JP2002163792A - Obstacle collision prevention supporting system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an obstacle collision prevention supporting system for self-diagnosing, that ability for detecting an obstacle is deteriorated due to a unit fault and bad weather and informing a driver that a system is not operating. SOLUTION: The obstacle collision prevention supporting system is provided with a camera, which includes a mark board whose one side is not less than 50 cm in the view of 100 m and imaging an image, a means obtaining an evaluation value from the luminance value of a mark board area in the image, normalizing it by the evaluation value in fine weather and detecting the change of an environment state, a means-storing reference data formed of the evaluation value obtained, by installing the mark board in a position concerned in the past and detecting it at every change of the environment state and a vehicle position detection result, a self-diagnosing means collating the detected evaluation value with reference data and judging the detection ability of a sensor by a specified threshold and a means dividing a judged result and a unit fault detection result, generating unit operation information and informing the driver of the operation state of the system.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an obstacle collision for improving safety by detecting information such as an obstacle with a visible image sensor and providing the information to a driver in a curve section where accidents frequently occur. This is related to the prevention support system.Especially, when a functional failure such as a decrease in the detection performance of the sensor occurs due to a failure of the device or bad weather, etc., the system can operate normally by diagnosing the performance degradation of the sensor and the device failure. The present invention relates to an obstacle collision prevention support system that ensures the reliability and safety of information provision by notifying a driver that no information is provided.

[0002]

2. Description of the Related Art AHS (Advanced Cruise-Assist Syste
m) aims to improve safety and efficiency, and among them, AHS, which aims to improve safety, consists of smart cars (intelligent cars) and smartways (intelligent roads). By cooperating and exchanging information on obstacles and crossing vehicles, etc., which were impossible in the past, in real time, it provides information on delays in finding the driver, alerts you to erroneous decisions, assists you in operating errors, and provides safety. This is a system that realizes safe driving and reduces accidents. To date, the selection of services to be preferentially implemented based on traffic accident statistical analysis has been considered. Among them, the necessity for obstacle collision prevention support in curved sections has been clarified.

An obstacle collision prevention support system uses a camera installed on a roadside pole and an image captured by a camera in a curved section where accidents frequently occur, a stationary vehicle, a low-speed vehicle, and a reverse running vehicle existing in the curved section. Obstacle detection means comprising an image processing device for detecting an obstacle such as an oncoming vehicle,
Obstacle information creating means comprising an information processing device for creating provision information based on the output of the obstacle detecting means, and an information board installed on the roadside or a vehicle-to-vehicle communication device to provide information to a driver of a passing vehicle. The system is configured with obstacle information providing means, and aims to support safe driving by providing information to a driver, warning, and the like.

However, a visible image sensor mainly used as an obstacle detecting means detects an obstacle by an image processing device using an image picked up by a camera. It will be significantly reduced.

FIG. 13 shows a conventional image processing apparatus described in the IEICE technical report PRMU97-6.
Camera 11 for capturing an image, input image storage means 2 for storing an image captured by camera 11 as digital data
1. Initial detection means 50 for performing initial object detection on a partial area in an input image, tracking means 51 for tracking an object,
This is an apparatus that includes an output unit 52 that outputs a processing result.

FIG. 14 is a cross-sectional view of Japanese Patent Application Laid-Open No. 63-188741.
The conventional visibility measuring device described in Japanese Patent Laid-Open No. H10-260, which is a light-dark detection device 200 that detects the light-dark contrast of a judgment sign, and a light-dark contrast when the judgment sign is viewed from close up and a light-dark contrast detected by the light-dark detection device 200. An image processing device 201 for obtaining a visibility based on the image processing device 201 is provided. The image processing device 201 is composed of a plurality of blocks. The A / D converter 300 converts the image information output from the light and dark detection device as an analog signal into a digital signal. The A / D converter 300 converts the image information into a digital signal. It has an image memory 301 for storing image data, a CPU 302 for controlling the processing of the image processing apparatus 201, a memory 303 connected to the CPU 302, and an output unit 304 for outputting the processing result of the CPU 302.

The operation of the conventional image processing device will be described. First, an image photographed by the camera 11 is converted into a digital image by the input image storage means 21 and stored as an input screen.

Next, the initial detection means 50 performs an initial object detection on a predetermined area in the input image. First, the target area is differentiated in the vertical direction to enhance the horizontal light / dark pattern, and this is projected and added in the vertical direction to create an analysis waveform. A threshold value is applied to this analysis waveform to determine the rising edge and the falling edge of the waveform, and an area sandwiched between the two is defined as the horizontal position of the object. Further, a light-dark pattern in the horizontal direction is projected in the horizontal direction on an area within the object horizontal position, and the object vertical position is determined with a position at which the projection value becomes maximum. The image and position coordinates of the object area obtained here are output to the tracking means 51 as a result of the initial detection.

Next, the tracking means 51 uses the image of the object area detected by the initial detection means in the past as a template, calculates the similarity by light and shade pattern matching, and tracks the detected object.

Next, the operation of the conventional visibility measuring device shown in FIG. 14 will be described. The light / dark detection device 200 captures an image including a determination marker that is separately colored black and white, and outputs image data as an analog signal. At this time, the judgment mark is set at a position separated from the light / dark detection device 200 by a distance R.

In the image processing device 201, first, the image data sent from the light / dark detection device 200 is converted by the A / D converter 3.
At 00, the signal is converted into a digital signal and stored in the image memory 301. Next, the CPU 302 reads the luminance value Bt of the portion painted black and the luminance value Bb of the portion painted white, targeting the determination marker region in the image, and obtains the light-dark contrast Cd of the determination marker from the following equation.

Cd = | Bt−Bd | / Bb

Next, the CPU 302 determines the visibility V based on the light-dark contrast Cd of the judgment sign at the distance R and the light-dark contrast Co of the judgment sign when viewed from a short distance.
Is obtained by the following equation, and is output to the output unit 304.
The visibility V indicates a visible distance.

V = R × [In (E) / In (Cd / Co)] where E is a constant.

[0015]

The image processing apparatus used in the conventional obstacle collision prevention support system is as described above.
Obstacles are detected without taking into account environmental conditions such as rain and fog that affect the field of view of the camera.If obstacles cannot be detected, obstacles to be actually detected are not within the field of view of the camera. It is impossible to judge whether the visibility is deteriorated due to the body condition or the environmental condition, and whether or not an obstacle or the like cannot be detected in spite of the fact.

In the obstacle collision prevention support system,
If an obstacle cannot be detected despite the presence of an obstacle, the driver may assume that there is no obstacle, which increases the danger. Therefore,
There is a problem that it is necessary to provide the system as an important function to enable self-diagnosis of device failure or sensor performance degradation and to notify the driver that the system is not operating normally. To this end, the system itself must be able to detect equipment failures and diagnose sensor performance degradation, and if equipment failures or performance degradation are diagnosed, the driver must be notified that the system is not operating. . In order to solve this problem, a method of using a conventional visibility measuring device in combination is also conceivable.However, the conventional visibility measuring device seeks general visibility as a visibility as described above. It is not something that can judge a failure and does not judge an environmental state in the sense that it is an environmental state where an obstacle can be detected.

[0017]

SUMMARY OF THE INVENTION The present invention solves the problems of the conventional system as described above, and reduces the detection performance of a visible image sensor due to detection of equipment failure and occurrence of rain, fog, and the like. Automatically notifies the driver that the system is not operating when a device failure is detected as a result of the self-diagnosis, or when a decrease in detection performance is determined by the self-diagnosis. This is an obstacle collision prevention support system.

[0018]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described below based on embodiments with reference to the drawings.

[0019]

Embodiment 1 FIG. 1 is a schematic equipment layout diagram in one embodiment to which the present invention is applied. In FIG. 1, the equipment is arranged in a curve section 100 where accidents frequently occur. AHS that mounts a stopped vehicle 102 and an oncoming vehicle 103 that cannot perform the operation, and obtains real-time information by road-to-vehicle communication with on-board equipment
Vehicle 104, non-AHS vehicle 1 for obtaining information from information board 6
05, 1 from pole 2, cameras 11 and 12, camera 12
The size of one side provided at a height of 3.8 m or more of the pole 2 to which the camera 11 is attached within the field of view within 00 m is 50 c.
m or more, a roadside processing device 4 provided with an image processing device and an information processing device, a road-vehicle communication interface, a beacon antenna 5 of the road-vehicle communication device, and the like.

FIG. 2 is a schematic configuration diagram of the first embodiment. The luminance of a mark area is extracted as an observation value from an image of a camera for picking up a mark plate to obtain an evaluation value, and the evaluation value is obtained in the past when the visibility is the best. Environmental condition detecting means 23 for detecting a change in the environmental state that influences the camera field of view such as rain and fog by normalizing with the evaluated value, and inquiring the evaluation value output from the environmental state detecting means with the vehicle detection reference data, Self-diagnosis means 24 for judging and outputting the detection capability of the obstacle detection means based on a predetermined threshold value; equipment failure detection means 25 for detecting a failure of a camera or the like; processing results of the obstacle detection means, self-diagnosis means and equipment failure detection means Output means 26 for outputting the information, information creating means 31 for outputting the outputs of the obstacle information creating means, the equipment failure detecting means and the self-diagnosing means as an edit section, and an information board installed on the roadside Rui is composed of system operation notification means 41 for notifying the obstacle information providing unit and system operation abnormality that provide obstacle information to the passing vehicle driver by road-vehicle communication device.

Next, the operation of the system of the first embodiment will be described with reference to FIGS.
This will be described with reference to FIG. FIG. 3 is a processing flowchart of the present invention. FIG. 4 is a diagram for explaining the distribution of luminance and the size of the mark plate. 5 to 8 show that the mark plate shown in FIG. 4 is installed 40 m, 60 m, 80 m, and 100 m in front of the camera, and the evaluation value of the environmental state detected for each change of the environmental state and the detection position of the traveling vehicle are obtained by experiments. 5 shows vehicle detection reference data (1) to (4). FIG. 9 is a diagram showing the correlation coefficient between the evaluation values of the vehicle detection reference data (1) to (4) and the vehicle detection position. FIG. 10 shows the device operation information creating unit and the obstacle information creating unit. FIG. 4 is a diagram illustrating a data structure to be output.

First, the presence or absence of a device failure for detecting a failure of a camera or the like is detected (step T2). In the device failure detection, for example, an image synchronization error can be detected by monitoring an image synchronization signal.

The camera 12 captures an image including the mark plate 3 (step T1).
The image captured in step 2 is stored as digital data (step T3). As shown in FIG. 4, the mark plate 3 of the image stored in the input image storage means 21 has a central portion painted white and a peripheral portion painted black, and the size of the mark plate is in front of the camera. In order to obtain a stable image even if it is set at a distance of 80 m to 100 m, the length of each side of the mark plate area is set to about 10 pixels or more so that the number of pixels is about 10 or more.
cm or more. Input image storage means 2
The luminance is obtained as an observation value from the mark plate area in the image stored in No. 1. For example, as shown in FIG. 4, a horizontal observation line is set at the center of a mark plate image having a width of n pixels, and the luminance of each image in the horizontal direction is obtained. FIG. 4 shows a difference in distribution of luminance between an image capturing the mark during normal weather and during bad weather. As shown in 32 at normal time and 33 at bad weather, the distribution of luminance changes in the gradient of the luminance value at the boundary between black and white, and this gradient represents the environmental state.

Next, the environmental condition detecting means 23 calculates an environmental condition evaluation value (step T8). In this step, for example, the environmental state evaluation value S is obtained for the target region from the luminance value output from the observation value by the following equation. Here, Pj is a luminance value at a pixel position j between the observation lines -L to L.

(Equation 1)

Next, the environmental state detecting means 23 sets a standard evaluation value for fine weather obtained in the past, which is obtained in the past (step T10), and normalizes it (step T9). The normalized evaluation value D to be normalized is obtained by normalizing with the standard evaluation value Smax at the time of fine weather by the following equation. D = S / Smax

Next, the self-diagnosis unit 24 compares the normalized evaluation value output from the environmental condition detection unit 23 with the vehicle detection reference data, determines the detection capability of the obstacle detection unit 22 based on a predetermined threshold, and outputs the determination result. (Step T11).
Here, the vehicle detection reference data is set in advance as described below.

A plurality of mark plates are moved forward from the camera by a distance R.
Different positions, for example, the distance R from the camera is 40 m,
The environmental state is set at a position forward of 60 m, 80 m, and 100 m, and the environmental state detected by the environmental state detecting means 23 and the obstacle detecting means 22 for detecting the environmental state at each of a plurality of mark plate installation positions in the past for each change in the environmental state. And the position at which the traveling vehicle can be detected.

FIGS. 5 to 8 show a case where a mark plate having a side size of 50 cm is placed at a distance R from the camera of 40 m, 60 m, 80 m and 1 m.
The table shows reference data (1) to (4) of a distance at which a vehicle can be detected and a normalized evaluation value D when installed at a position in front of 00 m. The reference data (1) to (4) are data obtained from an experimental facility capable of generating and setting rain and fog environments under arbitrary conditions. FIG. 9 shows the correlation coefficient between the distance at which the vehicle can be detected and the normalized evaluation value D based on the result. According to the results of FIG. 9, the correlation coefficient is 0.82 or more for the mark installed at a distance R of up to 100 m, and particularly the mark installed within 80 m has a high correlation coefficient of 0.9 or more. If the size of the mark plate is 50 cm or more, or the number of pixels in the mark plate region is about 10 pixels or more, a change in the environmental state can be detected.

The reference data (1) obtained by the above method
(4) is stored and set as reference data corresponding to the installation position of the mark plate (step T13). Alternatively, it may be stored as reference data for each of a plurality of mark plates, and may be selectively set from the stored reference data according to the installation positions of the camera and the mark plate (step T12), or may be interpolated with respect to the distance. .

The normalized evaluation value output from the environmental state detecting means 23 is collated with the reference data, and the obstacle detecting ability is determined based on a predetermined threshold and output (step T11). The position of the sensor is determined based on the vehicle detection capability of the visible image sensor. The vehicle detection range is defined based on the vehicle detection capability of the sensor, that is, a technical condition that allows the presence and speed of the vehicle to be specified by image processing from the captured image. Based on current visual image sensor performance, the vehicle detection range of the sensor can be adjusted by adjusting the camera angle.
In a curved section, the camera is deeply depressed to improve the detection performance of an area close to the camera. The vehicle detection range in the longitudinal direction of the visible image sensor that monitors the curve section is 20 to 100 m.
Is defined in the range. Therefore, the detection range that must be detected by the sensor is within 100 m and is determined by the arrangement interval of the cameras. For example, the detection range that the sensor must be able to detect is 20
When the distance is set to 80 m, the reference data shown in FIG. 7 is set.
That is, the normalized evaluation value D corresponding to the value of the vehicle detection distance 80 m shown on the vertical axis of FIG. 7 is set as the predetermined threshold Dref. During the actual operation of the system, the normalized evaluation value D output when the environmental condition deteriorates due to the generation of fog or the like is equal to the predetermined threshold Dr.
When the value falls below ef, it can be diagnosed that a decrease in the obstacle detection performance has occurred. From the above, one side is 50cm
By using the above mark plate or a mark plate in which the number of pixels in the mark plate region is about 10 pixels or more, 100 m
It is possible to diagnose the deterioration of the detection performance up to. The height of the mark plate is preferably set to 3.8 m or more so that the mark plate is not blocked by a large vehicle.

Next, the obstacle detecting means 22 is the same means as the conventional image processing apparatus, and performs initial detection of an obstacle (step T).
4) Perform tracking (step T5). Thereafter, the processing result output means 26 determines the processing result to be output (step T
6) Yes. When a failure is detected by the device failure detection unit 25 or when the determination by the self-diagnosis unit 24 is equal to or smaller than a predetermined threshold, the determination result is used as the processing result. Otherwise, the detection result of the obstacle detection unit 22 is used as a processing result. Is output (steps T6 and T14).

Device failure detecting means 25 and self-diagnosing means 24
The output from the obstacle means 22 is output to the information creating means 31.
To process each output, edit and output. FIG. 1 shows a data structure output from the information creating means 31.
0 is shown. The header part 34 of the data structure is data common to each device constituting the obstacle collision prevention support system such as the transmission source, the transmission destination, and the time. The data unit 35 determines the type of data by the obstacle information creating unit, such as the type of an event that has determined a detection event such as a stopped vehicle or a low-speed vehicle, an obstacle position,
The obstacle ID, oncoming vehicle ID, oncoming vehicle position, detection time, and the like are edited and output. The data type by the device operation information creating means is edited and output as described below. 0: Normal (when there is no device failure and the self-diagnosis means determines that there is no decrease in the detection capability of the sensor). 1: When a device failure is detected. 2: When the self-diagnosis unit determines that the detection capability of the sensor has decreased.

Based on the data output created by the editing and classification, an information providing content is determined by an obstacle information providing means for providing obstacle information to a driver of a passing vehicle and a system operation notifying means for notifying an abnormal operation of the system. Then, the information is output by the information board or the road-vehicle communication device. For example, when the data type by the device operation information creating means is 0, the obstacle information providing means uses the data of the obstacle information creating means to indicate that "there is a vehicle stopped 100 m ahead,""there is a low-speed car 100 m ahead," Information such as "car approaching" is determined and output. When the data type is 1, "service stopped" or the like is determined, and when the data type is 2, "adjusting" or the like is determined and output by the system operation notifying means. The output of the data type can be used as useful data also as maintenance information at the time of equipment failure by editing and sorting.

In this embodiment, through the above steps,
A self-diagnosis of a decrease in the detection performance of the visible image sensor due to a change in the environmental state due to the detection of a device failure or the occurrence of rain, fog, or the like can automatically perform self-diagnosis, and notify the driver of the system operation status. In the present embodiment, the method of obtaining the evaluation value of the environmental state detecting means 23 is described by a method of extracting the luminance as the observation value. However, the same procedure as that of the conventional visibility measuring device is used to calculate the average value of the white and black luminances. Alternatively, the contrast of the mark plate may be determined, and this may be used as the evaluation value. Further, in the present embodiment, the environmental state detecting means is shown by using the mark plate, but may be another target on the road, for example, a white line on the road.

Further, in addition to the function of the obstacle collision prevention support system, the evaluation value of the environmental condition detecting means is converted into the visibility V and calculated, so that the visibility information is provided to the driver in advance as the environmental condition deterioration ahead. The function provided as can also be used together.

Second Embodiment A schematic equipment layout diagram, a schematic configuration diagram, and a processing flow diagram of this embodiment are the same as those of the first embodiment. The operation of the second embodiment will be described with reference to FIGS. FIG. 11 is a data diagram illustrating a normalized characteristic value D corresponding to a temporal change of the environmental state evaluation value when the environment such as fog changes suddenly.

In this embodiment, steps T1 to T11 are the same as in the first embodiment. The self-diagnosis unit 24 compares the evaluation value output from the environmental state detection unit with reference data,
When the determination result output T14 determines that the detection capability of the obstacle detection means has decreased after the operation from step T1 to T11 in which the detection capability of the obstacle detection means is determined to be lower than the predetermined threshold value, the determination result is the same for one time. Output as

As shown in FIG. 11, the normalized characteristic value D corresponding to the temporal change of the environmental state such as fog is assumed to be a case where the environmental state suddenly changes due to fog. In such a case, even if it is determined that the detection capability of the obstacle detection means has deteriorated, the determination of the reduction of the detection capability and the cancellation of the reduction are repeated in a short time because of a sudden change in the environmental state. Even if the notification is given, the effect is thin, and there is a possibility that the reliability of the information provision may be impaired by increasing annoyance. Therefore, when the detection capability is determined to be lower, the determination result is output as the same determination for a certain period of time in consideration of, for example, the passing time of the traveling vehicle.

In this embodiment, through the above steps,
Even when the environmental state repeatedly changes suddenly when the detection capability is determined to be low, the driver can be notified of the abnormal operation state of the system as safe side information.

Embodiment 3 FIG. 12 is a schematic device layout diagram of the present embodiment. The size of one side provided on the back of the camera 12 and the information board 6 within a visual field within 100 m from the camera 12 is 50 mm.
cm mark plate.

The schematic configuration, processing flow, and
The operation is the same as in the first embodiment. The information board that provides the information of the oncoming vehicle to the driver is preferably installed close to the start point of the curve so that the driver entering the curve section can obtain the latest information on the oncoming vehicle. Provided on the back of the board, it can be included in the field of view of the camera.

With the above-described installation means, the mark plate can be configured as a part of the information plate.

[0043]

As described above, according to the first aspect of the present invention, the detection capability of the visible image sensor is automatically reduced due to the deterioration of the environmental condition due to the detection of equipment failure or the occurrence of rain or fog. Self-diagnosis to improve maintainability. In addition, since the mark plate and the camera are commonly installed on the same pole, and the visible image sensor itself includes the self-diagnosis means, a simple system configuration can be achieved.

According to the second aspect of the present invention, even if the environmental state repeatedly changes suddenly, it is possible to notify the driver of the abnormal operation state of the system as safe side information.

According to the third aspect of the present invention, since the mark plate can be configured as a part of the information plate, it is not necessary to newly provide a pole for attaching the mark plate.

[Brief description of the drawings]

FIG. 1 is a schematic device layout diagram of Embodiment 1 of the present invention.

FIG. 2 is a schematic configuration diagram of Embodiment 1 of the present invention.

FIG. 3 is a processing flowchart of the first embodiment of the present invention.

FIG. 4 is an explanatory diagram of a mark plate and distribution of luminance.

FIG. 5 is a diagram showing reference data (1).

FIG. 6 is a diagram showing reference data (2).

FIG. 7 is a diagram showing reference data (3).

FIG. 8 is a diagram showing reference data (4).

FIG. 9 is a diagram showing correlation coefficients between evaluation values of reference data (1) to (4) and vehicle detection positions.

FIG. 10 is an explanatory diagram of a data structure output from a device operation information creating unit and an obstacle information creating unit.

FIG. 11 is a data diagram illustrating a normalized characteristic value D corresponding to a temporal change in an environmental state.

FIG. 12 is a schematic device layout diagram of Embodiment 3 of the present invention.

FIG. 13 is a configuration diagram of a conventional image processing apparatus.

FIG. 14 is a configuration diagram of a conventional visibility measurement device.

[Explanation of symbols]

 2 Pole 3 Mark plate 4 Roadside processing device 5 Beacon antenna 6 Mark plate 11 Camera 12 Camera 21 Input screen storage means 22 Environmental condition detection means 23 Self-diagnosis means 24 Device failure detection means 25 Processing result output means 31 Information creation means 32 Normal time 33 Bad weather 34 Header 35 Data section 41 Obstacle information providing means and system operation notifying means 50 Initial detecting means 51 Tracking means 52 Output means 100 Curve section 101 Wall blocking view, etc. 102 Stopped vehicle 103 Oncoming vehicle 104 AHS vehicle 105 Non AHS vehicle 200 Light / dark detection device 201 Image processing device 202 A / D converter 301 Image memory 302 CPU 303 Memory 304 Output unit

Claims (3)

[Claims] 1. An obstacle detecting means comprising: a camera installed on a roadside pole; and an image processing device that detects an obstacle such as a stationary vehicle or a low-speed vehicle existing in a curved section using an image captured by the camera. Obstacle information creation means comprising an information processing device for creating provision information based on the output of the obstacle detection means, and an information version installed on the roadside, or obstacle information to a driver of a passing vehicle by a road-to-vehicle communication device. In an obstacle collision prevention support system having an obstacle information providing means to provide, an equipment failure detection means for detecting a failure of a camera or the like, and an environmental state detection means for detecting an environmental state such as rain and fog which influences a camera view Self-diagnosis means for self-diagnosing and outputting the detection capability of the obstacle detection means from the output of the environmental state detection means, and operation of the equipment based on the outputs of the self-diagnosis means and the equipment failure detection means An obstacle collision prevention support system, comprising: equipment operation information creating means for creating state information; and system operation notifying means for notifying a driver of the operating state of the system, wherein the environmental state detecting means comprises: Of the cameras, a mark plate having a side of 50 cm or more provided on a pole to which at least one camera is attached, and photographing both the mark plate and obstacles on the road including the mark plate within a field of view of 100 m or less. Detects changes in environmental conditions by extracting the luminance of the mark area from the image of the camera that captures the mark plate and obtaining the evaluation value, and normalizing the evaluation value obtained in the past and when the weather was fine in the past. Environmental condition detecting means and obstacle detecting means for installing a mark plate at the position in front of the camera in the past, and detecting an environmental state. Further, in the past, there is provided means for storing and setting an evaluation value of the environmental state detected for each change of the environmental state and reference data including the vehicle position detection result, and the evaluation value output from the environmental state detecting means is referred to as reference data. Self-diagnosis means for collating and judging a decrease in the detection capability of the obstacle detection means based on a predetermined threshold value and outputting the same. The equipment operation information creating means edits and outputs the outputs of the equipment failure detection means and the self-diagnosis means. An obstacle collision prevention support system, characterized in that: 2. The self-diagnosis unit compares the evaluation value output from the environmental state detection unit with reference data, and when it is determined by a predetermined threshold that the detection capability of the obstacle detection unit has deteriorated, the determination result is determined to be the same for a predetermined time. The obstacle collision prevention support system according to claim 1, wherein the obstacle collision prevention support system outputs the information. 3. A mark plate is provided on the back of the information plate,
2. The obstacle collision prevention support system according to claim 1, further comprising: an environmental state detection unit including a camera that captures both the mark plate and an obstacle on the road within a visual field within 0 m.