JP2008052453A - Traveling support system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a traveling support system for enabling many persons to recognize poor visibility of many spots at the same time and in real time while suppressing the increase of costs. <P>SOLUTION: A visibility index numeralization part 100 calculates the visibility index of a road by processing a road image from a road camera 110. A poor visibility information collection part 200 calculates the rank value of the calculated visibility index as a poor visibility level based on the subjective evaluation of human being, and collects/stores the calculated poor visibility level and image information and weather information as poor visibility information. A poor visibility information transmission part 300 provides the stored poor visibility information through predetermined information transmitting means (personal computer 410, information kiosk 420, portable telephone 430, road information board 440, car navigation 450, and road information radio 460 or the like) to a user. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a driving support system, and more particularly to a driving support system at the time of visibility failure using a visibility index based on a digital image.

  Visibility disturbance occurs due to various factors such as snowstorm, snowfall, rainfall, fog, and haze. Depending on the factors, the location where visibility impairment occurs and how it changes over time vary, and sudden visibility impairment in unexpected locations is also expected. Therefore, in order to travel safely when visibility is impaired, it is very important to understand the local situation. Visibility disturbances do not occur regularly as described above, so collision accidents that encounter unexpected visibility disturbances are continual, and accidents with poor visibility lead to multiple collisions that increase in size. There is a tendency. Therefore, whether or not visibility loss can be known in advance has a great influence on safe driving.

  For this reason, it is strongly desired to grasp multi-point visibility problems simultaneously and in real time.

  Conventionally, as a method of knowing visibility disturbance due to snowstorm or heavy fog, there are a method of measuring visibility with an instrument such as a visibility meter and a method of browsing road images. Since the former measures the visibility as a numerical value, there is an advantage that the data can be easily stored and the data use range is wide. Moreover, since the latter can be confirmed directly with an image, there is an advantage that a visibility disorder can be reliably grasped.

  However, since this prior art does not relate to a known literature invention, there is no prior art document information to be described.

  However, each of the above prior arts has the following problems.

  First, the method of measuring visibility with a meter (such as a visibility meter) has problems in terms of cost and accuracy maintenance. For example, in measurement using a visibility meter, a change in light transmittance or reflectance due to water droplets or suspended particles in the air is measured, and the obtained result is converted into a visibility distance. However, in order to maintain the accuracy of the visibility meter, periodic inspections and adjustments are necessary, and since this adjustment is performed using a special device, it is necessary to remove the instrument and bring it to an inspection facility, which also increases the cost. large. In addition, since the visibility distance is greatly affected by the installation location, the visibility meter often outputs a visibility distance that differs from the field of view felt by the driver or road manager (hereinafter referred to as “driver” etc.). Low. For this reason, it is difficult to maintain accuracy in visibility measurement using a meter. Further, since a visibility meter is more expensive than other weather instruments, it is difficult to grasp visibility obstacles at many points using a visibility meter in terms of cost.

  Further, in the method by browsing road images, it is difficult to store the images as data, and there is a restriction in terms of use that there is no means for grasping the visibility disorder other than browsing the images as videos. In addition, although a video sent from a road camera (for example, an ITV camera or a CCTV camera for road monitoring) already deployed along the road is an effective means for grasping the visibility disorder, this method However, there is a restriction that only images from a limited camera that can provide video are available. For this reason, there is a restriction that information on many points cannot be provided at one time. In other words, such image information has a problem that it is difficult to accumulate information and a problem that the utilization method and range are limited.

  Therefore, in order to suppress the increase in cost, it is assumed that a large number of road cameras that are already installed are used, and in addition, many people use video display devices for visibility problems in the section where such road cameras are installed. The realization of a method that can be known in various situations, such as before traveling in a car or during traveling, without being held is desired.

  The present invention has been made in view of such points, and an object of the present invention is to provide a driving support system in which many people can simultaneously grasp multi-point visibility problems in real time while suppressing an increase in cost. And

  The driving support system according to the present invention includes a visibility index calculation unit that calculates a road visibility index by performing image processing on a road image, and the visibility index rank value calculated by the visibility index calculation unit A visibility disorder degree calculation unit that calculates a visibility disorder degree based on subjective evaluation, a visibility disorder information storage unit that stores visibility disorder information including the visibility disorder degree calculated by the visibility disorder degree calculation unit, and the visibility disorder information A visibility failure information providing unit that provides visibility failure information stored in the storage unit via a predetermined information transmission unit, and the visibility index calculation unit converts a road image into a frequency component and converts A configuration is adopted in which the frequency distribution of a region corresponding to human contrast sensitivity is acquired by filtering the subsequent frequency distribution, and a road visibility index is calculated using the obtained frequency distribution.

  According to the present invention, it is possible for a large number of people to grasp a visibility disorder at multiple points simultaneously and in real time while suppressing an increase in cost.

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

  First, prior to the description of this embodiment, basic terms used in this specification are defined.

  “Camera” means various types of cameras arranged along the road for various purposes such as monitoring and investigation of the road. In this specification, the term “road camera” is also used in the same meaning.

  “Digital image” broadly means a digitized image regardless of the type of still image, moving image, camera, or the like.

  “Road image” means a digital image in which roads, road surroundings, and traffic conditions are recorded.

  “Visibility impairment” means, for example, that the light transmittance in the air decreases due to fog, rain, snow, snowstorm, haze, dust, etc. It means a situation that causes

  “Visibility index” means an index indicating the visibility (visibility) of an image obtained by image processing of a road image. This visibility index is one of the central concepts of the present invention, and will be described in detail later, including a visibility index quantification method (obtained by performing specific image processing on a road image as will be described later). explain.

  “Visibility hindrance” means an index (a visibility index rank value) that indicates the visibility (visibility) of a road front view (or visibility) when driving as a driver. This visibility failure degree is also one of the central concepts of the present invention, and includes a visibility failure degree determination method (as will be described later, the value of a visibility index is determined based on a subjective evaluation of a road image). This will be described in detail later.

  “Visibility disorder information” is information that comprehensively indicates the current visibility disorder as a section (for example, a section in which the visibility disorder from the area before the eyelid to the area beyond the eyelid is concerned). This means information including comprehensive information such as road images and weather information that determines visibility obstacles, centering on the degree of visibility obstacles at multiple points determined from the visibility index. The visibility index that is the basis of the visibility failure degree is also included in the visibility failure information.

  “Meteorological information” means current values and predicted values of weather such as snowfall and temperature, which are factors that cause visibility problems.

  FIG. 1 is an overall configuration diagram of a driving support system according to an embodiment of the present invention.

  The driving support system shown in FIG. 1 is a driving support system at the time of visibility failure using a visibility index based on a digital image, and is roughly divided into a visibility index digitizing unit 100, a visibility failure information collecting unit 200, and a visibility failure. An information transmission unit 300 is included.

  The visibility index digitizing unit 100 is a part that digitizes a visibility index using a road image, and includes, for example, a road camera 110, an image collection device 120, and a visibility index digitizing device 130. Yes. The visibility index digitizing unit 100 digitizes the visibility of the image by performing image processing on the digital image from the road camera 110 (“visibility index”).

  As described above, the road camera 110 is a variety of cameras provided along the road for various purposes such as monitoring and investigation of the road. The road camera 110 is configured by, for example, an ITV camera or a CCTV camera. As the road camera 110, for example, it is preferable to use a number of cameras already installed along the road in order to suppress an increase in cost. The road camera 110 transmits a digital image (road image) that records the road, the road periphery, and the traffic situation to the image collection device 120.

  The image collection device 120 collects and accumulates road images sent from the road camera 110 and transmits them to the visibility index digitizing device 130 and the visibility failure information collection unit 200. In particular, in the present embodiment, for example, the image collection device 120 extracts and records a still image from a moving image sent from the road camera 110 and stores it in the visibility index digitizing device 130 and the visibility failure information collection unit 200. Send each one.

  The visibility index digitizing device 130 performs image processing on a road image (here, for example, a still image) sent from the image collecting device 120 and digitizes the visibility of the image, that is, the visibility index. Is calculated. The obtained visibility index is transmitted to the visibility defect information collection unit 200.

  The visibility failure information collecting unit 200 simultaneously displays various visibility failure related information, specifically, for example, the road image itself, the visibility index obtained from the road image, the visibility failure degree obtained from the visibility index, and weather information. This is the part to collect and record. More specifically, the visibility obstacle information collecting unit 200 is 1) a multi-point road necessary for grasping visibility obstacles on the road from the road cameras 110 installed along the road via the image collecting device 120. 2) Visibility index from the visibility index digitizing device 130, 3) Visibility obstacle degree determined from the visibility index based on human subjective evaluation, 4) Weather information which is a factor causing visibility disorder, Are collected at the same time, and are aggregated as visibility fault information that can grasp the entire situation of a long road section or a wide range of visibility faults. The visibility failure information collection unit 200 includes, for example, a visibility failure degree calculation device 210, a weather information collection device 220, a visibility failure information editing device 230, and a road map database 240.

  The visibility impediment degree computing device 210 uses the visibility index sent from the visibility index digitizing device 130 in accordance with a criterion established based on a subjective evaluation by a human, for example, a determination based on an image of a subject. Calculate visibility impairment. That is, the visibility impediment degree calculation device 210 is based on the visibility index so that the driver can know the degree of visibility impediment, and the visibility ahead of the road assuming that the vehicle actually travels (visibility impediment). Degree). The obtained visibility failure degree is transmitted to the visibility failure information editing device 230.

  The meteorological information collection device 220 collects meteorological information, which is a factor causing visibility disturbance. For example, the weather information collection device 220 is connected to the weather information center 250. The weather information center 250 provides all weather information related to the visibility disorder.

  The visibility failure information editing device 230 includes a road image from the image collection device 120, a visibility index from the visibility index digitizing device 130, a visibility failure degree from the visibility failure degree calculation device 210, and a weather information collection device 220. Collect meteorological information and edit visibility information based on the collected information. In other words, the visibility failure information editing device 230 provides visibility information such as road images and weather information as information that comprehensively indicates the current visibility failure as a section, focusing on the degree of visibility failure at multiple points determined from the visibility index. Visibility disorder information including information to be judged is created. The obtained visibility failure information is sent to the visibility failure information transmission unit 300.

  The road map database 240 is a database that stores road map data. The road map database 240 and the visibility obstacle information editing device 230 are mutually accessible.

  The visibility failure information transmitting unit 300 accumulates each digitized visibility failure information and creates a database, and converts the visibility failure degree into text characters, pictograms, and voices, and the driver's needs and usage scenes (location for obtaining information). Visibility information is provided by various means and timing according to the timing, information equipment, etc. The visibility failure information transmission unit 300 includes, for example, a Web server 310, a visibility failure information transmission device 320, and a visibility failure information search device 330.

  More specifically, the visibility failure information transmission unit 300 has a function of transmitting a visibility failure degree, a road image, and weather information according to needs and an information device that a user receives. For example, the visibility defect information transmission unit 300 displays all information on the home page of the personal computer 410 or the information kiosk 420 using images and characters (text characters, pictograms), or compact information using pictograms and text characters. Is displayed on the mobile phone site of the mobile phone 430, the visibility obstacle degree is character data, and is displayed on the road information board 440 and the car navigation system 450, and the visibility obstacle degree is voice data, and the road information radio 460 and the car navigation system 450 are generally used. It is distributed to a radio broadcasting station (not shown), or when the degree of visibility failure exceeds a certain level, the degree of visibility failure is delivered as text data to the user via mobile mail or personal computer mail. Although not shown, the visibility failure information transmission unit 300 can also distribute all information to TV broadcast stations using images, characters, and sounds.

  The Web server 310 converts the visibility failure degree edited by the visibility failure information editing device 230 into text characters, pictograms, and the like, along with the PC 410 and the visibility failure information (road information, weather information) other than the visibility failure degree. Web screens (Web pages) such as the information kiosk 420 and the mobile phone 430 are created. In this embodiment, the Web and the audio data are separated from each other. However, it is also possible to provide visibility failure information using audio data on the Web.

  The visibility failure information transmission device 320 converts the visibility failure degree edited by the visibility failure information editing device 230 into text characters, pictograms, voice data, and the like, so that the cellular phone 430, the personal computer 410, the road information board 440, the car navigation system 450, It transmits to road information radio 460 etc.

  When the visibility failure information search device 330 receives the search request (including vehicle position / travel direction information), the visibility failure information search device 330 communicates with the visibility failure information editing device 230 to view the visibility failure information ahead of the vehicle in the traveling direction (visibility failure degree, road Information, weather information) and the obtained visibility failure information is transmitted to the search request destination via the visibility failure information transmission device 320. The search request is transmitted from the car navigation system 450 that can use the GPS 470, for example.

  As described above, the driving support system according to the present embodiment includes the visibility index digitizing unit 100, the visibility failure information collecting unit 200, and the visibility failure information transmitting unit 300. This system calculates the degree of visibility impairment based on all digital images including road images from the road cameras 110 installed along the road, and relates the degree of visibility impairment to the visibility impairment. Providing drivers with road images and weather information. As a result, the driver can obtain visibility failure information anytime, anywhere, such as at home, at work, or while traveling, using various devices such as the personal computer 410, the mobile phone 430, the car navigation system 450, and the road information board 440. For this reason, it is possible to avoid severe visibility hindrance time by changing the departure time or changing the route in a drive with all visibility impairment such as snowstorm and fog without encountering visibility impairment. For example, it can support safe driving when visibility is impaired.

  FIG. 2 is an explanatory diagram of a visibility evaluation method used in the present embodiment.

  This visibility evaluation method is a method for determining the visibility of an image from the spatial frequency of the still image. That is, in this method, a human contrast sensitivity function is used as an evaluation index for poor visibility. A snowstorm or fog corresponds to reducing or even eliminating spatial frequency information with high contrast sensitivity from an image in human view. Actually, an image taken when the snowstorm or fog is dark is almost white regardless of the background. The visual field is good if there is much spatial frequency information in a region where human contrast sensitivity is high in a two-dimensional still image (hereinafter simply referred to as “image”), and if the information is small, the visual field is poor. For example, in FIG. 2, when the visibility is good, the contrast in the screen 501 is large, and the difference in intensity between black and white is large. On the other hand, when the visibility is poor, the contrast in the screen 502 is small, and the difference in intensity between black and white is small.

  Therefore, in this method, the spatial frequency of the image is used as an evaluation index for poor visibility, and the visibility of the image is quantified (quantified) from the spatial frequency of the region that is easy for humans to see by filtering using human contrast sensitivity. ) (Visibility index). As will be described later, this visibility index is the sum of power spectrum values obtained by Fourier transformation.

  However, with this visibility index, it is difficult for humans to distinguish and evaluate visibility, so grouping is performed based on human senses. For example, in this method, as an evaluation value of the visibility by the subject, the visibility index is grouped and categorized based on the result of the subject experiment (VS value). That is, the VS value is a numerical value obtained by grouping the visibility index based on the sense of the subject. In the evaluation result 503 illustrated in FIG. 2, the VS value is set to 1 to 12. This evaluation result 503 is a result of an experiment for confirming the correlation between the visibility index and the visibility value visually.

  As a result of the experiment, it was confirmed that there is a correlation between the visibility index and the visual visibility value. Therefore, in this method, the VS values are further grouped to set the visibility disorder degree (visibility level as the rank of the visibility index) in four stages. Specifically, the visibility level 4 is a level where the visibility is 500 m or more and the visibility is good. The visibility level 3 is when the visibility is 200 to 500 m, and the visibility level 2 is when the visibility is 100 to 200 m. The visibility level 1 is a level where the visibility is less than 100 m and the visibility is poor. Here, the visibility is worse as the numerical value of the visibility level is smaller. In this embodiment, what is finally provided is the visibility degree of visibility in the four stages.

  In this embodiment, the degree of visibility disturbance (visibility level) to be provided is set to four levels, but the present invention is not limited to this, and it is within a range where human beings can distinguish and determine visibility. The number of stages can be arbitrarily set according to the purpose of providing information. However, in practice, the number of steps of the visibility level is preferably 2 to 7, more preferably 3 to 5, and most preferably 4. For example, by setting four levels of visibility, it is possible to more accurately convey a situation where visibility is poor. In this embodiment, the smaller the value of the visual field level, the worse the visual field. However, the present invention is not limited to this and may be reversed.

  Next, the overall operation of the driving support system according to the present embodiment will be described with reference to FIG. FIG. 3 is a sequence diagram showing a process of each component.

  First, the road camera 110 captures various road images and transmits them to the image collection device 120 of the visibility index digitizing unit 100.

  Upon receiving the road image, the visibility index digitizing unit 100 extracts a still image by capturing a moving image or the like. Then, after sequentially performing the extraction operation of the extracted image, the FFT (Fast Fourier Transform) processing, and the spatial frequency band filtering processing based on human contrast sensitivity, the power spectrum is summed up, and the visibility showing visibility Calculate the indicator. The calculated visibility index is transmitted to the visibility failure information collection unit 200. On the other hand, the extracted still image is also transmitted to the visibility defect information collection unit 200.

  The visibility failure information collecting unit 200 accumulates the still image sent from the visibility index digitizing unit 100 and actually travels the vehicle based on the visibility index sent from the visibility index digitizing unit 100. It calculates and accumulates forward visibility (degree of visibility impairment) when it is assumed to do, and collects and accumulates weather information that is a factor of visibility impairment. Then, the visibility obstacle information, road image, and weather information data related to the visibility on the road are collated with the road map data stored in the road map database 240 and edited to organize the visibility obstacle information database. The visibility obstacle degree, road image (still image), and weather information collected and accumulated here are provided to the user 400 via the visibility obstacle information transmission unit 300.

  The visibility impediment information transmission unit 300 converts the visibility impediment degree into text characters, pictograms, or audio data, and 1) creates Web screens of the personal computer 410, the information kiosk 420, and the mobile phone 430, and 2) visibility impediments. 3) Visibility failure information is displayed on the road information board 440 when visibility failure occurs, and 4) Information is provided by automatic voice via the road information radio 460 when visibility failure occurs. 5) Visibility Before the failure occurrence section, the front visibility failure occurrence state is transmitted to the car navigation system 450. Accordingly, in the case of 1), the user 400 obtains information by looking at various screens. In the case of 2), the user 400 obtains the state of occurrence of the visibility disorder by e-mail. In the cases of 3) and 4), Information is obtained from the roadside information facility while traveling, and in the case of 5), the information on the front visibility failure occurrence state can be obtained from the car navigation system 450 before entering the visibility failure occurrence section. In the case of 5), the user 400 transmits information (vehicle position information) such as the vehicle position and the traveling direction by the GPS 470 via the car navigation system 450, and the visibility failure information transmission unit 300 that receives this information collects the visibility failure information. Accessing the unit 200, the vehicle visibility information in the forward direction of the vehicle is searched based on the vehicle position information and transmitted to the car navigation system 450.

  Hereafter, each part of the driving assistance system which concerns on this Embodiment is demonstrated in detail.

  FIG. 4 is a flowchart showing the operation of the image collection device 120 in the present embodiment.

  First, the image collection device 120 selects the road camera 110 (S1000), and communicates with the selected road camera 110 (S1100). As a result, if communication is possible (S1200: YES), it is confirmed whether or not the road camera 110 is at the normal angle of view (S1300). As a result of the confirmation, if the road camera 110 is at the normal angle of view (S1300: YES), road images of the road camera 110 are collected (S1400). Road images are collected by extracting still images from moving images sent from the road camera 110 by capturing moving images or the like. The collected road images (still images) are accumulated in the image collection device 120 (S1500). Note that a series of processing (step 1 processing) from step S1000 to step S1500 is repeated until communication with all road cameras 110 is completed, that is, processing for all points is completed.

  FIG. 5 is a block diagram showing the configuration of the visibility index digitizing apparatus 130 in the present embodiment.

  The visibility index digitizing device 130 inputs an image (still image) of a multi-point road camera 110 and performs an evaluation image cut-out operation, and a digital image cut out by the image input unit 131. An FFT processing unit 132 that performs FFT processing, a filter processing unit 133 that applies a spatial frequency bandpass filter based on human visual sensitivity to spectrum data output from the FFT processing unit 132, and an output of the filter processing unit 133 A visibility calculation unit 134 that digitizes (calculates) the visibility of an image using the result, and an abnormal value determination unit 135 that determines whether the calculation result (visibility index) of the visibility calculation unit 134 is a normal value or an abnormal value. And a visibility index storage unit 136 that stores a visibility index according to the determination result of the abnormal value determination unit 135. At this time, the visibility index storage unit 136 stores the visibility index as it is when the visibility index obtained by the visibility calculation unit 134 is a normal value, and sets the visibility index as an error when the visibility index is an abnormal value. Set to and store. The visibility index digitizing device 130 is configured by, for example, a dedicated or general-purpose computer.

  FIG. 6 is a flowchart showing a procedure for converting the visibility index into a numerical value used in this embodiment.

  This flowchart is an algorithm for extracting information related to poor visibility from a two-dimensional still image. A spatial frequency range with good human contrast sensitivity is specified, and a visibility index is obtained from the sum of power spectrum values within the range.

  First, it is determined which part of the input still image (road image) is to be cut out as an evaluation image. For example, adjustment is performed so that the entire distant road overlooking the image is included in the cut-out image. The image area is set to a power of 2 such that the number of pixels is 128 × 128 or 256 × 256 so that FFT processing can be performed. Since the image is a normal color, the representation of each image is converted to 256 gradations from 0 to 255 so that only the brightness component is present. This converted brightness component is called a pixel value (or pixel value) and is displayed on the screen in a gray scale (usually white to black).

  Next, using a two-dimensional FFT, the brightness density distribution for each pixel unit of the input evaluation image is Fourier-transformed and decomposed into spatial frequency components. The Fourier transform expresses the density distribution of pixels by superimposing trigonometric functions. The spatial frequency indicates the density distribution pattern of the image and its strength. The lack of high-frequency components means that the distance information is decreasing, and the strength of the spatial frequency means a situation where the subject to be imaged is covered with a veil. Snowstorm and fog affect the presence of high-frequency components (fine concentration distribution) and the strength of the entire spatial frequency (dynamic range of concentration distribution). The sum of squares of the amplitudes of various trigonometric functions subjected to Fourier transform is called a power spectrum and represents the strength corresponding to each spatial frequency.

  It is known that vision perceives only a certain spatial frequency band like auditory sense. The filter processing unit 133 extracts a power spectrum in a spatial frequency band with high human contrast sensitivity characteristics. In order to correspond to the human contrast sensitivity, the spatial frequency of the image is converted from the spatial frequency of “cycles / pixel (cpp: cycles / pixe1)” to the spatial frequency of “cycles / angle (cpd: cycles / degree)”. Set the bandwidth. The power spectrum values that have passed through this band are summed to obtain a visibility index.

  FIG. 7 is a flowchart showing the operation of the visibility index digitizing apparatus 130 in the present embodiment.

  First, the visibility index digitizing apparatus 130 performs a visibility index calculation process on a new image (S2000).

  FIG. 8 is a flowchart showing the contents of the visibility index calculation process (S2000) of FIG.

  First, the image input unit 131 performs the clipping operation for the FFT processing as described above (S2010), and then the FFT processing unit 132 performs the FFT processing (S2020). Specifically, two-dimensional frequency analysis of the input digital image is performed using FFT. Then, the filter processing unit 133 performs the above filter processing on the input power spectrum (S2030). Specifically, in consideration of the resolution of the camera and the lens field of view, the spatial frequency of the image is converted from the spatial frequency of “cycle / pixel (cpp)” to the spatial frequency of “cycle / angle (cpd)”. Apply a spatial frequency bandpass filter based on visual sensitivity. As the spatial frequency based on human visual sensitivity, for example, an area having good human visual sensitivity is used. For example, 1.5 cpd to 18 cpd adopted in the contrast sensitivity test is used as the region where the human visual sensitivity is good. Out of this range, that is, a spatial frequency region lower than 1.5 cpd or higher than 18 cpd is cut. Then, the visibility calculation unit 134 calculates a visibility index (S2040). Specifically, the power spectrum values in the spatial frequency of the high contrast sensitivity region after the filter processing are summed to obtain a visibility index. At this time, the visibility index of the image transmitted in the case of a camera failure or a wiring system failure is a value that does not fall within an assumed range. Therefore, the abnormal value determination unit 135 determines whether the visibility index obtained in step S2040 is a normal value or an abnormal value (S2050). This determination is performed based on whether or not the visibility index is within an assumed range. As a result of this determination, if the obtained visibility index is a normal value, the visibility index is stored as it is in the visibility index storage unit 136 (S2070). On the other hand, when the obtained visibility index is an abnormal value, the visibility index is set as an error (S2060) and stored in the visibility index storage unit 136 (S2070). After the storage process is completed, the process returns to the main flowchart of FIG.

  Then, the visibility index calculated in step S2000 is transferred to the visibility failure degree calculation device 210 of the visibility failure information collection unit 200 (S2100). Note that the series of processing from step S2000 to step S2100 is executed for all new images.

  FIG. 9 is a block diagram illustrating a configuration of the visibility failure information collection unit 200 according to the present embodiment.

  As described above, the visibility failure information collection unit 200 includes the visibility failure degree calculation device 210, the weather information collection device 220, the visibility failure information editing device 230, and the road map database 240. As shown in FIG. 9, the visibility obstacle degree calculation device 210 includes a visibility obstacle degree calculation unit 211 that calculates a visibility obstacle degree from a visibility index, and a visibility obstacle degree conversion table for calculating a visibility obstacle degree from a visibility index. 212. The visibility obstacle degree calculation device 210 (particularly, the visibility obstacle degree calculation unit 211) calculates the visibility obstacle degree from the visibility index, and outputs the visibility index to the visibility obstacle information editing device 230 in addition to the obtained visibility obstacle degree. . Further, the visibility failure information editing device 230 mainly edits the visibility failure information editing that collates each of the visibility failure degree, the road image, and the weather information related to the visibility on the road with the road map data. 231 and a visibility failure information database 232 storing the processing result of the visibility failure information editing unit 231. Note that the visibility index can be directly transmitted from the visibility index digitizing device 130 to the visibility failure information editing device 230 and recorded without passing through the visibility failure degree computing device 210.

  FIG. 10 is a flowchart showing a processing procedure of the visibility failure information collection unit 200 in the present embodiment.

  Visibility obstacle degree calculation part 211 judges whether there is a new visibility index from visibility index digitizing device 130 (S3000), and when there is a new visibility index (S3000: YES), visibility is determined. With reference to the obstacle degree conversion table 212, the visibility obstacle degree is calculated from the visibility index (S3100), and the visibility obstacle degree obtained together with the visibility index is the visibility obstacle information via the visibility obstacle information editing unit 231. It accumulates in the database 232 (S3200).

  Further, the visibility failure information editing unit 231 determines whether or not there is a new road image from the image collection device 120 (S3300). If there is a new road image (S3300: YES), the road image is displayed. It accumulates in the visibility failure information database 232 (S3400).

  In addition, the weather information collection device 220 determines whether there is new weather information from the weather information center 250 or the like (S3500). If there is new weather information (S3500: YES), the weather information collection device 220 displays the weather information. Then, it is stored in the visibility failure information database 232 via the visibility failure information editing unit 231 (S3600).

  The visibility failure information editing unit 231 determines whether there is new accumulated information in the visibility failure information database 232 (S3700). If there is new accumulated information (S3700: YES), the road map database 240 is determined. , The storage information is linked with road map data and stored (S3800).

  In addition, the process regarding three information, ie, the process regarding a visibility parameter | index (step S3000-step S3200), the process regarding a road image (step S3300-step S3400), and the process regarding a weather information (step S3500-step S3600) are not necessarily required. There is no need to execute (accumulate information) in this order, and preferably parallel processing is performed. Each time various kinds of information are accumulated in the visibility failure information database 232, accumulation linked to the road map data is performed (steps S3700 to S3800).

  FIG. 11 is a block diagram illustrating a configuration of the visibility failure information transmission unit 300 according to the present embodiment.

  As described above, the visibility failure information transmission unit 300 includes the Web server 310, the visibility failure information transmission device 320, and the visibility failure information search device 330. As shown in FIG. 11, the visibility failure information transmitting apparatus 320 includes a visibility failure degree text conversion unit 341 that converts the visibility failure degree into text characters, a visibility failure degree pictogram conversion unit 342 that converts the visibility failure degree into pictograms, A character for transmitting character information (text characters, pictograms) respectively output from the visibility failure degree sound conversion unit 343 that converts the visibility failure degree into sound data, and the visibility failure degree text conversion unit 341 and the visibility failure degree pictogram conversion unit 342 The information transmission unit 321, the audio information transmission unit 322 that transmits the audio information output from the visibility failure degree audio conversion unit 343, and the search result of the visibility failure information (visibility failure information ahead in the traveling direction of the vehicle) to the car navigation 450 It comprises a car navigation information transmission unit 323 for transmission.

  Further, the Web server 310 includes a visibility disorder degree text conversion unit 341, a visibility disorder degree pictogram conversion unit 342, and a visibility disorder degree character output from the visibility disorder degree text conversion unit 341 and the visibility disorder degree pictogram conversion unit 342, respectively. A PCWeb display unit 311 that displays a Web screen for the personal computer 410 and the information kiosk 420 using information (text characters, pictograms) and a specific road image and weather information stored in the visibility failure information database 232; Using the character information (text characters, pictograms) of the visibility impairment degree respectively output from the text conversion unit 341 and the visibility impairment pictogram conversion unit 342, and the specific road image and weather information accumulated in the visibility impairment information database 232, Mobile phone W that displays a Web screen for mobile phone 430 It is composed of a b display unit 312.

  Further, the visibility failure information search device 330 receives the vehicle position information (vehicle position, traveling direction, etc.) transmitted from the traveling vehicle on which the car navigation system 450 is mounted, and the received vehicle position information. In addition, a visibility failure information search unit 332 that searches for visibility failure information (visibility failure degree, road image, weather information) ahead of the traveling direction of the vehicle with reference to the visibility failure information database 232 is configured.

  In the present embodiment, the Web server 310 and the visibility failure information transmission device 320 are configured to share the visibility failure level text conversion unit 341 and the visibility failure level pictogram conversion unit 342. However, the present invention is not limited thereto. However, it is also possible to have a configuration in which the visibility disorder degree text conversion unit 341 and the visibility disorder degree pictogram conversion unit 342 are independently provided.

  FIG. 12 is a flowchart illustrating a processing procedure for request type information provision of the visibility failure information transmission unit 300 in the present embodiment. Here, the “request type” means a case where a user accesses and browses information such as a personal computer Web, an information kiosk, and a mobile phone Web.

  First, the visibility failure information transmission unit 300 refers to the visibility failure information database 232 in the visibility failure level text conversion unit 341 and the visibility failure level pictogram conversion unit 342, and the visibility failure level to be provided at regular time intervals. Are converted into text characters and pictograms (S4000), respectively, and the visibility failure information including the degree of visibility failure after conversion and the specific road image and weather information stored in the visibility failure information database 232 are respectively displayed on the Web display units 311 and 312. (S4100). In response to this, the PCWeb display unit 311 receives the text characters and pictograms output from the visibility disorder degree text conversion unit 341 and the visibility disorder degree pictogram conversion unit 342, respectively, and specific roads accumulated in the visibility disorder information database 232. The web screen for the personal computer 410 and the information kiosk 420 is displayed using the image and the weather information. Further, the mobile phone web display unit 312 stores the character information (text characters, pictograms) of the visibility disorder degree output from the visibility disorder degree text conversion unit 341 and the visibility disorder degree pictogram conversion unit 342 and the visibility disorder information database 232, respectively. The web screen for mobile phone 430 is displayed using the specific road image and weather information. Such a series of processes is performed at regular time intervals as described above, for example. That is, in this system, information is updated at regular time intervals.

  FIG. 13 is a flowchart illustrating a push-type information provision processing procedure of the visibility failure information transmission unit 300 according to the present embodiment. Here, the “push type” means a case where information is automatically provided according to conditions such as an emergency mail to a mobile phone, a road information board, and a road information radio.

  First, the visibility failure information transmission unit 300 is a constant time interval with reference to the visibility failure information database 232 in the visibility failure degree text conversion unit 341, the visibility failure degree pictogram conversion unit 342, and the visibility failure degree speech conversion unit 343. Then, the degree of visibility obstacle to be provided is converted into text characters, pictograms, and audio data (S5000), and the degree of visibility obstacle after conversion is stored in the visibility obstacle information transmitting device 320 (S5100). Then, it is determined whether or not the visibility failure degree exceeds a value (threshold value) set in advance by the user (S5200). If the visibility failure degree exceeds the set value (S5200: YES), the character information transmission unit The text information is transmitted to the emergency mail and road information board 440 of the personal computer 410 or the mobile phone 430 via 321 respectively, and the voice information is transmitted to the road information radio 460 via the voice information transmission unit 322 (S5300). As a result, it is possible to provide information according to the degree of visibility disorder required by the user, that is, the visibility disorder level (visibility level).

  FIG. 14 is a flowchart illustrating a processing procedure for providing information for car navigation by the visibility failure information transmitting unit 300 according to the present embodiment.

  When the vehicle position information receiving unit 331 receives information (vehicle position information) such as the traveling position and traveling direction of the vehicle from the car navigation system 450 mounted on the vehicle (S6000), the visibility disorder information transmitting unit 300 receives the visibility disorder information. The retrieval unit 332 retrieves and acquires information corresponding to the vehicle (visibility obstacle information ahead of the traveling direction of the vehicle) from the visibility obstacle information database 232 (S6100), and the obtained visibility obstacle information is stored in the visibility obstacle information transmission device 320. The data is transferred to the car navigation information transmission unit 323 (S6200). Then, the visibility failure information is transmitted to the car navigation system 450 of the vehicle via the car navigation information transmission unit 323 (S6300).

  FIG. 15 is a diagram illustrating an example of a screen display of the personal computer 410 or the information kiosk 420 in the present embodiment.

  A display screen 600 shown in FIG. 15 includes a map area 601 and two related information providing areas 602 and 603. In the map area 601, in addition to providing current view information (for example, four levels of view levels, that is, a visual disturbance degree) 604, an image 605 is also provided for camera points that can provide a road image. That is, the visual field level is provided for all the camera points in the section, and the image is further provided for points where the provision of camera images is permitted. As a result, the driver can keep track of the road field of view and can also help select routes. In the related information provision area 602, an overview is prepared so that the current visibility situation can be immediately grasped. The related information provision area 603 also provides weather prediction (future weather information) as reference data for future actions.

  FIG. 16 is a diagram illustrating an example of a screen display of the mobile phone 430 in this embodiment.

  On the display screen (Web image) 610 shown in FIG. 16A, the visibility situation on the route between points is displayed as a visibility obstacle degree (a symbol mark of a stepwise visibility level) 611. In addition, in the upper area 612 of the display screen 610, the current approximate visibility situation is displayed in text. Further, weather prediction (future weather information) is also provided in the lower area 613 of the display screen 610 as reference data for future actions. In addition, in the display screen (Web image) 610a shown in FIG. 16B, a camera that can provide a road image is provided by a camera icon (linked to the image and displayed by double-clicking) 614.

  FIG. 17 is a diagram showing an example of an emergency mail display of the mobile phone 430 in the present embodiment.

  In the example shown in FIG. 17, an emergency mail at the occurrence of a visibility failure is notified to the display unit 431 of the mobile phone 430.

  FIG. 18 is a diagram showing a display image of the road information board 440 in the present embodiment.

  In the example shown in FIG. 18, an overview is displayed on the display unit 441 of the road information board 440 so that the current visibility situation can be immediately grasped, and in some cases, weather prediction (future Weather information).

  FIG. 19 is a diagram showing an image of information provision on radio 460 in this embodiment.

  In the example shown in FIG. 19, an overview is transmitted via radio 460 so that the current visibility situation can be immediately grasped, and in some cases, weather forecasts (future weather information as future reference information) ).

  FIG. 20 is a diagram showing an image of information provision in car navigation system 450 in the present embodiment. FIG. 20A shows a case where the map is a two-dimensional display, and FIG. 20B shows a case where the map is a three-dimensional display. In the case of providing information by the car navigation system 450, information can be provided by updating the visibility information in front of the traveling direction as needed according to the traveling position of the vehicle, and information can also be provided by voice in addition to the car navigation screen.

  A display screen 670 shown in FIG. 20A is provided with a map area 671 and a related information provision area 672. In the map area 671, in addition to providing the current visibility information (for example, four levels of visibility levels, that is, the visibility failure degree) 673, the camera point that can provide the road image is also provided with the image 674, so that the driver can In addition to continuously grasping the road field of view, it can also be used for route selection. In particular, in the case of the car navigation system 450, in order to provide the visibility information after grasping the current position and traveling direction of the vehicle, the driver can more continuously grasp the visibility of the road and also select the route. Can be useful. In the related information provision area 672, an overview is prepared so that the current visibility situation can be immediately grasped. The blank area 675 in the map area 671 also provides weather prediction (future weather information) as reference data for future actions. On the display screen 670a shown in FIG. 20B, a three-dimensional map is displayed in the map area 671a.

  The driving support system having the above configuration and operation has the following various merits.

(1) The degree of visibility disturbance at multiple points can be quantified.
The degree of visibility disturbance (easy to see) is difficult to measure mechanically because human subjectivity is included. The camera image that directly determines the visibility by human eyes is a reliable and effective means of grasping the visibility disturbance, but it is qualitative data (it can express visibility and difficulty in viewing only by feeling) It was difficult to make an automatic determination, and it was impossible to grasp and determine the visibility disorder at many points in a short time and to provide it to many people. According to the present invention, it is possible to collect and grasp the degree of visibility failure at a large number of points where cameras have been installed almost in real time.

(2) It is possible to provide visibility failure information according to various user needs and user scenes.
A camera image cannot grasp a visibility disorder other than browsing as a video. According to the present invention, the degree of visibility disturbance is digitized from an image, so that it can be freely converted into text characters, pictograms, voices, and the like. For this reason, visibility disability information is made available to the driver by various means (homepage, mobile phone, e-mail, TV, radio, car navigation system, road information board, etc.) in various scenes including at home and at work as well as on the move. This point has the greatest merit of the present invention.

(3) It is possible to identify the most severely disturbed visibility.
Until now, for example, in the case of a heel section, only information with limited spots such as a camera image at the top of the ridge can be obtained. However, the visibility defect does not always occur at a specific location, and the visibility failure location changes depending on the situation. In addition, the visibility obstacles change from moment to moment as the weather changes. In the present invention, the visibility obstacle degree at a large number of points on a long road section can be provided in real time, so that it is obvious at a glance where the worst is and the advantage of clearly showing the actual visibility obstacle situation is great.

(4) The spatial movement of visibility disturbance can be grasped.
If the visibility information is limited to only a limited part of the heel section, the situation suddenly gets worse and suddenly gets better. In reality, however, visibility disorders are moving spatially. Since the visibility failure information transmitting apparatus 300 can provide a list of visibility failure statuses at a large number of points, it is possible to determine whether this forward visibility failure (line of sight) is worsened or improved, and how long is the change time? I can know.

(5) It is possible to fill in missing information.
Even if several road images are missing or water drops or snow adhere to one camera, it is possible to fill a hole because a plurality of road images are used. In addition, abnormal values can be eliminated and stable visibility failure information can be provided.

(6) Visibility failure information can be easily stored and a long-term visibility database can be constructed.
Until now, continuous visibility failures along the road have been limited to only a few locations, so behavior and countermeasures based on experience and intuition have been forced against visibility failures such as snowstorms and fog. The temporal and spatial accumulation of the degree of visibility impairment is as follows: 1) Where should the measures be concentrated? 2) When will it be easy for visibility impairment to occur? 3) Can be compared with other routes 4) Meteorological information It brings various benefits, such as being able to predict visibility impairment from the combination.

(7) Effective use and multi-functionality of road images are possible.
The road manager needs to browse and monitor a very large number of road images for a long time. Monitoring road images that require human judgment leads to an increase in the work burden, and there is also a concern that oversight due to human error may occur. Such problems can be cleared by collecting information on visibility and automatically determining whether it is good or bad. After receiving the warning about the deterioration of visibility failure automatically sent from the visibility failure information transmission device 320, the administrator only needs to check the road image directly, and the effort to wait for the occurrence of an event that does not know when it will occur is unnecessary. Contributes to improved management capabilities (such as oversight of visibility problems) and efficiency (such as reduction of image monitoring burden). Moreover, by incorporating the system of the present invention into a road image, the camera not only functions as a mere video collection device but also functions as a visibility failure (visibility) collection device. Can be planned.

  The driving support system according to the present invention is useful as a driving support system in which many people can simultaneously grasp a multi-point visibility problem in real time while suppressing an increase in cost.

1 is an overall configuration diagram of a driving support system according to an embodiment of the present invention. Explanatory drawing of the visibility evaluation method used in this embodiment The sequence diagram which shows the process of each component of the driving assistance system which concerns on this Embodiment Flowchart showing the operation of the image collection device in the present embodiment The block diagram which shows the structure of the visibility parameter | index digitization apparatus in this Embodiment. Flow chart showing the procedure for digitizing the visibility index used in the present embodiment The flowchart which shows operation | movement of the visibility parameter | index digitization apparatus in this Embodiment. The flowchart which shows the content of the visibility parameter | index calculation process of FIG. The block diagram which shows the structure of the visibility disorder | damage | failure information collection part in this Embodiment. The flowchart which shows the process sequence of the visibility disorder | damage | failure information collection part in this Embodiment. The block diagram which shows the structure of the visibility disorder | damage | failure information transmission part in this Embodiment. The flowchart which shows the processing procedure of request type | mold information provision of the visibility failure information transmission part in this Embodiment The flowchart which shows the processing procedure of push type | mold information provision of the visibility disorder | damage | failure information transmission part in this Embodiment. The flowchart which shows the process sequence of the information provision for car navigation of the visibility disorder | damage | failure information transmission part in this Embodiment The figure which shows an example of the screen display of the personal computer or information kiosk in this Embodiment The figure which shows an example of the screen display of the mobile telephone in this Embodiment The figure which shows an example of the display of the emergency mail of the mobile telephone in this Embodiment The figure which shows the image of a display of the road information board in this Embodiment The figure which shows the image of information provision with the radio in this Embodiment The figure which shows the image of information provision with the car navigation system in this Embodiment

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Visibility index digitizing part 110 Road camera 120 Image collecting device 130 Visibility index digitizing device 200 Visibility obstacle information collecting part 210 Visibility obstacle degree computing device 220 Weather information collecting device 230 Visibility obstacle information editing device 240 Road map database 250 Weather Information Center 300 Visibility Disorder Information Transmitting Unit 310 Web Server 320 Visibility Disorder Information Transmitting Device 330 Visibility Disorder Information Searching Device 341 Visibility Disturbance Degree Text Conversion Unit 342 Visibility Disturbance Degree Pictogram Conversion Unit 343 Visibility Disturbance Degree Voice Conversion Unit 410 Personal Computer 420 Information Kiosk 430 Mobile phone 440 Road information board 450 Car navigation system 460 Road information radio 470 GPS

Claims (19)

A visibility index calculation unit that performs image processing on a road image to calculate a road visibility index;
A visibility failure degree calculation unit that calculates a rank value of the visibility index calculated by the visibility index calculation unit as a visibility failure degree based on human subjective evaluation;
A visibility disorder information storage unit that stores visibility disorder information including the visibility disorder degree calculated by the visibility disorder degree calculation unit;
A visibility failure information providing unit that provides visibility failure information stored in the visibility failure information storage unit via a predetermined information transmission unit;
The visibility index calculation unit
The road image is converted into frequency components, the converted frequency distribution is filtered to obtain the frequency distribution of the region corresponding to human contrast sensitivity, and the road visibility index is calculated using the obtained frequency distribution. ,
Driving support system. The visibility index calculation unit
As the road image, an image taken by a camera installed along the road is input, and the input image is subjected to image processing to calculate a visibility index.
The driving support system according to claim 1. The visibility disturbance degree calculation unit
Grouping the visibility index based on human subjective evaluation to have a criterion for determining a rank value;
According to the determination criterion, the visibility index rank value calculated by the visibility index calculation unit is calculated as the visibility impairment degree.
The driving support system according to claim 1. The visibility disturbance degree is a rank value having any number of stages from 2 to 7.
The driving support system according to claim 3. The visibility disorder information storage unit is
As the visibility failure information, in addition to the visibility failure degree, at least one of the visibility index, the road image, and weather information is stored.
The driving support system according to claim 1. The visibility disorder information storage unit is
Means for obtaining road map data;
Storing the visibility disorder information in association with the road map data;
The driving support system according to claim 1. The visibility disorder information providing unit
Means for converting the visibility impairment degree stored in the visibility impairment information storage unit into text characters;
Means for converting the visibility failure degree stored in the visibility failure information storage unit into a pictograph;
Means for converting the visibility failure degree stored in the visibility failure information storage unit into sound, and at least one of
Providing the degree of visibility disturbance after conversion via the corresponding information transmission means;
The driving support system according to claim 1. The visibility disorder information providing unit
Have a web server,
The web server
Means for creating a web page suitable for the corresponding information transmission means using the visibility fault information in order to enable viewing of the visibility fault information stored in the visibility fault information storage unit;
Means for storing the created web page;
Having
The driving support system according to claim 1. The information transmission means is at least one of a personal computer, an information kiosk, and a mobile phone.
The driving support system according to claim 8. The visibility disorder information providing unit
A visibility failure information transmitter,
The visibility disorder information transmitting device is
Means for converting the visibility failure information stored in the visibility failure information storage unit into a data format suitable for the corresponding information transmission means;
Means for transmitting the visibility defect information after conversion to the information transmission means;
Having
The driving support system according to claim 1. The information transmission means is at least one of a personal computer, an information kiosk, a mobile phone, a road information board, a road information radio, and a car navigation system.
The driving support system according to claim 10. The visibility disorder information transmitting device is
When the visibility disturbance degree exceeds a predetermined threshold value, the converted visibility impairment information is transmitted to the information transmission means.
The driving support system according to claim 10. The information transmission means is at least one of a personal computer, a mobile phone, a road information board, and a road information radio.
The travel support system according to claim 12. The visibility disorder information providing unit
It further has a visibility disorder information search device,
The visibility disorder information retrieval device
Means for receiving vehicle position information;
Means for retrieving visibility failure information corresponding to the received vehicle position information from the visibility failure information storage unit,
The visibility disorder information transmitting device is
Means for converting visibility obstacle information retrieved by the visibility obstacle information retrieval device into a data format suitable for information transmission means mounted on the vehicle;
Means for transmitting the visibility defect information after conversion to the information transmission means;
Having
The driving support system according to claim 10. The information transmission means is a car navigation system.
The driving support system according to claim 14.   The visibility parameter | index calculation apparatus which comprises the visibility parameter | index calculation part used for the driving assistance system in any one of Claims 1-15.   A visibility obstacle degree calculation device constituting a visibility obstacle degree calculation unit used in the driving support system according to any one of claims 1 to 15.   A visibility failure information storage device constituting a visibility failure information storage unit used in the driving support system according to any one of claims 1 to 15.   A visibility failure information providing apparatus constituting a visibility failure information providing unit used in the driving support system according to any one of claims 1 to 15.

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