JP2008003657A - Driving information aggregation device, system, information aggregation method, and information aggregation program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technology which does not plot the same event in the same place, regarding the technology for plotting an event occurrence place acquired by a drive recorder. <P>SOLUTION: This driving information aggregation device has an output information storage device storing at least one of a place where a predetermined event occurred to a vehicle, the acceleration of the vehicle when the predetermined event occurred, the speed of the vehicle when the predetermined event occurred, and image data when the predetermined event occurred, including the place, as information to be output. When the difference between event information input from the drive recorder, and the information to be output, read from a collected event information storage means, are not within predetermined values, the input event information is not stored as new information to be output, in the collected event information storage means. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a technique for collecting and processing near-miss events using a device mounted on a vehicle.

  There is a drive recorder as a recording device that records situation information at the time of an accident or near-miss. This drive recorder monitors the state of the vehicle with an acceleration sensor or the like, and when a dangerous state is detected, records the location, vehicle state, video information, etc. of the vehicle before and after that. These recorded information can be used for, for example, accident reproduction, accident investigation, safe driving guidance by near-miss experience, and the like. Such techniques are described in Patent Document 1, Non-Patent Document 1, and Non-Patent Document 2.

  Here, there is a “Traffic Safety Map” published by the Traffic Accident Comprehensive Analysis Center (Italda). In some cases, when an accident or a near-miss event occurs, the position is plotted on a map, the points where the accident occurred frequently are visualized, and the user is alerted to the possibility of an accident occurring in the vicinity. There is a technique for plotting a dangerous state occurrence position acquired by the above-described conventional drive recorder on a map like a “traffic safety map”.

JP 09-235491 A Japan Society of Automotive Engineers, 2005 Spring Meeting, Academic Lecture Preprints No.54-05 Nikkei Electronics 2005 issue October issue p101-p119 "Drive Recorder Your driving and recording"

  Conventional drive recorders record information triggered by near-acceleration or sudden acceleration / deceleration associated with an accident. For this reason, when the number of vehicles to be collected increases, near-miss events are collected enormously. For this reason, for example, in a place where many dangerous situations occur, such as a place where there is a lot of popping out or a place where the line of sight is poor, similar cases occur multiple times in the same place. In such a case, when the above-described conventional technique for plotting the dangerous state occurrence position on the map is applied, a plurality of similar cases are displayed at the same place, resulting in a map that is difficult to see.

  The present invention has been made in view of such circumstances, and in the technology for plotting event occurrence positions on a map, even when the same case occurs at the same location, a technology that does not display a plurality at the same location is provided. Objective.

  The present invention has been made to achieve the above object, and compares information acquired by a drive recorder with information registered so far so as not to draw similar information on a map. It is characterized by that.

  Further, the present invention provides event information including at least one of a place where a predetermined event occurs in the vehicle, an acceleration of the vehicle when the predetermined event occurs, and a speed of the vehicle when the predetermined event occurs. An operation information aggregating apparatus that outputs from an output means, an event information storage means that stores the event information, and an aggregate event information that stores information output from the output means among the event information as aggregate event information At least one of storage device, location, acceleration, and speed included in each event information read from the event information storage device, and location, acceleration, speed included in the aggregate event information read from the aggregate event information storage device If the difference is not within a predetermined value, the event information is stored in the aggregate event information storage means as new aggregate event information, If the difference is within a predetermined value, characterized by having a a similarity determination means for additionally stored in the aggregated event information storage means said event information as about event information said population.

  According to the technique of the present invention, in the technique of plotting event occurrence positions on a map, even when the same case occurs at the same place, it is possible not to display a plurality of cases at the same place. This makes it easy to create a map that is easy to see.

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

<First Embodiment>
A first embodiment will be described.

  First, a configuration example of a system for plotting event occurrence positions on a map will be described with reference to FIG.

  In FIG. 1, the system of this embodiment includes an event information aggregation device 1, an event information collection device 2, a vehicle 3, a communication network 4, and the like. The event information collection device 2 is a conventional drive recorder or the like, and is mounted on the vehicle 3 to acquire information indicating a situation where an event has occurred, a position where the event has occurred, and the like. The event information aggregating apparatus 1 is an information processing apparatus such as a PC (Personal Computer) or a server, for example, and includes information indicating a situation where an event has occurred from the event information collecting apparatus 2 and position information where the event has occurred. , Plot the location of the event on the map.

  Note that the numbers of the event information aggregating apparatus 1 and the event information collecting apparatus 2 are not limited to those shown in FIG. 1, and the numbers thereof may be arbitrary. Further, an information processing apparatus (not shown) may be connected via the communication network 4 or the like, and input / output of information described later may be performed by this information processing apparatus.

  A configuration example of the event information aggregating apparatus 1 will be described with reference to FIG. The event information aggregating apparatus 1 includes a CPU (Central Processing Unit) 11, a memory 12, a storage device 13, a connection interface 14, an input device 15, an output device 16, a communication interface 17, and the like. The CPU 11, the memory 12, the storage device 13, the connection interface 14, the input device 15, the output device 16, the communication interface 17, etc. are connected to each other via a bus 18.

  The storage device 13 is, for example, a storage medium such as a CD-R (Compact Disc-Recordable) or a DVD-RAM (Digital Versatile Disk-Random Access Memory), a drive device for the storage medium, an HDD (Hard Disk Drive), or the like. .

  The event information aggregating apparatus 1 is connected to the event information collecting apparatus 2 via the connection interface 14. In addition, the event information aggregation device 1 may be connected to the event information collection device 2 via the communication interface 17 or the like.

  The input device 15 is, for example, a keyboard, a mouse, a microphone, or the like. The output device 16 is, for example, a display, a speaker, a printer, or the like.

  The storage device 13 includes a program 131, an event information table 132, an aggregate event table 133, map information 134, and the like. The program 131 is for realizing functions to be described later. The event information table 132 stores event information acquired by the event information collection device 2. The aggregate event table 133 stores aggregate event information plotted on a map. The map information 134 is map information including map image data and the like.

  The CPU 11 implements an event information reception unit 111, an attribute registration reception unit 112, a similarity determination unit 113, a display processing unit 114, and the like by loading the program 131 into the memory 12 and executing it. The event information reception unit 111 stores the event information acquired by the event information collection device 2 in the event information table 132. The attribute registration receiving unit 112 receives attribute information of each event information and additionally stores it in the event information table 132. The similarity determination unit 113 determines whether the event information in the event information table 132 is similar to the event information in the aggregated event table 133. If there is no similar event, the aggregated event table 133 is determined as a new event. To store. The display processing unit 114 plots and outputs the position where the event has occurred on the map from the aggregated event information read from the aggregated event table 133 and the map information 134. Further, the display processing unit 114 outputs image data of the designated aggregation event.

  In the event information aggregating apparatus 1, the operations of the event information receiving unit 111, the attribute registration receiving unit 112, and the display processing unit 114 are the same as those in the prior art that plots the event occurrence position in the table on the map, and the similarity determination The section 113 is different from the prior art in that it does not plot similar events by determining whether or not the event information in the event information table 132 is similar to the event information in the aggregate event table 133.

  Next, information in the storage device 13 will be described.

  First, the event information table 132 will be described.

  An example of the event information table 132 is shown in FIG. In FIG. 2, the event information table 132 includes an event ID 201, an occurrence date 202, an occurrence time 203, a latitude 204, a longitude 205, a situation 206, a type 207, a release 208, vehicle information 209, and the like. The event ID 201, the occurrence date 202, the occurrence time 203, the latitude 204, the longitude 205, the situation 206, the type 207, the release 208, the vehicle information 209, and the like are associated with each other.

  The event ID 201 is identification information of an event detected by each event information collection device 2. Occurrence date 202 and occurrence time 203 are the occurrence date and time of the event with the corresponding event ID. Latitude 204 and longitude 205 are the latitude and longitude of the place where the event with the corresponding event ID has occurred. The situation 206 indicates the driving situation of the vehicle 4 when the event with the corresponding event ID occurs. The type 207 indicates the type of what specifically occurred with the event with the corresponding event ID. Public 208 indicates whether or not to release an event with a corresponding event ID. The vehicle information 209 indicates the state of the vehicle within a predetermined time including the time when a predetermined event occurs. Specifically, for example, the vehicle information 209 includes vehicle position, speed, acceleration, image data, and the like for each date and time.

  The event ID 201, the occurrence date 202, the occurrence time 203, the latitude 204, the longitude 205, the vehicle information 209, and the like in the event information table 132 are event information acquired from the event information collection device 2 by an operation example described later. The status 206, type 207, disclosure 208, and the like are information that is input in accordance with an instruction from the user or the like according to an operation example described later.

  Next, the aggregate event table 133 will be described.

  An example of the aggregated event table 133 is shown in FIG. In FIG. 3, the aggregate event table 133 includes an aggregate event ID 301, a latitude 302, a longitude 303, a situation 304, a type 305, an event ID 306, feature information 307, and the like. Aggregated event ID 301, latitude 302, longitude 303, situation 304, type 305, event ID 306, feature information 307, and the like are associated with each other.

  The aggregate event ID 301 is identification information of icons to be plotted on the map. Latitude 302 and longitude 303 are the latitude and longitude of the position where the event indicated by the corresponding aggregate event ID 301 has occurred. The situation 304 is the situation of the vehicle 3 when the event indicated by the corresponding aggregate event ID 301 occurs. The type 305 indicates the type of what specifically occurred at the position where the event indicated by the corresponding aggregated event ID 301 occurred. The event ID 306 is an event ID of an event that has occurred at the position where the event indicated by the corresponding aggregate event ID 301 has occurred. The characteristic information 307 is information for determining whether or not the event is similar to the event indicated by the corresponding aggregated event ID 301, and is, for example, acceleration, speed, image data, or the like acquired by the event information collection device 2.

  The information in the consolidated event table 133 is stored by an operation example described later, but is newly registered, updated, deleted, etc. according to the information input via the input device 15 or the communication interface 17 or the like. Also good.

  Next, a configuration example of the event information collection device 2 will be described with reference to FIG. The event information collection device 2 is the same as that in the prior art.

  The event information collection device 2 includes a camera 41, an acceleration sensor 42, a GPS (Global Positioning System) reception device 43, a calculation unit 44, a memory 45, a storage device 46, and the like. The camera 41, the acceleration sensor 42, the GPS receiver 43, the calculation unit 44, the memory 45, the storage device 46, and the like are connected via a bus 47.

  The camera 41 captures at least the front of the vehicle 3. The acceleration sensor 42 acquires accelerations of the vehicle 3 in the up / down, left / right, and front / rear directions. The GPS receiver 43 receives a signal from a GPS artificial satellite. The calculation unit 44 is, for example, a CPU, an MPU (Micro Processing Unit), or the like. The storage device 46 is a non-working storage device such as a flash memory.

  The memory 45 has a log information table 431 and the like. The log information table 431 includes the acceleration of the vehicle 3, the shooting data captured by the camera 41, the speed of the vehicle 3, the current position, while the vehicle 3 is traveling or instructed by a driver or the like. Stores information such as date and time.

  The storage device 46 includes an event information table 432 and the like. When a predetermined event that is considered to be caused by the occurrence of a dangerous state occurs, the event information table 432 includes acceleration, photographing data, and a predetermined amount of time in the log information table 431 centered on the date and time when the event occurred. Stores the current position.

  The calculation unit 44 implements a log information acquisition unit 411 and an event detection unit 412 by executing a program (not shown) read from the storage device 46 or the like. The log information acquisition unit 411 acquires image data captured by the camera 41, acceleration data acquired by the acceleration sensor 42, etc., for example, every predetermined time or every predetermined distance, and further receives the current position at that time by GPS. Calculated from the signal received by the device 43, the speed of the vehicle 3 is calculated from the current position calculated this time and the current position calculated last time, and these image data, acceleration, current position, speed, and internal clock (not shown) ) Etc. are stored in the log information table 431 in association with the current date and time. The log information acquisition unit 411 holds the data in the log information table 431 for a certain period of time, and sequentially deletes data from the oldest data.

  When the event detection unit 412 detects a predetermined event that is considered to be caused by the occurrence of a dangerous state, the event detection unit 412 issues an event ID, and from the log information table 431, image data, acceleration, The current position, speed, date, etc. are read, and the issued event ID is associated with the read image data, acceleration, current position, speed, date, etc. and stored in the event information table 432. Further, the event detection unit 412 reads out the image data, acceleration, current position, speed, date, etc. during the predetermined time after the occurrence of the event from the log information table 431 and associates it with the event ID issued earlier. , And stored in the event information table 432 as described above.

  Here, the predetermined event detected by the event detection unit 412 is, for example, a situation where dangerous driving or dangerous driving is expected. Specifically, for example, the event detection unit 412 determines whether or not the data exceeds a threshold value after the sensor value data from the acceleration sensor 42 is subjected to a low pass filter and a high pass filter. This filter is intended to avoid false detection due to fine vibrations and slopes such as slopes. When the data exceeds the threshold value, the event detection unit 412 determines that a dangerous driving or a situation where a dangerous driving is expected.

  In addition, for example, the event detection unit 412 determines the presence or absence of a moving body such as another vehicle or a passerby by acquiring a differential image of images captured at different dates and times by the camera 41 that captures the front. As a result of this determination, when it is determined that there is a moving body and that the moving body is moving in the traveling direction of the vehicle 3, the event detection unit 412 is in a situation where dangerous driving is expected. Is determined.

  An example of the event information table 432 is shown in FIG.

  Here, the event information table 432 indicates the date and time when a predetermined event is detected, information indicating the position of the vehicle 3, and the situation of the vehicle 3 within a predetermined time before and after the predetermined event is detected. Information is stored in a separate table. Hereinafter, when these tables are distinguished and described, for example, a symbol such as “event information table 432a” is given.

  In FIG. 5A, an event information table 432a is a table that stores information indicating the date and time when a predetermined event is detected, the position of the vehicle 3, and the like. The event information table 432a includes an event ID 501, an occurrence date 502, an occurrence time 503, a latitude 504, a longitude 505, and the like. The event ID 501, the occurrence date 502, the occurrence time 503, the latitude 504, the longitude 505, etc. are associated with each other. The event ID 501 is identification information issued by the event detection unit 412 each time a predetermined event is detected. The occurrence date 502 and the occurrence time 503 are the date and time when the event indicated by the corresponding event ID 501 has occurred. Latitude 504 and longitude 505 are the latitude and longitude of the place where the event indicated by the corresponding event ID 501 has occurred.

  In FIG. 5B, an event information table 432b is a table that stores event information indicating the situation of the vehicle 3 within a predetermined time centered on the time when a predetermined event is detected. The event information table 432b includes an event ID 511, time 512, latitude 513, longitude 514, speed 515, acceleration 516, image data 517, and the like. The event ID 511, time 512, latitude 513, longitude 514, speed 515, acceleration 516, image data 517, and the like are associated with each other. The event ID 511 is identification information issued by the event detection unit 412 every time a predetermined event is detected. Time 512 is the time when the corresponding speed 515, acceleration 516, image data 517, and the like are reached. Latitude 513 and longitude 514 are the latitude and longitude of the place where the event indicated by the corresponding event ID 511 occurs. The speed 515 is the speed of the vehicle 3 at the time 512 when the event indicated by the corresponding event ID 511 occurs. The acceleration 516 is the acceleration of the vehicle 3 at the time 512 when the event indicated by the corresponding event ID 511 occurs. The image data 517 is image data captured by the camera 41 when the event indicated by the corresponding event ID 511 occurs and at the corresponding time 512.

  FIG. 6 shows an example in which the acceleration is graphed among the event information acquired in this way. In the example of FIG. 6, the time when the trigger is applied is set to 0 seconds (reference numerals 602 and 612), and the speed information before and after that, the acceleration information before and after the left and right, and the like are shown. A graph 601 in FIG. 6A is an example in the case where the brake is suddenly applied, decelerated, and then accelerated. Further, a graph 611 in FIG. 6B is an example in the case where a trigger is applied due to vertical vibration.

With such waveform data alone, it is not known what kind of event has occurred. In other words, it may simply be rough driving or acquired due to road steps. In order to identify this, it is necessary to view the video information before and after that. If you are managing or viewing near-miss events within a limited range of individuals or individuals, it is possible to identify whether each event is a noise event or what type of near-miss, but multiple vehicles If you collect and share the information, it will be enormous.
The event information aggregating apparatus 1 of the present embodiment is for improving the efficiency of the work.

  Next, an operation example will be described.

  As described above, since the operation of the event information collection device 2 is the same as that of the prior art, the description of the operation example of the event information collection device 2 is omitted, and only the operation example of the event information aggregation device 1 is described.

  First, an example of an operation for registering event information from the event information collection device 2 will be described with reference to FIG.

  The event information collection device 2 is connected to the event information aggregation device 1 via the communication network 4 or the connection interface 14. The event / event information aggregating apparatus 1 stores the event information acquired by the event information collecting apparatus 2 in a storage device such as a removable flash memory, and connects the storage device to the connection interface 14 or the like. You may get it.

  In FIG. 7, when the event information acquired by the event information collection device 2 is input (S 701), the event information reception unit 111 of the event information aggregation device 1 stores the input event information in the event information table 132. (S702). Specifically, for example, the event information reception unit 111 acquires the event information table 432 from the event information collection device 2. Next, the event information reception unit 111 stores the acquired information in the event information table 432 in the event information table 132. Specifically, for example, the event information reception unit 111 includes the event ID 501, the occurrence date 502, the occurrence time 503, the latitude 504, the longitude 505, and the like of the event information table 432 a, the event ID 201, the occurrence date 202, Stored as occurrence time 203, latitude 204, longitude 205, and the like. In addition, the event information receiving unit 111 stores the speed 515, acceleration 516, image data 517, and the like associated with the event ID stored in the above process in the event information table 432b as vehicle information 209 in the event information table 132. . In addition, here, the event information receiving unit 111 sets a flag indicating that the data is newly received in association with the event ID 201, the occurrence date 202, the occurrence time 203, the latitude 204, the longitude 205, and the like stored in S702. It may be given.

  Next, an operation example for acquiring attributes such as the type of acquired event will be described with reference to FIG.

  In FIG. 8, the attribute registration receiving unit 112 outputs registration screen data from the output device 16 (S801). Specifically, the attribute registration receiving unit 112 selects an event in which a part or all of the situation 206, the type 207, the public 208, and the like corresponding to each other is not stored from the event information table 132, and the event ID 201 of the event is stored. The occurrence date 202, the occurrence time 203, the latitude 204, the longitude 205, and the like are read out, and the read information is output from the output device 16 together with the map information 134 and the screen format for displaying on the screen. An example of a screen output to the output device 16 by this screen data is shown in FIG. In FIG. 9, a screen 901 is an example of a screen for accepting an attribute instruction for each event. The screen 901 includes an area 911, an area 912, an area 913, and the like. The area 911 is an area where the position where the event has occurred is plotted and displayed on a map. In this area 911, an event icon 921 indicating the occurrence location of each event is displayed by positioning the read latitude 204, longitude 205, etc. in the map information 134. In the area 912, an event ID 201, an occurrence date 202, an occurrence time 203, and the like are displayed. The user selects any of the event icons 921 displayed in the area 911 using the input device 15 or an input device (not shown). Then, the attribute registration receiving unit 112 reads the image data from the vehicle information 209 corresponding to the event ID 201 of the event that occurred at the position of the selected event icon 921 in the event information table 132, and outputs the read image data to the output device 16. Output to. This image data is displayed in the area 913 of the screen 901. The user presses the control button 931 using the input device 15 to instruct reproduction, rewinding, fast-forwarding, etc. of the image displayed in the area 913. Thereby, it is possible to confirm what kind of event has occurred. The user recognizes the content of the event by viewing the video when the event occurs, and inputs attributes such as the status, type, and availability of the event. The user uses the input device 15 or the like to specify an attribute by selecting, for example, pull-down or the like for each event type, situation, or the like in the area 912. The “situation” of this attribute is, for example, a driving situation such as turning right, turning left, or going straight. The “type” is, for example, sudden braking, sudden steering, noise, or the like. Here, the noise is, for example, an event that occurs due to a road surface condition. That is, the event information aggregating apparatus 1 determines that an event has occurred when the acceleration is equal to or greater than a predetermined value, and holds information related to the event. Here, this change in acceleration is not only caused by the driver's operation to avoid danger, such as sudden braking, sudden steering, etc., but it is the same depending on the road condition such as a step on the road surface, for example. It may occur constantly at the place. Noise refers to an event that occurs due to such road surface conditions. The user determines whether or not the event is noise by referring to an image displayed in the area 913, and instructs it as attribute information. Further, the user designates whether or not to disclose each event by, for example, checking a check box using the input device 15 or the like.

  Note that the attribute type is not limited to driving causes such as sudden braking and sudden steering, but can include external causes of occurrence of the event, such as jumping out and interruption.

  In FIG. 8, when the attribute registration receiving unit 112 receives the attribute information designated in this way (S802), the attribute registration receiving unit 112 additionally stores it in the event information table 132 (S803). Specifically, for example, the attribute registration receiving unit 112 corresponds to the event ID 201 indicating the event in which the information is input, with information such as the status, type, and disclosure availability specified in the area 912 of the image 901 described above. To be stored as status 206, type 207, public 208, and the like.

  Next, an operation example for determining whether or not an event similar to the newly received event information has already been registered will be described with reference to FIG.

  In FIG. 10, the similarity determination unit 113 selects one of the newly received events (S1001). Specifically, for example, the similarity determination unit 113 selects one row from the event information table 132 in descending order or the like. Here, the similarity determination unit 113 determines whether each event in the event information table 132 is an event to be selected here, based on whether or not a flag indicating that the event has been newly received is assigned. May be. Next, the similarity determination unit 113 selects one of the aggregate events (S1002). Specifically, for example, the similarity determination unit 113 selects one row from the aggregate event table 133 in descending order or the like. Next, the similarity determination unit 113 determines whether or not the aggregate event selected in S1002 is similar to the event selected in S1001 (S1003). Here, the criteria for similarity determination used for the determination are arbitrary, but in the present embodiment, when similarity is determined only by information acquired by the event information collection device 2 and information acquired by the event information collection device 2 And the attribute information instructed by the above-described operation example.

  First, an example in which similarity is determined based only on information acquired by the event information collection device 2 will be described.

  In this case, the similarity determination unit 113 performs determination using at least one including the event occurrence position among the event occurrence position, speed, acceleration, image data, and the like. Regarding the event occurrence position, for example, the similarity determination unit 113 reads the latitude 204 and longitude 205 corresponding to the event selected in S1001 from the event information table 132. Furthermore, the similarity determination unit 113 reads the latitude 302 and longitude 303 corresponding to the aggregate event selected in S1002 from the aggregate event table 133. The similarity determination unit 113 determines that the locations are the same when the distance between the read latitude 204 and longitude 205 and the latitude 302 and longitude 303 is within a predetermined distance, for example, within 30 meters.

  Further, regarding the similarity of speed, acceleration, image data, and the like, for example, the similarity determination unit 113 reads the vehicle information 209 corresponding to the event selected in S1001 from the event information table 132. Further, the similarity determination unit 113 reads the feature information 307 and the like corresponding to the aggregate event selected in S1002 from the aggregate event table 133. The similarity determination unit 113 calculates similarity based on a change in vehicle speed, a change in acceleration data, a difference in image data, and the like included in the vehicle information 209 and the feature information 307. When determining from a change in vehicle speed or a change in acceleration data, for example, a pattern matching technique used in conventional signal processing may be used. Specifically, for example, waveform data is stored as feature vector data in the feature information 307, and the similarity determination unit 113 is acquired from the speed and acceleration included in the vehicle information 209 of the event selected in S1001. The distance between the feature vector and the feature vector data of the feature information 307 is compared, and it is determined whether or not they are similar depending on whether this distance is within a predetermined threshold. Further, when the determination is made based on the difference between the image data, for example, conventional image processing may be used. Specifically, for example, a plurality of reference image data is stored in the feature information 307, and the similarity determination unit 113 includes the image data included in the vehicle information 209 of the event selected in S1001 and the feature information. A difference image with the image data of 307 is acquired, and it is determined whether or not they are similar depending on whether or not the number of pixels of the difference image is within a predetermined threshold.

  Next, an example will be described in which a determination is made using both the information acquired by the event information collection device 2 and the attribute information instructed by the above operation example.

  In this case, the similarity determination unit 113 determines whether or not they are similar based on whether or not the attribute information, that is, the status, type, and the like match in addition to the event occurrence position, speed, acceleration, image data, and the like described above. To do. Specifically, for example, the similarity determination unit 113 reads the status 206, the type 207, and the like corresponding to the event selected in S1001 from the event information table 132. Further, the similarity determination unit 113 reads the status 304, the type 305, and the like corresponding to the event selected in S1002 from the aggregated event table 133. The similarity determination unit 113 determines that the attribute information matches when the read status 206 and status 304 match the type 207 and type 305. Here, the attribute information match determination may be one or both of the situation and the type. The similarity determination unit 113 determines whether or not they are similar based on the determination results of both the determination of the event occurrence position, speed, acceleration, image data, and the like and the determination based on the attribute information.

  Here, this similarity determination is instructed by the above-described case where the similarity is determined only by the information acquired by the event information collection device 2, the information acquired by the event information collection device 2, and the above-described operation example. In addition to performing the determination with both of the attribute information, both may be performed. Specifically, for example, first, when the similarity determination unit 113 determines that the positions are the same in the determination based on the above-described position information, and the type of the aggregated event is “noise”, the event information collection device 2 may be determined to be similar to the aggregated event without determining both the information acquired by 2 and the attribute information instructed by the above-described operation example. In this case, the similarity determination unit 113 may further store the status, type, and the like of the aggregated event determined to be similar to the status 206, type 207, etc. corresponding to the event selected in S1001 in the event information table 132. . As a result, an operation for setting an attribute for each noise event becomes unnecessary, and the accessibility of a dangerous event can be improved.

  As a result of the determination in S1003, if the aggregate event selected in S1002 is similar to the event selected in S1001, the similarity determination unit 113 regards the event selected in S1001 as belonging to the aggregate event selected in S1002. Stored in the aggregated event table 133 (S1004). Specifically, for example, the similarity determination unit 113 adds the event ID of the event selected in S1001 to the event ID 306 corresponding to the aggregated event selected in S1002 of the aggregated event table 133. Here, the similarity determination unit 113 may calculate an average value of values such as latitude 302 and longitude 303 corresponding to the aggregate event ID selected in S1002 of the aggregate event table 133, acceleration in the feature information 307, speed, and the like. .

  As a result of the determination in S1003, when the aggregate event selected in S1002 and the event selected in S1001 are not similar, the similarity determination unit 113 performs the above determination for all the aggregate events in the aggregate event table 133. It is determined whether or not it has been performed (S1005).

  As a result of the determination in S1005, when the above determination is not performed for all the aggregate events in the aggregate event table 133, the similarity determination unit 113 performs the above-described process of S1002 again, and selects 1 of the unselected aggregate events. Select one.

  As a result of the determination in S1005, when the above determination is performed for all the aggregate events in the aggregate event table 133, the similarity determination unit 113 sets the event selected in S1001 as a new aggregate event in the aggregate event table 133. Store (S1006). Specifically, for example, the similarity determination unit 113 issues a new aggregate event ID and stores it in the aggregate event table 133. Further, the similarity determination unit 113 reads out the latitude 204, longitude 205, situation 206, type 207, vehicle information 209, and the like corresponding to the event selected in S1001 from the event information table 132, and newly issues the aggregated event table 133. Stored in the latitude 302, longitude 303, status 304, type 305, feature information 307, etc. associated with the aggregated event ID. Furthermore, the similarity determination unit 113 stores the event ID of the event selected in S1001 in the event ID 306 associated with the currently issued aggregated event ID in the aggregated event table 133.

  After the process of S1004 or after the process of S1006, the similarity determination unit 113 determines whether there is an unselected event among the newly received events (S1007).

  As a result of the determination in S1007, if there is an unselected event, the similarity determination unit 113 performs the processing subsequent to S1001 again.

  If there is no unselected event as a result of the determination in S1007, the similarity determination unit 113 ends the process.

  Thus, in this embodiment, it is possible to aggregate similar events and plot the event occurrence positions according to the information in the aggregate event table 133.

  Here, an example of a map based on a conventional technique for positioning and plotting a position where a predetermined event has occurred is shown in a map 2301 in FIG. In FIG. 23A, an icon 2311 indicates a position where an event has occurred. Furthermore, FIG. 23B shows an example of a map when a plurality of events occur at the same position in the conventional technology. Like the map 2321 in FIG. 23B, in the related art, there are cases where icons 2331 are densely packed at a specific place. As described above, since this map is for publicizing dangerous places, it is not necessary to display icons for the number of events that have occurred, and conversely, the map is difficult to see.

  On the other hand, in the technique of the above-described embodiment, even when the screen 2321 in FIG. 23B is displayed, similar events are displayed with one icon 1111 as in the screen 1101 in FIG. It becomes possible. In this case, the display processing unit 114 reads the latitude 302 and longitude 303 for each aggregate event from the aggregate event table 133, and the map image read from the map information 134 corresponds to the latitude 302 and longitude 303 for each read aggregate event. Display processing is performed by compositing icons at the positions to be performed. As a result, it becomes easy to create a map for publicly known dangerous places.

  The display processing unit 114 can represent the difference between events by changing the color and shape for each event type. In this case, for example, an icon table (not shown) in which the event type is associated with icon data having a different color or shape is stored in advance in the storage device 13 or the like. The display processing unit 114 reads the type 305 corresponding to the aggregated event to be displayed from the aggregated event table 133, and reads the icon data corresponding to the read type 305 from the table. The display processing unit 114 synthesizes and displays the read icon data at a position on the map image corresponding to the latitude 302 and longitude 303 for each aggregation event. In addition, the display processing unit 114 can visualize the frequency of events by changing the color, shape, and size according to the number of events grouped in one icon as similar events. In this case, for example, an icon table (not shown) in which the number of events is associated with icon data having a different color or shape is stored in advance in the storage device 13 or the like. The display processing unit 114 counts the number of event IDs in the event ID 306 corresponding to the aggregated event to be displayed from the aggregated event table 133, and reads icon data corresponding to the counted number from the table. The display processing unit 114 synthesizes and displays the read icon data at a position on the map image corresponding to the latitude 302 and longitude 303 for each aggregation event.

  The display processing unit 114 may output not only plots on a map such as the screen 1101 but also image data acquired by the event information aggregation device 1. An example of the screen in that case is shown in FIG. In FIG. 12, an output device 16 such as one display displays a screen 1201, a screen 1211, and the like. A screen 1201 is obtained by plotting event occurrence positions on a map, and is the same as the screen 1101 described above. A screen 1211 is used to display image data acquired by the event information aggregation device 1. Note that the image data displayed on this screen 1211 is only the image data registered as publicly available. When the user designates any icon on the screen 1201 using the input device 15, the display processing unit 114 displays an event ID 306 associated with the aggregated event ID 301 indicating the designated aggregated event from the aggregated event table 133. read out. Next, the display processing unit 114 reads out the occurrence date 202 and the like associated with the release 208 “public” from the read event ID 306 from the event information table 132 and displays it in the area 1212 in the screen 1211. Control. When the user designates any event in the area 1212 using the input device 15, the display processing unit 114 is included in the vehicle information 209 associated with the event ID of the designated event from the event information table 132. The read image data and the like are read, and the read image data is output to the output device 16. This image data is displayed in an area 1213 of the screen 1211.

  Note that the map of the screen 1201 and the image data of the screen 1211 may be arranged in one screen as shown in FIG. At this time, the date of occurrence of the area 1212 is also arranged in the same screen.

  As described above, the collected event information can be browsed by the display processing unit 114. The display processing unit 114 selectively performs browsing processing according to the attribute for each event stored in the aggregated event table 133. Specifically, by not displaying an event designated as non-disclosure, it is possible to control information disclosure reflecting the intention of a near-miss experience person.

  Note that the timing at which the similarity determination operation example illustrated in FIG. 10 is started is arbitrary. For example, there is a case where an instruction by a user or the like is input every predetermined time, or a case where new event information is input from the event information collection device 2.

  The order of performing the attribute information registration operation shown in FIG. 8 and the similarity determination operation shown in FIG. 10 is arbitrary, and the similarity determination may be performed after the attribute information registration. Also, the attribute information may be registered after the similarity determination. When the attribute information is registered after the similarity determination is performed, the screen example for registering the attribute information does not accept the input of the attribute information for each event as shown in FIG. The input of attribute information may be accepted.

  In the first embodiment described above, when the event information aggregating apparatus 1 is a server on the network, the public / private attributes are, for example, user authentication using a user ID, a password, and the like. It can be controlled so that it can be set only by the user who generated it. At this time, the event data for which the public / private attribute is not set may be disclosed only to the user who generated the event and private to other users. Thereby, personal information can be protected. Moreover, when it becomes public, the type may be controlled so that it can be changed by other users. As a result, not only the processing by the event information aggregating apparatus 1 described above but also the event aggregation can be performed based on the opinions from a plurality of users, so the automation accuracy of the aggregation can be improved. Furthermore, by adding a comment from another user for each event so that it can be viewed, the event can be objectively analyzed, and the guidance effect for safe driving can be enhanced.

<Second Embodiment>
A second embodiment will be described.

  In the first embodiment described above, both information that can be disclosed and information that cannot be disclosed are stored in the storage device of one device, and information on events that can be disclosed by the device is output. In the second embodiment described below, for example, whether or not an event can be disclosed is registered at a terminal such as an individual or an office, and only information on an event registered as being openable is stored in a storage device of an information processing apparatus such as another server. And the information processing apparatus outputs event information.

  A system configuration example of the second embodiment will be described with reference to FIG. In addition, below, the same thing as the above-mentioned 1st Embodiment gives the same code | symbol, abbreviate | omits description, Only a different part is demonstrated in detail.

  The system according to the second embodiment includes an event information processing device 5, an event aggregation device 6, a communication network 4, and the like. The event information processing device 5 and the event aggregation device 6 are connected via the communication network 4.

  The event information processing apparatus 5 is an information processing apparatus such as a PC used in an individual or an office. The user registers whether or not the event information acquired by the event information collection device 2 is open using the event information processing device 5. The event information processing device 5 transmits only the event information registered as publicly available to the event aggregation device 6.

  The event aggregation device 6 plots the event occurrence position on the map in the same manner as described above from the event information transmitted from each event information processing device 5, and the event information processing device 5 or the like plots the event occurrence position. Send image data etc. at the time of event occurrence.

  The numbers of event information processing devices 5 and event aggregation devices 6 are not limited to those shown in FIG. 13, and the numbers may be arbitrary. In addition, in FIG. 13, the vehicle 3 is omitted, but each event information collection device 2 is mounted on each vehicle 3. Further, an information processing device (not shown) may be connected to the event information processing device 5 and the event aggregation device 6 via the communication network 4 or the like, and input / output of information to be described later may be performed by this information processing device.

  Next, configuration examples of the event information processing device 5 and the event aggregation device 6 will be described.

  First, the event information processing apparatus 5 will be described.

  The event information processing apparatus 5 includes a CPU 51, a memory 52, a storage device 53, a connection interface 54, an input device 55, an output device 56, a communication interface 57, and the like. The CPU 51, the memory 52, the storage device 53, the connection interface 54, the input device 55, the output device 56, the communication interface 57, etc. are connected to each other by a bus 58.

  The storage device 53 is, for example, a storage medium such as a CD-R or DVD-RAM, a drive device for the storage medium, an HDD, or the like. The storage device 53 includes a program 1311, an event information table 132, and the like. The program 1311 is for realizing functions to be described later. The event information table 132 stores event information acquired by the event information collection device 2, and is the same as that in the first embodiment.

  The event information processing device 5 is connected to the event information collection device 2 via the connection interface 14. Further, the event information aggregating apparatus 1 may be connected to the event information collecting apparatus 2 via the communication interface 57 or the like.

  The input device 55 is, for example, a keyboard, a mouse, a microphone, or the like. The output device 56 is, for example, a display, a speaker, a printer, or the like.

  The CPU 51 implements an event information reception unit 111, an attribute registration reception unit 112, a transmission processing unit 1301, and the like by loading the program 1311 into the memory 52 and executing it. The event information reception unit 111 and the attribute registration reception unit 112 are the same as those in the first embodiment. The transmission processing unit 1301 includes the event information corresponding to the public 208 “possible” and the event information corresponding to the type 207 “noise” and the vehicle 3 or the vehicle among the event information in the event information table 132. 3 is transmitted to the event aggregating apparatus 6. This event information is, for example, event ID 201, occurrence date 202, occurrence time 203, latitude 204, longitude 205, situation 206, type 207, vehicle information 209, etc. in the event information table 132. The identification information may be input together with the event information from the event information collection device 2, for example, or may be identification information instructed by a user or the like. The transmission timing of the event information by the transmission processing unit 1301 may be arbitrary. For example, it may be transmitted after the attribute information of each event information is registered by the same operation as described above, or at every predetermined time. You may send it.

  Next, the event aggregation device 6 will be described.

  The event aggregation device 6 includes a CPU 61, a memory 62, a storage device 63, an input device 64, an output device 65, a communication interface 66, and the like. The CPU 61, the memory 62, the storage device 63, the input device 64, the output device 65, the communication interface 66, etc. are connected to each other by a bus 67.

The storage device 63 is, for example, a storage medium such as a CD-R or a DVD-RAM, a drive device for the storage medium, an HDD, or the like. The storage device 63 includes a program 1312, an event information table 1321, an aggregate event table 133, map information 134, and the like. The program 1312 is for realizing functions to be described later. The event information table 1321 stores event information transmitted from the event information processing apparatus 5. The consolidated event table 133 and the map information 134 are the same as those in the first embodiment. The input device 64 is, for example, a keyboard, a mouse, a microphone, or the like. The output device 65 is, for example, a display, a speaker, a printer, or the like.

  The CPU 61 implements an event information reception unit 1302, a similarity determination unit 113, a display processing unit 114, and the like by loading the program 1312 into the memory 62 and executing it. The similarity determination unit 113 and the display processing unit 114 are the same as those in the first embodiment described above. The event information receiving unit 1302 stores the event information transmitted from the event information processing device 5 in the event information table 1321.

  An example of the event information table 1321 is shown in FIG.

  14, the event information table 1321 includes an event ID 201, a vehicle ID 210, an occurrence date 202, an occurrence time 203, a latitude 204, a longitude 205, a situation 206, a type 207, and the like. The event ID 201, the vehicle ID 210, the occurrence date 202, the occurrence time 203, the latitude 204, the longitude 205, the situation 206, the type 207, and the like are associated with each other. The event ID 201, the occurrence date 202, the occurrence time 203, the latitude 204, the longitude 205, the situation 206, the type 207, and the like are the same as those in the event information table 132 described above. The vehicle ID 210 is identification information of each vehicle 3 or the event information collection device 2 installed in the vehicle 3. This identification information is transmitted from the event information processing apparatus 5 together with the event information.

  The similarity determination unit 113 determines whether or not the event in the event information table 1321 is similar to the aggregated event in the aggregated event table 133 by the same operation as in the first embodiment. When the display processing unit 114 receives an information request from the event information processing apparatus 5 or an information terminal (not shown) having a browser or the like, the display processing unit 114 plots the event occurrence position by the same operation as in the first embodiment. Send data such as maps and images at the time of the event. The screen example output by this data is the same as that in the first embodiment described above.

  As described above, in the second embodiment, since the user of data designates disclosure / non-disclosure and only the information that can be disclosed is stored in the storage device of the apparatus that discloses the information, personal information is protected. It is possible.

Further, as shown in the first embodiment, it is also possible to configure so that a general browsing user other than the experienced person can view and set the attribute for each event. Thereby, it becomes possible to reduce the setting operation of the experience person and to collect objective opinions.
<Third Embodiment>
A third embodiment will be described.

  In the third embodiment described below, the event aggregation device 6 according to the second embodiment described above is configured to identify the aggregated events that have occurred a predetermined number of times or more from the event information transmitted from each event information processing device 5. This is fed back to the event information processing apparatus 5.

  A system configuration example of the third embodiment will be described with reference to FIG. In addition, below, the same thing as the above-mentioned 1st Embodiment and 2nd Embodiment gives the same code | symbol, abbreviate | omits description, Only a different part is demonstrated in detail.

  In the event information processing apparatus 5 of the third embodiment, the event information processing apparatus 5 of the second embodiment described above further includes a frequent occurrence information reception unit 1502, a frequent occurrence similarity determination unit 1503, a frequent occurrence information table 1521, and the like. is there. The frequent occurrence information transmission unit 1501 and the frequent occurrence information reception unit 1502 are functions realized by the CPU 51 executing the program 1512. The frequent occurrence information transmission unit 1501 receives the frequent occurrence event information transmitted from the event aggregation device 6 and stores it in the frequent occurrence information table 1521. The frequent occurrence information reception unit 1502 determines whether or not the event information input from the event information collection device 2 is similar to the frequent occurrence event information in the frequent occurrence information table 1521. The attribute information of the event information is registered as the attribute information of the input event.

  The event aggregation device 6 according to the third embodiment is the one in which the event aggregation device 6 according to the second embodiment described above further includes a frequent occurrence information transmission unit 1501 and the like. The frequent occurrence information transmission unit 1501 is a function realized by the CPU 61 executing the program 1511. The frequent occurrence information transmission unit 1501 selects from the aggregated event table 133 an aggregated event that has occurred at a predetermined number or more, and transmits information on the aggregated event to the event information processing apparatus 5.

  Here, an example of the frequent occurrence information table 1521 will be described with reference to FIG.

  In FIG. 16, the frequent occurrence information table 1521 includes an aggregate event ID 1601, latitude 1602, longitude 1603, status 1604, type 1605, feature information 1606, and the like. Aggregation event ID 1601, latitude 1602, longitude 1603, status 1604, type 1605, feature information 1606, and the like are associated with each other. Aggregated event ID 1601, latitude 1602, longitude 1603, status 1604, type 1605, feature information 1606, etc. are the aggregated event ID 301, latitude 302, longitude 303, status 304, type 305, feature information 307, etc. of the above-mentioned aggregate event table 133. The same.

  It should be noted that the information in the frequent occurrence information table 1521 is stored by an operation example to be described later, but is newly registered, updated, deleted, etc. according to the information input via the input device 55 or the communication interface 57 or the like. Also good.

  Next, an operation example will be described.

  First, an operation example in which the event aggregation device 6 transmits an event that has occurred a predetermined number of times or more to each event information processing device 5 will be described with reference to FIG.

  The frequent occurrence information transmission unit 1501 reads aggregated event information of aggregated events that have occurred in a predetermined number or more from the aggregated event table 133 (S1701). Therefore, the frequent occurrence information transmission unit 1501 reads the event ID in each event ID 306 from the aggregate event table 133, counts the number of event IDs, and if the counted number is equal to or greater than a predetermined threshold, the event ID 306 And the corresponding integrated event information 301, latitude 302, longitude 303, status 304, type 305, feature 307, and the like are read. This threshold value may be determined in advance or updated according to information input via the input device 64 or the communication interface 66. Next, the frequent occurrence information transmission unit 1501 transmits the information read out in S1701 to the event information processing apparatus 5 (S1702). Here, the frequent occurrence information transmission unit 1501 may transmit the same information to all the event information processing devices 5, or may transmit different information for each event information processing device 5.

  The frequent occurrence information receiving unit 1502 of the event information processing apparatus 5 stores the information transmitted from the event aggregation apparatus 6 by the above-described operation in the frequent occurrence information table 1521. Specifically, for example, the frequent occurrence information reception unit 1502 displays the received aggregated event information 301, latitude 302, longitude 303, status 304, type 305, feature 307, and the like as aggregated event ID 1601, latitude 1602, Stored as longitude 1603, status 1604, type 1605, feature information 1606, and the like.

  Next, an operation example for setting the attribute information of event information from the received multiple event information will be described with reference to FIG.

  In FIG. 18, the frequent occurrence similarity determination unit 1503 selects one of the events (S1801). Specifically, for example, the frequent occurrence similarity determination unit 1503 selects one row from the event information table 132 in descending order or the like. Here, the frequent occurrence similarity determination unit 1503 may select only events for which the status 206 and the type 207 in the event information table 132 are blank and the attribute information is determined not to be set.

  Next, the frequent occurrence similarity determination unit 1503 selects one of the frequent occurrence events (S1802). Specifically, for example, the frequent occurrence similarity determination unit 1503 selects one row from the frequent occurrence information table 1521 in descending order or the like. Next, the frequent occurrence similarity determination unit 1503 determines whether the frequent occurrence event selected in S1802 is similar to the event selected in S1801 (S1803). Here, the criterion for similarity determination used for determination is arbitrary, but in the present embodiment, it is assumed that similarity is determined only by information acquired by the event information collection device 2. Since this operation example is the same as S1003 described above, a description thereof will be omitted.

  If the multiple aggregation event selected in S1802 is similar to the event selected in S1801 as a result of the determination in S1803, the multiple similarity determination unit 1503 selects attribute information of the multiple aggregation event selected in S1802 in S1801. The event information is stored in the event information table 132 as attribute information of the event (S1804). Specifically, for example, the frequent occurrence similarity determination unit 1503 reads from the frequent occurrence information table 1521 the status 1604 and type 1605 corresponding to the frequent occurrence aggregate event selected in S1802, and the event information table 132 in the event selected in S1801. Are stored as a status 206, a type 207, and the like.

  As a result of the determination in S1803, when the multiple aggregation event selected in S1802 and the event selected in S1801 are not similar, the multiple similarity determination unit 1503 performs the above-described processing on all the multiple aggregation events in the multiple occurrence information table 1521. It is determined whether or not the determination has been made (S1805).

  As a result of the determination in S1805, when the above-described determination is not performed for all the frequent aggregation events in the frequent occurrence information table 1521, the multiple occurrence similarity determination unit 1503 performs the above-described processing of S1802 again to select an unselected multiple aggregation event. Select one of them.

  As a result of the determination in S1805, when the above determination is made for all the frequent aggregation events in the frequent occurrence information table 1521, or after the processing in S1804 described above, the multiple similarity determination unit 1503 newly receives the event It is determined whether there is any unselected one (S1806).

  As a result of the determination in S1806, when there is an unselected event, the frequent occurrence similarity determination unit 1503 performs the processing subsequent to S1801 again.

  If there is no unselected event as a result of the determination in S1806, the frequent similarity determination unit 1503 ends the process.

In the first and second embodiments described above, the user refers to an image or the like to determine and register attribute information such as type or situation. However, in this case, even when the same event occurs in the same place, it is necessary to register attribute information for each event. Here, as in the third embodiment described above, it is determined whether or not the information acquired by the event information collection device 2 is similar to the aggregated event. If they are similar, the attribute of the aggregated event is determined. Is set as an attribute of event information, so that it is not necessary to set an attribute for all events. In particular, noise that is distributed unnecessarily can be classified by centrally managing noise events. By gathering noise events such as road steps from multiple individual users and returning them to individual event management again as multiple events, for example, even the road steps that users first pass are recognized as noise It becomes possible to do.
<Fourth Embodiment>
A fourth embodiment will be described.

  In the fourth embodiment, when the event information collection device 2 has the function such as the frequent occurrence similarity determination unit 1503 of the third embodiment described above and the frequent occurrence information table 1521 and the event is determined to be noise, The event information is not stored.

  A configuration example of the event information collection device 2 according to the fourth embodiment will be described with reference to FIG. In addition, below, the same thing as the above-mentioned 1st-3rd embodiment gives the same code | symbol, abbreviate | omits description, Only a different part is demonstrated in detail.

  In the event information collection device 2 of the fourth embodiment, the event information collection device 2 of the first to third embodiments described above further includes a frequent occurrence information table 1521 and the like. A detector 1901 is provided. The information in the frequent occurrence information table 1521 may be transmitted via the event information processing device 5 or may be transmitted directly from the event aggregation device 6. Further, the information in the frequent occurrence information table 1521 stored in a storage device such as a flash memory may be copied to the storage device 46.

  The event detection unit 1901 acquires the attribute information of the event information from the information of the frequent occurrence information table 1521, similarly to the frequent occurrence similarity determination unit 1503 described above. Furthermore, the event detection unit 1901 deletes the event information when the event information type is “noise”.

  Next, an operation example of the event detection unit 1901 will be described with reference to FIG. This operation example is activated after, for example, the event detection unit 1901 detects the occurrence of an event by the same operation example as the event detection unit 412 described above and stores information on the event.

  In FIG. 20, the event detection unit 1901 selects one of the frequently aggregated events (S2001). Specifically, for example, the event detection unit 1901 selects one row from the frequent occurrence information table 1521 in descending order or the like. Next, the event detection unit 1901 determines whether or not the multiple occurrence event selected in S2001 is similar to the event that has occurred this time (S2002). Here, the criterion for similarity determination used for determination is arbitrary, but in the present embodiment, it is assumed that similarity is determined only by information acquired by the event information collection device 2. Since this operation example is the same as S1003 described above, a description thereof will be omitted.

  As a result of the determination in S2002, when the multiple aggregation event selected in S2001 is not similar to the event that has occurred this time, the event detection unit 1901 determines the above-described determination for all the multiple aggregation events in the frequent occurrence information table 1521. Is determined (S2003).

  As a result of the determination in S2003, when the above-described determination is not performed for all the frequent aggregation events in the frequent occurrence information table 1521, the event detection unit 1901 performs the above-described processing of S2001 again, and the unselected multiple aggregation events Select one of them.

  As a result of the determination in S2003, when the above determination is made for all the frequent aggregation events in the frequent occurrence information table 1521, the event detection unit 1901 ends the process.

  On the other hand, as a result of the determination in S2002, when the multiple aggregation event selected in S2001 is similar to the event that has occurred this time, the event detection unit 1901 indicates that the type of the multiple aggregation event selected in S2001 is “noise”. It is determined whether or not (S2004). Specifically, for example, the event detection unit 1901 reads from the frequent occurrence information table 1521 the type 1605 corresponding to the frequent occurrence event selected in S2001, and determines whether this type 1605 is “noise”.

  As a result of the determination in S2004, when the type of the frequent aggregation event is “noise”, the event detection unit 1901 deletes the event information added this time from the event information table 432 (S2005). Specifically, from the event information table 432, the event ID 501 and event ID 511 of the event information added this time, the occurrence date 502, the occurrence time 503, the latitude 504, and the longitude 505 associated with each of the event ID 501 and the event ID 511, respectively. , Occurrence date 512, occurrence time 513, latitude 514, longitude 515, speed 515, acceleration 516, screen data 517, and the like are deleted.

  As a result of the determination in S2004, when the type of the frequent aggregation event is not “noise”, the event detection unit 1901 ends the process. Here, the event detection unit 1901 may store the attribute information of the multiple aggregate event selected in S2001 in the event information table 432a as attribute information of the event that has occurred this time. Specifically, for example, the event detection unit 1901 reads from the frequent occurrence information table 1521 the status 1604 and type 1605 corresponding to the frequent occurrence event selected in S2001, and corresponds to the event that occurred this time in the event information table 432a. It may be stored as the situation, type, etc.

  In the above-described fourth embodiment, the attribute information stored in the above-described third embodiment is used in the event information collection device 2. As a result, noise events such as road steps can be identified using the similarity between the position and behavior of the vehicle, and it is possible to omit storing unnecessary events in the event information table 432. The area can be used effectively.

Note that in the event information collection device 2 of the fourth embodiment, the information for determining whether or not the event is noise is the feature in the frequent occurrence information table 1521 created in the third embodiment as described above. Information may be used, but is not limited to this. For example, you may determine by the pattern information for determining whether it is noise. Such pattern information may be acquired experimentally using a typical road shape, for example. Further, the position information where noise is generated may be acquired by monitoring road facility information such as road works or using data collected by a special vehicle such as a probe car. Moreover, in order to determine whether an event is noise, you may determine only by any one of pattern information and position information. As a result, data creation processing and recognition processing can be reduced.
<Fifth Embodiment>
A fifth embodiment will be described.

  In the fifth embodiment described below, the event information aggregation device 1 of the first embodiment described above and the event information processing device 5 of the second to fourth embodiments described above identify individuals from the event information disclosed. Information that can be identified is deleted.

  A configuration example of the event information aggregation device 1 and the event information processing device 5 will be described with reference to FIG. In the example of FIG. 21, the case of the event information processing apparatus 5 of the third and fourth embodiments described above will be described as an example.

  The event information processing apparatus 5 further includes a personal information deletion unit 2101. The personal information deleting unit 2101 performs, for example, mosaic or mask processing on a human face, a vehicle license plate, or the like of image data. Such face area and license plate area recognition algorithms are based on conventional techniques such as face position recognition technology and car number recognition technology, and are recognized based on the color and shape of an object appearing in an image and an image pattern. The timing at which the personal information deletion unit 2101 performs processing on the image data is arbitrary. For example, when event information including image data from the event information collection device 2 is input, or the attribute information of the event information described above The registration process is started. In any case, the timing at which the personal information deletion unit 2101 performs processing on the image data may be any time before the event information is made public.

  An example of an image processed by the personal information deletion unit 2101 will be described with reference to FIG.

  In FIG. 22A, a screen 2201 is an image before processing by the personal information deletion unit 2101. By processing this screen 2201 by the personal information deletion unit 2101, a screen 2202 in FIG. 22B is obtained. In the screen 2202, areas 2211 and 2212 are areas where mosaic or mask processing has been performed.

  According to the fifth embodiment, it is possible to distribute a video from which personal information that can be opened to the public is removed. In addition, since information that does not remove personal information remains in the individual management means, it can be used for verification of accidents and the like.

  According to the first to fifth embodiments described above, it is possible to prevent overlapping events from being disclosed as different event information. In particular, the processing of noise events that occur in fixed places such as road steps becomes enormous as the amount of acquired data increases. In addition to noise, a plurality of similar events are registered in places where sudden braking due to popping out frequently occurs. At this time, it is not necessary to browse all the events for a user who only needs to browse a representative example for driving education or the like, and cannot browse efficiently. In the above-mentioned embodiment, since it becomes possible to prevent the duplication registration of such an event, it becomes possible to browse efficiently.

  The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and includes design changes and the like within a scope not departing from the gist of the present invention.

  For example, it is possible to visualize a point where noise frequently occurs from the collected event information. Thereby, it is possible to constitute a road condition monitoring system. In this monitoring system, a place where the road condition is bad and a deteriorated condition are inferred from the point where the noise occurs frequently and the vehicle behavior at that point. The estimation is performed by sampling standard behavior data according to the level of deterioration and comparing it with the acquired noise data.

  In addition, for example, there are cases where there are problems with road shapes, traffic signs, etc. at points where sudden steering and sudden braking events occur frequently. If these dangerous events occur frequently at the same point, the system can be configured to issue a warning to road users. As a result, roadside improvements can be achieved.

  Further, for example, a dangerous place on a route to a destination can be visualized by linking with a route guidance system such as an automobile navigation system. Thereby, the place of caution can be instructed before operation. It is also possible to search for operation routes that avoid dangerous places.

  Further, for example, the event information aggregation device 1 and the event information processing device 5 may be configured to count the number of published events, the number of attributes and comments set, and the number of browsing for each user. In this case, the charge to the user may be reduced or increased for sharing and using the event. This makes it possible to increase the incentive to contribute to the event and raise awareness of safe driving.

1 shows a system configuration example of a first embodiment of the present invention. In the embodiment, an example of an event information table is shown. In the same embodiment, an example of an aggregation event table is shown. In the embodiment, a configuration example of an event information collection device is shown. In the embodiment, an example of an event information table is shown. In the embodiment, a graph example of acceleration including the time when an event occurs in the vehicle is shown. In the embodiment, an operation example for receiving event information from the event information collection device is shown. In the same embodiment, an operation example for receiving attribute information of event information is shown. In the same embodiment, the example of a screen which receives the attribute information of event information is shown. In the same embodiment, an operation example of searching for an aggregate event similar to an event is shown. In the same embodiment, the example of a screen which displays an event occurrence position is shown. In the same embodiment, the example of a screen which displays an event occurrence position and the image at the time of event occurrence is shown. The system configuration example of 2nd Embodiment is shown. In the embodiment, an example of an event information table is shown. The system configuration example of 3rd Embodiment is shown. In the embodiment, an example of a frequent occurrence information table is shown. In the same embodiment, an operation example of transmitting frequent event information is shown. In the embodiment, an operation example for searching for an event similar to a multiple event is shown. The structural example of the event information collection apparatus of 4th Embodiment is shown. In the embodiment, an operation example for searching for an event similar to a multiple event is shown. In 5th Embodiment, the structural example of an event information processing apparatus is shown. In the embodiment, an example of a displayed screen is shown. The example of a screen displayed by a prior art is shown.

Explanation of symbols

1: event information aggregation device, 11: CPU, 12: memory, 13: storage device, 14: connection interface, 15: input device, 16: output device, 17: communication interface, 18: bus, 2: event information collection device 3: vehicle, 4: communication network, 111: event information reception unit, 112: attribute registration reception unit, 113: similarity determination unit, 114: display processing unit, 131: program, 132: event information table, 133: event aggregation Table: 134: Map information, 41: Camera, 42: Acceleration sensor, 43: GPS receiver, 45: Calculation unit, 46: Memory, 47: Storage device, 411: Log information acquisition unit, 412: Event detection unit, 431 : Log information table, 432: Event information table, 5: Event information processing device, 51: CPU, 52: Memory, 53: Storage device, 54: Connection Interface: 55: input device, 56: output device, 57: communication interface, 58: bus, 1301: transmission processing unit, 1311: program, 6: event aggregation device, 61: CPU, 62: memory, 63: storage device, 64: input device, 65: output device, 66: communication interface, 67: bus, 1302: event information reception unit, 1312: program, 1321: event information table, 1501: frequent information transmission unit, 1502: frequent information reception unit, 1503: frequent occurrence similarity determination unit, 1511: program, 1512: program, 1521: frequent occurrence information table, 1901: event detection unit, 2101: personal information deletion unit

Claims (10)

Output from the output means is event information including at least one of a location where a predetermined event has occurred in the vehicle, acceleration of the vehicle before and after the occurrence of the predetermined event, and speed of the vehicle before and after the occurrence of the predetermined event. A driving information aggregating device,
Event information storage means for storing the event information;
Among the event information, aggregate event information storage means for storing information output from the output means as aggregate event information,
One or more pieces of data including the location among the location, acceleration, and speed included in each event information read from the event information storage unit, and the location and acceleration included in the aggregate event information read from the aggregate event information storage unit Calculating a difference from one or more pieces of data including a place of speed, and if the difference is not within a predetermined value, the event information is stored in the aggregate event information storage means as new aggregate event information, and the difference is calculated. And a similarity determination means for additionally storing the event information as the aggregated event information when the value is within a predetermined value. The location in the event information including at least the location of the location where the predetermined event occurred in the vehicle, the acceleration of the vehicle before and after the occurrence of the predetermined event, and the speed of the vehicle before and after the occurrence of the predetermined event on the map A driving information aggregating device that draws and outputs to
Map information storage means for storing map data;
Event information storage means for storing the event information;
Among the event information, aggregate event information storage means for storing information to be output as aggregate event information,
A drawing means for drawing the location included in the aggregate event information read from the aggregate event information storage means on the map data read from the map information storage means;
Output means for outputting the drawn map data; one or more data including a place among the place, acceleration, and speed included in each event information read from the event information storage means; and the aggregate event information storage means If the difference is not within a predetermined value, the event information is used as new aggregate event information. Similarity judgment means for storing the event information in the aggregated event information storage means and, if the difference is not within a predetermined value, additionally storing the event information in the aggregated event information storage means as the aggregated event information. Driving information aggregation device. The location where the predetermined event occurred in the vehicle, the acceleration of the vehicle before and after the occurrence of the predetermined event, the speed of the vehicle before and after the occurrence of the predetermined event, and the surroundings of the vehicle before and after the occurrence of the predetermined event A driving information processing apparatus to which one event information including at least a place among photographed image data is input, and an aggregation apparatus that draws and outputs the place included in the event information on a map via a communication network A connected system,
The driving information processing apparatus is
Event information storage means for storing the event information;
Input means;
Attribute receiving means input by the input means for indicating whether or not to disclose the event information and storing the event information in the event information storage means;
The event information storage means reads out the event information provided with the public information indicating that it is to be disclosed, and has a transmission means for transmitting to the aggregation device,
The aggregation device is
Map information storage means for storing map data;
Among the event information, aggregate event information storage means for storing information to be output as aggregate event information,
A drawing means for drawing the location included in the aggregate event information read from the aggregate event information storage means on the map data read from the map information storage means;
Output means for outputting the drawn map data;
Receiving means for receiving event information transmitted from the driving information processing apparatus;
One or more data including the location among the location, acceleration, and speed included in the received event information, and the location among the location, acceleration, and speed included in the aggregate event information read from the aggregate event information storage unit When the difference with one or more data is calculated and the difference is not within a predetermined value, the received event information is stored in the aggregate event information storage means as new aggregate event information, and the difference is within the predetermined value. In some cases, the system includes: similarity determination means for additionally storing the received event information as the aggregated event information in the aggregated event information storage means. The location where the predetermined event occurs in the vehicle, the acceleration of the vehicle before and after the occurrence of the predetermined event, the speed of the vehicle before and after the occurrence of the predetermined event, the surroundings of the vehicle before and after the occurrence of the predetermined event A driving information processing apparatus to which at least one event information including a place is input among image data obtained by shooting the image data, and an aggregation apparatus that draws and outputs the place included in the event information on a map via a communication network Connected system,
The driving information processing apparatus is
Event information storage means for storing a plurality of the event information;
Input means;
The public information indicating whether or not to disclose the event information input by the input means and the type information indicating the event type of the event information are added to the event information and stored in the event information storage means Attribute accepting means;
The event information storage means reads out the event information provided with the public information indicating that it is to be disclosed, and transmits the information together with the type information provided to the event information to the aggregation device;
Aggregate information receiving means;
Attribute giving means,
The aggregation device is
Map information storage means for storing map data;
Among the event information and type information, aggregate event information storage means for storing information to be output as aggregate event information,
A drawing means for drawing the location included in the aggregate event information read from the aggregate event information storage means on the map data read from the map information storage means;
Output means for outputting the drawn map data;
Receiving means for receiving event information and type information transmitted from the driving information processing apparatus;
One or more data including the location among the location, acceleration, and speed included in the received event information, and the location among the location, acceleration, and speed included in the aggregate event information read from the aggregate event information storage unit When the difference between one or more data is calculated and the difference is within a predetermined value, the received event information and type information are stored in the aggregate event information storage unit as new aggregate event information, and the difference is If it is not within the predetermined value, the similarity determination unit that does not store the received event information and type information in the aggregate event information storage unit,
Aggregated event transmission means for transmitting the aggregated event information in the aggregated event information storage means to the driving information processing apparatus,
The aggregate information receiving means of the driving information processing apparatus receives the transmitted aggregate event information,
One or more pieces of data including the location among the location, acceleration, and speed included in the received aggregate event information, and the location and acceleration included in the aggregate event information read from the aggregate event information storage unit. When the difference between one or more data including the location of the speed is calculated and the difference is within a predetermined value, the type information included in the aggregated event information is set as the type of the event information in the event information. A system characterized by granting. The system according to claim 4, wherein
The type information includes a system in which the event includes noise generated at a predetermined location depending on road surface conditions. 6. The system of claim 5, wherein
Type information indicating that the transmission means of the driving information processing apparatus is provided with the public information indicating that it is disclosed from the event information storage means, and that the noise is generated at a predetermined location depending on road surface conditions Is read and transmitted to the aggregation device. A system according to any one of claims 3-6,
The similarity determination unit includes at least a place, location, acceleration, speed, and image included in the received event information, and a location, acceleration, speed, and image included in the aggregate event information read from the aggregate event information storage unit. The difference between at least the location of the data is calculated, and the difference is not within a predetermined value, and is included in the type information received together with the received event information and the aggregate event information read from the aggregate event information storage means When the type information matches, the received event information and type information are stored in the aggregated event information storage unit as new aggregated event information, the difference is within a predetermined value, and the received event information At least one of the type information received together with the type information included in the aggregate event information read from the aggregate event information storage means does not match That case, the system for causing additionally stored in the aggregated event information storing means event information and type information thus received as about event information said population. The location where the predetermined event occurs in the vehicle, the acceleration of the vehicle before and after the occurrence of the predetermined event, the speed of the vehicle before and after the occurrence of the predetermined event, the surroundings of the vehicle before and after the occurrence of the predetermined event An event information collection device that collects event information including at least a place among image data obtained by capturing an image and a driving information processing device to which the event information is input,
The driving information processing apparatus is
Event information storage means for storing the collected plurality of event information;
Input means;
Type information indicating the type of event in the event information input by the input means, and the event information storing means by adding to the event information type information including noise that occurs in a predetermined place depending on the road surface condition. Attribute receiving means for storing;
From the event information storage means, the event information provided with the type information whose type information is noise is read out and output to the event information collection device, the event information collection device,
Storage means for storing collected event information;
Input receiving means for inputting the output event information;
One or more pieces of data including the place among the place, acceleration, and speed included in each event information read from the storage means, and one of the places, acceleration, and speed included in the input event information. An event detecting means for calculating a difference from the above data and deleting the event information in the storage means when the difference is within a predetermined value. Output from the output means is event information including at least one of a location where a predetermined event has occurred in the vehicle, acceleration of the vehicle before and after the occurrence of the predetermined event, and speed of the vehicle before and after the occurrence of the predetermined event. An information collecting method by the driving information collecting device
The driving information collecting device is
Event information storage means for storing the event information;
Among the event information, there is aggregate event information storage means for storing information output from the output means as aggregate event information,
At least one of the location, acceleration, and speed included in each event information read from the event information storage means, and at least one of the location, acceleration, and speed included in the aggregate event information read from the aggregate event information storage means If the difference is not within a predetermined value, the event information is stored in the aggregated event information storage means as new aggregated event information. If the difference is within the predetermined value, the event information is A similarity determination step of additionally storing the aggregated event information in the aggregated event information storage unit as the aggregated event information. Output from the output means is event information including at least one of a location where a predetermined event has occurred in the vehicle, acceleration of the vehicle before and after the occurrence of the predetermined event, and speed of the vehicle before and after the occurrence of the predetermined event. An information aggregation program to be executed by the driving information aggregation device,
The driving information collecting device is
Event information storage means for storing the event information;
Among the event information, there is aggregate event information storage means for storing information output from the output means as aggregate event information,
At least one of the location, acceleration, and speed included in each event information read from the event information storage means, and at least one of the location, acceleration, and speed included in the aggregate event information read from the aggregate event information storage means If the difference is not within a predetermined value, the event information is stored in the aggregated event information storage means as new aggregated event information. If the difference is within the predetermined value, the event information is A similarity determination step of additionally storing the aggregated event information in the aggregated event information storage unit as the aggregated event information is executed.

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