JP4020071B2 - Ambient condition display device - Google Patents

Description

  The present invention relates to an ambient condition display device that displays the status of an obstacle existing around a vehicle.

  2. Description of the Related Art Conventionally, an apparatus that detects an obstacle such as another vehicle around the host vehicle, displays distance information to the obstacle, and alerts the driver is known (for example, Patent Document 1). In such an apparatus, there is an apparatus that captures an image with one camera and obtains a distance to the object from the relationship between the position of the object on the image and the imaging range of the camera.

  However, the height and angle of the camera relative to the road surface vary depending on the pitching behavior of the host vehicle. As a result, the imaging range of the camera varies, and as a result, the accuracy of the calculated distance is reduced. In order to solve this problem, in the apparatus disclosed in Patent Document 2, coordinate values on the image are obtained for a plurality of end points of a central broken line on the road surface whose distance is known, and each coordinate value and the focal length of the camera are used to calculate each coordinate value. The camera height and visual axis direction at the time are calculated. Thereby, the fluctuation | variation of the imaging range of the camera by the pitching behavior of the own vehicle is correct | amended, and the distance calculation precision to a target object is improved.

JP-A-11-283198 JP-A-7-120258

  In the apparatus disclosed in Patent Document 2, the distance calculation accuracy to the object is improved using the interval between the central broken lines on the road surface. However, the central broken line is drawn in a part of roads such as an automobile road and a highway, and there are actually many roads without the central broken line. In such a case, the distance calculation accuracy decreases.

  Furthermore, as the distance from the host vehicle to the object increases, the ratio of the position change amount on the image to the distance change amount decreases. For this reason, the apparatus disclosed in Patent Document 2 has a problem that the resolution of distance calculation decreases as the distance increases.

Surroundings display device according to the present invention includes an imaging means for obtaining captured image of surroundings of the vehicle, detected by the obstacle detection of other vehicles around the vehicle based on the captured image acquired by the imaging means as an obstacle Means, an azimuth angle calculating means for obtaining a lateral lateral azimuth angle of the other vehicle with respect to the own vehicle based on the captured image, estimating a traveling locus of the other vehicle, and extending in the direction of the estimated traveling locus and the spatial lateral azimuth angle. Based on the position calculation means for calculating the positional relationship between the own vehicle and the other vehicle by obtaining the intersection with the existing direction line as the position of the other vehicle with respect to the own vehicle, and the positional relationship calculated by the position calculation means Display means for displaying the surroundings of the host vehicle.

According to the present invention, based on the captured image of the vehicle surroundings obtained using the imaging means to detect other vehicles of the vehicle around the obstacle, and based on the captured image, the space of the other vehicle with respect to the vehicle Obtain the lateral azimuth. Then, by estimating the travel trajectory of the other vehicle, and obtaining the intersection of the estimated travel trajectory and the direction line extending in the direction of the obtained spatial lateral azimuth as the position of the other vehicle with respect to the own vehicle The positional relationship between the host vehicle and the other vehicle is calculated . As a result, when calculating the distance from the host vehicle to the other vehicle, it is possible to calculate the distance with high accuracy even on roads without the central broken line, and further maintain the distance calculation resolution even when the distance is long. can do.

  FIG. 1 shows the configuration of an ambient condition display device according to an embodiment of the present invention. This ambient condition display device (hereinafter referred to as this device) is mounted on a vehicle, detects other vehicles existing behind the host vehicle, and displays the positional relationship between the host vehicle and the other vehicle on a bird's eye view map. To do. The apparatus includes a camera 1, a vehicle sensor 2, an input image memory 3, a microcomputer 4, and a monitor 5.

  The camera 1 is installed at the rear of the host vehicle so as to capture the rear of the host vehicle, is used as a monocular camera, and outputs the captured image to the image memory 3 as an image signal. For example, a CCD camera or the like is used as the camera 1. The vehicle sensor 2 is a sensor for detecting the wheel speed pulses of the left and right wheels output from the host vehicle and the operation state of the winker lever, and outputs a signal based on the detection result to the microcomputer 4. Thereby, the behavior of the own vehicle is calculated | required in the microcomputer 4. FIG. The image memory 3 is a frame memory for storing and holding the image signal input from the camera 1 as image data. The image data stored in the image memory 3 is output to the microcomputer 4 in units of image frames under the control of the microcomputer 4.

  The microcomputer 4 inputs image data from the image memory 3, and extracts other vehicles located behind the host vehicle as an obstacle from the image using pattern matching. As is well known, this pattern matching is an image processing method in which features of an object are set in advance according to brightness, shape, etc. in an image and a portion matching the features is extracted. And the coordinate position on the image of the extracted other vehicle is calculated | required, and the space lateral azimuth | direction angle (shift angle of the position of the other vehicle with respect to the visual axis of the camera 1) is calculated by it. In this way, the other vehicle existing behind the host vehicle is detected.

  The microcomputer 4 also obtains the behavior of the host vehicle from the detection result of the vehicle sensor 2 as described above. At this time, based on the number of wheel speed pulses of the left and right wheels, the amount of movement of the host vehicle for each predetermined time is calculated by dead reckoning. The amount of change in the traveling direction at that time can be obtained by calculating the amount of inclination of the axle from the difference in the number of left and right wheel speed pulses. Thus, the travel locus of the host vehicle is obtained by sequentially adding the movement amount calculated every predetermined time to the first host vehicle position. Further, based on the operation state of the winker lever detected by the vehicle sensor 2, it is determined whether or not the lane of the host vehicle has been changed. When the driver operates the blinker lever to blink either the left or right blinker, it can be determined that the host vehicle has changed the lane from the original lane to the lane in the blinking direction of the blinker. Thus, the behavior of the own vehicle can be obtained by obtaining the travel locus and the lane change operation of the own vehicle.

  When the behavior of the host vehicle is obtained as described above, the microcomputer 4 further estimates the travel lane based on the behavior. The travel lane estimated here corresponds to an estimated trajectory when the vehicle travels on a road lane drawn with a predetermined width on the road, and this includes a road lane in which the host vehicle is traveling. A travel lane and a travel lane in a road lane adjacent to the travel lane are included. Based on the estimation result of the travel lane and the spatial lateral azimuth angle calculated as described above, the position of the other vehicle in the real space can be calculated. A specific calculation method will be described later.

  The monitor 5 displays the positional relationship between the host vehicle and the other vehicle on a bird's eye view map viewed from above the host vehicle based on the position of the other vehicle in the real space calculated by the microcomputer 4. The bird's-eye view map simulates a video from a viewpoint from the sky centered on the host vehicle, and is a form that displays an image of the situation around the host vehicle. By superimposing a marker or the like indicating the position of another vehicle on this bird's eye view map and displaying an image on the monitor 5 provided in the passenger compartment, it is possible to easily notify the driver of the positional relationship between the host vehicle and the other vehicle. .

  Next, a method for estimating the traveling lane based on the behavior of the host vehicle in the microcomputer 4 of FIG. 1 will be described with reference to FIG. A point 20-31 in FIG. 2 indicates a position in the real space of the host vehicle 100 obtained every predetermined time by the number of wheel speed pulses of the left and right wheels. This point 20-31 represents a traveling locus of the host vehicle 100 at predetermined time intervals, and by connecting these points, an estimated traveling lane in the traveling lane of the host vehicle indicated by reference numeral 101 is obtained. The estimated travel lane 101 is a line connecting points 20-31 in time series in consideration of variations such as detection errors.

  Further, a parallel line that is separated from the estimated travel lane 101 by a predetermined interval is obtained, and this is used as the estimated travel lane 102 in the adjacent road lane. The predetermined interval at this time can be set in advance according to the road lane width. Furthermore, by using a method such as collating with map data of the navigation device, the lane width of the road on which the host vehicle 100 is traveling is determined, and the estimated traveling lane 102 is obtained according to the lane width according to the determination result. The predetermined interval may be changed.

  As described above, an estimated traveling lane adjacent to the estimated traveling lane of the own vehicle can be obtained based on the traveling locus of the own vehicle obtained from the measurement result of the number of wheel speed pulses. Furthermore, when it is determined from the operating state of the blinker lever that the lane change operation of the host vehicle has been performed, the estimated travel lane adjacent to the estimated travel lane of the host vehicle is switched. By doing in this way, a driving lane can be estimated based on the behavior of the own vehicle.

  2 shows only one estimated travel lane 102 adjacent to the right side in the traveling direction of the host vehicle 100 (left direction in the figure), the estimated travel lane required in the present invention is shown in FIG. The content is not limited. With respect to the estimated travel lane corresponding to the lane in which the host vehicle is traveling, any number of estimated travel lanes adjacent to either the left or right or both sides can be obtained. At this time, the number of lanes of the road on which the host vehicle is traveling is determined by using a method such as collating with the map data of the navigation device, and the estimated number of lanes to be calculated according to the number of lanes is determined according to the determination result. It may be changed.

  Next, a method for calculating the lateral lateral azimuth angle in real space, that is, the deviation angle of the other vehicle position with respect to the visual axis of the camera 1 from the coordinate position on the image of the other vehicle in the microcomputer 4 will be described with reference to FIG. To do. FIG. 3A shows an object (others, etc.) at a position separated from the visual axis of the camera 1 by an angle θx in the horizontal direction using the camera 1 having a focal length f and an image sensor size (horizontal size) C. The vehicle) 200 is imaged. The viewing angle θ of the camera 1 at this time is known, and its value is determined by the focal length f and the image sensor size C.

FIG. 3B is a diagram illustrating an example of an image captured in the state of FIG. If the number of pixels in the horizontal direction of the image 40 is P and the object 200 is imaged at a position separated from the horizontal position 41 of the visual axis of the camera 1 by the number of pixels Px, the angle θx in the figure is (1). This angle θx is a spatial lateral azimuth angle in the real space of the other vehicle described above.
θx = (Px / P) · θ (1)

  Here, the horizontal position 41 of the visual axis of the camera 1 in FIG. 3B is fixed on the image 40 and is generally located at the center of the image 40. Therefore, the number of pixels Px in the above equation (1) can be obtained by extracting the other vehicle 200 that is the object from the image captured by the camera 1 using pattern matching. From this number of pixels Px, the known viewing angle θ, and the number of pixels P in the horizontal direction of the image 40, the spatial lateral azimuth angle θx can be calculated using Equation (1). In this manner, the spatial lateral azimuth angle in the real space of the other vehicle can be calculated from the coordinate position on the image.

  A method for calculating the position in the real space of the other vehicle existing behind the host vehicle in the microcomputer 4 of FIG. 1 based on the estimation result of the travel lane and the calculation result of the lateral lateral azimuth angle of the other vehicle described above. Will be described. In FIG. 4, estimated traveling lanes 101 and 102 are the traveling lanes described in FIG. 2, and an angle θx with respect to the visual axis direction (direction indicated by reference numeral 50) of the camera 1 mounted on the host vehicle 100 is illustrated in FIG. The spatial lateral azimuth angle.

  The position of the other vehicle 200 in the real space (position with reference to the host vehicle 100) is obtained as the intersection of the estimated traveling lane 102 and the direction indicated by reference numeral 60 that is separated from the visual axis direction 50 by the spatial lateral azimuth angle θx. be able to. Here, it is assumed that the other vehicle 200 is traveling on a road lane corresponding to the estimated travel lane 102. In this calculation method, it is necessary to specify in advance which travel lane the road lane in which another vehicle is traveling corresponds to, which will be described later.

  Based on the position of the other vehicle in the real space obtained as described above, the present apparatus displays the monitor 5 with a marker or the like indicating the position of the other vehicle superimposed on the bird's eye view map. And the driver is notified of the positional relationship with other vehicles existing behind the vehicle. In this way, the surrounding situation of the host vehicle is displayed.

  By calculating the position of the other vehicle as described above, the distance to the other vehicle can be accurately obtained based on the image captured by the monocular camera. The reason will be described next. In an image captured by a monocular camera, when another vehicle to be detected moves in the front-rear direction (perspective direction with respect to the host vehicle) in real space, the position on the image changes in the vertical direction. Further, when moving in the left-right direction in the real space, the position on the image changes in the horizontal direction. Here, the ratio of the amount of change in position on the image to the amount of movement in real space is generally greater in the latter than in the former, and the difference increases as the distance increases.

  For example, when an image of another vehicle about 100 m away is captured by a camera with 640 × 480 pixels and a viewing angle of 30 °, how much the positional change amount is equal to the pixel pitch in the vertical and horizontal directions of the image in real space. Compare the amount of movement. Then, in the vertical direction of the image, the pixel pitch corresponds to a movement amount of about 10 m in the real space, whereas in the horizontal direction, it corresponds to a movement amount of about 10 cm in the real space. That is, when the movement amount in the real space is measured using a monocular camera, the movement amount in the left-right direction can be measured with higher accuracy than in the front-rear direction.

  The distance from the host vehicle to the other vehicle in the real space can be obtained as the amount of movement in the front-rear direction. Conventionally, when calculating the distance to another vehicle using a captured image of a monocular camera, the amount of movement in the front-rear direction has been used. However, in this apparatus, as described above, the spatial lateral azimuth angle is calculated based on the amount of lateral movement from the visual axis position of the camera, and the distance to the other vehicle is calculated using the calculated spatial lateral azimuth angle. Therefore, it is possible to calculate the distance with higher accuracy than the conventional method, and it is possible to maintain the distance calculation resolution even when the distance is long.

  FIG. 5 is a diagram illustrating an example of a calculation result of the distance from the own vehicle to the other vehicle calculated from the captured image of the monocular camera when the other vehicle approaches the own vehicle at equal intervals. The horizontal axis represents elapsed time, and the vertical axis represents the distance calculation result. FIG. 5A shows an example of a calculation result based on the amount of movement in the front-rear direction as in the prior art, and FIG. 5B shows an example of a calculation result based on the amount of movement in the left-right direction as in the present apparatus. Show. Comparing FIG. 5 (a) and FIG. 5 (b), there is less vertical fluctuation in the calculation result in FIG. 5 (b), and the other vehicle is approaching the own vehicle at equal intervals. It can be seen that the error is smaller in the calculation result. Thus, it can be seen from the actual calculation result that the present apparatus can calculate the distance to the other vehicle with high accuracy.

  Next, a description will be given of a method of identifying which travel lane estimated by the road lane on which the other vehicle is traveling when calculating the distance to the other vehicle. As described above, in order to calculate the distance to another vehicle, it is necessary to associate the road lane in which the other vehicle is actually traveling with one of the travel lanes estimated from the behavior of the host vehicle. . Therefore, the distance to the other vehicle is roughly calculated based on the amount of movement in the front-rear direction in the captured image. This rough distance may have low accuracy as described above.

  The rough position of the other vehicle is calculated based on the rough distance to the other vehicle thus calculated and the spatial lateral azimuth described in FIG. Then, the travel lane passing through the closest position is specified as the travel lane corresponding to the road lane in which the other vehicle is traveling. In this way, since the positions through which each lane passes are discrete, the rough distance to the other vehicle calculated with low accuracy is used, and the road on which the other vehicle is traveling corresponds. Lanes can be specified. Based on the travel lane thus identified, it is possible to calculate the distance with high accuracy. In addition, when calculating the rough distance to other vehicles, the accuracy can also be improved by performing a statistical process with respect to the distance value calculated for every predetermined time. In this way, the distance to the other vehicle can be calculated with higher accuracy.

  A flowchart of the processing described above is shown in FIG. The processing flow of FIG. 6 is executed by the microcomputer 4 at predetermined time intervals, for example, every imaging frame interval in the camera 1. In step S100, the image data recorded in the image memory 3 is read. In this image data, luminance information of an image captured by the camera 1 is represented. That is, an image captured by the camera 1 is taken into the microcomputer 4 in step S100.

  In step S101, the part which shows the characteristic of other vehicles is extracted from the image read by step S100 using pattern matching. In step S102, if there is a portion extracted in step S101, it is detected as another vehicle existing behind the host vehicle. More specifically, in step S101, the degree of approximation with the image pattern for pattern matching is calculated for each region extracted from the read image. In step S102, the calculated degree of approximation is a predetermined value. An area exceeding the threshold is detected as another vehicle. In this way, by performing pattern matching in steps S101 and S102, the other vehicle behind the host vehicle is detected based on the captured image of the camera 1.

  In step S103, the wheel speed pulse signal is read from the vehicle sensor 2, and the number of pulses is counted. At this time, the number of pulses is counted for each of the left and right wheels. In step S104, the operating state of the blinker lever is determined based on the output signal from the vehicle sensor 2, and it is determined whether or not the lane change has been performed in the host vehicle. When the winker lever is not operated, it is determined that the lane change is not performed, and the process proceeds to step S105. On the other hand, if it is being operated, it is determined that the lane is being changed, and the process proceeds to step S108.

  In step S105, the travel locus of the host vehicle is calculated as described above by calculating the movement amount of the host vehicle based on the number of wheel speed pulses counted in step S103. In step S106, the travel lane is estimated based on the travel trajectory calculated in step S105. At this time, as described above, in addition to the travel lane corresponding to the road lane on which the host vehicle is traveling, the parallel adjacent travel lanes are also estimated. In step S107, the travel lane estimated in the previous process, that is, the predetermined process cycle for executing the process flow of FIG. 6, is updated with the travel lane estimated in step S106.

  Note that if the determination in step S104 is affirmative, that is, if the host vehicle is changing lanes, steps S105 to S107 are not executed, and thus the travel lane is not estimated. When the lane change is completed, the estimation of the travel lane is resumed from there, and the travel lane is continuously updated until the next lane change. At this time, the travel lane corresponding to the host vehicle and the travel lane adjacent thereto are switched in accordance with the travel road lane of the host vehicle after the change.

  In step S108, the other vehicle marker superimposed on the bird's-eye view map displayed on the monitor 5 until then is cleared. This other vehicle marker is displayed in step S113 of the previous process. In step S109, it is determined whether another vehicle has been detected in step S102. If another vehicle has been detected, the process proceeds to step S110, and if it has not been detected, the process flow of FIG. 6 ends.

  In step S110, it is determined whether the other vehicle detected in step S102 is undergoing a lane change. This determination is performed as follows. First, the rough position of the other vehicle is calculated from the image read in step S100 as described above. Next, it is determined whether or not the calculated rough position is a predetermined distance or more away from any of the travel lanes estimated so far. If it is separated by a predetermined distance or more, it is determined that the lane is being changed, and if it is not separated, it is determined that the lane is not being changed. If it is determined that a lane change is being performed, the process proceeds to step S111. If it is determined that a lane change is not being performed, the process proceeds to step S112.

  Note that an appropriate value can be set in advance for the predetermined distance used for determination as the threshold value in step S110. Alternatively, the lane width of the road on which the host vehicle is traveling may be determined by using a method such as collating with the map data of the navigation device, and the set value of the predetermined distance may be changed according to the determination result.

  In step S111, the position displayed on the bird's-eye map, that is, the positional relationship with the host vehicle is estimated for the other vehicle determined to be in the lane change in step S110. The relative speed with respect to the host vehicle in the real space is obtained from the moving speed on the image until the other vehicle immediately before the lane change. Based on this relative speed, the position in the real space calculated in step S112 executed immediately before the lane change, and the spatial lateral azimuth obtained from the lateral position on the image, the positional relationship with the host vehicle Is estimated. In this way, the display position on the bird's eye map can be estimated.

  On the other hand, in step S112, the position in real space is calculated as described in FIG. 4 for the other vehicle that is determined not to be in lane change in step S110. In this way, the display position on the bird's eye map is calculated. When a plurality of other vehicles are detected in step S110, the determination process of step S110 is performed for each of them, and the process of step S111 or S112 is performed for each other vehicle depending on the result. Like that.

  In step S113, a marker indicating the position of each other vehicle is displayed on the bird's-eye view map of the monitor 5 based on the display position estimated in step S111 and the display position calculated in step S112. After execution of step S113, the processing flow of FIG. In this way, the positional relationship between the host vehicle and the other vehicle behind it is displayed on the bird's-eye view map, and the driver is notified of the surrounding situation.

According to the embodiment described above, the following operational effects can be obtained.
(1) An other vehicle that is an obstacle is detected from an image captured behind the host vehicle that is imaged using the camera 1, and a spatial lateral azimuth angle of the other vehicle is obtained based on the captured image. Then, the distance from the host vehicle to the other vehicle is calculated by calculating the positional relationship between the host vehicle and the other vehicle based on the obtained spatial lateral azimuth angle. Since it did in this way, distance calculation with high accuracy is possible also on a road without a central broken line, and furthermore, resolution of distance calculation can be maintained even if the distance is long.

(2) Estimating the traveling lane in which the other vehicle is traveling, and using the intersection of the estimated traveling lane and the direction line extending in the direction of the spatial lateral azimuth as the position of the other vehicle with respect to the own vehicle, The positional relationship with other vehicles was determined. Since it did in this way, the positional relationship of the own vehicle and another vehicle can be calculated correctly.

(3) The traveling lane in which another vehicle is traveling is estimated based on the traveling locus of the host vehicle. At this time, based on the number of wheel speed pulses of the host vehicle detected by the vehicle sensor 2, the traveling locus of the host vehicle is obtained. Since it did in this way, the travel lane in which the other vehicle is drive | working can be estimated with the behavior of the own vehicle.

(4) A travel lane in which the host vehicle is traveling and a travel lane that is adjacent to the travel lane in parallel at a predetermined interval are estimated, and a travel in which another vehicle is traveling from any of the travel lanes. It was decided to identify the lane. Since it did in this way, even if it is a case where the traveling lane of the own vehicle and the traveling lane of another vehicle differ, the traveling lane of another vehicle can be estimated.

(5) When estimating a traveling lane that is adjacent to a traveling lane in which the host vehicle is traveling in parallel at predetermined intervals, if the predetermined interval is changed according to the lane width of the road, The driving lane can be estimated at a position suitable for the lane width.

(6) When estimating one or a plurality of driving lanes adjacent to the driving lane in which the host vehicle is driving, if the number changes according to the number of lanes on the road, it is suitable for the number of lanes on the road. A number of driving lanes can be estimated.

  In the above embodiment, the intersection of the calculated travel lane with the direction line extending in the direction of the calculated spatial lateral azimuth angle is determined as the position of the other vehicle, but the spatial lateral azimuth angle is determined by other methods. The position of the other vehicle can also be obtained by using this. For example, the approximate range of the relative distance from the host vehicle to the other vehicle is calculated based on the size of the other vehicle on the captured image of the camera 1, and the direction of the spatial lateral azimuth angle within the range of the relative distance is calculated. The position on the direction line extending to is determined as a position range in which another vehicle exists. By using the position range of the other vehicle thus determined and the lane position information obtained by detecting a white line on the road, the final position of the other vehicle can be determined.

  In the above embodiment, the obstacle detection means, the azimuth angle calculation means, and the position calculation means are realized by the microcomputer 4, but this and other configurations in the above embodiment are merely examples, and the features of the present invention are as follows. Each component is not limited to the above embodiment as long as it is not damaged.

It is a figure which shows the structure of the surrounding condition display apparatus by one Embodiment of this invention. It is a figure for demonstrating the method of estimating a driving | running lane. It is a figure for demonstrating the method to calculate a space lateral azimuth, (a) shows a mode that the other vehicle which is a target object is imaged, (b) has shown the captured image example. It is a figure for demonstrating the method of calculating the position of another vehicle. It is a figure which shows the example of a calculation result of the distance from the own vehicle to another vehicle, (a) shows the example of a calculation result by the movement amount of the front-back direction, (b) shows the example of the calculation result by the movement amount of the left-right direction. Yes. It is a flowchart performed in the surrounding condition display apparatus by one Embodiment of this invention.

Explanation of symbols

1: Camera 2: Vehicle sensor 3: Input image memory 4: Microcomputer 5: Monitor

Claims (6)

Imaging means for acquiring a captured image around the host vehicle;
Obstacle detection means for detecting other vehicles around the host vehicle as an obstacle based on a captured image acquired by the imaging means;
Azimuth angle calculating means for obtaining a spatial lateral azimuth angle of the other vehicle with respect to the host vehicle based on the captured image;
By estimating the travel locus of the other vehicle, and obtaining the intersection of the estimated travel locus and the direction line extending in the direction of the spatial lateral azimuth as the position of the other vehicle with respect to the host vehicle, Position calculating means for calculating a positional relationship between the host vehicle and the other vehicle ;
An ambient condition display device comprising: display means for displaying an ambient condition of the host vehicle based on the positional relationship calculated by the position calculating means. The ambient condition display device according to claim 1 ,
The ambient condition display device , wherein the position calculation means estimates a travel locus of the other vehicle based on a travel locus of the host vehicle. The ambient condition display device according to claim 2 ,
Pulse detecting means for detecting wheel speed pulses of the host vehicle,
An ambient condition display device characterized in that a traveling locus of the host vehicle is obtained based on the number of wheel speed pulses detected by the pulse detecting means. In the surroundings display apparatus in any one of Claims 1-3 ,
The position calculating means estimates a first traveling locus on a road lane in which the host vehicle is traveling and one or more second traveling locus parallel to the first traveling locus at predetermined intervals. An ambient condition display device that estimates the travel locus of the other vehicle by specifying the travel locus of the other vehicle from either the first travel locus or the second travel locus . The ambient condition display device according to claim 4 ,
An ambient condition display device that changes the predetermined interval according to a lane width of a road. The ambient condition display device according to claim 4 or 5 ,
An ambient condition display device characterized in that the number of the second traveling locus changes according to the number of road lanes.

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