image 90 shown in the composite image CQ2 of FIG. As the vehicle 9 moves backward, the brake ECU 84 derives a road surface friction coefficient of the road surface on which the vehicle 9 travels. Further, the vehicle speed sensor 86 detects the speed of the vehicle 9. The road surface friction coefficient and the speed of the vehicle 9 thus detected are input to the control unit 1 via the signal input unit 41.

  In the composite image CQ4 shown in FIG. 5, the vehicle 9 is curved in the left direction (−X direction) as the user of the vehicle 9 operates the steering wheel from the neutral state to the left direction (−X direction). An indicator MA4a indicating the predicted course of the vehicle 9 that moves backward is superimposed and displayed. The index MA4a will be described in detail with reference to FIGS.

  FIG. 6 is a diagram illustrating an index MA4a indicating the predicted course of the vehicle 9. In the following description, the direction and direction of the vehicle image 90 are the same as those of the vehicle 9 described with reference to FIG. In the following description, three-dimensional XYZ orthogonal coordinates shown in FIG. 6 are used. The XYZ axes are fixed relative to the vehicle image 90.

  The predicted course deriving unit 13 derives the predicted course based on the steering angle of the steering wheel of the vehicle 9 operated by the user, and an indicator MA4a indicating the predicted course is displayed on the display 21. The predicted course indicated by the index MA4a includes the predicted course ML31a of the rear wheel on the left side (−X direction) of the vehicle image 90 and the predicted course ML32a of the rear wheel on the right side (+ X direction) of the vehicle image 90. Note that the predicted course indicated by the index M4a changes so as to turn leftward (−X direction) based on the user's operation of the steering wheel leftward.

  In addition, the indicator MA4a includes two distance lines D3a and D4 that extend in the left-right direction (± X direction) and that each of the both ends contact with the two predicted courses ML31a and ML32a. The lengths of the distance lines D3a and D4 are substantially the same as the vehicle width W1 of the vehicle image 90. In the figure, a point p5a is an intersection of the left end (−X direction) of the distance line D3a and the predicted course ML31, and a point p6a is an intersection of the right end (+ X direction) of the distance line D3a and the predicted course ML32. Further, the point p7a is an intersection of the left end (−X direction) of the distance line D4 and the predicted course ML31, and a point p8a is an intersection of the right end (+ X direction) of the distance line D4a and the predicted course ML32.

  When the position of the rear bumper BP of the vehicle image 90 is used as a reference, the actual distance from the vehicle 9 to the distance line D3a is, for example, about 1.5 m, and the actual distance from the vehicle 9 to the distance line D4a. Is, for example, about 3.0 m.

  FIG. 7 is a diagram illustrating an index MA4 indicating a range in which an error in the predicted course of the vehicle 9 occurs. The predicted course indicated by the index MA4 includes a course range ML31 indicating the range of the predicted course of the rear wheels on the left side (−X direction) of the vehicle image 90 when the vehicle 9 moves backward, and the right side (+ X direction) of the vehicle image 90. A course range ML32 indicating the range of the predicted course of the rear wheel is included.

  The range in which the error in the predicted path occurs is an ideal predicted path that does not consider the error (hereinafter referred to as “ideal predicted path”) and a predicted path that considers the maximum error (hereinafter referred to as “maximum error path”). It corresponds to the interval. The ideal predicted course is derived based only on the steering angle of the steering wheel. On the other hand, the maximum error path is derived based on the steering angle of the steering wheel and the degree of factors that cause an error in the predicted path. Specifically, first, the ideal predicted courses ML31a and ML32a shown in FIG. Then, the road surface friction coefficient and the speed of the vehicle 9 are detected by the factor detecting unit 14, and the predicted course deriving unit 13 derives the maximum error courses ML31b and ML32b based on the road surface friction coefficient and the speed of the vehicle 9. The interval between the ideal predicted course ML31a derived in this way and the maximum error course ML31b corresponds to a range in which an error in the predicted course of the left rear wheel occurs. Further, the interval between the ideal predicted course ML32a and the maximum error course ML32b corresponds to a range in which an error in the predicted course of the left rear wheel occurs.

  The range in which the predicted course error occurs is examined by the positional relationship of the intersection of the predicted course and the distance line. Regarding the distance line indicating the position where the distance from the vehicle 9 is about 1.5 m, the positions of the intersections with the ideal predicted courses ML31a and ML32a are point p5a and point p6a, respectively. On the other hand, the positions of the intersections of this distance line with the maximum error paths ML31b and ML32b are points p5b and p6b, respectively.

  The distance (W2a) between the points p5a and p5b and the distance (W2a) between the points p6a and p6b indicate the range in which the predicted course error occurs at a distance of about 1.5 m from the vehicle 9. That is, there is a possibility that an error in a range from the ideal predicted course ML31a, ML32a to the maximum error course ML31b, ML32b on the diagonally right rear side may occur in the predicted course of the vehicle 9 due to a factor causing an error in the predicted course. . When the predicted course deriving unit 13 derives a range in which the predicted course error occurs, the distance line indicating the position where the distance from the vehicle 9 is about 1.5 m is the intersection point p5b with the maximum error course ML31b, ML32b, This is indicated by the distance line D3b having p6b at both ends.

  For the distance line indicating the position where the distance from the vehicle 9 is about 3.0 m, the positions of the intersections with the ideal predicted courses ML31a and ML32a are point p7a and point p8a, respectively. On the other hand, the positions of the intersections with the maximum error paths ML31b and ML32b are point p7b and point p8b, respectively.

  The distance (W2b) between the points p7a and p7b and the distance (W2b) between the points p8a and p8b indicate a range in which the predicted course error occurs at a distance of about 3.0 m from the vehicle 9. When the predicted route range is derived by the predicted route deriving unit 13, the distance line indicating the position at a distance of about 3.0 m from the vehicle 9 has the intersections p7b and p8b with the maximum error routes ML31b and ML32b at both ends. Is indicated by a distance line D4.

  Comparing the distance W2a, which is a range in which the predicted course error occurs at a distance of about 1.5 m from the vehicle 9, with the distance W2b, which is a range in which the predicted course error is generated at a distance of about 3.0 m from the vehicle 9, , The interval 2b is larger than the interval 2a. In this way, the range in which the predicted course error occurs increases as the distance from the vehicle 9 increases. The user recognizes a position where the vehicle 9 may pass as the vehicle 9 travels by superimposing the indicator M4 indicating the range in which such an error in the predicted course occurs on the image outside the vehicle and displaying it on the display 21. it can.

  Note that the range in which the predicted course error occurs varies depending on the traveling speed of the vehicle. For example, the sizes of the route ranges ML31 and ML32 illustrated in FIG. 7 change according to the speed of the vehicle 9. Specifically, the interval (W2a) between the points p5a and p5b and the interval (W2a) between the points p6a and p6b change according to changes in the speed of the vehicle 9. Further, the interval (W2b) between the points p7a and p7b and the interval (W2b) between the points p8a and p8b change according to changes in the speed of the vehicle 9.

  Next, returning to the display of the composite image showing the state in which the vehicle 9 is moved to the area corresponding to the space SA41, the description will be given. FIG. 8 is a diagram showing composite images CQ5 and CQ6 displayed on the display 21. As shown in FIG. Assume that the user returns the position of the steering wheel to the neutral position as the vehicle 9 moves backward after displaying the index MA4 indicating the range in which the predicted course error occurs as in the composite image CQ4 shown in FIG. In this case, the steering angle acquisition unit 12 acquires a signal from the steering angle sensor 83, and an index MA3 indicating a predicted course in which the vehicle 9 goes straight backward is superimposed and displayed on the composite image CQ5 as shown in FIG.

  The composite image CQ6 shows a state in which the vehicle 9 has moved straight back to the vicinity of the space SA41 between the other vehicle images 19 and 29 and moved backward as compared with the composite image CQ5.

  FIG. 9 is a diagram showing composite images CQ7 and CQ8 displayed on the display 21. As shown in FIG. Similar to the composite image CQ4 of FIG. 5, an index MA4b indicating a range in which a predicted course error occurs is superimposed on the composite image CQ7. Here, the main difference between the composite image CQ7 of FIG. 9 and the composite image CQ4 of FIG. 5 is the direction of the steering wheel operated by the user. In the composite image CQ7 of FIG. 9, an index MA4b indicating a predicted course that curves backward in the right direction in accordance with the user of the vehicle 9 operating the steering wheel from the neutral state to the right (+ X direction) is superimposed. Has been. Note that the range in which the predicted course error indicated by the index MA4b occurs is derived by the predicted course deriving unit 13 based on the road surface friction coefficient and the speed of the vehicle 9, similarly to the composite image CQ4 of FIG.

  In the composite image CQ <b> 8 shown in FIG. 9, the vehicle image 90 is included in the space 41 as the vehicle 9 is positioned in the area corresponding to the space 41. Thus, the user can smoothly move the vehicle 9 to the target position.

  In addition, the predicted course shown in the overhead view image as described above is displayed by superimposing the image displayed on the display 21 by being operated by the operation unit 22 of the user and superimposed on the outside image photographed by the rear one camera. The following is an example.

 FIG. 10 is a diagram in which an image captured by the back camera 52 is processed by the image generation unit 3 and displayed on the display 21. FIG. 10 shows a course range ML31 indicating a range in which an error in the predicted course of the left rear wheel of the vehicle 9 is generated, a path range ML32 indicating a range in which an error in the predicted path of the right rear wheel of the vehicle 9 is generated, and 2 An index MA4 indicating two distance lines D3b and D4 is displayed. When the user visually recognizes such an image, the user can recognize a position where the vehicle 9 may pass as the vehicle 9 travels.

<1-5. Processing flowchart>
FIG. 11 is a process flowchart of the image processing apparatus 100 according to the first embodiment. The image processing apparatus 100 acquires a camera image of the photographing unit 5 of the vehicle 9 (step S101), receives steering angle information from the steering angle sensor 83 via the signal input unit 41 (step S102), and step The process proceeds to S103.

  In step S103, the predicted course deriving unit 13 derives the predicted course of the vehicle 9 based on the information received from the steering angle sensor 83 (step S103), and the process proceeds to step S104.

  In step S104, the brake ECU 84 derives road surface information (for example, road surface friction coefficient) as the vehicle 9 travels (step S104), and the process proceeds to step S105.

  In step S105, the image processing apparatus 100 receives the speed information signal of the vehicle 9 from the vehicle speed sensor 86, and the process proceeds to step S106.

  In step S106, the factor detection unit 14 detects the road surface information derived by the brake ECU 84 and the speed information of the vehicle 9 derived by the vehicle speed sensor 86 as a degree of a factor causing an error in the predicted course, and the process of step S107 is performed. Proceed to

  In step S107, the predicted course deriving unit 13 derives a range in which the predicted path error occurs based on the degree of the factor that causes an error in the predicted path detected by the factor detecting unit 14 (step S107). Proceed to processing.

  In step S108, an index indicating the range where the predicted course error occurs is superimposed on the outside image, and the outside image superimposed with the index indicating the range where the error occurs is output to the navigation apparatus 20 via the navigation communication unit 42. (Step S108). Thereby, an index indicating a range in which an error occurs is displayed on the display 21, and the user can recognize a position where the vehicle 9 may pass as the vehicle 9 travels.

<Second Embodiment>
Next, a second embodiment will be described. The configuration and processing of the image display system in the second embodiment are substantially the same as those in the first embodiment, but are partially different. Therefore, the differences from the first embodiment will be described below. The explanation is centered. In the second embodiment, the factor detection unit 14 detects the degree of design tolerance such as a dimensional difference allowed in the design of the vehicle 9 as the degree of a factor causing an error in the predicted course.

  The degree of design tolerance is recorded in advance in the vehicle type data 4a of the nonvolatile memory 40 before the product of the vehicle 9 is shipped, and when the factor causing an error in the predicted course of the vehicle 9 is detected, The factor detection part 14 reads. Then, based on the degree of design tolerance, the predicted course deriving unit 13 derives a range in which the predicted path error occurs.

<2-1. Display image>
FIG. 12 is a diagram illustrating an index MA14 that indicates a range in which an error in the predicted course occurs. The index MA14 in FIG. 12 includes course ranges ML311 and ML312. These course ranges ML311 and ML312 are ranges in which the predicted course deriving unit 13 causes an error in the predicted course in consideration of the design tolerance as well as the road surface friction coefficient and the speed of the vehicle 9 as the degree of the factor causing the predicted course. Is derived.

  Therefore, the interval (W12a) between the points p5a and p15b and the interval (W12a) between the points p6a and p16b shown in FIG. 12 are larger than the interval W2a shown in FIG. The point p15b shown in the figure is about 1. from the maximum error path ML301b of the rear wheel on the left side of the vehicle image 9 derived from the road surface friction coefficient, the speed of the vehicle 9, and the design tolerance. This is an intersection with a distance line D3a indicating a position of 5 m. The point p16b is a position where the maximum error path ML302b of the rear wheel on the right side of the vehicle 9 derived based on the road surface friction coefficient, the speed of the vehicle 9, and the design tolerance is about 1.5 m from the vehicle 9. Is an intersection with a distance line D3a.

  Further, the interval (W12b) between the points p7a and p17b and the interval (W12b) between the points p8a and p18b shown in FIG. 12 are larger than the interval W12a shown in FIG. The point p17b shown in the figure is a distance between the vehicle 9 and the maximum error path ML301b of the left rear wheel of the vehicle 9 derived based on the road surface friction coefficient, the speed of the vehicle 9, and the design tolerance. This is the intersection with the distance line D4 indicating the position of 0 m. The point p18b is a position where the maximum error path ML302b of the rear wheel on the right side of the vehicle 9 derived based on the road surface friction coefficient, the speed of the vehicle 9, and the design tolerance, and a distance from the vehicle 9 of about 3.0 m. Is the intersection with the distance line D4. As described above, based on the internal factors of the vehicle, the user can recognize the position where the vehicle 9 may pass as the derived vehicle 9 travels.

<2-2. Processing flowchart>
FIG. 13 is a process flowchart of the image processing apparatus 100 according to the second embodiment. The difference between the process flowchart of the second embodiment shown in FIG. 13 and the process flowchart of FIG. 11 of the first embodiment is that a process for reading design tolerance information in step S201 is newly added. is there. And the process of step S107 of FIG. 11 is changed into the process of step S107a shown in FIG.

  In the process of step S107a, when the predicted course deriving unit 13 derives the range in which the predicted course error occurs, the design intersection is performed in addition to the road surface friction coefficient and the speed of the vehicle 9 described in the first embodiment. A new error factor. Other processes are the same as the process flowchart shown in FIG.

  In step S102 shown in FIG. 13, the steering angle information from the steering angle sensor 83 is received via the signal input unit 41 (step S102), and the process proceeds to step S201.

In step S201, the factor detection unit 14 reads design tolerance information of the vehicle 9 recorded in the vehicle type data 4a of the nonvolatile memory 40 (step S201), and proceeds to the process of step S103. Then, in the process of step S107a of the subsequent process, when the predicted course deriving unit 13 derives the predicted course, an error in the predicted course occurs using the design tolerance information as a degree of a factor that causes an error in the predicted course. Deriving a range.
<Third Embodiment>
Next, a third embodiment will be described. The configuration and processing of the image display system in the third embodiment are substantially the same as those in the first embodiment, but are partially different. Therefore, the differences from the first embodiment will be described below. The explanation is centered. If the speed of the vehicle 9 changes after the predicted course deriving unit 13 derives the range in which the predicted path error occurs, the range in which the predicted path error occurs changes. In the third embodiment, when the range in which the predicted course error occurs changes in this way, an index indicating the range in which the predicted course error before and after the change occurs is displayed.

<3-1. Display image>
FIG. 14 is a diagram illustrating an index MA24 indicating a range in which an error in the predicted course occurs. FIG. 14 shows a range in which two types of predicted course errors occur as the speed of the vehicle 9 changes. One of the two types is the same route range ML31, ML32 as in FIG. The other of the two types is the route ranges ML301 and ML302 (ranges indicated by hatching in FIG. 14) that have changed as the speed of the vehicle 9 changes after these route ranges ML31 and ML32 are derived. ). When the range in which these two types of predicted course errors occur is displayed on the display 21, the course range ML301 derived later is superimposed on the course range ML31 derived earlier. Further, the route range ML302 derived later is superimposed on the route range ML32 derived earlier.

  As described above, when the range in which the predicted course error occurs is changed in accordance with the speed of the vehicle 9, the range in which the predicted course error before the change occurs (the course range ML31, ML32) and the predicted course error after the change occur. By displaying the index MA24 indicating both the ranges (the course ranges ML301 and ML302), the user can recognize the range in which the predicted course error that changes according to the speed of the vehicle 9 occurs.

  The route range derived later may be darker in color than the previously derived route range. Further, the line thickness of the maximum error paths ML31c and ML32c derived after the speed change of the vehicle 9 is displayed thicker than the maximum error paths ML31b and ML32b derived before the speed change of the vehicle 9. May be. Thereby, the user can recognize the predicted course corresponding to the speed of the vehicle 9.

  In the case shown in FIG. 14, the course ranges ML301 and ML302 derived after the change in the speed of the vehicle 9 are narrower than the course ranges ML31 and ML32 derived before the change in the speed of the vehicle 9, respectively. Yes. This indicates that the speed of the vehicle 9 has decreased assuming that the road surface friction coefficient is constant. On the contrary, when the speed of the vehicle 9 increases, the course ranges ML301 and ML302 derived after the speed change are wider than the course ranges ML31 and ML32 derived before the speed change.

<Modification>
Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various modifications are possible. Below, such a modification is demonstrated. In addition, all the forms including the form demonstrated in the said embodiment and the form demonstrated below are combinable suitably.

  In the above-described embodiment, the degree of slippage of the road surface and the speed of the vehicle 9 are shown as the degree of the factor causing the error in the predicted course. However, the vehicle 9 detected by the gyro sensor 82 is also available. Based on the degree of the inclination, the predicted course deriving unit 13 may derive a range in which the predicted path error occurs. For example, when the vehicle 9 travels on a slope with a slope, it is possible to accurately derive a range in which an error in the predicted course is caused by considering the degree of the slope of the vehicle 9.

  In the above embodiment, when the vehicle 9 moves backward and moves the vehicle 9 to a target space, an index indicating a predicted course is superimposed on the vehicle exterior image and displayed behind the vehicle 9. As described above, in addition to this, when the vehicle 9 moves forward and moves the vehicle 9 to a target space, an index indicating the predicted course is superimposed on the outside image and displayed in front of the vehicle 9. Also good.

  Moreover, in the said embodiment, when the vehicle 9 moved backwards curvilinearly, it demonstrated using a design intersection as a grade of the factor which produces an error in a prediction course. On the other hand, even when the steering wheel of the vehicle 9 is operated to the neutral position (when the vehicle 9 recedes linearly), a range that causes an error in the predicted course by using the design tolerance as a factor. It can be derived with high accuracy. In this case, first, the image processing apparatus 100 receives a camera image from the photographing unit 5. Next, the steering angle acquisition unit 12 acquires that the steering angle of the steering wheel operated by the user is the neutral position. Therefore, the steering angle is not taken into consideration, and the predicted course deriving unit 13 derives a range in which an error occurs in the predicted course based on the speed of the vehicle 9 and the design tolerance. Then, an index indicating this range is superimposed on the outside image and displayed on the display 21.

  In the above embodiment, the factors detected by the factor detector 17 are the road surface friction coefficient detected by the brake ECU 84 and the speed of the vehicle 9 detected by the vehicle speed sensor 86. Then, based on the road surface friction coefficient and the speed of the vehicle 9, it has been described that the predicted route deriving unit 13 derives a predicted route range in which an error occurs. In addition, the factor detection unit 17 detects the degree of unevenness of the road surface on which the vehicle 9 travels detected by the suspension ECU 85, and the predicted route deriving unit 13 derives the range of the predicted route of the vehicle 9 based on the degree of unevenness of the road surface. You may make it do.

  In the above embodiment, the speed of the vehicle 9 is detected based on the signal from the vehicle speed sensor 86, but may be detected based on the vehicle speed signal from the brake ECU 84.

  In the above embodiment, the image processing apparatus 100 and the navigation apparatus 20 are described as separate apparatuses. However, the image processing apparatus 100 and the navigation apparatus 20 are arranged in the same casing and are integrated. It may be configured as.

  In the above embodiment, the display device that displays the image generated by the image processing device 100 is described as the navigation device 20, but a general display device that does not have a special function such as a navigation function. It may be.

  In the above embodiment, some of the functions described as being realized by the control unit 1 of the image processing apparatus 100 may be realized by the control unit 23 of the navigation apparatus 20.

  In the above embodiment, part or all of the signals described as being input to the control unit 1 of the image processing apparatus 100 via the signal input unit 41 are input to the navigation apparatus 20. Also good. In this case, the signal may be input to the control unit 1 of the image processing apparatus 100 via the navigation communication unit 42.

  Further, in the above-described embodiment, it has been described that various functions are realized in software by the arithmetic processing of the CPU according to the program. However, some of these functions are realized by an electrical hardware circuit. Also good. Conversely, some of the functions realized by the hardware circuit may be realized by software.

DESCRIPTION OF SYMBOLS 1 ... Control part 5 ... Image pick-up part 10 ... Main part 11 ... Image control part 12 ... Steering angle acquisition part 13 ... Predicted course derivation part 14 .... Factor detection unit

Claims (8)

An image display system mounted on a vehicle,
Receiving means for receiving an image outside the vehicle acquired by an imaging unit that images the periphery of the vehicle;
Obtaining means for obtaining a steering angle of the vehicle;
First deriving means for deriving a predicted course where the vehicle is predicted to travel based on the steering angle;
Detecting means for detecting a degree of a factor causing an error in the predicted course;
Second derivation means for deriving a maximum error path having a maximum error with respect to the predicted path based on a calculation process of a road surface friction coefficient related to the degree of the factor and a parameter of the vehicle speed ;
A display means for superimposing and displaying on the image outside the vehicle an index indicating a range which is a range constituted by the predicted course and the maximum error course, and becomes wider as the distance from the vehicle increases ;
Providing
An image display system characterized by the above. The image display system according to claim 1,
The detecting means detects the slipperiness of the road surface on which the vehicle travels and the speed of the vehicle as the degree of the factor;
An image display system characterized by the above. The image display system according to claim 1 or 2,
The detection means detects the design tolerance of the vehicle as the degree of the factor;
An image display system characterized by the above. The image display system according to claim 2,
The display means, when the range that is constituted by the said maximum error path and the predicted path in response to the speed of the vehicle is changed, and the predicted path of both the pre-change and after the change and the maximum error path Display an indicator of the range that consists of
An image display system characterized by the above. An image processing apparatus mounted on a vehicle,
Receiving means for receiving an image outside the vehicle acquired by an imaging unit that images the periphery of the vehicle;
Obtaining means for obtaining a steering angle of the vehicle;
First deriving means for deriving a predicted course where the vehicle is predicted to travel based on the steering angle;
Detecting means for detecting a degree of a factor causing an error in the predicted course;
Second derivation means for deriving a maximum error path having a maximum error with respect to the predicted path based on a calculation process of a road surface friction coefficient related to the degree of the factor and a parameter of the vehicle speed ;
Transmitting means for transmitting to the display device an index indicating a range that is configured by the predicted course and the maximum error course and becomes wider as the distance from the vehicle increases .
Providing
An image processing apparatus. An image display method for an image display system mounted on a vehicle,
(A) receiving an image outside the vehicle acquired by an imaging unit that captures the periphery of the vehicle;
(B) obtaining a steering angle of the vehicle;
(C) deriving a predicted course where the vehicle is predicted to travel based on the steering angle;
(D) detecting a degree of a factor causing an error in the predicted course;
(E) deriving a maximum error path having a maximum error with respect to the predicted path based on a calculation process of a road surface friction coefficient regarding the degree of the factor and a parameter of the vehicle speed ;
(F) a step of superimposing and displaying an index indicating a range which is a range constituted by the predicted course and the maximum error course and becomes wider as the distance from the vehicle is increased ;
Providing
An image display method characterized by the above. An image display system mounted on a vehicle,
Receiving means for receiving an image outside the vehicle acquired by an imaging unit that images the periphery of the vehicle;
Obtaining means for obtaining a steering angle of the vehicle;
First deriving means for deriving a predicted course where the vehicle is predicted to travel based on the steering angle;
Detecting means for detecting a degree of a factor causing an error in the predicted course;
Third deriving means for deriving a range in which the error of the predicted course occurs based on the degree of the factor;
Display means for superimposing and displaying an index indicating a range in which the error of the predicted course occurs on the outside image;
With
The detection means detects the speed of the vehicle as the degree of the factor,
The display means displays an index indicating a range in which the error in the predicted path before and after the change occurs when the range in which the error in the predicted path changes according to the speed of the vehicle. To do,
An image display system characterized by the above. The image display system according to claim 7,
The detecting means detects the slipperiness of a road surface on which the vehicle travels as the degree of the factor;
An image display system characterized by the above.

Images