JP6005475B2 - In-vehicle device, danger prediction method, and program - Google Patents

Description

  The present invention relates to an in-vehicle device and the like.

  2. Description of the Related Art Conventionally, a device that predicts the danger of a collision from the behavior of another vehicle and avoids the collision has been developed (see Patent Document 1).

JP2011-242887

  For example, the conditions to determine that the vehicle is dangerous depending on the driver's driving skills of other mobile units, such as the age group of the driver driving the mobile unit ahead and the number of years since the license was acquired Different. However, in the conventional vehicle-mounted device, it has not been possible to predict the danger according to the state relating to the driving skill of the driver of another moving body.

  The vehicle-mounted device according to the first aspect of the present invention relates to a risk determination condition storage unit that stores one or more risk determination conditions for determining a risk, and other driver related information that is information relating to drivers of other mobile objects. A risk determination that determines whether or not the other driver related information acquisition unit that acquires information and the other driver related information acquired by the other driver related information acquisition unit matches one or more of the risk determination conditions And a danger notification unit that outputs a danger message when the risk determination unit determines that one of the one or more risk determination conditions is met.

  With such a configuration, it is possible to perform risk prediction according to the state relating to the driving skill of the driver of another moving body.

  Further, the in-vehicle device of the second aspect of the present invention further includes a traveling state information acquisition unit that acquires traveling state information, which is information related to the traveling state, with respect to the first invention, Determine whether the other driver related information acquired by the other driver related information acquisition unit and the driving situation information acquired by the driving situation information acquisition unit match any one or more of the risk determination conditions It is an in-vehicle device.

  With such a configuration, it is possible to perform risk prediction according to the state relating to the driving skill of the driver of another moving body.

  Further, in the in-vehicle device according to the third aspect of the present invention, the other driver related information acquisition unit is a front image acquisition unit that acquires a front image that is an image in front of the moving body. The vehicle-mounted device includes other driver related information acquisition means for acquiring other driver related information from the front image acquired by the front image acquisition means.

  With such a configuration, the state relating to the driving skill of the driver of another moving body can be acquired using the front image.

  Further, in the in-vehicle device of the fourth invention, in contrast to the third invention, the other driver related information acquisition unit stores a driver sign image in which one or more driver sign images indicating the driver sign are stored. And a driver sign area detecting means for detecting an area that matches one of the one or more driver sign images from the front image acquired by the front image acquiring means. The driver sign information indicating the driver classification corresponding to the driver sign image that matches the area detected by the driver sign area detection means is acquired, and the risk determination section is acquired by the other driver related information acquisition section. This is an in-vehicle device that determines whether or not the driver classification information matches any one or more of the risk determination conditions.

  With such a configuration, the state relating to the driving skill of the driver of another moving body can be acquired based on the driver sign in the front image.

  In addition, the vehicle-mounted device according to the fifth aspect of the present invention is a number in which the other-driver related information acquisition unit detects a region that matches the license plate from the front image acquired by the front image acquisition unit. The plate area detection means further includes other driver related information acquisition means for acquiring license plate information indicating the contents described in the license plate from the area detected by the license plate area detection means. This is a vehicle-mounted device that determines whether or not the license plate information acquired by the other driver related information acquisition unit matches any one or more risk determination conditions.

  With such a configuration, the state relating to the driving skill of the driver of another moving body can be acquired based on the license plate in the front image.

  Further, in the in-vehicle device of the sixth aspect of the invention, in contrast to the fifth aspect of the invention, the other driver related information acquisition unit is described as a license plate condition that is a condition related to the contents described in the license plate. License plate management information storage means for storing one or more license plate management information having driver year information indicating the number of years related to the driver indicated by the contents, and the other driver related information acquisition means includes license plate information The driver year information corresponding to the license plate condition that matches is acquired from the license plate management information storage means, and the risk determination unit determines that the driver year information acquired by the other driver related information acquisition unit is 1 or more. This is an in-vehicle device that determines whether or not any of the conditions is met.

  With such a configuration, the state relating to the driving skill of the driver of another moving body can be acquired based on the license plate in the front image.

  In the on-vehicle device according to the seventh aspect of the invention, the other-driver related information acquisition unit receives other-driver related information that is information related to the driver of another moving body, relative to the first or second invention. It is an in-vehicle device provided with other driver related information receiving means.

  With such a configuration, the state relating to the driving skill of the driver of another mobile body can be received from the other mobile body.

  The on-vehicle device according to the eighth aspect of the present invention is the on-vehicle device that performs output according to the risk judgment condition determined by the risk judgment unit to match with any one of the first to seventh inventions. It is.

  With such a configuration, it is possible to change the output method, contents, and the like according to the determination result indicating the danger.

  Moreover, the vehicle-mounted device of the ninth aspect of the invention is a vehicle-mounted device that outputs a screen indicating that the danger notification unit is dangerous to any one of the first to eighth aspects of the invention.

  With such a configuration, it is possible to output a screen indicating a danger.

  According to the vehicle-mounted device or the like according to the present invention, it is possible to perform the risk prediction according to the state relating to the driving skill of the driver of another moving body.

Block diagram of in-vehicle device 1 in the first embodiment A flowchart for explaining the overall operation of the in-vehicle device 1 A flowchart for explaining whether or not the risk judgment condition is met. Figure showing an example of the same risk judgment condition Figure showing an example of the driver sign image Figure showing an example of the license plate management information The figure which shows the example of the front image The figure which shows the example of the contour extraction from the front image The figure which shows the example of a detection of the driver | operator sign area | region from the front image Figure showing an example of the same screen output Figure showing an example of the same screen output The figure which shows the example of detection of the license plate area from the front image Figure showing an example of the same risk judgment condition Overview of the computer system in the above embodiment Block diagram of a computer system in the above embodiment

  Hereinafter, embodiments of an in-vehicle device and the like according to the present invention will be described with reference to the drawings. In addition, since the component which attached | subjected the same code | symbol in embodiment performs the same operation | movement, description may be abbreviate | omitted again. In addition, the format, content, and the like of each information described in this embodiment are merely examples, and the format, content, and the like are not limited as long as the meaning of each information can be indicated.

(Embodiment 1)
In this embodiment, an in-vehicle device 1 that performs risk prediction according to a driver's state such as the age of a driver of another mobile body, an age group, and whether or not a driver is a beginner will be described.

  The in-vehicle device 1 according to the present embodiment is, for example, a car navigation system, a display / audio, or the like, and is usually mounted on a moving body. The moving body is, for example, an automobile, a motorcycle, a bicycle, or the like. The moving body may include a person.

  FIG. 1 is a block diagram of an in-vehicle device 1 in the present embodiment. The in-vehicle device 1 includes a risk determination condition storage unit 11, another driver related information acquisition unit 12, a traveling situation information acquisition unit 13, a risk determination unit 14, and a risk notification unit 15. The other driver related information acquisition unit 12 includes a driver sign image storage unit 121, a license plate management information storage unit 122, a front image acquisition unit 123, a driver sign region detection unit 124, a license plate region detection unit 125, and the like. Driver related information acquisition means 126 and other driver related information reception means 127 are provided.

  The risk determination condition storage unit 11 stores one or more risk determination conditions for determining a risk. The risk determination condition is usually a driver (hereinafter, appropriately, other driving) of another moving body (hereinafter, appropriately, other vehicle) that is not a moving body (hereinafter, appropriately, own vehicle) in which the vehicle-mounted device 1 is mounted. Is a condition related to the other driver.

  The other driver-related condition is a condition related to other driver-related information that is information related to a driver of another vehicle. The other driver related information is, for example, provided in the driver classification information indicating the classification of the other driver, the driver year information that is information related to the number of years of the other driver, or the moving body in which the other driver is driving. License plate information indicating the contents described in the license plate. The driver classification information is information indicating, for example, whether the driver is a beginner or an elderly person. Further, the driver classification information may be information indicating whether the driver is a visually handicapped person or a physically handicapped person, for example. The driver year information is information indicating, for example, the age of the driver, the age group of the driver, the driver's license acquisition year, the driving history, and the like. The number of years of license acquisition may be the number of months. Further, the license plate information is usually information indicating characters written on the license plate. The characters include numbers. Moreover, the said character is a headquarters, a classification number, a business discrimination character, a designated number, etc., for example. Further, the character may be, for example, a birth date, a license acquisition year, a number or a symbol indicating a driver classification, and the like. The license plate information may be information indicating the size of the license plate, the color of the license plate, and the like.

  From the above, other driver-related conditions include, for example, “the driver is a beginner”, “the driver's age is a predetermined age or higher”, and “the driver's age group is a predetermined age group” “The classification number written on the license plate is a predetermined number”.

  The other driver related information may be, for example, driver sign information that is information indicating a driver sign affixed to another vehicle. The driver sign is an initial driver sign called a so-called beginner mark, an old driver sign called a so-called elderly mark, or the like. The driver sign information is usually a driver sign image that is an image showing the driver sign, but may be driver classification information.

  The other driver-related condition may be, for example, a combination of conditions related to two or more types of information among the other driver-related information. The combination is usually a logical sum (OR), but may be a logical product (AND). For example, in the case of a combination of a condition relating to driver classification information and a condition relating to driver age information indicating the age of the driver, the other driver-related condition is, for example, “the driver is an elderly person, or The driver must be 70 years of age or older. In addition, in the case of a combination of the conditions related to the driver classification information and the conditions related to the driver license acquisition years information indicating the driver's license acquisition years, the other driver related condition is, for example, “the driver is a beginner. Or the driver's license has been acquired for less than one year. "

  Further, the danger determination condition may include a traveling condition condition that is a condition related to a traveling condition. The traveling situation condition is a condition relating to traveling situation information, which is information related to a traveling situation. The traveling situation information includes, for example, road-related information that is information relating to the road on which the vehicle is traveling, speed-related information that is information relating to the speed at the time of traveling, information related to other moving bodies that is information relating to relationships with other vehicles, weather Information related to the weather. As long as the traveling situation information is information related to the traveling situation, the type and content thereof are not limited.

  The road-related information is information indicating, for example, the road type, road structure, road name, road speed limit, and the like. Examples of road types include expressways, general roads, prefectural roads, and city roads. The road structure is, for example, a tunnel, a bridge, or an elevated.

  The speed-related information is information indicating, for example, the speed of the moving body, the acceleration of the moving body, the angular velocity of the moving body, the angular acceleration of the moving body, the change in the speed of the moving body, and the like. The change in speed is, for example, being faster or slower.

  In addition, the other mobile body related information includes, for example, the distance between the own vehicle and the other vehicle (inter-vehicle distance), the difference in speed between the own vehicle and the other vehicle, the difference in traveling direction between the own vehicle and the other vehicle, and the inter-vehicle distance. This is information indicating a change in the. The change in the inter-vehicle distance includes, for example, a decrease in the inter-vehicle distance, an increase in the inter-vehicle distance, approaching another vehicle, and moving away from the other vehicle.

  The weather related information is information indicating, for example, weather, precipitation, wind speed, wind direction, and the like.

  From the above, the traveling condition conditions are, for example, “running on a highway”, “running on a tunnel”, “running on a road having a narrower width than a predetermined width”, “It must be at a speed higher than the predetermined speed”, “The speed is increasing”, “It is a distance between vehicles below a predetermined distance”, “It is approaching another vehicle ahead”, “ "It's falling".

  Moreover, when it has driving condition conditions, a danger judgment condition is usually a combination of other driver related conditions and driving condition conditions. The combination is usually a logical product (AND), but may be a logical sum (OR).

  Moreover, the notification content information which shows the content which the below-mentioned danger alerting | reporting part 15 outputs may respond | correspond to the danger judgment conditions. The notification content information is, for example, “screen output” indicating that a danger message is output on the screen, “warning sound” indicating that a warning message is output using a warning sound, and characters to be output to the screen. “Danger!”, “Alert.mp3” for identifying a warning sound, and the like.

  The other driver related information acquisition unit 12 acquires other driver related information that is information related to the driver of the other vehicle. The other vehicle is usually in front of the own vehicle, but may be behind, left or right of the own vehicle. The “acquisition” includes “reception”. Further, the other driver related information acquisition unit 12 normally acquires the other driver related information periodically. Moreover, the other driver relevant information acquisition part 12 may acquire other driver relevant information according to the instruction | indication from a user, for example. Further, the other driver related information acquisition unit 12 usually acquires the other driver related information by means described later. That is, other driver related information acquired by each means described later is road related information acquired by the other driver related information acquisition unit 12.

  The driver sign image storage means 121 stores one or more driver sign images that are images indicating driver signs. The driver sign image is usually associated with driver classification information.

  The license plate management information storage means 122 stores one or more license plate management information having license plate conditions and other driver related information. The license plate condition is a condition regarding the contents described in the license plate, and is a condition regarding the license plate information. Further, the other driver related information included in the license plate management information is usually driver year information. Further, the driver year information may be, for example, an expression for calculating the driver year information from the license plate information, a program, or the like. In this case, the expression and program usually have variables and arguments for substituting license plate information.

  The front image acquisition unit 123 acquires a front image that is an image ahead of the moving body. The front image may be a video having the two or more images. The front image acquisition unit 123 acquires a front image, usually from an image sensor (solid-state imaging device) such as a CMOS or CCD, or a camera (digital still camera, digital video camera) using the image sensor. In this case, the front image acquisition unit 123 may include, for example, these devices, or may be realized by these devices. Further, the processing procedure of the front image acquisition means 123 is usually realized by software, and the software is recorded in a recording medium such as a ROM.

  The driver sign area detection unit 124 detects an area that matches the driver sign image from the front image acquired by the front image acquisition unit 123. The driver sign image is one of one or more driver sign images stored in the driver sign image storage unit 121. The driver sign image is usually an image that becomes a pattern in so-called pattern recognition. Further, an area that matches the driver sign image in the front image is hereinafter referred to as a driver sign area as appropriate. The term “match” is widely understood, including, for example, roughly matching, matching rate being a predetermined rate or more, matching as a result of considering rotation and inclination, and the like. The “match” is synonymous with “match”.

  In addition, the driver sign area detecting unit 124 detects the driver sign area by, for example, contour extraction (edge detection), pattern recognition of the extracted contour, or the like. For the pattern, a driver sign image is usually used. Note that contour extraction, pattern recognition, and the like are well-known techniques, and thus detailed description thereof is omitted. The method for detecting the driver sign area is not limited as long as the area can be detected.

  In addition, the driver sign area detecting means 124 usually acquires a driver sign image that matches the area by detecting the driver sign area. In addition, the driver sign area detection unit 124 may acquire, for example, an image of the area or two or more coordinates indicating the area by detecting the driver sign area. The image in the region is obtained by trimming the front image. Hereinafter, the image of the area is appropriately referred to as a driver sign area image. Moreover, the said coordinate is a coordinate in a front image.

  The license plate area detection unit 125 detects an area that matches the license plate from the front image acquired by the front image acquisition unit 123. The license plate area detecting means 125 normally holds an image showing the shape of the license plate. Hereinafter, the image is referred to as a license plate image. The image is usually an image that becomes a pattern in so-called pattern recognition. In addition, an area that matches the license plate in the front image is hereinafter appropriately referred to as a license plate area. The term “match” is widely understood, including, for example, roughly matching, matching rate being a predetermined rate or more, matching as a result of considering rotation and inclination, and the like.

  Note that the license plate area detecting means 125 normally detects the number plate area by the same method or means as the method or means for detecting the driver sign area by the driver sign area detecting means 124. Therefore, description of the method and means for detecting the license plate area is omitted.

  In addition, the license plate area detection unit 125 normally acquires an image of the area by detecting the license plate area. The image in the region is obtained by trimming the front image. In addition, the image of the area is hereinafter referred to as a license plate area image as appropriate. Further, the license plate area detection unit 125 may acquire, for example, two or more coordinates indicating the area by detecting the license plate area. The said coordinate is a coordinate in a front image.

  The other driver related information acquisition unit 126 acquires other driver related information from the front image acquired by the front image acquisition unit 123. The other driver related information acquisition means 126 normally acquires other driver related information from the driver sign area detected by the driver sign area detection means 124 or the license plate area acquired by the license plate area detection means 125. .

  For example, when the driver sign area detecting unit 124 detects the driver sign area and acquires a driver sign image that matches the driver sign area, the other driver related information acquiring unit 126 normally Driver classification information corresponding to the driver sign image is acquired from the driver sign image storage means 121. In this case, the other driver related information acquisition unit 126 may acquire the driver sign image acquired by the driver sign region detection unit 124, for example.

  Further, for example, when the driver sign region detection unit 124 acquires the driver sign region image as a result of detecting the driver sign region, the other driver related information acquisition unit 126 determines that the driver sign region matches the driver sign region. The driver classification information corresponding to the driver sign image obtained is acquired from the driver sign image storage means 121. The same applies when the driver sign area detection means 124 acquires two or more coordinates indicating the driver sign area.

  Further, for example, when the license plate area detection unit 125 acquires a license plate area image as a result of detecting the license plate area, the other driver related information acquisition unit 126 normally extracts the license plate area image from the license plate area image. Get license plate information that is the character of. Usually, OCR (Optical Character Recognition) is used to acquire characters in the image. Since OCR is a known technique, detailed description thereof is omitted.

  In addition, for example, when the license plate area detection unit 125 detects two or more coordinates indicating the number plate area as a result of detecting the number plate area, the other driver related information acquisition unit 126 usually has the two or more. A license plate area image that is an image of an area indicated by coordinates is acquired. Then, the other driver related information acquisition unit 126 acquires license plate information that is a character in the image by the same method as described above.

  Further, for example, after acquiring the license plate information, the other driver related information acquisition unit 126 acquires the driver year information corresponding to the license plate condition that the license plate information matches from the license plate management information storage unit 122. May be. In this case, the other driver-related information acquisition unit 126 usually matches any of the license plate conditions that the acquired license plate information has in one or more license plate management information stored in the license plate management information storage unit 122. Judge whether to do.

  For example, it is assumed that the license plate information is a classification number “330”. For example, it is assumed that the license plate condition is “classification number = 3 **”. The license plate condition means that the first digit of the classification number is “3”. In this case, the other driver related information acquisition unit 126 determines that the license plate information matches the license plate condition.

  Further, for example, it is assumed that the license plate information is the designated number “34-99”. Further, for example, it is assumed that the license plate condition is “designated number = ** − 99”. The license plate condition means that the last two digits of the designated number are “99”. In this case, the other driver related information acquisition unit 126 determines that the license plate information matches the license plate condition.

  The other driver related information receiving means 127 receives the other driver related information. The other driver related information receiving means 127 usually receives the other driver related information by so-called inter-vehicle communication. Further, the other driver related information receiving means 127 is usually realized by a wireless or wired communication means, but may be realized by a means for receiving a broadcast. Further, the processing procedure of the other driver related information receiving means 127 is usually realized by software, and the software is recorded in a recording medium such as a ROM.

  The other driver related information acquisition unit 12 may include a moving body region detecting unit that detects a moving body region that is a region matching the moving body from the front image. In this case, the moving body region detection means detects the region by, for example, contour extraction (edge detection) or pattern recognition of the extracted contour. In this case, the driver sign area detecting means 124 usually detects the driver sign area from the moving object area in the front image. Further, the license plate area detecting means 125 normally detects the license plate area from the moving body area in the front image. The method and procedure for detecting the driver sign area and the license plate area from the moving body area are the same as the method and procedure for detecting the driver sign area and the license plate area from the front image. Is omitted.

  The traveling situation information acquisition unit 13 acquires traveling situation information. The travel situation information acquisition unit 13 usually acquires travel situation information regularly. Moreover, the driving situation information acquisition unit 13 may acquire the driving situation information according to an instruction from the user, for example.

  For example, when acquiring road-related information, the traveling situation information acquisition unit 13 normally includes a map information storage unit (not shown) and a current position information acquisition unit (not shown). The map information storage means stores map information indicating a map. Further, the current position information acquisition unit acquires current position information indicating the current position.

  The kind of map which map information shows is not ask | required. The map information is usually in the KIWI format used in car navigation, but may be, for example, so-called raster data or so-called vector data. In addition, the map information usually has one or more road information indicating roads. The road information is usually information having one or more pieces of information for expressing roads on a map. The road information is usually road type information indicating the type of road, road structure information indicating the structure of the road, road name information indicating the name of the road, road section information indicating the section of the road, starting point, ending point, and passage of the road. It has road position information indicating the position of a point or the like. The position information is usually longitude and latitude information indicating longitude and latitude. The map information may include, for example, terrain information indicating terrain, terrain range information indicating the range of the terrain, and the like. The terrain range information usually has one or more position information, and the terrain range is indicated by the position indicated by the one or more position information. Moreover, the map information may have, for example, one or more pieces of point information indicating one or more points on the map. Such points include, for example, stations, tourist attractions, parks, theme parks, and other structures.

  The current position information is usually information indicating longitude and latitude, but may be information indicating coordinates on the map, altitude, and the like.

  For example, when acquiring road-related information indicating the type of road (hereinafter referred to as road type information as appropriate), the driving situation information acquisition unit 13 normally uses the current position information acquired by the current position information acquisition unit, Get road type information. For example, the traveling state information acquisition unit 13 first acquires road information indicating a road located at the current position indicated by the current position information from one or more road information included in the map information stored in the map information storage unit. To do. At this time, the traveling situation information acquisition unit 13 normally determines whether or not the distance between the current position indicated by the current position information and the road position indicated by the road position information included in the road information is short. Identify the road located at the current location. And the driving | running | working condition information acquisition part 13 acquires the road type information which the said road information has from the acquired road information. The method and procedure for acquiring other road-related information such as the structure of the road are the same as the method and procedure for acquiring road type information, and thus description thereof is omitted.

  In addition, for example, when acquiring speed-related information, the running-time situation information acquisition unit 13 acquires speed-related information from an acceleration sensor, a gyro, a device that displays information acquired from these devices, or the like. Further, in this case, the traveling situation information acquisition unit 13 may have, for example, these devices or may be realized by these devices.

  In addition, for example, when acquiring other moving body related information, the traveling state information acquisition unit 13 is, for example, a laser distance measuring device, a device for measuring a distance such as an infrared distance sensor, or an image in front of the host vehicle. From devices such as image sensors (solid-state imaging devices) such as CMOS and CCD that acquire front images, cameras using image sensors (digital still cameras, digital video cameras), speed sensors that measure the speed of other vehicles, etc. Get mobile object related information. In this case, the running situation information acquisition unit 13 may have, for example, these devices or may be realized by these devices. Note that the front image may be a front image acquired by the front image acquisition unit 123.

  For example, when weather-related information is acquired, the travel-time situation information acquisition unit 13 normally acquires weather-related information from devices such as an illuminometer, a cloud meter, and an anemometer. In this case, the running situation information acquisition unit 13 may have, for example, these devices or may be realized by these devices.

  In the above case, the processing procedure of the traveling situation information acquisition unit 13 is usually realized by software, and the software is recorded in a recording medium such as a ROM.

  The other driver related information acquisition unit 12 and the traveling situation information acquisition unit 13 respectively acquire predetermined information according to the contents of the risk determination conditions stored in the risk determination condition storage unit 11, for example. May be.

  For example, when the risk determination condition includes a condition related to the driver classification information, the other driver related information acquisition unit 12 acquires the driver classification information. Specifically, for example, the other driver related information acquisition unit 126 acquires the driver classification information by using the driver sign area detected by the driver sign area detection unit 124.

  Further, for example, when the risk determination condition includes a condition related to license plate information, the other driver related information acquisition unit 12 acquires license plate information. Specifically, for example, the other driver related information acquisition unit 126 acquires the license plate information using the license plate region detected by the license plate region detection unit 125.

  Further, for example, when the risk determination condition includes a condition related to the driver age information, the other driver related information acquisition unit 12 acquires the driver age information. Specifically, for example, the other driver related information acquisition unit 126 acquires the driver age information corresponding to the license plate condition that the acquired license plate information matches from the license plate management information storage unit 122.

  In addition, for example, when the risk determination condition includes a condition regarding road type information, the traveling situation information acquisition unit 13 acquires road type information. Further, for example, when the risk determination condition includes a condition related to other moving body related information indicating the inter-vehicle distance, the traveling state information acquisition unit 13 acquires other moving body related information indicating the inter-vehicle distance. For example, when the danger determination condition includes a condition related to weather-related information indicating the weather, the traveling situation information acquisition unit 13 acquires weather-related information indicating the weather.

  The risk determination unit 14 determines whether or not the other driver related information acquired by the other driver related information acquisition unit 12 meets any one or more of the risk determination conditions. Further, the risk determination unit 14 may determine, for example, whether the other driver related information does not match any of the one or more risk determination conditions.

  For example, it is assumed that the other driver related information acquired by the other driver related information acquisition unit 12 is the driver classification information “beginner”. For example, it is assumed that the risk determination condition is “(classification = beginner) or (number of years of license acquisition ≦ 1 year)”. The risk judgment condition means that the driver is a beginner or the driver's license acquisition period is one year or less. In this case, the risk determination unit 14 determines that the driver classification information matches the risk determination condition.

  Further, for example, it is assumed that the other driver related information acquired by the other driver related information acquisition unit 12 is driver age information “72 years old” indicating the age of the driver. Further, for example, it is assumed that the risk judgment condition is “(classification = elderly) or (age ≧ 70 years old)”. The risk judgment condition means that the driver is an elderly person or that the driver's age is 70 years or older. In this case, the risk determination unit 14 determines that the driver age information matches the risk determination condition.

  Further, for example, it is assumed that the other driver related information acquired by the other driver related information acquisition unit 12 is the license plate information “Kobe 330 is 12-34”. Further, for example, it is assumed that the risk judgment condition is “classification number = 33 *”. The risk judgment condition means that the first two digits of the classification number written on the license plate are “33”. In this case, the risk determination unit 14 determines that the license plate information matches the risk determination condition.

  Further, for example, it is assumed that the other driver related information acquisition unit 12 acquires driver classification information “beginner” and driver license acquisition year information “8 months” indicating the driver's license acquisition year. Further, for example, it is assumed that the risk judgment condition is “(age ≧ 70 years old) or (license acquisition years ≦ 1 year)”. The risk judgment condition means that the driver's age is 70 years or older, or the driver's license acquisition period is one year or less. In this case, the risk determination unit 14 determines that the driver license acquisition year information of the two other driver related information acquired by the other driver related information acquisition unit 12 matches the risk determination condition.

  Further, for example, it is assumed that the other driver related information acquisition unit 12 acquires the driver classification information “elderly”. Further, for example, it is assumed that the traveling situation information acquisition unit 13 acquires road type information “highway”. Further, for example, it is assumed that the risk determination condition is “(classification = elderly) & (road type = highway)”. The risk judgment condition means that the driver of the other vehicle ahead is an elderly person and is traveling on a highway. In this case, the risk determination unit determines that the driver classification information and the road type information match the risk determination condition.

  Further, for example, when the notification content information is associated with the risk determination condition, the risk determination unit 14 usually displays the notification content information associated with the risk determination condition determined that the other driver-related information matches with the risk determination condition. Obtained from the judgment condition storage unit 11.

  The risk notification unit 15 is dangerous when the risk determination unit 14 determines that the other driver related information acquired by the other driver related information acquisition unit 12 matches one or more of the risk determination conditions. Outputs the effect. Further, for example, the danger notification unit 15 outputs a danger message when the danger determination unit 14 determines that the other driver-related information does not match any one or more of the risk determination conditions. Also good.

  The “outputting the danger” usually means outputting information indicating the danger. The output includes display on a display, sound output, projection using a projector, printing with a printer, transmission to an external device, storage in a recording medium, and other processing devices and other programs. It is a concept that includes delivery of processing results. In addition, regarding transmission, accumulation, and delivery of processing results, an output target is finally presented to the user. Further, as a result of transmission, storage, and delivery of processing results, for example, a device such as a so-called drive recorder may be started, or video recording by a so-called video camera or digital camera may be started. Further, as a result of the output, the user is usually notified that it is dangerous.

  In addition, “dangerous” means, for example, that the driver of the front moving body is a beginner of driving, the driver of the front moving body is an elderly person, or the sudden braking of the front moving body. This is widely understood, including attention to the vehicle, attention to the distance between the vehicle and the vehicle in front, and attention to driving.

  In addition, the output method and means are usually determined in advance, but this need not be the case. Otherwise, the danger notification unit 15 may output a danger message according to the notification content information acquired by the danger determination unit 14, for example. For example, if the notification content information is “screen output”, the danger notification unit 15 outputs, for example, characters and images on the screen. For example, if the notification content information is “warning sound”, the danger notification unit 15 outputs, for example, a predetermined warning sound or a warning sound included in the notification content information.

  Moreover, the danger alerting | reporting part 15 outputs on the screen that it is dangerous normally. In the case of outputting the screen, for example, when the map is output on the screen or when the front image is output, the danger notification unit 15 normally outputs the output content that has already been output. Overlay and output text and images.

  Also, the risk notification unit 15 normally determines that the risk determination unit 14 does not meet any one or more of the risk determination conditions after determining that the risk determination unit 14 meets any one or more of the risk determination conditions. During that time, it keeps outputting that it is dangerous. Further, for example, the danger notification unit 15 outputs that the danger determination unit 14 is dangerous for a predetermined time after determining that the danger determination unit 14 meets one of the one or more risk determination conditions, and then outputs the output. You may end.

  Further, the danger notification unit 15 may or may not include an output device such as a display or a speaker. The danger notification unit 15 can be realized by driver software of an output device or driver software of an output device and an output device.

  The risk judgment condition storage unit 11, the driver sign image storage unit 121, and the license plate management information storage unit 122 are preferably non-volatile recording media, but can also be realized by volatile recording media. Moreover, the process in which predetermined information is memorize | stored in the danger judgment condition storage part 11 does not ask | require. For example, the predetermined information may be stored in the risk determination condition storage unit 11 via a recording medium, a communication line, an input device, or the like.

  Further, the other driver related information acquisition unit 12, the driver sign area detection unit 124, the license plate area detection unit 125, the other driver related information acquisition unit 126, and the risk determination unit 14 are usually realized by an MPU, a memory, or the like. obtain. Further, the processing procedure of the other driver related information acquisition unit 12 and the like is usually realized by software, and the software is recorded in a recording medium such as a ROM. The other driver related information acquisition unit 12 and the like may be realized by hardware (dedicated circuit).

  Next, the overall operation of the in-vehicle device 1 will be described using a flowchart. Note that the i-th information in the predetermined information is described as “information [i]”. FIG. 2 is a flowchart showing the overall operation of the in-vehicle device 1.

  (Step S201) The in-vehicle device 1 determines whether or not a reception unit (not shown) has received a power-on instruction. If accepted, the process proceeds to step S202; otherwise, the process returns to step S201.

  (Step S202) The in-vehicle device 1 performs a power ON process.

  (Step S203) The in-vehicle device 1 determines whether or not a reception unit (not shown) has received a power-off instruction. If accepted, the process proceeds to step S204; otherwise, the process proceeds to step S205.

  (Step S204) The in-vehicle device 1 performs a power-off process.

  (Step S205) The front image acquisition unit 123 determines whether or not it is the timing for acquiring the front image. For example, when it is determined in advance that the forward image is to be periodically acquired, the forward image acquisition unit 123 determines whether or not a predetermined time has elapsed since the previous image was previously acquired. If it is the acquisition timing, the process proceeds to step S206. If not, the process proceeds to step S210.

  (Step S206) The front image acquisition means 123 acquires a front image.

  (Step S207) The driver sign area detecting unit 124 determines whether one or more driver sign images are stored in the driver sign image storing unit 121. If stored, the process proceeds to step S208; otherwise, the process proceeds to step S211.

  (Step S208) The driver sign area detecting means 124 detects the driver sign area from the front image acquired in Step S206.

  (Step S209) The other driver related information acquisition unit 126 acquires the driver classification information from the driver sign image storage unit 121 using the driver sign region detected in Step S208.

  (Step S210) The other driver related information acquisition unit 12 determines whether or not the other driver related information receiving unit 127 has received the other driver related information. If received, the process proceeds to step S215; otherwise, the process returns to step S203.

  (Step S211) The license plate area detecting means 125 detects the license plate area from the front image acquired in step S206.

  (Step S212) The other driver related information acquisition means 126 acquires license plate information from the license plate area detected in step S211.

  (Step S213) The other driver related information acquisition unit 126 determines whether or not one or more license plate management information is stored in the license plate management information storage unit 122. If stored, the process proceeds to step S214; otherwise, the process proceeds to step S215.

  (Step S214) The other driver related information acquisition unit 126 acquires driver year information corresponding to the license plate condition that matches the license plate information acquired in step S213 from the license plate management information storage unit 122.

  (Step S215) The traveling situation information acquisition unit 13 determines whether it is the timing for acquiring the traveling situation information. For example, when it is determined in advance that periodic travel situation information is acquired, the travel situation information acquisition unit 13 determines whether or not a predetermined time has elapsed since the previous travel situation information was acquired. to decide. If it is the acquisition timing, the process proceeds to step S216. If not, the process proceeds to step S217.

  (Step S216) The traveling situation information acquisition unit 13 acquires the traveling situation information.

  (Step S217) The risk determination unit 14 stores the other driver related information acquired by the other driver related information acquisition unit 12 and the travel situation information acquired by the travel situation information acquisition unit 13 in the risk determination condition storage unit 11. It is determined whether or not any one or more stored risk determination conditions are met. Details of this processing will be described with reference to the flowchart of FIG. Further, as a result of this processing, the risk determination unit 14 substitutes “1” or “0” for a match flag indicating whether or not the other driver related information matches the risk determination condition.

  (Step S218) The danger notification unit 13 determines whether or not the match flag is 1. When it is 1, it progresses to step S217, and when that is not right, it returns to step S203.

  (Step S219) The danger notification unit 15 outputs a danger message.

  In the flowchart of FIG. 2, the process may be terminated by powering off or a process termination interrupt.

  FIG. 3 is a flowchart showing a determination process of whether or not the risk determination condition in step S215 in the flowchart of FIG. 2 is met. In the flowchart of FIG. 3, it is assumed that the risk determination condition storage unit 11 stores m risk determination conditions.

  (Step S301) The risk determination unit 14 sets 0 to the match flag.

  (Step S302) The risk determination unit 14 determines whether or not the other driver related information acquisition unit 12 has already acquired the driver classification information. If it has been acquired, the process proceeds to step S303, and if not, the process proceeds to step S304.

  (Step S303) The risk determination unit 14 sets the driver classification information in the array Target [] that stores information for determining whether or not the risk determination condition is met.

  (Step S304) The risk determination unit 14 determines whether or not the other driver related information acquisition unit 12 has already acquired the license plate information. If it has been acquired, the process proceeds to step S305, and if not, the process proceeds to step S306.

  (Step S305) The risk determination unit 14 adds license plate information to Target [].

  (Step S306) The risk determination unit 14 determines whether or not the other driver related information acquisition unit 12 has acquired the driver year information. If it has been acquired, the process proceeds to step S307, and if not, the process proceeds to step S308.

  (Step S307) The risk determination unit 14 adds the driver year information to Target [].

  (Step S308) The risk determination unit 14 determines whether or not the traveling situation information acquisition unit 13 has acquired the traveling situation information. If it has been acquired, the process proceeds to step S309. If not, the process proceeds to step S310.

  (Step S309) The risk determination unit 14 adds the running situation information to Target [].

  (Step S310) The risk determination unit 14 sets 1 to the counter i.

  (Step S311) The risk determination unit 14 determines whether or not the information stored in Target [] matches the risk determination condition [i]. If they match, the process proceeds to step S312; otherwise, the process proceeds to step S313.

  (Step S312) The risk determination unit 14 sets 1 to the match flag. Then, the process returns to the upper process.

  (Step S313) The risk determination unit 14 determines whether i is m. If m, the process returns to the upper process, and if not, the process proceeds to step S314.

  (Step S314) The danger determination unit 14 increments i by 1, and returns to step S311.

(Concrete example)
Next, a specific example of the operation of the in-vehicle device 1 will be described. In this specific example, the moving body is assumed to be an automobile. Further, the in-vehicle device 1 is assumed to be a car navigation system (hereinafter referred to as “car navigation”) installed in an automobile. Further, it is assumed that the risk determination condition storage unit 11 stores the risk determination condition shown in FIG. The risk judgment condition (item name: condition) is associated with an ID (item name: ID) for uniquely identifying the record. In addition, it is assumed that the driver sign image storage unit 121 stores the driver sign image shown in FIG. The driver sign image (item name: image) includes an ID (item name: ID) for uniquely identifying a record and driver classification information (item name: description) indicated by the driver sign image. With correspondence. Further, it is assumed that the license plate management information storage unit 122 stores the license plate management information shown in FIG. The license plate management information includes an ID (item name: ID) for uniquely identifying a record, a license plate condition (item name: condition), and other driver related information (item name: other driver). Have.

(Example 1)
In this example, an example in which the other driver related information acquisition unit 12 acquires the other driver related information by detecting the driver sign from the front image will be described.

  First, it is assumed that a user (driver) gets into a car and starts driving. Then, the front image acquisition unit 123 starts to periodically acquire the front image.

  Next, it is assumed that the front image acquisition unit 123 acquires the front image shown in FIG. 7 at the timing of acquiring the front image.

  Next, the driver sign area detecting means 124 detects the contour from the image of FIG. Then, it is assumed that the driver sign area detecting means 124 has acquired the image shown in FIG.

  Next, the driver sign area detecting unit 124 detects a driver sign area that is an area that matches any of the driver sign images in FIG. 5 from the image in FIG. 8. At this time, the driver sign region detecting means 124 normally determines whether the shape of each figure in FIG. 8 matches the shape of the driver sign image in FIG. As a result, it is assumed that the driver sign region detecting means 124 determines that the shape of the figure shown in FIG. 9 in FIG. 8 matches the shape of the driver sign image of “ID = 001” in FIG. Then, the driver sign area detecting means 124 acquires the image of FIG. 9 as the driver sign area.

  Next, the other driver related information acquisition means 126 is “ID = 001” in FIG. 5 which is the driver classification information corresponding to the driving sign image that matches the driver sign area detected by the driver sign area detecting means 124. The driver classification information “beginner” is acquired.

  Next, it is assumed that the travel situation information acquisition unit 13 determines that it is the timing of acquisition of the travel situation information, and has acquired road type information “highway” indicating the type of road that is running.

  Next, the risk determination unit 14 determines that the driver classification information “beginner” acquired by the other driver related information acquisition unit 12 and the road type information “highway” acquired by the traveling situation information acquisition unit 13 are as shown in FIG. It is determined whether or not any of the four risk determination conditions is met. Then, the risk judgment unit 14 matches the risk judgment condition “{(classification = beginner) or (classification = elderly)} & (road type = highway)” of “ID = 012” in FIG. Judge that. The risk judgment condition means that “the driver of the other vehicle is a beginner or an elderly person, and the running road is an expressway”.

  Next, the danger notification unit 15 outputs a danger message. Here, it is assumed that the in-vehicle device 1 includes a screen and outputs an image shown in FIG. In this case, for example, as illustrated in FIG. 11, the danger notification unit 15 outputs information (here, an image) indicating that the danger is superimposed on the already output image.

(Example 2)
In this example, an example in which the other driver related information acquisition unit 12 acquires the other driver related information by detecting the license plate from the front image will be described.

  First, as in Example 1, it is assumed that the front image acquisition unit 123 acquires the front image shown in FIG. 7 at the timing of acquiring the front image.

  Next, the license plate area detecting means 125 detects the contour from the image of FIG. Then, it is assumed that the license plate area detection unit 125 has acquired the image shown in FIG.

  Next, the license plate area detecting means 125 detects a license plate area which is an area matching the license plate from the image of FIG. At this time, the license plate area detection means 125 normally determines whether or not the shape of each figure in FIG. 8 matches the shape of the license plate. As a result, it is assumed that the driver sign region detection means 124 determines that the shape of the figure shown in FIG. 12 in FIG. 8 matches the shape of the license plate. Then, the license plate area detecting unit 125 acquires the image of FIG. 12 as a license plate area.

  Next, the other driver related information acquisition means 126 performs character recognition by OCR on the image of FIG. 12 and acquires license plate information “Kobe 339 is 12-34”. At this time, the other driver related information acquisition unit 126 divides the license plate information by a space, “Kobe” indicating the headquarters, “339” indicating the classification number, and “ha” indicating the business discrimination character. Alternatively, “12-34” indicating the designated number may be obtained separately.

  Next, it is assumed that the traveling situation information acquisition unit 13 determines that it is the timing of acquisition of the traveling situation information and has acquired speed information “65 km / h” indicating the speed.

  Next, the risk determination unit 14 determines the license plate information “Kobe 339 is 12-34” acquired by the other driver related information acquisition unit 12 and the speed information “65 km / h” acquired by the traveling situation information acquisition unit 13. Determines whether any of the risk determination conditions in FIG. 4 is met. Then, the risk determination unit 14 determines that the information is the risk determination condition “{(classification number = ** 1) or (classification number = ** 9)} & (speed ≧ 60 km / d” of “ID = 013” in FIG. h) ”. The risk judgment condition means “the last digit of the license plate classification number is 1 or 9, and the speed is 60 km / h or more”.

  Next, as in the case of Example 1, the danger notification unit 15 outputs a danger message.

  In addition, in the above, the other driver related information acquisition unit 126 determines whether the acquired license plate information “Kobe 339 is 12-34” matches any of the license plate conditions of FIG. Other driver information corresponding to the license plate condition determined to match may be acquired. In this case, the other driver related information acquisition unit 126 sets the acquired license plate information to the license plate condition “(classification symbol = LL) or (classification number = ** 9)” of “ID = 012” in FIG. Judge that it matches. The license plate condition means “the classification symbol written on the license plate is LL or the last digit of the classification number written on the license plate is 9.” Then, the other driver related information acquisition means 126 acquires the other driver related information “elderly person” of “ID = 012” in FIG. 6. The other driver related information is driver classification information.

  Next, the risk determination unit 14 determines that the driver classification information “elderly” acquired by the other driver related information acquisition unit 12 is “(classification = elderly)” or “the risk determination condition of“ ID = 014 ”in FIG. (Age ≧ 75 years old) or (License acquisition years ≦ 6 months) ”. The risk judgment condition is “the driver of the other vehicle is an elderly person, the driver of the other vehicle is 75 years old or older, or the driver's license acquisition period is 6 months. It means “below”.

  Next, as in the case of Example 1, the danger notification unit 15 outputs a danger message.

  In FIG. 6, the license plate condition “(license acquisition date = Yes)” of “ID = 013” means “the driver's license acquisition date is described in the license plate”. In other words, this means that “the other driver related information acquisition unit 12 has acquired information indicating the driver's license acquisition date from the license plate”. Further, “ID = 013” and other driver-related information “License Acquisition Year (License Acquisition Year)” indicates a program (function) for calculating the license acquisition year from the license acquisition year.

  In FIG. 6, the license plate condition “(date of birth = present)” of “ID = 014” means “the driver's date of birth is written on the license plate”. In other words, this means that “the other driver related information acquisition unit 12 has acquired information indicating the driver's date of birth from the license plate”. Further, “ID = 014” and other driver related information “age (date of birth)” indicates a program (function) for calculating the age from the date of birth.

(Example 3)
In this example, an example in which the other driver related information acquisition unit 12 receives the other driver related information will be described.

  First, it is assumed that the other driver related information receiving means 127 is in a state where it can periodically receive the transmitted other driver related information.

  Next, it is assumed that the other driver related information receiving unit 127 receives the driver classification information “beginner”. At this time, it is assumed that the traveling situation information acquisition unit 13 has acquired the road type information “highway”. In this case, the risk judgment unit 14 determines that the driver classification information “beginner” and the road type information “highway” are the risk judgment condition “{(classification = beginner) or“ ID = 012 ”in FIG. (Classification = Elderly)} & (Road type = Expressway) ".

  Further, for example, it is assumed that the other driver related information receiving unit 127 receives the license plate information “Kobe 339 is 12-34”. At this time, it is assumed that the traveling situation information acquisition unit 13 acquires the speed information “65 km / h”. In this case, the risk determination unit 14 determines that the license plate information “Kobe 339 is 12-34” and the speed information “65 km / h” are the risk determination condition “{(classification number) of“ ID = 013 ”in FIG. = ** 1) or (classification number = ** 9)} & (speed ≧ 60 km / h) ”.

  Further, for example, it is assumed that the other driver related information receiving means 127 receives the license acquisition year information “4 months”. In this case, the risk determination unit 14 determines that the license acquisition year information “4 months” indicates that the risk determination condition “(classification = elderly) or (age ≧ 75 years) or (license acquisition) of“ ID = 014 ”in FIG. Year number ≦ 6 months) ”.

  In addition, since the example of the output to the effect by the danger alerting | reporting part 15 is the same as that of Example 1 and Example 2, description is abbreviate | omitted.

(Example 4)
In this example, an example in which notification content information is associated with a risk determination condition stored in the risk determination condition storage unit 11 will be described. The risk judgment conditions are as shown in FIG. In FIG. 13, the notification content information is an item name “notification content”. Since the other items are as described above, the description thereof is omitted.

  First, for example, the risk determination unit 14 determines that the other driving related information acquired by the other driver related information acquiring unit 12 and the driving situation information acquired by the driving situation information acquisition unit 13 are “ID = Suppose that it is determined that the risk determination condition “012” is met. Then, the risk determination unit 14 acquires the notification content information “warning screen 01” of “ID = 012” in FIG. The notification content information indicates that an image prepared in advance identified by the “warning screen 01” is output on the screen. In addition, it is assumed that the image is stored in a predetermined storage area of the in-vehicle device 1.

  Next, the danger notification unit 15 acquires an image identified by the “warning screen 01” from a predetermined storage area. Then, the danger notification unit 15 outputs the acquired image on the screen. The state of the output is, for example, FIG.

  Further, for example, it is assumed that the risk determination unit 14 determines that the other driving related information acquired by the other driver related information acquisition unit 12 matches the risk determination condition of “ID = 015” in FIG. 13. Then, the risk determination unit 14 acquires notification content information “warning sound 02” of “ID = 015” in FIG. 13. The notification content information indicates that music data prepared in advance identified by “warning sound 02” is reproduced and output to a speaker. The music data is, for example, a warning sound. The music data is stored in a predetermined storage area of the in-vehicle device 1.

  Next, the danger notification unit 15 acquires music data identified by “warning sound 02” from a predetermined storage area. And the danger alerting | reporting part 15 reproduces | regenerates the said acquired music data, and outputs a warning sound to a speaker.

  As mentioned above, according to the vehicle-mounted apparatus 1 by this Embodiment, according to the state regarding the driving skill of the driver | operator of other vehicles, such as the age group of the driver who is driving the front mobile body, and the number of years since the license acquisition Risk prediction. Thereby, for example, when the driver of the moving body ahead is a beginner or when the driver is an elderly person, it can be notified to the user that it is dangerous, and accidents can be prevented in advance. be able to.

  Moreover, according to the vehicle-mounted device 1 according to the present embodiment, the state relating to the driving skill of the driver of the other vehicle, the type of road on which the own vehicle is traveling, the speed of the own vehicle, the inter-vehicle distance from the other vehicle, etc. The risk prediction can be performed according to the situation when the vehicle is running. Thus, for example, when traveling on an expressway, if there is a vehicle that a beginner is driving ahead, or if the distance between the vehicle and the moving body that the beginner is driving is short, the elderly will drive at high speed. In such a case, it can be notified to the user that it is dangerous, and accidents can be prevented.

  Further, in each of the above embodiments, it goes without saying that two or more communication units existing in one apparatus may be physically realized by one medium.

  The in-vehicle device in each of the above embodiments may be, for example, a stand-alone device or a server device in a server / client system. In the latter case, for example, risk prediction may be performed as an ASP (Application Service Provider).

  In each of the above embodiments, each process or each function may be realized by centralized processing by a single device or a single system, or distributed by a plurality of devices or a plurality of systems. It may be realized by being processed.

  In each of the above embodiments, each component may be configured by dedicated hardware, or a component that can be realized by software may be realized by executing a program. For example, each component can be realized by a program execution unit such as a CPU reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory.

  Moreover, the software which implement | achieves the vehicle-mounted apparatus in each said embodiment is the following programs, for example. In other words, this program uses a computer that can access a risk determination condition storage unit in which one or more risk determination conditions for determining a risk as a risk, and other drivers that are information on drivers of other mobile objects. It is determined whether or not the other driver related information acquisition unit that acquires the related information and the other driver related information acquired by the other driver related information acquisition unit match any one of the one or more risk determination conditions. The risk determination unit and the risk determination unit function as a risk notification unit that outputs a danger message when it is determined that any one of the one or more risk determination conditions is met.

  Note that the program does not include at least processing that is performed only by hardware.

  The program may be executed by being downloaded from a server or the like, or a program recorded on a predetermined recording medium (for example, an optical disk such as a CD-ROM, a magnetic disk, a semiconductor memory, or the like) is read out. May be executed. Further, this program may be used as a program constituting a program product.

  Moreover, the computer which performs the said program may be single, and plural may be sufficient as it. That is, centralized processing may be performed, or distributed processing may be performed.

  FIG. 14 is an overview diagram of the computer system 9 that executes the above-described program to realize the in-vehicle device of the above-described embodiment. The above-described embodiments can be realized by computer hardware and a computer program executed thereon.

  14, the computer system 9 includes a computer 901 including a CD-ROM drive 9011 and an FD drive 9012, a keyboard 902, a mouse 903, and a monitor 904.

  FIG. 15 is a block diagram of the computer system 9. In FIG. 15, a computer 901 is connected to an MPU 9013, a ROM 9014 for storing a program such as a boot-up program, and an MPU 9013 in addition to a CD-ROM drive 9011 and an FD drive 9012, and temporarily commands the application program. A bus for mutually connecting a RAM 9015 for storing a temporary storage space, a hard disk 9016 for storing application programs, system programs, and data, a CD-ROM drive 9011, an FD drive 9012, an MPU 9013, etc. 9017. Although not shown here, the computer 901 may further include a network card that provides connection to a LAN.

  A program that causes the computer system 9 to execute the functions of the vehicle-mounted device or the like of the above-described embodiment is stored in the CD-ROM 9101 or FD 9102, inserted into the CD-ROM drive 9011 or FD drive 9012, and further stored in the hard disk 9016. May be forwarded. Alternatively, the program may be transmitted to the computer 901 via a network (not shown) and stored in the hard disk 9016. The program is loaded into the RAM 9015 when executed. The program may be loaded directly from the CD-ROM 9101, the FD 9102, or the network.

  The program does not necessarily include an operating system (OS), a third-party program, or the like that causes the computer 901 to execute the functions of the in-vehicle device of the above-described embodiment. The program only needs to include an instruction portion that calls an appropriate function (module) in a controlled manner and obtains a desired result. How the computer system 9 operates is well known and will not be described in detail.

  The present invention is not limited to the above-described embodiments, and various modifications are possible, and it goes without saying that these are also included in the scope of the present invention.

  As described above, the in-vehicle device according to the present invention has an effect that it is possible to perform risk prediction according to the state relating to the driving skill of the driver of another moving body, and is useful as a navigation device or the like.

DESCRIPTION OF SYMBOLS 1 In-vehicle apparatus 11 Risk judgment condition storage part 12 Other driver related information acquisition part 13 Running condition information acquisition part 14 Risk judgment part 15 Risk notification part 121 Driver sign image storage means 122 License plate management information storage means 123 Front image acquisition Means 124 Driver sign area detection means 125 License plate area detection means 126 Other driver related information acquisition means 127 Other driver related information reception means

Claims (4)

A risk determination condition storage unit that stores one or more risk determination conditions for determining a risk;
Other driver related information acquisition unit for acquiring other driver related information, which is information related to the driver of another moving body,
A risk determination unit that determines whether the other driver related information acquired by the other driver related information acquisition unit matches any of the one or more risk determination conditions;
A risk notification unit that outputs a danger message when the risk determination unit determines that any one of the one or more risk determination conditions is satisfied ;
The other driver related information acquisition unit
Forward image acquisition means for acquiring a forward image that is an image in front of the moving body;
From the front image acquired by the front image acquisition means, license plate area detection means for detecting an area that matches the license plate;
Other driver related information acquisition means for acquiring license plate information indicating the contents described in the license plate from the area detected by the license plate area detection means,
The risk judging unit
An in- vehicle device that determines whether or not the license plate information acquired by the other driver related information acquisition unit matches any of the one or more risk determination conditions . The other driver related information acquisition unit
Number in which one or more license plate management information having license plate conditions that are conditions related to the contents described in the license plate and driver years information indicating the number of years related to the driver indicated by the described contents is stored Plate management information storage means,
The other driver related information acquisition means includes:
Obtain driver year information corresponding to the license plate condition that matches the license plate information from the license plate management information storage means,
The risk judging unit
The in-vehicle device according to claim 1 , wherein it is determined whether or not the driver year information acquired by the other driver related information acquisition unit matches any of the one or more risk determination conditions. A risk determination condition storage unit that stores one or more risk determination conditions for determining a risk;
A risk prediction method performed using another driver-related information acquisition unit, a risk determination unit, and a risk notification unit,
The other driver related information acquisition unit,
Other driver related information acquisition step for acquiring other driver related information that is information related to the driver of another mobile unit,
The risk determination unit
A risk determination step of determining whether or not the other driver related information acquired by the other driver related information acquisition unit matches any of the one or more risk determination conditions;
The danger notification unit
A risk notification step of outputting a danger message when the risk determination unit determines that any one of the one or more risk determination conditions is met ,
The other driver related information acquisition step includes:
A front image acquisition substep of acquiring a front image that is a front image of the moving body;
From the front image acquired in the front image acquisition substep, a license plate region detection substep for detecting a region that matches the license plate;
From the area detected in the license plate area detection substep, the other driver related information acquisition substep for acquiring license plate information indicating the contents described in the license plate,
The risk judging unit
A risk prediction method for determining whether or not the license plate information acquired by the other driver related information acquisition unit matches any of the one or more risk determination conditions . A computer that can access a risk determination condition storage unit in which one or more risk determination conditions for determining a risk is stored,
Other driver related information acquisition unit for acquiring other driver related information, which is information related to the driver of another moving body,
A risk determination unit that determines whether the other driver related information acquired by the other driver related information acquisition unit matches any of the one or more risk determination conditions;
When the risk determination unit determines that any one of the one or more risk determination conditions is met, a program for functioning as a risk notification unit that outputs a danger message ,
The other driver related information acquisition unit
Forward image acquisition means for acquiring a forward image that is an image in front of the moving body;
From the front image acquired by the front image acquisition means, license plate area detection means for detecting an area that matches the license plate;
Other driver related information acquisition means for acquiring license plate information indicating the contents described in the license plate from the area detected by the license plate area detection means,
The risk judging unit
A program for causing a computer to function as a determination as to whether or not the license plate information acquired by the other driver related information acquisition unit matches any of the one or more risk determination conditions .