JP6159052B2 - Information providing method and information providing apparatus - Google Patents

Description

  The present invention relates to an information providing method and an information providing apparatus.

  In order to prevent traffic accidents, efforts are being made to make use of examples of accidents that actually occurred or cases that could develop into accidents. An example of such an approach is a technique for creating a near-miss map by developing near-miss data collected from a taxi equipped with a drive record on a map. The “near-miss” refers to, for example, a case where the person is likely to encounter an accident and feels confused or relieved, and includes an example that may develop into an accident.

  Explaining this, the drive recorder overwrites the information previously stored in the memory with the output from the sensor for a predetermined time, thereby changing the old sensor output to the new sensor output in the memory. Update. Examples of such “sensors” include various sensors mounted on a vehicle, such as a GPS receiver and an acceleration sensor. At this time, the drive recorder operates as follows when the output of the sensor satisfies a predetermined condition, for example, when the output value of the acceleration sensor satisfies a condition corresponding to a sudden handle or sudden acceleration. That is, the drive recorder obtains the output of the sensor for a predetermined time, for example, 10 seconds from the time point when the previous condition is satisfied among the information stored in the memory, and saves it in the storage memory. Furthermore, the drive recorder stores the output of the sensor in the storage memory until a predetermined time, for example, 5 seconds elapses after the previous condition is satisfied. Thus, when the output of the sensor satisfies the previous condition, the drive recorder stores the output of the sensor for a predetermined time before and after that point in the storage memory. For this reason, when the sensor output is recorded before and after the point in time when the near-miss is estimated, the sensor output may be recorded as a result even in the case of an accident that has actually developed from a near-miss. Using this drive recorder, a near-miss database is created in which information such as near-miss ID (identification), occurrence date / time, latitude, longitude, and address is associated. Then, a near-miss map is created by mapping a plurality of near-miss data on the electronic map. By referring to the near-miss map, the user can identify a point where near-miss occurs frequently and recognize a dangerous place.

“Car Watch Automobile Engineering Society, Introduction of Near-miss Database”, [online], [Search April 22, 2011], Internet <http://car.watch.impress.co.jp/docs/news/20090402_80336 .html>

  However, as described below, the above-described conventional technology has a problem that it has a limit to be useful for accident prevention.

  In other words, the user only recognizes the frequent occurrence points of the near-miss from the near-miss map. Even if the user recognizes a near-miss frequent occurrence point, it is not possible to distinguish a case where special attention must be paid when traveling at the frequent occurrence point. Therefore, the near-miss map described above cannot reduce the risk that an accident with the same cause as a near-miss has occurred in the past, and cannot be a drastic measure for accident prevention.

  The disclosed technology has been made in view of the above, and provides an information providing method and an information providing apparatus capable of discriminating between cases where special attention is required and cases where a normal level is sufficient depending on the traveling direction. With the goal.

  In the information providing method disclosed in the present application, the computer calculates the movement locus of the vehicle when the first sensor determines that the running state of the vehicle matches the dangerous state based on the detection value of the second sensor. Execute the process. Further, the computer executes a process of counting a plurality of movement trajectories including the movement trajectory for each region on the road and for each traveling direction. Further, the computer executes a process of outputting support information based on the totaled result to the other computer in response to a request from the other computer.

  According to one aspect of the information providing method disclosed in the present application, there is an effect that it is possible to discriminate between cases where special attention is required and cases where only a normal level is sufficient depending on the traveling direction.

FIG. 1 is a diagram illustrating the configuration of the information providing system according to the first embodiment. FIG. 2 is a block diagram illustrating a functional configuration of the device mounted on the vehicle according to the first embodiment. FIG. 3 is a block diagram illustrating a functional configuration of the information providing apparatus according to the first embodiment. FIG. 4 is a diagram illustrating an example of the near data. FIG. 5 is a diagram illustrating an example of an intersection table. FIG. 6 is a diagram illustrating an example of a road table. FIG. 7 is a diagram illustrating an example of a method for setting a traffic pattern. FIG. 8 is a diagram illustrating an example of a method for setting a traffic pattern. FIG. 9 is a diagram showing an example of the near miss amount data. FIG. 10 is a schematic diagram of an intersection included in the incident amount data shown in FIG. FIG. 11 is a diagram illustrating an example of the near link data. FIG. 12 is a block diagram illustrating a functional configuration of the device mounted on the vehicle of the service subscriber according to the first embodiment. FIG. 13A is a diagram illustrating an example of a navigation screen. FIG. 13B is a diagram illustrating an example of a navigation screen. FIG. 14 is a flowchart illustrating the procedure of the aggregation process according to the first embodiment. FIG. 15 is a flowchart illustrating the procedure of the navigation process according to the first embodiment. FIG. 16 is a diagram illustrating the configuration of the information providing system according to the second embodiment. FIG. 17 is a block diagram illustrating a functional configuration of the information providing apparatus according to the second embodiment. FIG. 18 is a diagram for explaining normalization of the near amount. FIG. 19 is a diagram for explaining normalization of the near amount. FIG. 20 is a diagram illustrating an example of the near amount data including the near amount after normalization. FIG. 21A is a diagram illustrating an example of a near miss map. FIG. 21B is a diagram illustrating an example of a near miss map. FIG. 22 is a flowchart illustrating the procedure of the information providing process according to the second embodiment. FIG. 23 is a flowchart illustrating the procedure of the similarity search process according to the second embodiment. FIG. 24 is a diagram for explaining an application example. FIG. 25 is a diagram for explaining an application example. FIG. 26 is a diagram for explaining an application example. FIG. 27 is a schematic diagram illustrating an example of a computer that executes an information providing program according to the first to third embodiments.

  Embodiments of an information providing method and an information providing apparatus disclosed in the present application will be described below in detail with reference to the drawings. Note that this embodiment does not limit the disclosed technology. Each embodiment can be appropriately combined within a range in which processing contents are not contradictory.

[Configuration of information provision system]
First, the configuration of the information providing system according to the present embodiment will be described. FIG. 1 is a diagram illustrating the configuration of the information providing system according to the first embodiment. As shown in FIG. 1, the information providing system 1 accommodates an information providing device 10, drive recorders 30 </ b> A to 30 </ b> C, sensor groups 31 </ b> A to 31 </ b> C, a navigation device 50, and a GPS receiver 54. In the example of FIG. 1, when the vehicles 3A to 3C pass through the intersection, cases where the traveling state obtained from the sensor groups 31A to 31C matches the dangerous state are totaled according to the traveling direction of the vehicle at the intersection. The case where it provides to the navigation apparatus 50 of the following vehicle 5 is assumed.

  The information providing device 10, the drive recorders 30 </ b> A to 30 </ b> C, and the navigation device 50 are connected via a network 9 so that they can communicate with each other. The network 9 can employ a communication network such as the Internet (Internet), a LAN (Local Area Network), and a VPN (Virtual Private Network) regardless of wired or wireless. In the example of FIG. 1, the case where one information providing device, three drive recorders, and one navigation device are accommodated is illustrated, but the disclosed system is not limited thereto. That is, the disclosed system can be applied to a case where an arbitrary number of drive recorders and navigation devices are accommodated.

  Among these, the drive recorders 30A to 30C are recorders that record the sensor outputs of the sensor groups 31A to 31C mounted on the vehicles 3A to 3C. As one aspect | mode of this sensor group 31A-31C, the GPS (Global Positioning System) receiver 32 mentioned later, the acceleration sensor 33, the vehicle speed sensor 34, the camera 35, etc. are mentioned. Moreover, as one aspect | mode of vehicle 3A-3C, it is a vehicle carrying drive recorder 30A-30C, for example, arbitrary vehicles, such as a general vehicle, a business vehicle, and a special vehicle, are mentioned. Hereinafter, when the vehicles 3A to 3C, the drive recorders 30A to 30C, and the sensor groups 31A to 31C are collectively referred to without distinction, they are described as “vehicle 3”, “drive recorder 30”, and “sensor group 31”, respectively. There is a case.

  As an example, the drive recorder 30 determines whether or not an acceleration output from an acceleration sensor 33 described later in the sensor group 31 satisfies a predetermined condition. Here, the predetermined condition is a condition for determining whether or not the traveling state of the vehicle 3 is applicable to a case to be detected as a near-miss. For example, dangerous conditions such as whether the value output by the acceleration sensor is greater than or equal to a threshold value indicating sudden braking, or whether it is applicable to the behavior of acceleration appearing in the vehicle body when a sudden steering is performed, etc. are defined It is a condition. In addition to the acceleration sensor, a condition based on a value output by another sensor such as a steering angle sensor may be used. Further, the drive recorder 30 may make a determination based on outputs from two or more sensors. Such a “dangerous state” is a case where the output of the sensor meets a predetermined condition. The “running state” refers to an output value or a combination of output values collected by an acceleration sensor or a steering angle sensor.

  At this time, when the acceleration satisfying the above condition is measured, the drive recorder 30 obtains data in which sensor outputs collected by the sensor group 31 before and after the acceleration satisfies the condition are associated with each time. accumulate. As a result, the position information and acceleration collected by the sensor group 31 in the period before and after the time when the driver of the vehicle 3 is estimated to have suddenly braked or steered, that is, the time when the occurrence of near-miss is estimated. , Speed and video are accumulated. At this time, as the sensor output is accumulated around the time when the near-miss is estimated, the sensor output may be accumulated as a result even in the case of an accident that has actually developed from a near-miss. In the following, data in which position information, acceleration, speed, and video frame number are associated with each time in a period before and after the time point when near-miss occurrence is estimated will be referred to as “missing candidate data”. There is a case.

  Thereafter, the drive recorder 30 provides information on the near-missing candidate data that has been accumulated since the last upload when a predetermined period has elapsed since the near-term candidate data was uploaded to the information providing apparatus 10 last time. Upload to device 10. In addition, although the case where the near candidate data is uploaded to the information providing apparatus 10 at regular intervals is illustrated here, the present invention is not limited to this. For example, the drive recorder 30 uploads near-miss candidate data in real time when it detects the occurrence of a near-miss, uploads at a regular time, or uploads in response to a request from the information providing apparatus 10 it can.

  The information providing device 10 is a device that counts the occurrence amount of near-miss according to the traveling direction of the vehicle at the intersection based on the near-candidate data uploaded from the drive recorder 30. In addition, the information processing apparatus 10 executes a service for providing near-miss occurrence amounts totaled for each traveling direction to the navigation apparatus 50 of the service subscriber's vehicle 5. Here, in the following, the occurrence amount of near-miss may be referred to as “near amount”. As an example, when the information providing apparatus 10 receives position information from the navigation apparatus 50 mounted on the service subscriber's vehicle 5, the information providing apparatus 10 calculates the amount of incident related to an intersection located within a predetermined range from the position. Reply to

  Here, the information providing apparatus 10 according to the present embodiment uses the near-miss candidate data generated by the drive recorder 30 when the traveling state collected by the acceleration sensor 33 or the like matches the dangerous state in the area on the road. Aggregate by direction of travel straight, left or right. In addition, when providing information to other devices, the information providing device 10 according to the present embodiment outputs support information based on the amount of incidents totaled for each traveling direction.

  For this reason, in the information providing apparatus 10 according to the present embodiment, when there are many near misses in an area on the road, for example, at an intersection, there is a high possibility that it is dangerous when the intersection is passed in any direction of travel. It is possible to make the user grasp whether or not. Therefore, in the information providing apparatus 10 according to the present embodiment, when the vehicle passes the intersection in the traveling direction in which near-misses are frequently occurring, pay more attention than when traveling in the other traveling direction to the driver, You can prepare to perform recognition, judgment and operation according to the direction of travel. Therefore, according to the information providing apparatus 10 according to the present embodiment, the risk of reoccurrence of an accident with the same cause as that when a near-miss occurred in the past is reduced by allowing the user to recognize the traveling direction to which special attention should be paid. As a result, it is possible to contribute to accident prevention. The direction of travel is not limited to going straight, turning right, and turning left. For example, in more detail, it may be defined as a combination of a road at the time of entry and a road at the time of escape among a plurality of roads forming an intersection.

  The navigation device 50 is a device that guides the route to the driver by comparing a position on the road included in the planned travel route of the vehicle 5 with an electronic map (not shown). Here, as an example, the navigation device 50 transmits the current position of the service subscriber's vehicle 5 to the information providing device 10. The following explanation is given assuming that is provided.

  For example, the navigation device 50 monitors whether the current position of the service subscriber's vehicle 5 measured by the GPS receiver 54 has approached within a predetermined distance from the intersection. At this time, the navigation device 50 executes the following process when the current position approaches within a predetermined distance from the intersection. In other words, the navigation device 50 determines whether or not the amount of near miss in the direction of travel of the intersection scheduled to be most recently guided from the current position exceeds the predetermined threshold among the amount of near miss provided by the information providing device 10 for each travel direction. Determine whether. And the navigation apparatus 50 performs the navigation which alerts the near-miss at the said intersection, when the amount of incidents exceeds the threshold value.

  In addition, although the case where the navigation apparatus 50 transmits the current position of the service subscriber's vehicle 5 to the information providing apparatus 10 is illustrated here, it is not always necessary to transmit the current position. In other words, the navigation device 50 can arbitrarily select a position on the road included in the planned travel route for which the search for the own device has been performed and transmit it to the information providing device 10. For example, the navigation device 50 can also count the number of intersections on the planned travel route from the current position and transmit the position of the intersection or the destination position that is a predetermined number ahead. This makes it possible to acquire not only the intersection where guidance is scheduled most recently but also an intersection scheduled to travel afterwards for the amount of nearness according to the traveling direction.

[Configuration of device mounted on vehicle]
Subsequently, a functional configuration of the device mounted on the vehicle according to the present embodiment will be described. FIG. 2 is a block diagram illustrating a functional configuration of the device mounted on the vehicle according to the first embodiment. As shown in FIG. 2, the vehicle 3 includes a GPS receiver 32, an acceleration sensor 33, a vehicle speed sensor 34, a sensor group 31 such as a camera 35, a communication I / F unit 36, a reader / writer 37, and a drive recorder 30. Is installed.

  Among these, the GPS receiver 32 measures position information such as latitude and longitude by receiving radio waves from a plurality of GPS satellites and determining the distance to each GPS satellite. The acceleration sensor 33 is a sensor that measures the acceleration of the vehicle 3. As an aspect of the acceleration sensor 11a, a three-axis acceleration sensor that measures acceleration in the X-axis direction, the Y-axis direction, and the Z-axis direction can be employed. As a method for measuring acceleration, any method such as a semiconductor method, a mechanical method, an optical method, or the like can be adopted. The vehicle speed sensor 34 is a sensor that measures the speed of the vehicle 3 from vehicle speed pulses generated in proportion to the rotational speed of the axle. The camera 35 is an imaging device mounted on the vehicle 3. As an aspect of the camera 35, an imaging device using a charge coupled device (CCD), a complementary metal oxide semiconductor (CMOS), or the like can be employed.

  2 exemplifies the case where the GPS receiver 32, the acceleration sensor 33, the vehicle speed sensor 34, and the camera 35 are provided. However, it is not always necessary to provide four sensors, and at least the GPS receiver 32 and the acceleration sensor 33 are provided. As long as it is installed. Furthermore, other sensors may be used. For example, you may have a rudder angle sensor etc.

  The drive recorder 30 is a recorder that records the sensor outputs of the sensor groups 31A to 31C. As an example, the drive recorder 30 monitors whether or not the acceleration output from the acceleration sensor 33 satisfies a predetermined condition, for example, the behavior of the acceleration that appears in the vehicle body when sudden braking or sudden steering is performed. . At this time, when the acceleration satisfying the previous condition is measured, the drive recorder 30 is a near candidate in which the sensor outputs collected by the sensor group 31 before and after the time when the acceleration satisfies the condition are associated with each time. Data is stored in an internal memory (not shown). Thereafter, when a predetermined period has elapsed since the last upload of near-missing candidate data, the drive recorder 30 transmits the near-missing candidate data that has been stored in the internal memory since the last upload to the communication I / F. Upload to the information providing apparatus 10 via the unit 36. Here, the case where the near candidate data including the video is uploaded to the information providing apparatus 10 will be described. However, it is not always necessary to upload the video, and at least the position information and the acceleration are associated with each time. Upload data.

  The communication I / F unit 36 is an interface that performs communication control with another device, for example, the information providing device 10. For example, the communication I / F unit 36 transmits the near candidate data accumulated by the drive recorder 30 to the information providing apparatus 10. As an aspect of the communication I / F unit 36, a network interface card (NIC) such as a LAN card or a modem can be employed.

  In addition, although the case where the drive recorder 30 transmits the near miss candidate data to the information providing apparatus 10 via the communication I / F unit 36 is illustrated here, it is not always necessary to perform upload by communication. For example, the drive recorder 30 can also upload near-miss candidate data via a recording medium. In this case, the reader / writer 37 is controlled by the drive recorder 30 and the near miss candidate data is written to the memory card 20.

  The reader / writer 37 is a device that reads or writes recorded information in an IC tag by communicating with an IC (Integrated Circuit) tag built in the memory card 20. The reader / writer 37 emits an electromagnetic wave within an effective distance determined by the proximity type or near type specification. Using this electromagnetic wave, power is generated by a coil-type antenna incorporated in the IC tag of the memory card 20 to enable data communication. After that, the reader / writer 37 writes the near-miss candidate data input from the drive recorder 30 to the IC tag of the memory card 20.

  Thus, the drive recorder 30 can deliver the near miss candidate data to the information providing device 10 by causing the reader / writer provided in the information providing device 10 to read the memory card 20 in which the near miss candidate data is written. Here, the case where the near-miss candidate data is written to the non-contact type memory card 20 is illustrated, but the memory card 20 does not necessarily need to be the non-contact type, and a storage device such as an HDD (Hard Disk Drive) Can also be used.

  Here, an event-type drive recorder that records the sensor output before and after the time when the sensor output of the acceleration sensor or the like satisfies a predetermined condition, that is, when it is estimated that an event such as a sudden brake or a sudden handle has occurred. The case where it employ | adopts was illustrated. However, the disclosed apparatus can be applied not only when an event type drive recorder is used, but also when a constant recording type drive recorder is employed.

  For example, when the drive recorder is a constant recording type, the constant recording type drive recorder records the sensor output collected by the sensor group 31 in association with information related to time. At this time, the always-recording type drive recorder satisfies the condition when the output of the sensor satisfies a predetermined condition, for example, when the output value of the acceleration sensor satisfies a condition corresponding to a sudden handle or sudden acceleration. The time or information that can specify the time is further recorded. In addition, the always-recording type drive recorder transmits the sensor output associated with each time and the time when the condition is satisfied or the information that can specify the time to the information providing apparatus 10. At this time, only the sensor output before and after the time satisfying the above condition among the sensor outputs recorded in association with the time is extracted by the always-recording type drive recorder, and information is provided after generating the near candidate data You may make it output to the apparatus 10. FIG. Moreover, it is good also as making the information provision apparatus 10 perform generation of near-miss candidate data.

  1 and 2 exemplify the case where near candidate data is collected using the drive recorder 30, a digital tachograph may be employed instead of the drive recorder 30, and the drive recorder and digital Both tachographs can be used. As described above, when both the drive recorder and the digital tachograph are employed, it is preferable to synchronize the time of the clock referred to by both devices. For example, data in which video frame numbers are associated with each time by a drive recorder and data in which various sensor outputs are associated with each time by a digital tachograph may be output in different systems. Also in this case, the drive recorder and the digital tachograph are preferably transmitted to the information providing apparatus 10 after adding information capable of identifying the time when occurrence of the near-miss is estimated.

[Configuration of Information Providing Device]
Next, a functional configuration of the information providing apparatus according to the present embodiment will be described. FIG. 3 is a block diagram illustrating a functional configuration of the information providing apparatus according to the first embodiment. As illustrated in FIG. 3, the information providing apparatus 10 includes a communication I / F unit 11, a storage unit 13, and a control unit 15. Further, the information providing apparatus 10 may further include a reader / writer 12. The information providing apparatus 10 has functions other than the function units shown in FIG. 3 such as various function units of a known computer, such as various input devices and audio output devices.

  The communication I / F unit 11 is an interface that performs communication control with other devices such as the drive recorder 30 and the navigation device 50. For example, the communication I / F unit 11 receives near miss candidate data from the drive recorder 30. Further, the communication I / F unit 11 receives current position information from the navigation device 50, or transmits a near amount for each intersection traffic pattern to the navigation device 50 based on an instruction from the output unit 15d described later. . As an aspect of the communication I / F unit 11, a network interface card such as a LAN card or a modem can be employed.

  The reader / writer 12 is a device that communicates with an IC tag built in the memory card 20 to read or write recorded information in the IC tag. The reader / writer 12 emits an electromagnetic wave within an effective distance determined by the proximity type or near type specification. Using this electromagnetic wave, power is generated by a coil-type antenna incorporated in the IC tag of the memory card 20 to enable data communication. Then, the reader / writer 12 reads near-miss candidate data recorded on the IC tag of the memory card 20.

  The storage unit 13 is a storage device such as a semiconductor memory element such as a flash memory, a hard disk, or an optical disk. The storage unit 13 is not limited to the type of storage device described above, and may be a RAM (Random Access Memory) or a ROM (Read Only Memory).

  The storage unit 13 stores various programs such as an OS (Operating System) executed by the control unit 15 and an information providing program that provides the amount of incidents totaled for each traffic pattern. Further, the storage unit 13 stores, as an example of data necessary for executing the program executed by the control unit 15, the near data 13a, the node link data 13b, the near amount data 13c, and the near link data 13d. .

  The near data 13a is data related to the near hat. As an example, in the near data 13a, data that remains after the data that was erroneously estimated to be near by the drive recorder 30 among the near candidate data collected from the drive recorder 30 is excluded by the filter processing unit 15a described later is registered. Is done.

  As one aspect of the near data 13a, data in which the near ID, date / time, latitude, longitude, and file name are associated can be employed. “Hearing ID” here refers to identification information for identifying a near-miss. Further, the “file name” indicates a name given to a file of a video captured by the camera 35 before and after the time when it is estimated that a near-miss occurred. FIG. 4 is a diagram illustrating an example of the near data. In the example of FIG. 4, it is shown that the near-miss of the near-miss ID “00001” is generated at the latitude “35.50.00” and the longitude “139.55.00” at 10:10:00 on March 9. Furthermore, it indicates that the file name of the video related to the near-miss is “ID000010309101000.jpg”. Further, in the example of FIG. 4, it is shown that a near-miss of the near-miss ID “00002” occurred at 12:13:14 on March 9 at latitude “34.55.00” and longitude “138.46.00”. . Furthermore, it indicates that the file name of the video related to the near-miss is “ID000010309121314.jpg”.

  In the example of FIG. 4, the date and time when a near-miss occurred, the position information such as latitude and longitude, and the near-data associated with the video file name are illustrated, but other information other than this can also be associated. As an example, near data further associated with at least one of the transition of position information, the transition of acceleration, and the transition of speed included in the near candidate data can be employed. As another example, near data in which environmental information such as weather and brightness in which a near-miss has occurred can be further associated. As a further example, near data that further associates driving information such as vehicle / driver ID, blinker, shift, brake, steering angle of steering wheel, lights, hazard lamps and wipers is adopted. You can also.

  The node link data 13b is data in which the relationship between nodes and links is defined. A node is an area on a map specified by latitude and longitude. The node is, for example, an intersection or a landmark. A link is a road defined by two nodes and connecting the nodes. As an example, the node link data 13b is referred to by a counting unit 15c described later in order to specify the traveling direction of the vehicle from the transition of position information included in the near candidate data collected from the drive recorder 30. As another example, the node link data 13b is referred to by the output unit 15d described later in order to specify an intersection located within a predetermined range from the position notified from the navigation device 50.

  Here, as an aspect of the node link data 13b, an intersection table in which the shape of an intersection is defined and a road table in which the shape of a road connecting a plurality of intersections are defined are included.

  Among these, the intersection table is a table in which the intersection ID, latitude, longitude, and connection road ID are associated with each other. Here, “intersection ID” refers to an identifier for identifying an intersection on a road, and “road ID” refers to an identifier for identifying a road. The “connection road ID” refers to the road ID of each road connected to the intersection. For example, when the north direction of the intersection is used as a reference, the road ID of the road connected to the intersection is registered as “road ID 1” in the clockwise direction from the north direction of the intersection among the roads connected to the intersection. Registered as “road ID 2”... “Road ID 5” clockwise. Here, it is assumed that the intersection center, for example, the latitude and longitude of the intersection of the road are registered as coordinates representative of the intersection area, but the latitude and longitude of a plurality of points that specify the extension of the intersection area are assumed. It does not matter if you register. Thus, when defining the intersection area by the center of the intersection, for example, a predetermined range from the center of the intersection, for example, within 30 m is defined as the intersection area, or by a polygon having the center of the intersection as the center of gravity. You can define areas for intersections. In addition, here, the case where the intersection is a node has been illustrated, but an arbitrary area on the road, for example, the location of a landmark or a feature can be substituted for the node.

  FIG. 5 is a diagram illustrating an example of an intersection table. In the example of FIG. 5, the location of the intersection with the intersection ID “0011” is the latitude “35.50.01” and the longitude “139.55.02”, and the road IDs “0056”, “0057”, and “0058” Indicates that the road is connected.

  The road table is a table in which road IDs, intersection IDs, and connection directions are associated with each other. The “connection direction” here refers to the direction in which the road extends from the intersection, and is expressed by, for example, the angle at which the road extension direction deviates from the north direction of the intersection. In this case, the road extending right north from the intersection is 0 degrees, and the road extending right south from the intersection is 180 degrees. In addition, although the case where the intersection ID and the connection direction are associated with each road ID is illustrated here, other information such as the number of road lanes and traffic regulations may be further associated.

  FIG. 6 is a diagram illustrating an example of a road table. In the example of FIG. 6, the road with the road ID “0056” is in the north direction of the intersection with the intersection ID “0011”, the road with the road ID “0057” is in the east direction of the intersection with the intersection ID “0011”, and the road ID This indicates that the road “0058” is connected in the west direction of the intersection with the intersection ID “0011”. In addition, in the example of FIG. 6, the road with the road ID “0057” among the roads with the road ID “0056” to the road ID “0061” has two intersections with the intersection ID “0011” and the intersection ID “0012” in the east-west direction. Indicates tying.

  Here, the intersection table shown in FIG. 5 and the road table shown in FIG. 6 are shown as the node link data. However, the disclosed apparatus is not limited to the illustrated one, and known road network information is used as the node link data. Can be applied as

  The near amount data 13c is data indicating the near amount. As an example, in the near amount data 13c, the near amount totaled for each traveling direction of the vehicle by the below-described totaling unit 15c is registered for each intersection. As another example, the incident amount data 13c is output by an output unit 15d described later in order to output an incident amount for each traveling direction for an intersection located within a predetermined range from the current position of the service subscriber's vehicle 5. Referenced.

  As one aspect of the near miss amount data 13c, data in which the near amount of a vehicle passing through the intersection in the same traveling direction is associated with each traveling direction of the vehicle at the intersection can be adopted.

  Here, in this embodiment, the traveling direction of the vehicle at the intersection is defined by a traffic pattern in which the route from when the vehicle enters the intersection until it exits is classified into a plurality of patterns according to a predetermined standard. 7 and 8 are diagrams illustrating an example of a method for setting a traffic pattern. These examples of FIGS. 7 and 8 show examples of setting of a traffic pattern at a crossroad intersection. In the example of FIG. 7, the traffic patterns p1 to p4 entering the intersection and the traffic patterns p5 to p8 exiting from the intersection are set separately. In this case, a traffic pattern from p1 to p8 is set for each of the four roads connected to the intersection in each of two directions of the approach direction to the intersection and the exit direction from the intersection, that is, a total of eight directions. Further, in the example of FIG. 8, the traffic patterns P1 to P3 are set with the approach direction to the intersection and the exit direction from the intersection as one set of traveling directions. In this case, for each of the four roads connected to the intersection, three traffic patterns of right turn P1, left turn P2 and straight travel P3, that is, traffic patterns in a total of 12 directions are set.

  As a modified example of the method of setting the traffic pattern shown in FIG. 7, two traffic patterns are set for only a part of the roads connected to the intersection, that is, the forward route and the return route, and the remaining roads are the forward route and the return route. Can be set as one traffic pattern. In addition, as a modification of the method of setting the traffic pattern shown in FIG. 8, instead of setting three traffic patterns of right turn, left turn and straight travel, it causes an accident compared to a right turn and a right turn that are likely to cause an accident. It is also possible to set two traffic patterns, difficult straight ahead and left turn. Furthermore, as a modification of the method for setting the traffic pattern shown in FIG. 8, a traffic pattern called a U-turn at an intersection can be set in addition to the above three patterns.

  As an example, the near amount data 13c in which the traffic pattern shown in FIG. 8 is set is shown in FIG. FIG. 9 is a diagram illustrating an example of the near miss amount data 13c. FIG. 10 is a schematic diagram of an intersection included in the near amount data 13c shown in FIG. In the example of FIG. 9, the amount of nearness by traffic pattern at the two intersections of the intersection ID “0011” and the intersection ID “0012” shown in FIGS. 5 and 6 is illustrated. In the example of FIG. 10, the two intersections of the intersection ID “0011” and the intersection ID “0012” shown in FIGS. 5 and 6 and the six roads of the road ID “0056” to the road ID “0061” are included. It is schematic.

  As shown in FIG. 9, the incident amount data 13c is data in which an intersection ID, a traffic pattern ID, an approach road ID, an exit road ID, and an incident amount are associated with each other. Furthermore, as shown in FIG. 9, the near amount data 13c associates the near amount for each vehicle type of taxi and truck. The “entry road ID” here refers to a road ID of a road used when entering an intersection. The “escape road ID” refers to a road ID of a road used when escaping from an intersection. The “passage pattern ID” refers to an identifier that uniquely identifies a combination of an intersection ID, an approach road ID, and an exit road ID. In the example of FIG. 9, the taxi and truck industries are exemplified as the vehicle type, but the near amount may be registered in the general vehicle and business vehicle categories, and the manufacturer, displacement, or paint may be registered. The amount of near miss may be registered according to color.

  As shown in FIG. 10, an intersection with an intersection ID “0011” is an intersection of T-shaped roads including three roads with a road ID “0056” to a road ID “0058”. Therefore, since there are six combinations of the approach road ID and the exit road ID at the intersection with the intersection ID “0011” shown in FIG. 9, six traffic patterns are set. For example, a traffic pattern ID “0000011111” for entering from a road with an entry road ID “0056” and exiting from a road with an exit road ID “0057” is set. Further, a traffic pattern ID “0000011112” for entering from the road with the entry road ID “0056” and exiting from the road with the exit road ID “0058” is set. Similarly, the traffic patterns of the traffic pattern ID “0000011113” to the traffic pattern ID “0000011116” specified by the approach road ID and the exit road ID are set at the intersection of the intersection ID “0011”. Since the intersection with the intersection ID “0012” is a crossroad intersection as shown in FIG. 10, a total of 12 directions of passage patterns are set in the same manner as the traffic pattern setting method shown in FIG. 8.

  The near link data 13d is data in which a link with a near hat generated in the traffic pattern is associated with each traffic pattern at each intersection. The “link” here refers to a link for associating the traffic pattern of each intersection with the near data 13a. For example, a near ID or a video file name can be used. As an aspect of the near link data 13d, data in which a traffic pattern ID and a near ID are associated can be employed. Here, although the case where the near ID is associated with the traffic pattern ID is illustrated, the near ID may be associated with a combination of the intersection ID, the approach road ID, and the escape road ID without using the traffic pattern ID.

  FIG. 11 is a diagram illustrating an example of the near link data 13d. In the example of FIG. 11, out of all six combinations of the approach road ID and the exit road ID at the intersection with the intersection ID “0011”, the incidents in four traffic patterns of the traffic pattern ID “0000011111” to the traffic pattern ID “0000011114” The link with the data 13a is illustrated. As shown in FIG. 11, four near data of near IDs “00105”, “01882”, “32224”, and “07003” are linked to the traffic pattern of the traffic pattern ID “0000011111”.

  The control unit 15 has an internal memory for storing programs defining various processing procedures and control data, and executes various processes using these. As shown in FIG. 3, the control unit 15 includes a filter processing unit 15a, a calculation unit 15b, a totaling unit 15c, and an output unit 15d.

  The filter processing unit 15 a is a processing unit that filters the near candidate data collected from the drive recorder 30. That is, the filter processing unit 15a uses the speed and acceleration included in the near candidate data to execute near miss determination of the near hat in more detail than the drive recorder 30, thereby storing the near miss candidate data determined to be false. 13 to be excluded from registration.

  As one aspect, the filter processing unit 15 a activates processing when near-miss data is acquired from the drive recorder 30 via the communication I / F unit 11 or the memory card 20. First, the filter processing unit 15a includes the position information measured at the time that triggered the drive recorder 30 among the position information included in the near candidate data, that is, the occurrence point of the near hat in an area defined as an intersection. It is determined whether or not it is included. By this determination, only near-missing candidate data that is estimated that a near-miss occurred at the intersection is registered in the storage unit 13 as near-miss data.

  Then, when the near-miss occurrence point is within the intersection, the filter processing unit 15a observes the speed difference over a predetermined observation section, for example, 2 seconds before and after the time when the near-miss occurrence is estimated. Subsequently, the filter processing unit 15a determines whether or not a deceleration of a predetermined threshold, for example, 10 km / h or more has been observed before and after the trigger. Thus, only near-miss candidate data that can be estimated to have undergone rapid deceleration are extracted.

  Further, the filter processing unit 15a executes the following process when a predetermined threshold deceleration is observed in the observation section. That is, the filter processing unit 15a has a predetermined time interval, for example, within 2 seconds, at which the jerk takes a maximum value and a minimum value in the observation section, and the difference between the maximum value and the minimum value of the jerk is It is further determined whether or not a predetermined threshold value, for example, 0.06 or more. Thus, it is determined in more detail whether or not sudden deceleration has been performed, and only near-miss candidate data that can be estimated that rapid deceleration has been performed is extracted. At this time, when the time interval between the maximum value and the minimum value of the jerk in the observation section is within a predetermined period, and the difference between the maximum value and the minimum value of the jerk is equal to or greater than a predetermined threshold, It can be estimated that sudden deceleration has occurred. “Jerk acceleration” refers to a change in acceleration per unit time and is also called jerk.

  Then, the filter processing unit 15a has a time interval between the maximum value and the minimum value of the jerk in the observation section within a predetermined period, and the difference between the maximum value and the minimum value of the jerk is a predetermined threshold value. In the above case, the following processing is executed. That is, the filter processing unit 15a determines whether or not the integral value of the jerk over a predetermined period, for example, 5 seconds, after showing the minimum value of the jerk in the observation section is a predetermined threshold, for example, −0.252 or less. Determine further. Thus, it is determined whether or not there is a room for the driver to release the brake after sudden braking. At this time, when the integral value of the jerk is equal to or less than a predetermined threshold in the observation section, it can be estimated that the driver has no room to loosen the brake and is likely to be a near-miss.

  As described above, the filter processing unit 15a performs the near-miss determination of the near-miss by the drive recorder 30 by using the speed and acceleration included in the near-miss candidate data. Then, the filter processing unit 15a registers only the near candidate data that is highly likely to be a near-miss, that is, determined to be true, in the storage unit 13 as near-miss data.

  At this time, the filter processing unit 15a extracts only the data at the occurrence point of the near-miss from the data included in the near-miss candidate data from the viewpoint of reducing the capacity when registering the near-term data in the storage unit 13, and extracts the extracted data. Register as “near data”. As an example, the filter processing unit 15a assigns a near-miss ID to the near-miss candidate data that is likely to be a near-miss, that is, true. The filter processing unit 15a then calculates the latitude, longitude, and video at the time that triggered the drive recorder 30 from among the data in which position information, acceleration, speed, and video are associated with each other as the near candidate data. Extract. In addition, the filter processing unit 15a regards the time when the drive recorder 30 is activated as the date and time when the near-miss occurred, and data that associates the date and time, latitude, longitude, and video with the near-missed near ID. Is registered in the storage unit 13 as “near data”. Here, the case where only the data of the occurrence point of the near-miss is registered as the near-case data is exemplified, but the near-candidate data collected from the drive recorder 30 may be directly registered as “near-occurrence data”.

  By such filtering, that is, compared to the case where all near miss candidate data are counted, the near data generated in the storage unit 13 can improve the reliability of the near miss occurrence amount.

  The calculation unit 15b uses the detected value of the GPS receiver 32 of the vehicle 3 as the movement trajectory of the vehicle 3 when the drive recorder 30 determines that the traveling state of the vehicle 3 collected by the acceleration sensor 33 matches the dangerous state. It is a processing part which calculates based on. As one aspect, when the near data is registered in the storage unit 13 by the filter processing unit 15a, the calculation unit 15b is based on a plurality of pieces of position information included in the near candidate data regarding the near data registered this time. The travel locus of the vehicle 3 is calculated. For example, the calculation unit 15b calculates a travel locus from time-series changes in latitude and longitude in a period before and after a time point when near-miss occurrence is estimated.

  The totaling unit 15c is a processing unit that totalizes the travel trajectory of the vehicle 3 calculated by the calculation unit 15b for each region on the road and for each traveling direction. As one aspect, the totaling unit 15 c performs map matching between the travel locus of the vehicle 3 calculated by the calculation unit 15 b and the node link data 13 b stored in the storage unit 13, so that the vehicle 3 at the intersection is processed. Identify the traffic pattern. At this time, the totaling unit 15c increments the near amount of the traffic pattern ID corresponding to the previously identified traffic pattern of the vehicle 3 in the near amount of the near amount data 13c. Furthermore, the totaling unit 15c generates a link with the near data by registering the near ID registered as near data at this time in the storage unit 13 in association with the traffic pattern ID of the intersection.

  The output unit 15d is a processing unit that outputs the amount of incidents totaled for each traffic pattern to another computer in response to a request from the other computer. As an aspect, when the output unit 15d receives position information from the navigation device 50 mounted on the service subscriber's vehicle 5, the output unit 15d extracts an intersection located within a predetermined range, for example, 500 m from the position. At this time, the output unit 15d extracts an intersection ID having a latitude and longitude within 500 m from the center from the intersection table, with the latitude and longitude received from the navigation device 50 as the center. Then, the output unit 15 d refers to the near amount data 13 c stored in the storage unit 13 and outputs the near amount for each traffic pattern regarding the intersection ID extracted from the intersection table to the navigation device 50.

  Here, it is assumed that the ID system of the node link data used by the information providing apparatus 10 and the navigation apparatus 50 is the same, but the ID system of the node link data is not necessarily the same. For example, when the ID system of the node link data is different between the information providing device 10 and the navigation device 50, the information providing device 10 holds a correspondence table that holds the correspondence relationship between the intersection ID and the road ID in both devices. Keep it. After that, the output unit 15d refers to the correspondence table and converts the road ID for defining the intersection ID and the traffic pattern into the ID system of the node link data used in the navigation device 50, and then outputs it. That's fine. Thereby, even when the ID system of the node link data is different between the information providing apparatus 10 and the navigation apparatus 50, the navigation apparatus 50 can execute notification regarding the near miss.

[Configuration of equipment mounted on service subscriber's vehicle]
Next, a functional configuration of an apparatus mounted on a service subscriber's vehicle according to the present embodiment will be described. FIG. 12 is a block diagram illustrating a functional configuration of the device mounted on the vehicle 5 of the service subscriber according to the first embodiment. As shown in FIG. 12, the service subscriber vehicle 5 includes a display input unit 51, a voice output unit 52, a communication I / F unit 53, a GPS receiver 54, and a navigation device 50.

  The display input unit 51 is a displayable and inputable device that can accept an operation input on a display device such as a liquid crystal panel or a display. As an example, the display input unit 51 displays the map information output by the navigation device 50, a notification screen that alerts the user to route guidance or near-miss, and also inputs instructions to the navigation device 50, such as setting a purpose. Or accept.

  The audio output unit 52 is a device that outputs audio. As an example, the voice output unit 52 outputs a voice for route guidance output by the navigation device 50 or a voice for calling attention to a near-miss. As an aspect of the audio output unit 52, a speaker or the like can be given.

  The communication I / F unit 53 is an interface that performs communication control with another apparatus, for example, the information providing apparatus 10. For example, the communication I / F unit 53 transmits the position information measured by the GPS receiver 54 to the information providing apparatus 10, and receives the amount of nearness for each traffic pattern regarding the intersection from the information providing apparatus 10. . As an aspect of the communication I / F unit 53, a network interface card such as a LAN card or a modem can be employed.

  The GPS receiver 54 measures position information such as latitude and longitude by receiving radio waves from a plurality of GPS satellites and determining the distance to each GPS satellite.

  The navigation device 50 is a device that guides the route to the driver by comparing a position on the road included in the planned travel route of the vehicle 5 with an electronic map (not shown). As an example, the navigation device 50 monitors whether or not the current position of the service subscriber's vehicle 5 measured by the GPS receiver 54 has approached within a predetermined distance from the intersection. At this time, the navigation device 50 executes the following process when the current position approaches within a predetermined distance from the intersection. That is, the navigation device 50 determines whether or not the near amount of the traffic pattern corresponding to the route being guided out of the near amount provided for each traffic pattern by the information providing device 10 exceeds a predetermined threshold. And the navigation apparatus 50 performs the navigation which alerts the near-miss at the said intersection, when the amount of incidents exceeds the threshold value. Note that a value designed by the administrator is set as the threshold value. Further, different threshold values may be set depending on the time zone, weather, and location. Furthermore, the threshold value may be set such that the number of near misses is equal to or greater than a certain ratio with respect to the traffic volume of the traffic volume survey result.

  13A and 13B are diagrams illustrating an example of a navigation screen. In these examples of FIG. 13A and FIG. 13B, the incident amount of the traffic pattern that goes straight on the T-shaped road in the north direction does not exceed the threshold value, and the incident amount of the traffic pattern that turns right on the T-shaped road in the east direction exceeds the threshold value. Show the case. As shown in FIG. 13A, when a route in which the service subscriber's vehicle 5 goes straight on the T-shaped road in the north direction is specified, the near miss amount does not exceed the threshold value. Therefore, the navigation device 50 performs normal navigation by causing the display input unit 51 to display only the route guidance that goes straight on the T-shaped road in the north direction. On the other hand, as shown in FIG. 13B, when the route of the service subscriber's vehicle 5 turning right on the T-shaped road is routed, the near amount exceeds the threshold. For this reason, the navigation device 50 causes the display input unit 51 to display a route guidance for turning the T-shaped road to the east and alerting the near-miss to attention. At this time, the navigation device 50 can also output from the voice output unit 52 a voice message that calls attention to the near-miss.

[Process flow]
Next, a processing flow of the information providing system according to the present embodiment will be described. Here, after (1) the aggregation process executed by the information providing apparatus 10 is described, the (2) navigation process executed by the navigation apparatus 50 will be described.

(1) Aggregation Process FIG. 14 is a flowchart illustrating the procedure of the aggregation process according to the first embodiment. This tabulation process is started when near candidate data is acquired from the drive recorder 30 via the communication I / F unit 11 or the memory card 20.

  As illustrated in FIG. 14, the filter processing unit 15 a acquires near miss candidate data from the drive recorder 30 via the communication I / F unit 11 or the memory card 20 (step S <b> 101).

  Then, the filter processing unit 15a determines whether or not the position information measured at the time when the drive recorder 30 is triggered out of the position information included in the near candidate data, that is, whether the occurrence point of the near hat is included in the intersection. (Step S102). If the near-miss occurrence point is not included in the area defined as the intersection (No at Step S102), the process proceeds to Step S109.

  If the occurrence point of a near-miss is included in the area defined as an intersection (Yes at step S102), the filter processing unit 15a determines whether the speed, acceleration, and jerk included in the near-miss candidate data satisfy a predetermined condition. It is further determined whether or not (step S103). Even when the speed, acceleration, and jerk included in the near candidate data do not satisfy the predetermined conditions (No at Step S103), the process proceeds to Step S109.

  At this time, when the speed, acceleration, and jerk included in the near-missing candidate data satisfy the predetermined conditions (Yes at Step S103), the data of the near-miss occurrence point is extracted from the near-missing candidate data and stored as near-missing data. 13 is registered (step S104).

  Thereafter, the calculation unit 15b calculates the travel locus of the vehicle 3 from time-series changes in latitude and longitude included in the near-missing candidate data related to near-miss data registered this time (step S105). Then, the totaling unit 15c performs map matching between the travel locus of the vehicle 3 calculated by the calculation unit 15b and the node link data 13b stored in the storage unit 13, thereby causing the traffic pattern of the vehicle 3 at the intersection Is specified (step S106).

  Subsequently, the totaling unit 15c increments the near amount of the traffic pattern ID corresponding to the previously identified traffic pattern of the vehicle 3 in the near amount of the near amount data 13c (step S107).

  Thereafter, the totaling unit 15c registers the near data of the near data in the storage unit 13 in association with the traffic pattern ID of the intersection, thereby generating a link between the near data and the traffic pattern (step S108).

  Then, until all near miss candidate data acquired from the drive recorder 30 has been processed (No at Step S109), the processes from Steps S102 to S108 are repeated. Thereafter, when all near miss candidate data acquired from the drive recorder 30 are processed (Yes at Step S109), the process is terminated.

(2) Navigation Process FIG. 15 is a flowchart illustrating the procedure of the navigation process according to the first embodiment. This navigation process is a process that is repeatedly executed when the navigation device 50 is powered on.

  As shown in FIG. 15, when a predetermined period has passed (Yes at Step S301), the navigation device 50 executes the following process. That is, the navigation device 50 transmits the positional information measured by the GPS receiver 54 to the information providing device 10, and as a response, determines the amount of nearness for each traffic pattern related to the intersection located within a predetermined range from the current position. Obtain (step S302). If the predetermined period has not elapsed (No at Step S301), the process proceeds to Step S303 without executing Step S302.

  Then, the navigation device 50 monitors whether or not the current position of the service subscriber's vehicle 5 measured by the GPS receiver 54 has approached within a predetermined distance from the intersection (step S303).

  At this time, when the current position approaches within a predetermined distance from the intersection (Yes at Step S303), the navigation device 50 executes the following process. In other words, the navigation device 50 identifies the amount of nearness of the traffic pattern corresponding to the route being guided out of the amount of nearness provided for each traffic pattern by the information providing device 10 (step S304). Subsequently, the navigation device 50 determines whether or not the amount of miss of the traffic pattern corresponding to the route being guided exceeds a predetermined threshold (step S305).

  If the incident amount exceeds the threshold (Yes at Step S305), the navigation device 50 executes navigation that alerts the near-miss at the intersection (Step S306). On the other hand, when the amount of near miss does not exceed the threshold (No at Step S305), the navigation device 50 performs normal navigation (Step S307).

  Note that the information providing apparatus may perform the navigation processing according to FIG. For example, the information providing apparatus receives information including a rule scheduled to travel from the navigation apparatus 50 in advance. Then, the information providing device transmits navigation information to the navigation device based on the planned travel route and the vehicle position information and the amount of near miss received from the navigation device periodically. The navigation information is information including a warning message for the driver. In other words, in the present embodiment, as an example of the case where the information providing apparatus 10 outputs the amount of incidents totaled for each intersection and traffic pattern by the totaling unit 15c as support information to be output to another computer, for example, the navigation apparatus 50. However, it is not limited to this. For example, the information providing apparatus 10 outputs navigation information generated based on the vehicle position information transmitted from the navigation apparatus 50 and the near amount data 13c stored in the storage unit 13 to the navigation apparatus 50 as support information. You can also. At this time, the information providing apparatus 10 generates navigation information that alerts a near-miss at the intersection when the amount of the incident pattern of the intersection corresponding to the planned travel route of the vehicle 5 exceeds a predetermined threshold. And output to the navigation device 50.

[Effect of Example 1]
As described above, in the information providing apparatus 10 according to the present embodiment, when near-miss occurs frequently in an area on the road, for example, at an intersection, it may be dangerous when passing the intersection in any direction of travel. It is possible to make the user grasp whether the property is high. Therefore, in the information providing apparatus 10 according to the present embodiment, when the vehicle passes the intersection in the traveling direction in which near-misses are frequently occurring, pay more attention than when traveling in the other traveling direction to the driver, You can prepare to perform recognition, judgment and operation according to the direction of travel. Therefore, according to the information providing apparatus 10 according to the present embodiment, the risk of reoccurrence of an accident with the same cause as that when a near-miss occurred in the past is reduced by allowing the user to recognize the traveling direction to which special attention should be paid. As a result, it is possible to contribute to accident prevention.

  Further, the information providing apparatus 10 according to the present embodiment provides the navigation apparatus 50 with the amount of nearness according to the traveling direction regarding intersections existing within a predetermined range from the position received from the navigation apparatus 50 of the service subscriber's vehicle 5. . For this reason, in the information provision apparatus 10 which concerns on a present Example, when the service subscriber's vehicle 5 approachs an intersection, it can alert | report the amount of nearness according to the advancing direction of the said intersection in real time. Therefore, according to the information providing apparatus 10 according to the present embodiment, it is possible to support effective driving by preventing accidents.

  In the above-described first embodiment, the case where the amount of incident for each intersection traffic pattern is provided according to the current position notified from the navigation device 50 has been exemplified. An amount can also be provided. Therefore, in this embodiment, a case will be described in which a near-miss map is provided by developing on the electronic map the amount of incident for each intersection traffic pattern.

  FIG. 16 is a diagram illustrating the configuration of the information providing system according to the second embodiment. As illustrated in FIG. 16, the information providing system 2 is different from the information providing system 1 illustrated in FIG. 1 in that it includes an information providing device 70 and an information processing terminal 80. In addition, below, the same code | symbol is attached | subjected to what exhibits the same function, and the description is abbreviate | omitted.

  The information processing terminal 80 is a terminal device that executes information processing. As an aspect of the information processing terminal 80, in addition to a fixed terminal such as a personal computer (PC), a mobile terminal such as a mobile phone, a PHS (Personal Handyphone System) or a PDA (Personal Digital Assistant) may be used. Can be adopted. The information processing terminal 80 is used not only for service subscribers but also for arbitrary users including general end users.

[Configuration of Information Providing Device]
FIG. 17 is a block diagram illustrating a functional configuration of the information providing apparatus according to the second embodiment. In the information providing apparatus 70 illustrated in FIG. 17, the control unit 71 further includes a normalization unit 71 a and a search unit 71 c as compared with the information providing apparatus 10 illustrated in FIG. 3. Also, the information providing apparatus 70 shown in FIG. 17 is different from the information providing apparatus 10 shown in FIG. 3 in that some of the functions of the output unit 71b are different. Further, the information providing device 70 shown in FIG. 17 is different from the information providing device 10 shown in FIG. 3 in that a part of the near miss data 72a stored in the storage unit 72 is different.

  Among these, the normalization part 71a is a process part which normalizes the near amount of the near amount data 72a. As one aspect, the normalization unit 71a starts processing when the near amount is updated by the totaling unit 15c. At this time, the normalization unit 71a normalizes the near amount of each traffic pattern ID belonging to the intersection ID in which the near amount is updated in the near amount data 72a. In addition, the normalization unit 71 a registers the near amount after normalization of each traffic pattern ID in the near amount data 72 a of the storage unit 72. Here, the case where the near amount is normalized every time the near amount is updated by the totaling unit 15c is illustrated, but normalization of the near amount can be executed at an arbitrary timing. For example, the normalization unit 72a can also normalize the near amount when a predetermined period has elapsed since the previous normalization.

  As an example of such a normalization method, there is a method of summing up the near amount of all the traffic patterns at each intersection and calculating the ratio of the near amount for each traffic pattern with respect to the total value. Note that, by normalizing, even if the amount of incident is different for each intersection, it is possible to evaluate intersections having similar tendencies by the ratio of the amount of incident generated for each traffic pattern. 18 and 19 are diagrams for explaining normalization of the near amount. In these examples of FIG. 18 and FIG. 19, the number surrounded by a square indicates the near amount, the number surrounded by an ellipse indicates the normalized value, and the near amount of the traffic pattern in which the arrow is not illustrated is zero. Shall.

In the example of FIG. 18 is a Hiyari amount of traffic pattern P _A to escape to enter an intersection from the east of the road to the west of the road is "one-time", escape to enter an intersection from the north of the road to the south of the road Hiyari amount of traffic pattern P _B which is "99 times". In this case, the normalization unit 71a, by dividing Hiyari amount of traffic patterns P _A "1" in the total value of the near-miss of the total traffic pattern "100 = 1 + 99", Hiyari of traffic patterns P _A The quantity normalization value “0.01” is calculated. Furthermore, the normalization unit 71a, by dividing Hiyari amount of traffic pattern P _B to "99" in the total value of the near-miss of the total traffic pattern "100", Hiyari amount of normalized values of the traffic pattern P _B "0.99 Is calculated.

In the example of FIG. 19, the incident amount of the traffic pattern P _α that enters the intersection from the east road and exits to the west road is “10 times”, and enters the intersection from the north road and exits to the south road. Hiyari amount of traffic pattern _P β that is "990 times". In this case, the normalization unit 71a, by dividing Hiyari amount of traffic patterns P _alpha "10" the total value of the near-miss of the total traffic patterns "1000 = 10 + 990", Hiyari the traffic pattern P _alpha The quantity normalization value “0.01” is calculated. Furthermore, the normalization unit 71a, by dividing Hiyari amount of traffic patterns P _beta to "99" in the total value of the near-miss of the total traffic pattern "100", Hiyari amount of normalized values of the traffic pattern P _beta "0.99 Is calculated. In the example of FIGS. 18 and 19, the case where the near amount is normalized regardless of the vehicle type such as a taxi or a truck is illustrated, but the near amount may be normalized for each vehicle type.

  Here, when the intersections shown in FIGS. 18 and 19 are compared in a macro view of the entire intersection, the intersection shown in FIG. 19 has a total amount of near miss 10 times larger than the intersection shown in FIG. For this reason, the intersection shown in FIG. 19 is an intersection with a large amount of incident, and the intersection shown in FIG. 18 is an intersection with a small amount of incident. However, when the intersections shown in FIGS. 18 and 19 are compared with each other at a microscopic field for each intersection, the normalization value with a total value of 1 indicates that the traffic pattern passing from north to south is “0.99”, and from east to west. Becomes the same value of “0.01”. It can be seen that the intersections shown in FIG. 18 and FIG. 19 are intersections having similar characteristics in occurrence of near-miss. As described above, the normalization unit 71a normalizes the near amount of the traffic pattern ID at the intersection where the near amount has been updated in order to make a comparison with a microscopic field of view.

  In addition, although the case where the near amount was normalized by calculating the ratio was illustrated here, the disclosed apparatus is not limited to this, and can be normalized to other index values. As an example, the disclosed apparatus normalizes the numerical value of “0.0 to 1.0” where the total value of the near misses is “1”, then sets “0.0 to 0.1” to level 1 and “0.1 to 0.2” to level 2 Thus, it can be converted into a level value divided into arbitrary hierarchies. As another example, the disclosed device converts the incident amount into an index value in the order of “N”, “N−1”, “N−2”... May be.

  FIG. 20 is a diagram illustrating an example of the near amount data 72a including the near amount after normalization. The near miss amount data 72a shown in FIG. 20 includes the near miss amount before normalization in addition to the near miss amount data 13c shown in FIG. It is associated. FIG. 20 shows an example of normalization performed without distinguishing between vehicle types. Therefore, in FIG. 20, the incident amount of each traffic pattern before normalization differs between the taxi and the truck, but the incident amount of each traffic pattern after normalization is the same between the taxi and the truck. In normalization, normalization may be performed for each vehicle type.

  The output unit 71b is a processing unit that outputs a near-miss map by developing on the electronic map the near amount for each intersection passage pattern stored in the storage unit 72 as the near amount data 72a.

  As an aspect, when the output unit 71b receives a near-miss map browsing request from the information processing terminal 80, the output unit 71b does not illustrate an electronic map corresponding to a region specified by the browsing request, for example, a region such as a prefecture or a municipality. Read from internal memory. Then, the output unit 71b creates a near-miss map in which the display mode of the intersection is changed according to the total value of the near-miss amounts of all the traffic patterns of the intersection included in the electronic map of the area specified by the browsing request. Output to the terminal 80. For example, the output unit 71b creates a near-miss map in which an intersection where the near amount is zero is plain, an intersection where the near amount is 1 to 10 is yellow, and an intersection where the near amount is 11 to 20 is red. Subsequently, when the output unit 71b receives the designation of the intersection on the near-miss map displayed on the information processing terminal 80, the output unit 71b is included in each traffic pattern together with the amount of incident for each traffic pattern of the intersection ID that has received the designation. The near ID is displayed on the information processing terminal 80. Thereafter, when the output unit 71b receives selection of a near-miss ID, the output unit 71b calls the near-miss video stored in the storage unit 13 using the file name corresponding to the near-miss ID that has received the selection, and then displays the video. Is distributed to the information processing terminal 80. Note that the output unit 71b may provide a normalized near amount instead of the near amount.

  21A and 21B are diagrams illustrating an example of a near-miss map. As shown in FIG. 21A, in the near-miss map 40A, near-miss occurs at the intersections of the intersection IDs “0011” and “0012”, and the display mode is distinguished from other intersections. When the intersection with the intersection ID “0011” is designated on the near-miss map 40A, as shown in FIG. 21B, the incident amount for each traffic pattern is displayed together with the enlarged view of the intersection with the intersection ID “0011”. Is displayed. In the example of FIG. 21B, the amount of incident when turning right from the north direction to the west direction at the T-junction is the highest at “20”. In the example of FIG. 21B, the amount of incident when turning right from the east direction to the north direction at the T-junction is “10”, which is the next highest. In the example of FIG. 21B, the near miss amount when the vehicle goes straight from the west to the east on the T-junction is “5”, which is the next highest. In this way, in the example shown in FIG. 21B, since the amount of incident when turning right from the north direction to the west direction at the T-junction is high, pay attention to vehicles passing in the east-west direction when turning right at the end of the T-junction. It turns out that it is important to do.

  The search unit 71c is a processing unit that searches for an intersection whose shape and amount of incident are similar to an intersection designated on the near-miss map.

  Explaining this, when the search unit 71c receives a similar intersection search request from the information processing terminal 80, the intersection ID of the designated intersection that has been designated on the near-miss map among the intersection IDs stored in the intersection table. All road IDs associated with are read out. Thus, the number of roads connected to the designated intersection is specified. Further, the search unit 71c reads out the connection direction having the road ID of the road connected to the designated intersection among the connection directions stored in the road table and corresponding to the intersection ID of the designated intersection. Thereby, the connection direction of the road connected to the designated intersection is specified.

  After that, the search unit 71c searches the intersection table and the road table as intersections of similar candidates for intersections having similar numbers and directions of roads connected to the designated intersection. For example, the search unit 71c matches the number of roads connected to the designated intersection, and the displacement of the connection direction with the road connected to the designated intersection is within a predetermined range, for example, “± 5 degrees”. Search for an intersection. At this time, the search unit 71c determines whether the shape of each intersection is similar between the intersection table and the intersection defined in the road table while rotating the connection direction of the road connected to the designated intersection. To do. For this shape similarity determination, a technique for searching for a shape having a known topology with the same shape can be suitably applied. Note that the user can set arbitrary values for the “number of roads” and the “connection direction” as determination criteria for similarity of shape via the information processing terminal 80. Further, as other road attributes, information such as prefectural road / national road type, road width, number of road lanes, etc. may be similarly set, and similar candidates including them may be narrowed down and searched.

  After that, when a similar candidate intersection is searched, the search unit 71c refers to the near amount data 72a and searches for intersections having a similar amount to the specified intersection from among the similar candidate intersections. For example, the search unit 71c reads the near amount of each traffic pattern ID corresponding to the intersection ID of the designated intersection, and reads the near amount of each traffic pattern ID corresponding to the intersection ID of the intersection of similar candidates. At this time, when the necessity of normalization is specified as the search condition, the search unit 71c reads the near amount corresponding to the specified necessity of normalization. Furthermore, when the vehicle type is specified as the search condition, the search unit 71c reads the near amount corresponding to the specified type. After that, the search unit 71c searches for an intersection where the difference in the amount of nearness between all the passing patterns is within a predetermined range between the designated intersection and the intersection of similar candidates. In this way, intersections having similar shapes and near-miss amounts are searched as similar intersections. The user can set an arbitrary value for the “difference in incident amount” as a determination criterion for traffic volume similarity via the information processing terminal 80.

[Process flow]
Subsequently, a flow of processing of the information providing system according to the present embodiment will be described. Here, after (1) the information providing process executed by the information providing apparatus 70 is described, the procedure of the (2) similarity search process is described.

(1) Information Provision Processing FIG. 22 is a flowchart illustrating a procedure of information provision processing according to the second embodiment. This information providing process is activated when a near-miss map browsing request is received from the information processing terminal 80.

  As illustrated in FIG. 22, the output unit 71b displays a near-miss map in which the display mode of the intersection is changed according to the total value of the near-miss amounts of all the intersection patterns included in the electronic map of the area specified by the browsing request. Create and output to the information processing terminal 80 (step S501).

  Subsequently, when the output unit 71b receives designation of an intersection on the near-miss map displayed on the information processing terminal 80 (step S502), the output unit 71b executes the following process. In other words, the output unit 71b outputs the near ID included in each traffic pattern to the information processing terminal 80 together with the amount of incident for each traffic pattern of the intersection ID that has received the designation (step S503).

  Thereafter, when selection of a near ID is received (Yes at step S504), the output unit 71b executes the following process. That is, the output unit 71b uses the file name corresponding to the near-miss ID that has received the selection to call the near-miss video stored in the storage unit 13, and then distributes the video to the information processing terminal 80 (step). S505). If the selection of the near ID is not accepted (No at step S504), the process proceeds to step S506.

  When a similar intersection search request is received from the information processing terminal 80 (Yes in step S506), the search unit 71c executes the following process. That is, the search unit 71b executes a similarity search process for searching for an intersection having a shape and a near miss amount similar to an intersection designated on the near-miss map (step S507), and proceeds to step S504. If a similar intersection search request is not received from the information processing terminal 80 (No at Step S506), the process proceeds to Step S504.

(2) Similarity Search Processing FIG. 23 is a flowchart illustrating a procedure of similarity search processing according to the second embodiment. This similarity search process is a process corresponding to step S507 shown in FIG. 22, and is started when a similar intersection search request is received from the information processing terminal 80 (Yes in step S506).

  As shown in FIG. 23, the search unit 71c searches the intersection table and the road table as intersections of similar candidates for intersections having similar numbers and directions of roads connected to the designated intersection designated on the near-miss map. (Step S701).

  At this time, if a similar candidate intersection is searched (Yes in step S702), the search unit 71c refers to the near amount data 72a, and the intersection where the specified intersection and the near amount are similar among the similar candidate intersections. As a similar intersection (step S703). If there is no intersection of similar candidates (No at step S702), the process ends as it is.

  Here, when a similar intersection is searched (Yes at step S704), the output unit 71b sends the near ID included in each traffic pattern to the information processing terminal 80 together with the amount of incident for each traffic pattern of the intersection ID of the similar intersection. Output (step S705), the process is terminated. If there is no similar intersection (No at step S704), the process is terminated as it is.

[Effect of Example 2]
As described above, in the information providing apparatus 70 according to the present embodiment, when near-miss occurs frequently in an area on the road, for example, at an intersection, it may be dangerous when the intersection is passed in any direction of travel. It is possible to make the user grasp whether the property is high. Therefore, in the information providing apparatus 70 according to the present embodiment, when the vehicle passes through the intersection in the traveling direction in which near-misses are frequently occurring, pay more attention than when traveling in the other traveling direction to the driver, You can prepare to perform recognition, judgment and operation according to the direction of travel. Therefore, according to the information providing apparatus 70 according to the present embodiment, it is possible to reduce the risk that an accident with the same cause as that when a near-miss occurred in the past by recognizing the traveling direction to which the user should be particularly careful. As a result, like Example 1, it is possible to contribute to accident prevention. In addition, by providing a near amount for each traveling direction, the user can grasp a traffic pattern in which near-miss occurs frequently. Therefore, it is possible to take countermeasures for intersections with frequent near-miss occurrences for traffic patterns with frequent near-miss occurrences. Therefore, the user can efficiently take measures against the intersection.

  Further, the information providing apparatus 70 according to the present embodiment accepts designation of an intersection as an example of an area on a road. Furthermore, the information providing apparatus 70 according to the present embodiment searches for a point that is similar in shape and amount of incident to the intersection. In addition, the information providing apparatus 70 according to the present embodiment provides a near amount for each traveling direction regarding the intersection obtained as a search result. For this reason, in the information providing apparatus 70 according to the present embodiment, it is possible to search for an intersection where the traffic environment is similar to the occurrence point of the near miss or the accident occurrence point. Therefore, according to the information providing apparatus 70 according to the present embodiment, it can be used for urban design for designing signs, signals, road widths, and the like, and for traffic safety education for educating precautions at intersections with high risk of accidents. become. Furthermore, a similar search can be performed in a wider range by performing a similar search based on the normalized near amount.

  Further, the information providing apparatus 70 according to the present embodiment refers to the near data 13a associated with the file ID of the video captured by the camera 35 at the time of occurrence of the near ID and near incident, and sets the near ID that has been designated. Provide further associated video. For this reason, in the information provision apparatus 70 which concerns on a present Example, the cause which a near miss generate | occur | produces can be confirmed visually. Therefore, according to the information providing apparatus 70 according to the present embodiment, it is possible to take drastic measures for accident prevention.

  Although the embodiments related to the disclosed apparatus have been described above, the present invention may be implemented in various different forms other than the above-described embodiments. Therefore, another embodiment included in the present invention will be described below.

[Video other than in-vehicle camera]
In the first embodiment and the second embodiment described above, the case where the video captured by the drive recorder 30 is registered in the storage unit 13 is illustrated, but the disclosed apparatus is not limited thereto. That is, the disclosed apparatus can also register an image captured by a camera installed on a road in association with a near ID.

  For example, the disclosed apparatus holds a road camera table in which the camera ID of a camera installed on a road is associated with the intersection ID of an intersection captured by the camera. Then, when registering incident data in the storage unit 13, the disclosed apparatus reads the camera ID corresponding to the intersection ID of the intersection where the incident occurred in the road camera table. In addition, the disclosed device stores, in the storage unit 13, images over a predetermined period before and after the time when the drive recorder 30 is triggered among the images captured by the camera having the camera ID read from the road camera table. You can also register for. At the same time, the disclosed apparatus associates the near file ID with the file name of the video imaged by the drive recorder 30 and the file name of the video imaged by the camera installed on the road and registers it as near data. As a result, the disclosed apparatus can accumulate images captured from various directions regarding a scene where a near-miss occurred.

[Total traffic volume]
Further, in the above-described first and second embodiments, the case where the amount of incidents by intersection traffic patterns is counted is illustrated, but the disclosed device is not limited to this, and the traffic volume by intersection traffic patterns is counted. You can also For example, when a drive recorder or a digital tachograph is widely installed in a vehicle, it becomes possible to accurately determine the traffic volume for each intersection traffic pattern. At this time, it is more preferable to apply a constant recording type drive recorder to the vehicle instead of an event type.

  That is, the disclosed apparatus increments the traffic volume of the corresponding traffic pattern after specifying the traffic pattern passing through the intersection from the locus of the position information, as in the case of calculating the amount of near misses. In this way, the traffic volume can be totaled according to the traffic pattern with the aid of the configuration for totalizing the amount of near misses. Therefore, the disclosed apparatus can search not only the near amount but also an intersection with a similar traffic amount. Note that the disclosed device may search for an intersection having similar traffic instead of the near amount.

[Route specification]
For example, in the above-described second embodiment, the case where an intersection is accepted as an area on a road when searching for a similar intersection is illustrated, but the disclosed apparatus is not limited thereto. For example, the disclosed apparatus can be similarly applied to a case where designation of a route including a plurality of intersections is received.

  That is, the disclosed apparatus refers to the intersection table and the road table, and searches for a route that is similar to the designated route and the number of intersections, the number of roads connected to each intersection, and the connection direction as similar candidate routes. . At this time, the disclosed apparatus may search for a route having a distance between intersections, that is, a route having a difference in a ratio of lengths of roads connecting the intersections within a predetermined value, as a similar candidate route. The distance between the intersections may be calculated using the latitude and longitude of each intersection, or the road length may be registered in the road table.

24-26 is a figure for demonstrating an application example. In the examples of FIGS. 24, 25, and 26, the amount of near-left turn incident is zero, and there are only two traffic patterns in which the amount of incident exists. Each of the routes shown in FIGS. 24, 25 and 26 includes a crossroad intersection A and a five-way intersection B, and the amount of each incident is equal. However, the routes shown in FIG. 24, FIG. 25 and FIG. 26 are different from each other in the east, west, south and north directions, and the distance between the intersections A ₃ and B ₃ shown in FIG. 26 is the distance between the intersections A ₁ and B ₁ shown in FIG. the distance between, more longer than the distance between the intersection a ₂ and B ₂ as shown in FIG. 25.

  Here, assuming that the route shown in FIG. 24 is a designated route and it is determined whether or not it is similar to the route shown in FIGS. 25 and 26, the disclosed apparatus performs the same as in the case of executing a shape similarity search. Even if the east, west, north, and south directions are different, it is determined that they are similar if the difference in the near amount is within a predetermined range. In other words, the disclosed apparatus determines that the path shown in FIG. 24 and the path shown in FIG. At this time, the disclosed apparatus determines that the route illustrated in FIG. 26 is also a similar route when the setting is made to ignore the difference in distance between the intersections. On the other hand, the disclosed apparatus determines that the route illustrated in FIG. 26 is not similar to the route illustrated in FIG. 24 when the setting is made so as not to ignore the difference in distance between the intersections. As described above, the disclosed apparatus can search for a route similar to the designated route even when designation of a route including a plurality of intersections is received.

[Search alternatives]
In the second embodiment, the case where map matching is used when searching for an intersection whose shape is similar to that of the designated intersection is exemplified. However, the disclosure apparatus is not limited to this, and similarity determination using a raster image is performed. As an alternative, a known image processing determination method may be applied. For example, the disclosed apparatus can use a method of comparing vector data obtained by chain-coding both an intersection image to be searched and an intersection image to be determined from contour information, thinning, and the like. In addition, the disclosed device can perform comparison using a feature value such as a histogram of both the intersection image to be searched and the intersection image to be determined, or template matching to be compared using a template obtained from the intersection image to be searched. Can also be used. Furthermore, the disclosed apparatus can also use feature amount identification determination or the like using learning in which an intersection image to be searched is a teacher image. Note that the disclosed apparatus may use both or one of the intersection image to be searched and the intersection image to be determined as it is, as well as the known determination, or perform comparison such as rotation or enlargement / reduction as appropriate. Also good.

  In addition, each component of each illustrated apparatus does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured. For example, you may make it connect the filter process part 15a, the calculating part 15b, the totaling part 15c, or the output part 15d via a network as an external device of an information provision apparatus. In addition, the filter processing unit 15a, the calculation unit 15b, the totaling unit 15c, or the output unit 15d each have another device, and are connected to the network to cooperate to realize the function of the information providing device. Also good.

[Information provision program]
The various processes described in the above embodiments can be realized by executing a prepared program on a computer such as a personal computer or a workstation. In the following, an example of a computer that executes an information providing program having the same function as that of the above embodiment will be described with reference to FIG.

  FIG. 27 is a schematic diagram illustrating an example of a computer that executes an information providing program according to the first to third embodiments. As illustrated in FIG. 27, the computer 100 includes an operation unit 110a, a speaker 110b, a camera 110c, a display 120, and a communication unit 130. Further, the computer 100 includes a CPU 150, a ROM 160, an HDD 170, and a RAM 180. These units 110 to 180 are connected via a bus 140.

  As shown in FIG. 27, the HDD 170 includes an information providing program 170a that exhibits the same functions as the filter processing unit 15a, the calculation unit 15b, the totaling unit 15c, and the output unit 15d described in the first embodiment. Stored in advance. Further, the HDD 170 exhibits the same functions as the filter processing unit 15a, the calculation unit 15b, the totaling unit 15c, the normalization unit 71a, the output unit 71b, and the search unit 71c described in the second embodiment. The information providing program 170a to be stored may be stored in advance. The information providing program 170a may be integrated or separated as appropriate, like the respective components shown in FIGS. In other words, all data stored in the HDD 170 need not always be stored in the HDD 170, and only data necessary for processing may be stored in the HDD 170.

  Then, the CPU 150 reads the information providing program 170 a from the HDD 170 and expands it in the RAM 180. Thereby, as shown in FIG. 27, the information provision program 170a functions as an information provision process 180a. The information providing process 180a expands various data read from the HDD 170 in an area allocated to itself on the RAM 180 as appropriate, and executes various processes based on the expanded various data. The information providing process 180a includes processes executed by the filter processing unit 15a, the calculation unit 15b, the totaling unit 15c, and the output unit 15d illustrated in FIG. 3, for example, the processing illustrated in FIGS. The information providing process 180a is a process executed by the filter processing unit 15a, the calculation unit 15b, the totaling unit 15c, the normalization unit 71a, the output unit 71b, and the search unit 71c shown in FIG. 17, for example, FIG. 23 may be included. In addition, each processing unit virtually realized on the CPU 150 does not always require that all processing units operate on the CPU 150, and only a processing unit necessary for the processing needs to be virtually realized.

  Note that the information providing program 170a is not necessarily stored in the HDD 170 or the ROM 160 from the beginning. For example, each program is stored in a “portable physical medium” such as a flexible disk inserted into the computer 100, so-called FD, CD-ROM, DVD disk, magneto-optical disk, or IC card. Then, the computer 100 may acquire and execute each program from these portable physical media. In addition, each program is stored in another computer or server device connected to the computer 100 via a public line, the Internet, a LAN, a WAN, etc., and the computer 100 acquires and executes each program from these. It may be.

DESCRIPTION OF SYMBOLS 1 Information provision system 3A, 3B, 3C Vehicle 5 Service subscriber vehicle 9 Network 10 Information provision device 11 Communication I / F unit 12 Reader / writer 13 Storage unit 13a Near incident data 13b Node link data 13c Near incident amount data 13d Near incident link table 15 Control unit 15a Filter processing unit 15b Calculation unit 15c Totaling unit 15d Output unit 30A, 30B, 30C Drive recorder 31A, 31B, 31C Sensor group 32 GPS receiver 33 Acceleration sensor 34 Vehicle speed sensor 35 Camera

Claims (4)

A computer that processes information collected from an in-vehicle computer installed in a vehicle.
Based on the detection value acquired from the first sensor of the vehicle, the movement trajectory of the vehicle when it is determined that the traveling state of the vehicle matches the dangerous state is the detection value of the second sensor of the vehicle. Calculate based on
An intersection on a road on which a vehicle has passed, a road on which the vehicle enters the intersection, and an exit from the intersection on a plurality of movement tracks including the movement locus determined that the traveling state matches the dangerous state For each combination of escape roads
Information indicating the running state when it is determined that the running state of the vehicle matches a dangerous state based on a detection value acquired from a first sensor of the vehicle, an intersection on a road on which the vehicle has passed, Corresponding to the combination of the approach road where the vehicle enters the intersection and the escape road where the vehicle escapes from the intersection,
Normalizing the total value of the trajectory of the dangerous state for each combination of the intersection on the road that the vehicle has passed, the approach road on which the vehicle enters the intersection, and the escape road on which the vehicle escapes from the intersection;
When an intersection designation and a search request for a similar intersection similar to the designated intersection are received from another computer connected to the computer via a network, the designated intersection , shape, and normality reduction has been searched for similar cross point where the aggregate values are similar, with the normalized aggregate value of the similarity intersection approach road to the similar intersection, and, responding to the combination of the outgoing roads from the intersection A method of providing information, comprising: executing a process of outputting a traveling state determined to match the attached dangerous state to the other computer . In the output process,
When said other computer accepts a search request for the similar intersection, information providing method according to claim 1, wherein the computer is characterized by accepting specification of intersection on the electronic map to be provided to the other computers. In the searching process,
The intersection where the number of roads to be connected and the connection direction are similar to the designated intersection is searched as a candidate for the similar intersection, and the designated intersection and the normal are selected from the similar intersection candidates. information providing method according to claim 1 or 2 of been the aggregate values, characterized in that the search for an intersection similar as the similarity intersection. In the searching process ,
The computer further executes a process of searching for a route similar to the specified route when specification of a route including a plurality of intersections is received as the search request from the other computer. The information providing method according to 1, 2, or 3 .

Images