Data processing system, data processing method, data processing apparatus, and program

Abstract

To simply acquire analysis information regarding a mobile object.SOLUTION: A data processing system comprises: a storage unit which stores mobile object information acquired in a time series manner by being linked with time information; a synthesis method specification unit which specifies a synthesis method; a mobile object information specification unit which specifies a plurality of pieces of mobile object information regarding synthesis processing from the stored mobile object information; an allocation unit which allocates feature quantity information included in each of the plurality of pieces of mobile object information regarding the synthesis processing on the basis of a predetermined division; an acquisition unit which acquires frequency or occurrence probability of the feature quantity information for every predetermined division for each of the plurality of pieces of mobile object information regarding the synthesis processing; a synthesis result acquisition unit which acquires a synthesis result in which the specified synthesis method is applied to the frequency or the occurrence probability of the acquired feature quantity information for every predetermined division in each of the plurality of pieces of mobile object information regarding the synthesis processing; and an output unit which outputs the acquired synthesis result.SELECTED DRAWING: Figure 7

Description

Technical Field

[0001] The present invention relates to a data processing system, a data processing method, a data processing apparatus, and a program for analyzing information of a moving object.

Background Art

[0002] There is a need to obtain information about a moving object (not particularly limited, but for example, in addition to devices such as automobiles, bicycles, airplanes, helicopters, drones, ships, etc., walking is also included conceptually as an example), such as acceleration, speed, position information, angular velocity, etc., and use it for some analysis. For example, there is a social need to evaluate the driving of a moving object based on this information, evaluate the road through which the moving object passes, etc. Patent Document 1 discloses a driving diagnosis system that generates statistical information based on time-series information regarding acceleration as vehicle behavior data collected from various sensors installed in a vehicle via a car navigation device.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, when evaluating driving content, etc., no sufficiently simple tool has been proposed, and it has been necessary for the user or administrator of the moving object to perform part or all of the analysis themselves. In particular, when there are a plurality of moving objects to be analyzed, it has been difficult for non-experts to analyze these plurality of moving objects as a whole or in combination.

[0005] An object of the present invention is to enable easy acquisition of analysis information regarding a moving object.

Means for Solving the Problems

[0006] One aspect of the present invention includes a storage unit that stores mobile object information acquired in a time series in association with time information, a synthesis method specifying unit that specifies a synthesis method, a mobile object information specifying unit that specifies a plurality of pieces of mobile object information related to synthesis processing from the stored mobile object information, an allocation unit that allocates feature amount information included in each of the plurality of pieces of mobile object information related to the synthesis processing based on a predetermined classification, an acquisition unit that acquires the frequency or occurrence probability of the feature amount information for each of the predetermined classifications for each of the plurality of pieces of mobile object information related to the synthesis processing, a synthesis result acquisition unit that acquires a synthesis result obtained by applying the specified synthesis method to the frequency or occurrence probability of the feature amount information for each of the predetermined classifications acquired for each of the plurality of pieces of mobile object information related to the synthesis processing, and an output unit that outputs the acquired synthesis result, and is a data processing system.

Advantages of the Invention

[0007] According to the present invention, analysis information regarding a mobile object can be easily acquired.

Brief Description of the Drawings

[0008]

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Mode for Carrying Out the Invention

[0009] Hereinafter, an example of an embodiment for carrying out the present invention will be described with reference to the drawings. In the description of the drawings, the same reference numerals may be given to the same elements, and redundant descriptions may be omitted. Moreover, the constituent elements described in these embodiments are merely examples, and are not intended to limit the scope of the present invention thereto.

[0010] The outline of this embodiment will be described. FIG. 1 is a diagram showing a vehicle that is a collection target of moving body information, and the result of collecting and visualizing acceleration information generated as the vehicle travels by a data processing device in this embodiment.

[0011] FIG. 1 is a plan view of a vehicle (an example of a "moving body") as viewed from above, and shows the cumulative collection results of acceleration information generated as the vehicle travels. The definitions of the symbols in the upper part of FIG. 1 are as follows. · "FR" indicates the front along the traveling direction of the vehicle (FR-RR direction). · "RR" indicates the rear along the traveling direction of the vehicle (FR-RR direction). · "LS" indicates the left side with reference to the traveling direction of the vehicle (FR-RR direction). · "RS" indicates the right side with reference to the traveling direction of the vehicle (FR-RR direction). · "RP" indicates a plane defined by the traveling direction of the vehicle (FR-RR direction) and the lateral direction (LS-RS direction) orthogonal to the traveling direction of the vehicle (FR-RR direction) (hereinafter referred to as the "reference plane").

[0012] The lower part of FIG. 1 represents the magnitude of the acceleration in the reference plane RP using the distance from the origin. The direction in the reference plane RP is represented using the angle from a predetermined direction (for example, the traveling direction (FR-RR direction)). The number of plots or density in the reference plane RP is represented using shading.

[0013] In this embodiment, the sensing data such as the acceleration information collected in this way is processed according to the data content and then transmitted to the server 230 connected to the data processing device 210.

[0014] The communication between the data processing device 210 and the server 230 in this embodiment will be described. FIG. 2 is an explanatory diagram of the communication between the data processing device 210 and the server 230 according to this embodiment.

[0015] The data processing device 210 can be inserted into, for example, a socket of an automobile (as an example, a cigarette socket, an electric supply socket, or a connection socket) and fixed inside the vehicle of the automobile. The electric supply socket or the connection socket is, for example, a socket that supports USB (Universal Serial Bus). Of course, the data processing device 210 is not limited to such a device, and for example, it may be a drive recorder or any other IoT device, etc. As long as they have each component of the data processing device 210 described below alone or in combination of a plurality of devices, they may be provided in the vehicle in any manner. The data processing device 210 is connected to the server 230 via the mobile terminal 220 or directly. Note that the data processing device 210 may be a device such as a smartphone. In this case, for example, the function of the data processing device 210 may be included in the mobile terminal 220 described below. In this case, for example, the acceleration information may be calculated from the position information acquired by the position information acquisition unit 212 described below. The data processing device 210 is configured to collect the moving body information, which is the data related to the vehicle in FIG. 1.

[0016] The mobile terminal 220 is a device that exists inside or near the vehicle and is held by a user (e.g., a driver) who gets into the vehicle. The mobile terminal 220 is configured to control communication between the data processing device 210 and the server 230. The mobile terminal 220 is, for example, a smartphone or a tablet. As described above, the data processing device 210 may communicate with the server 230 without going through the mobile terminal 220.

[0017] The server 230 stores and processes data collected by at least one data processing device 210. Further, it is configured to provide the result of data processing based on the stored data to an external device, for example, a device used by a vehicle administrator.

[0018] The configuration of the data processing device 210 of this embodiment will be described.

[0019] As shown in FIG. 2, the data processing device 210 includes, for example, an acceleration information acquisition unit 211, a position information acquisition unit 212, a time information acquisition unit 213, a processing unit 214, and a communication unit 215, and is configured to acquire moving body information, which is information about the vehicle in which the data processing device 210 is installed. The acceleration information acquisition unit 211 acquires the acceleration of the vehicle and is configured to acquire the acceleration by, for example, a piezoelectric acceleration sensor. Note that the acceleration of the vehicle may be calculated based on the position information acquired by the position information acquisition unit 212, which will be described later, or the speed information acquired by a speed information acquisition unit (not shown), and in such a case, the acceleration information acquisition unit 211 may not be provided. The position information acquisition unit 212 acquires the position information (e.g., latitude and longitude information) of the data processing device 210 at predetermined intervals based on radio waves coming from GNSS satellites (e.g., GPS satellites). That is, the position information of the vehicle in which the data processing device 210 is installed can be acquired. The time information acquisition unit 213 is configured to acquire time information (e.g., a timestamp) generated based on information regarding the time obtained from a built-in clock or an external time information providing server and based on information indicating the collection period Pc corresponding to the information obtained from the acceleration sensor 212 and the position information acquisition unit 212. The processing unit 214 is configured to generate moving body information, which is information regarding the vehicle, by performing predetermined data processing on the acquisition value by the acceleration information acquisition unit 211, the acquisition value by the position information acquisition unit 212, and the acquisition value by the time information acquisition unit. The processing unit 214 is, for example, a microcomputer. The processing unit 214 realizes the functions of the data processing device 210 by executing a predetermined program (e.g., a program stored in the memory within the microcomputer). The communication unit 215 is configured to transmit the moving body information, which is the processing result of the processing unit 214, to the outside. The communication unit 215 is, for example, a communication interface.

[0020] The configuration of the server 230 according to this embodiment will be described.

[0021] As shown in FIG. 2, the server 230 includes a communication unit 231, a storage unit 232, and a processing unit 233. The communication unit 231 is configured to control communication between the server 230 and a device (e.g., the mobile terminal 220 or the data processing device 210) directly or indirectly (e.g., through a network such as the Internet) connected to the server 230. The communication unit 231 is, for example, a communication interface. The storage unit 232 is configured to store various data, and stores, for example, the data received by the communication unit 231 and a program for realizing the functions of the server 230 (e.g., the functions of executing each process of the server 230 described later). The processing unit 233 is configured to process the data stored in the storage unit 232. The processing unit 233 is, for example, a processor (as an example, a CPU (Central Processing Unit)). The processing unit 233 realizes the functions of the server 230 by executing the program stored in the storage unit 232.

[0022] For example, the processing unit 233 extracts the occurrence frequency in each section based on a predetermined section for the acceleration information included in each of the plurality of units of moving body information specified as the moving body information related to the synthesis process among the stored moving body information, and obtains the result of synthesizing the frequency extraction content. As another example, the processing unit 233 calculates a driving score using the acceleration information acquired for the moving body based on the driving score calculation model stored in the storage unit 232. The driving score is, by way of example and not limitation, a score for the driving quality in a vehicle. In the present embodiment, the description is made on the premise of a logic in which the driving score tends to decrease when an acceleration with a large scalar value is acquired, but the content of the logic is not particularly limited.

[0023] The content from data acquisition to data storage in the present embodiment will be described. FIG. 3 is a flowchart of the process from data acquisition to data storage according to the present embodiment. FIG. 5 is an explanatory diagram of the addition of time information in FIG. 3.

[0024] As shown in FIG. 3, the data processing device 210 executes acquisition of acceleration information and position information (S100). In the present embodiment, although acquisition of position information is described in addition to acceleration information, the information to be acquired only needs to include at least position information. When only position information is acquired, as described above, acceleration information may be calculated based on the acquired position information, and the calculation may be performed in the data processing device 210 or the server 230 or the like. Further, for example, in addition to these pieces of information, at least one of, for example, vehicle identification information, speed information, steering wheel information, accelerator information, brake information, remaining fuel or battery remaining capacity, and load capacity information may be acquired together and appropriately transmitted to the server 230 at the same timing as the acceleration information transmission or at a separate timing.

[0025] Specifically regarding the acquisition of acceleration information, the acceleration information acquisition unit 211 acquires the acceleration generated during the running of the vehicle at a predetermined frequency Tm (for example, every 0.2 seconds).

[0026] The processing unit 212 performs coordinate transformation on the acquired value by the acceleration information acquisition unit 211 to align the axial direction of the acceleration information acquisition unit 211 with the axial direction of the vehicle (for example, the traveling direction (FR-RR direction)). The processing unit 212 stores the value after the coordinate transformation in a storage device (for example, a memory in the microcomputer or a storage device connected to the microcomputer).

[0027] Similarly, the position information acquisition unit 214 acquires the position information that changes as the vehicle runs at a predetermined frequency Tn (for example, every 0.5 seconds). Here, the periods of Tm and Tn may be the same, and regardless of whether they are synchronous or asynchronous, the content of the periods is not particularly limited.

[0028] The processing unit 212 stores the position information acquired from the position information acquisition unit 214 in the storage device. As a result, these multiple acquired pieces of information are stored in the storage device.

[0029] After step S100, the data processing device 210 executes compression processing (S101) on the acceleration information.

[0030] Specifically, in the compression process in step S101, the processing unit 212 assigns each acquired value obtained in step S100 to each section discretely divided by the reference plane RP as shown in FIG. 4. In the example shown in FIG. 4, for the magnitude of acceleration, it is represented in 8 levels (arbitrary unit) from 0 to 7, and for the direction, it is divided by polar coordinates that represent 360 degrees in 32 levels (arbitrary unit) from 0 to 31 clockwise with respect to the vehicle traveling direction x as a reference. The processing unit 212 converts the acquired value into a certain data format by approximating the acquisition points located within each section with any vertex of the section. For example, the acquired value v1 in FIG. 4 is converted to the closest vertex (r: 5, d: 29) among the vertices of the section containing the acquisition point corresponding to the acquired value.

[0031] For example, if the scalar value in the acquired acceleration information is less than a predetermined threshold value, all the corresponding acceleration information may be compressed as 0. Further, this compression method is an example of reducing the capacity for improving data handling efficiency, and the content of the compression method is not particularly limited. Also, without compressing the data, the process may proceed to the process of step 102 while retaining the acquired data.

[0032] After step S101, the data processing device 210 executes addition of time information (S102). In adding the time information, for example, as shown in FIG. 5, the processing unit 212 adds time information unique to each collection period Pc to a combination of a plurality of acceleration information and position information collected within one collection period Pc (for example, 1000 milliseconds). The time information is, for example, information indicating each collection period Pc (for example, information representing the start time and / or end time of the collection period Pc), or a code generated based on the information indicating each collection period Pc. The addition of time information is not limited to this and can be done in an appropriate manner. For example, at least one acceleration information or position information may be added to each time stamp, or one acceleration information or one position information may be added every predetermined time (e.g., 5 seconds). That is, when these information are used for analysis later, the method is not particularly limited as long as acceleration information or position information can be obtained at a sufficient frequency.

[0033] After step S102, the data processing device 210 executes a transmission process (S103). Specifically, the communication unit 213 transmits the generated data (that is, the acceleration information and position information subjected to compression processing with time information added thereto) to the server 230 every predetermined transmission interval (for example, 1.0 second).

[0034] Here, the timing for associating time information is not limited to the timing when the moving body information is stored in the storage device inside the data processing device 210. It may be associated with the time information at that point when the moving body information is transmitted externally from the data processing device 210, or when the transmitted moving body information is received by the server 230 and stored in the storage unit 232 inside the server 230, it may be associated with the time information at that point.

[0035] Note that it is preferable that the data processing device 210 obtains at least one of an identifier for identifying a user of the vehicle equipped with the data processing device 210 and an identifier of the data processing device 210 and transmits it to the server 230. This data transmission may be performed in association with those data each time the transmission process of S104 is performed, or may be performed at a separate timing. In this case, the server 230 stores the data transmitted from the data processing device 210 in S104 in association with at least one of the user identifier and the identifier of the data processing device 210.

[0036] When the user designates at least one of the identifier of the data processing device 210 and the identifier of the user, for example, via the mobile terminal 220, and information on the data to be extracted (for example, time or period), the server 230 has a function of extracting the data corresponding to the user's designation. This function can be provided externally, for example, as an application programming interface (API).

[0037] The server 230 holds the acceleration values and position information compressed in snapshots for each time determined by the time information. Therefore, the server 230 can extract the data at any time for each moving object and extract the cumulative data over a predetermined period.

[0038] Note that what is included in the moving object information stored in the storage unit 232 of the server 230 is not limited to the acceleration information, time information, and position information, and any information related to the moving object may be associated and stored. For example, driver information, passenger information, related person (for example, owner, administrator, etc.) information, affiliation (group, company, etc.) information, remaining fuel information, load capacity information, remaining battery power information, weather information (weather, temperature, humidity, etc.), driving score (a score indicating driving quality, for example, calculated based on information such as acceleration), and the like can be mentioned. These information may be obtained from a separate device provided in the moving object, obtained by user input through the mobile terminal 220, obtained through an administrator terminal (not shown) operated by a person managing the moving object, or obtained from a site that appropriately provides such information via the Internet if it is general information (for example, weather information).

[0039] Hereinafter, an example of analyzing the data acquired and stored from the data processing device 210 and displaying the analysis result will be shown.

[0040] FIG. 6 is a diagram showing an example of an interface used for displaying the analysis results of data stored in a server. Similarly, FIG. 7 is a diagram showing another example of an interface used for displaying the analysis results of the stored data. FIG. 8 is an enlarged view of the acceleration distribution diagram included in FIG. 7. FIG. 9 is a diagram displayed when 501 is selected in the distribution diagram 406 shown in FIG. 8, and it is a list display of the situation where the acceleration corresponding to the area 501 is acquired.

[0041] The interface shown in FIG. 6 is composed of the following respective areas. · Area 401: It shows the items of the content displayed in areas 402 to 404, such as the type of analysis result, and the items can be selected by user input. The content corresponding to the selected item (in FIG. 6, it is "Daily Report") is displayed in areas 402 to 404. · Area 402: It displays information on the vehicle or individual (driver) and date that are the objects of analysis. In addition to the target date, the driver's name, driver's identifier, vehicle number, telephone number, etc. are displayed, and the vehicle or individual, and the date can be specified by user input. · Area 403: It displays the total driving time, total driving distance, destination and the distance between destinations, and driving time, etc. in the driving content corresponding to the vehicle or individual, and date information specified in area 402. · Area 404: It shows the information from a geographical perspective in the driving content corresponding to the vehicle or individual, and date information specified in area 402 on a map. The route corresponding to the driving content is shown, and the positions defined as destinations are indicated by numbered circles, which correspond to the numbers of each destination in area 403.

[0042] The interface shown in FIG. 7 is composed of the following respective areas. · Area 401: It is the same as area 401 in FIG. 6, and the state is such that "Driving History" is selected by user input. The content corresponding to the selected "Driving History" is displayed in areas 402, 404 to 407. · Area 402: Similar to Area 402 in FIG. 6, it displays information about the vehicle or individual (driver) and date to be analyzed. Note that the analysis target may be multiple targets. For example, all vehicles to be managed, etc. may be specified, and displays regarding those vehicle groups may be made. · Area 405: It shows the driving scores corresponding to the vehicle or individual, date, and time zone specified in Area 402, including the overall score, the score regarding handling, the score regarding acceleration, and the score regarding deceleration. · Area 406: It displays the mapping of the acceleration acquired for the vehicle or individual, date, and time zone specified in Area 402. Details will be described later. · Area 407: It shows the information from a geographical perspective in the driving content corresponding to the vehicle or individual and date information specified in Area 402 on a map. It is substantially the same as Area 404 in FIG. 6, but as a difference, the position defined as the destination is not shown by a numbered circle. Instead, a mark (either handling, acceleration, or deceleration) corresponding to the driving content is attached to the position where a specific driving content is detected. That is, a handling mark is attached to the position where a specific driving content regarding handling (for example, an acceleration having a scalar value of a predetermined value or more in the left - right direction) is acquired. Similarly, an acceleration mark and a deceleration mark are respectively displayed at the positions where specific driving contents regarding acceleration and deceleration (an acceleration of a predetermined value or more in the forward or backward direction) are acquired. Furthermore, check boxes are displayed in the vicinity of the displayed marks, and the user can select the check boxes by user input.

[0043] In the interface shown in FIG. 7, when a check box provided at a position where a specific driving content is detected is checked by user input, the driving score is recalculated in a form in which the driving information observed at the checked position is not reflected in the driving score (for example, a form in which the driving information regarding such a specific driving content is deleted from the information input to the driving score calculation logic and recalculated, but not limited thereto, and any appropriate form may be used). That is, it is possible to grasp the driving score assuming that such a specific driving has not been performed.

[0044] FIG. 8 is an enlarged view of region 406 in the interface shown in FIG. 7. Region 406 is a mapping of acceleration information acquired from a data processing device (hereinafter referred to as an acceleration distribution). In the present embodiment, for the acceleration information acquired from the data processing device 210 provided in one vehicle, the occurrence frequency is counted for each predetermined section, and a display based on the count value is performed for each section region. Here, the predetermined section is preferably the same as the section in the compression process of step S101 by the data processing device 210. However, for convenience of acquiring moving body information from a plurality of moving bodies, different types of data processing devices 210 or devices equivalent thereto are used, so that the acceleration information is not necessarily generated based on a common section. Therefore, when generating the acceleration distribution, it is preferable to assign each acceleration information to a unified section in the server 230.

[0045] In the example of FIG. 8, the greater the distance from the center, the greater the acceleration, and the direction of the region as seen from the center indicates the direction of the acquired acceleration. Also, the absence of the display of a region indicates that the corresponding acceleration has not been acquired, that is, the corresponding acceleration has not been observed. Also, the concentration of the corresponding region is changed according to the acquired frequency for expression. For example, region 501 corresponds to the case where a large acceleration has been acquired in the deceleration direction, and is expressed darker than region 503 which corresponds to the case where a slightly large acceleration has been acquired in the acceleration direction. That is, the occurrence frequency of the acceleration corresponding to region 501 is higher than that of region 503. Similarly, region 502 indicates that a slightly large acceleration has been acquired for leftward handling.

[0046] Here, when the first region 501 is selected by user input, the screen shown in FIG. 9 is displayed. Specifically, this screen displays a map near the position and information on the driving route on the map in the situation where the acceleration corresponding to the first region 501 has been acquired on the map. Further, in the present embodiment, assuming that there are a plurality of situations where the acceleration corresponding to the first region 501 has been acquired, information on the corresponding plurality of situations is list-displayed in a selectable manner. The display order is in the order of the acquisition time being closer to the current time, but it is not particularly limited. When one of the plurality of displayed situations is selected by user input, the screen showing the details of the selected situation shown in FIG. 10 is displayed.

[0047] In FIG. 10, the vicinity area (for example, a 1-kilometer square area) of the position where such acceleration was acquired is enlarged and displayed, so that it is possible to grasp what shape the road was. Also, along the vehicle's route, it is possible to know what kind of acceleration was acquired. Specifically, the circles in FIG. 10 indicate the magnitude of the acceleration, and the arrows in the circles indicate the direction of the acceleration. Here, when the magnitude of the acceleration is small, the display of the arrow is omitted. Furthermore, the circle display itself may be omitted. In addition, as shown in FIG. 10, in this embodiment, driver information, information regarding the position, information regarding the display range, date and time information, remaining fuel information, driving time information, speed information, weather information (weather, temperature, humidity, etc.), and driving score are displayed. Of course, these are not limited to these information, and any information that can be obtained from the data processing device 210, information that can be inferred from the acquired information, and information that can be obtained by the server 230 through the Internet or the like may be used. For example, the following information may be displayed. · Information regarding the vicinity of the position (traffic congestion, presence or absence of nearby construction, etc.) · Status of the moving body (loaded weight, charge level of an electric vehicle, wear degree of tires, etc.) · Information regarding another moving body that passed through the vicinity of the position at the same time · Driving content (such as the content of acceleration) at the nearby position by the vehicle (or its driver) over a certain period in the past

[0048] Furthermore, the interface shown in area 406 not only shows a map regarding the acceleration distribution in units of a specific driver or moving body, but can also display the content obtained by synthesizing the acceleration distributions of a plurality of units. In this case, the content of the moving body information to be synthesized is not particularly limited, but it is preferable to synthesize the moving body information regarding substantially the same period. For example, if one of the synthesis targets is the moving body information for one month, it is preferable that the other synthesis targets are also for one month. Note that it does not have to be accumulated continuously for one month, and it may be the sum of the amounts for one month extracted from non-consecutive separate time zones. Also, the synthesis method may be any one of addition, subtraction, multiplication, and division, or a combination thereof as appropriate, and is not particularly limited thereto.

[0049] For example, the following synthesis contents can be cited. <Example 1> For a moving object, obtain the result of the difference in the acceleration distribution in different periods (for example, the previous month and this month). <Example 2> For two moving objects, obtain the difference in the acceleration distribution in the same period (for example, the previous month). <Example 3> For a plurality of moving objects, obtain the result of adding the acceleration distributions in the same period (for example, the first week of this month). <Example 4> For a plurality of moving objects, obtain the result of adding the acceleration distributions in a period under certain conditions (for example, 2 hours after the lunch break on a working day this month). <Example 5> For a plurality of moving objects managed by one department, obtain the result of the difference between the addition result of the acceleration distributions in the period of the first condition and the addition result of the acceleration distributions in the period of the second condition for a plurality of moving objects managed by another department. <Example 6> For a moving object, obtain the change rate (ratio) of the acceleration distribution in different periods (for example, the previous month and this month). <Example 7> For a moving object driving in a certain area, perform an OR operation on the acceleration distribution in a certain period to obtain the tendency of the acceleration that has not occurred. <Example 8> For a moving object, perform an XOR operation on the acceleration distributions in different periods (for example, the month one year ago and this month) to obtain the tendency of the acceleration with differences.

[0050] Hereinafter, in this embodiment, when a plurality of acceleration distributions are synthesized and an arbitrary acceleration region is selected from the synthesis result, the content of the analysis result generated and displayed will be described. FIG. 11 is a flowchart of the process from the synthesis of a plurality of acceleration distributions to the display of the analysis result according to this embodiment.

[0051] The processes performed according to the following flowchart are started, not limited to but by way of example, triggered by the following matters on the premise that certain moving body data has been accumulated. ·In the safe driving diagnosis service, at the analysis timing (for example, set monthly) ·Received an analysis request from the user ·Detected moving body information of a predetermined content (for example, in the target moving body, an acceleration value equal to or greater than a predetermined threshold has been obtained continuously for 3 days, a collision accident has occurred, etc.)

[0052] As shown in FIG. 11, the server 230 specifies what kind of synthesis to perform (S1100). Specifically, for example, it may be that the user directly specifies the synthesis method as an input from a terminal connected to the server 230 through a network, or the synthesis method may be specified by the user making an input to specify any of the following predetermined synthesis processes. ·Find the difference between two acceleration distributions obtained at different times in one moving body → Subtraction for two acceleration distributions ·Find the sum of multiple acceleration distributions obtained at different times in one moving body → Addition for multiple acceleration distributions ·Find the difference between two acceleration distributions obtained during the same period in two moving bodies → Subtraction for two acceleration distributions ·Find the sum of acceleration distributions obtained during the same period in multiple moving bodies → Addition for multiple acceleration distributions ·Find the sum of acceleration distributions obtained at different times in multiple moving bodies → Addition for multiple acceleration distributions ·Find the ratio of acceleration distributions obtained in two different periods in one moving body → Division for two acceleration distributions[[ID=3�]] Note that the synthesis method is not limited to these, and appropriate operations are applicable.

[0053] Next, the server 230 identifies identifiable information of the moving body information related to the synthesis process (S1101). Specifically, for example, from a terminal connected to the server 230, when the user inputs information that can identify the moving body information, the corresponding moving body information is identified, and the acceleration distribution included in the identified moving body information is identified. Here, the information specified for identifying the moving body information related to the synthesis process only needs to include at least the moving body and the period, and may also include other information. For example, it may include any one or more of information such as position (region), driver, weather, load (for example, limited to cases where it is 80% or more of the maximum load ratio, etc.).

[0054] The identification of the moving body and the period in S1101 is preferably performed based on the synthesis method identified in S1100. For example, when the synthesis method identified in S1100 is "the difference between two acceleration distributions obtained in different periods for one moving body", the server 230 outputs an interface that causes the user to input one target moving body and specify a plurality of periods. Examples of the interface will be described later.

[0055] Note that the order of S1100 and S1101 is not particularly limited, and it may be reversed. That is, it is also possible to first identify the moving body and the period in the moving body information to be synthesized, and then identify the synthesis method. Or, first identify the moving body and the period related to the moving body information that is part of the synthesis target, then identify the synthesis method, and then identify the remaining moving body information that is the synthesis target. That is, it is also possible to first identify a part of the synthesis target that is the axis of the synthesis process, and then identify the remaining synthesis target after the synthesis method is identified. At this time, when at least one piece of moving body information that is the axis of the synthesis process is identified and the synthesis method is identified, it is preferable that the server 230 presents information about the candidates for the remaining synthesis targets and allows the user to select to identify the remaining synthesis targets.

[0056] For example, if acceleration information in last month's mobile body information of a certain mobile body is first identified as one of the combination targets, and subtraction is identified as the combination method, considering that it is preferable to use mobile body information relating to approximately the same period as the combination target by subtraction, and that time, mobile body, region, etc. can be considered as comparison points, for example, the following mobile body information may be extracted as a candidate for the remaining combination target and presented preferentially to the user to recommend selection, or may be identified as the remaining combination target. Here, preferential presentation may include, for example, a method of displaying some of the mobile body information of the identified combination target and one or more remaining combination target candidates extracted based on the identified combination method in a manner different from the other candidates. - Information on the same moving object for the past month (for example, the month before last, or the same month one year ago) - Information about another vehicle for the past month. This other vehicle may be, for example, a vehicle selected by the user, a vehicle traveling in the same area as the target vehicle, another vehicle under the control of the same person, a vehicle driven by a driver with a similar driving history or driving quality to the driver, a vehicle of the same model, or a randomly selected vehicle. Average movement information for a specified area (e.g., the same region, the same prefecture, the whole country, etc.) for the last month In other words, the mobile bodies may be the same or different, may be different but in the same area, may have the same or different managers, may have the same or different driving history or driving quality, and various selection methods can be applied without any particular restrictions.

[0057] As a further example, if the acceleration distribution for the past month for a certain mobile object is first identified as one of the objects to be synthesized, and if additive synthesis is identified as the synthesis method, it is preferable to use mobile object information relating to approximately the same period as the object to be synthesized by additive synthesis. Also, considering that time, organization, region, etc. can be considered as comparison criteria, for example, the following mobile object information is extracted as a candidate for the remaining objects to be synthesized, and is presented to the user preferentially to recommend selection, or is identified as the remaining object to be synthesized. · Mobility information for the past several months (e.g., the month before last and several months before that) of the same moving object · Mobility information for the same month of some or all of the moving objects in the group to which the target moving object belongs

[0058] As a further example, when the acceleration distribution for the previous month of a certain moving object is specified as one of the objects to be combined, for example, a combination of the following mobility information and combination methods is extracted as a candidate and preferentially presented to the user for selection, or specified as the remaining objects to be combined and combination methods. · Mobility information for the past several months (e.g., the month before last and several months before that) of the same moving object, and subtraction · Mobility information for the past several months (e.g., the month before last and several months before that) of the same moving object, and addition · Mobility information for the previous month of another moving object, and subtraction · Average mobility information for a predetermined range (e.g., the same area, the same prefecture, the whole country, etc.) in the previous month, and subtraction · Mobility information for the same month of some or all of the moving objects in the group to which the target moving object belongs, and addition

[0059] Here, when specifying the remaining objects to be combined and the combination method based on a certain mobility information specified as one of the objects to be combined, for example, candidates for the remaining mobility information to be combined are presented to the user based on the specified mobility information, and the user is allowed to select to determine the remaining mobility information to be combined. Then, based on all the specified mobility information to be combined, the combination method may be specified or candidates may be presented for the user to determine. When extracting candidates for the remaining mobility information to be combined based on the mobility information corresponding to the specified mobility information, for example, location information included in these mobility information, as well as driver information, passenger information, related person (e.g., owner, administrator, etc.) information, affiliation (group, company, etc.) information, remaining fuel information, load capacity information, remaining battery power information, weather information, driving score, etc. included in the mobility information may be used.

[0060] Similarly, for example, candidates for synthesis methods identified based on the identified moving body information may be presented to the user, and the user may be allowed to select to determine the synthesis method. Then, based on the identified moving body information and the identified synthesis method, the remaining moving body information to be synthesized may be identified or candidates may be presented for the user to determine. Furthermore, similarly, for example, based on the moving body information identified as one of the synthesis targets, candidates for one or more synthesis methods are identified. Based on the moving body information identified as one of the synthesis targets and each of these synthesis method candidates, candidates for the remaining moving body information to be synthesized are identified, and combinations of the synthesis method candidates and the corresponding remaining synthesis target candidates are presented for the user to determine.

[0061] That is, by specifying all or part of the synthesis targets and the synthesis method, based on the content of the moving body information corresponding to the specified synthesis target and / or the synthesis method, the remaining synthesis targets and synthesis methods may be preferentially presented, recommended, or determined.

[0062] FIG. 12, FIG. 13, and FIG. 14 show an example of an interface for identifying the remaining synthesis targets by specifying part of the synthesis targets and the synthesis method. The interface is provided, for example, in a display unit or an input unit such as an administrator terminal. As shown in each figure, the interface is composed of area A1, area A2, and area A3. Area A1 is an area for specifying part of the synthesis targets, area A2 is an area for specifying the synthesis method, and area A3 is an area for specifying the remaining synthesis targets.

[0063] FIG. 12 shows an example of an interface displayed when identifying a part of the object to be synthesized. The corresponding area, area A1, is composed of an object A11 showing the acceleration distribution of a part of the object to be synthesized and an object A12 which is an area for setting information for identifying a part of the object to be synthesized. In object A12, as information for identifying a part of the object to be synthesized, for example, the driver, driving period, driving area, and weather are to be set. However, the information set in object A12 is not particularly limited as long as it is information for identifying a part of the object to be synthesized. Also, in FIG. 12, for the driver, start date and end date of the driving period, and weather, a pull-down method is used for determination, and for the driving area, it is an interface assuming direct input. However, the input method is not particularly limited to these, and any input method such as check boxes, radio buttons, or an operation of selecting an intended area on the map for the driving area can be applied. The interface shown in FIG. 12 is at the point where the driver is set as AAA, the driving period is from January 1, 2022, to January 31, 2022, the driving area is the 23 wards of Tokyo, Mitaka City, Musashino City, Komae City, Chofu City, and Nishi-Tokyo City, and for the weather, no specification is made by the pull-down method and one of sunny and rainy is to be selected. Note that in area A2, since the synthesis method has not been specified yet, no information is displayed. For area A3, since a part of the object to be synthesized and the synthesis method have not been identified, the remaining part of the object to be synthesized cannot be identified yet, and similarly, no information is displayed.

[0064] FIG. 13 shows an example of an interface displayed when identifying the synthesis method after a part of the object to be synthesized has been identified. The corresponding area, area A2, is composed of an object A21 showing candidates for the synthesis method, "addition (+)", "subtraction (−)", "division (÷)", and "multiplication (×)", in a pull-down manner. In the area A1 for specifying a part of the synthesis target, information such as the driver, driving period, driving area, and weather, which is information for specifying a part of the synthesis target, has already been set, and a gray color indicating a fixed state is attached so that no further changes can be made. Here, when the setting in the area A1 is completed, it may be possible to set the area A2 with the content of the area A1 fixed, or it may be possible to set both the area A1 and the area A2 without an order relationship. Also, in the area A3, although a part of the synthesis target has been specified, the synthesis method has not been specified yet, so the remaining synthesis target cannot be specified and no information is displayed.

[0065] FIG. 14 shows an example of an interface that displays information on candidates for the remaining synthesis target based on the specified part of the synthesis target and the synthesis method after a part of the synthesis target and the synthesis method have been specified. The corresponding area, area A3, includes an object A311 showing the acceleration distribution, an object A312 showing information for specifying candidate 1, which is the first candidate for the remaining synthesis target, and an object A313 showing a check box for determining candidate 1 as the remaining synthesis target, as information for candidate 1, which is the first candidate for the remaining synthesis target, and an object A321 showing the acceleration distribution, an object A322 showing information for specifying candidate 2, which is the second candidate for the remaining synthesis target, and an object A313 showing a check box for determining candidate 2 as the remaining synthesis target, as information for candidate 2, which is the second candidate for the remaining synthesis target. In the area A1 for specifying a part of the synthesis target, information such as the driver, driving period, driving area, and weather, which is information for specifying a part of the synthesis target, has already been set and is grayed out. Also, in the area A2, the synthesis method has already been specified as "subtraction" and is grayed out.

[0066] As shown in Fig. 14, a part of the synthesis target is specified with the driver being "AAA", the driving period being one month (31 days) from January 1, 2022 to January 31, 2022, the driving area being the 23 wards of Tokyo, Mitaka City, Musashino City, Komae City, Chofu City, and Nishi-Tokyo City, and the weather being "unspecified" (i.e., regardless of the weather). Since the synthesis method is specified as "subtraction (-)", it is preferable to extract a comparison target having a quantity similar to that of a part of the synthesis target as the remaining synthesis target. Therefore, as candidate 1, the driver, driving area (since the amount of information exceeds the displayable amount, the parts that cannot be displayed are indicated as "…" and the display is omitted), weather, and driving period length (one month; 31 days) are the same, while the driving period time is different (from December 1, 2021 to December 31, 2021), or as candidate 2, the driver is different (the driver is "BBB"), and the driving period length and time, driving area, and weather are the same. And since the user has checked the checkbox of object A323 of candidate 2, candidate 2 is specified as the remaining synthesis target.

[0067] Also, based on all the specified synthesis targets, a specific example of specifying the synthesis method will be described below. For example, when the mobile body information for the previous month of one mobile body and the mobile body information for the previous month of another mobile body are specified as the synthesis targets, since they are mobile body information of approximately the same quantity for different mobile bodies, assuming the purpose of comparison, the synthesis method is preferably subtraction, for example. Whether to present subtraction as the synthesis method to the user, recommend it (for example, preferentially present it by changing the display mode from other candidates), or determine subtraction as the synthesis method. Also, when the purpose of comparison is assumed, instead of subtraction, division may be presented, recommended (for example, by preferentially presenting it), or determined as the synthesis method. Conversely, when mobile body information of different quantities is specified as the synthesis target, since subtraction and division do not seem preferable, for example, addition may be recommended. Furthermore, for example, when the mobile body information for the previous month in a plurality of mobile bodies and the mobile body information for the month before last in another plurality of mobile bodies with the same owner are identified as the synthesis targets, since they are mobile body information of the same owner, for the purpose of referring to the cumulative result, addition is preferably used as the synthesis method, and whether to preferentially present addition as the synthesis method to the user, (for example, by preferentially presenting it) recommend it, or determine addition as the synthesis method.

[0068] In the above description, two mobile body information are identified as the synthesis targets, and one synthesis method is identified as the synthesis method for these two synthesis targets. However, the number of synthesis targets and the number of synthesis methods are not limited to this, and any number can be applied. For example, it is assumed that four pieces of mobile body information, A, B, C, and D, are identified as the synthesis targets, and for these identified synthesis targets, addition of A and B (A + B), addition of C and D (C + D), and subtraction of (A + B) and (C + D) ((A + B) - (C + D)) are synthesized. In this case, first, for example, when A is identified, based on the identified A, the remaining synthesis targets B, C, and D can be identified, and a combination of addition and subtraction as the synthesis method can be identified, or these candidates can be identified and presented to the user for selection. As an example, when A is the mobile body information for the previous month in a certain area (Area 1) of a certain mobile body, B can be identified as the mobile body information in another area (Area 2) of the same mobile body in the same month, C can be identified as the mobile body information in Area 1 of the same mobile body in another month, and D can be identified as the mobile body information in Area 2 of the same mobile body in the same month as C. That is, for example, it applies when it is desired to compare the driving conditions of the previous month and another month not only in Area 1 but also in Area 2 for a certain mobile body. Similarly, for example, when B and C are identified as the synthesis targets and a similar ((○ + B) - (C + ○)) (where ○ indicates that the synthesis target is not identified) is identified as the synthesis method, the remaining synthesis targets A and D can be identified or presented as candidates based on B, C, and the above synthesis method.

[0069] Note that the object of synthesis here may be interpreted in units of a set of moving object information obtained by dividing the moving object information at regular intervals as described above, or in units of each piece of obtained moving object information. That is, in the former case, it is understood that synthesis is performed by addition, subtraction, etc. using a set based on a certain criterion as a unit, and in the latter case, it is synthesized by addition until a certain set is formed, and further synthesis by addition, subtraction, etc. is performed on the set formed by the addition synthesis.

[0070] Next, based on the information of the moving object and the period specified in S1101, the server 230 specifies the moving object information to be synthesized (S1102). Specifically, the server 230 specifies the moving object information corresponding to the specified moving object and period information from the information stored in the storage unit 232 of the server 230.

[0071] Next, the server 230 synthesizes the acceleration distribution corresponding to the specified moving object information using the specified synthesis method (S1103). Specifically, the server 230 applies the specified synthesis method to the frequency in each of the specified moving object information for each predetermined section. For example, when the specified synthesis method is "the difference between two acceleration distributions obtained in different periods for one moving object", the difference value between the values of the two frequencies is obtained for each predetermined section.

[0072] Thereafter, the server 230 outputs the synthesis result (S1104), and for example, the synthesis result is displayed on the display unit of the user terminal. At this time, it may be possible to display the sections worthy of attention, such as those with large frequency values, in a manner distinguishable from other sections. By doing so, it is possible to make it easy for the user to identify the sections with large values and prompt the user to select them as sections related to the analysis process. Note that the notable section is not particularly limited to the case where the value is greater than a predetermined threshold. As other examples, there are cases where the value is within the top 10% in all sections, cases where the variation in the frequency value in the section is large (for example, the variance value is greater than a predetermined threshold), and cases where it is significantly larger than the surrounding sections (for example, it is a predetermined multiple or more of the average value or the maximum value of the adjacent 4 sections), and so on.

[0073] FIG. 15 shows an example expressing the difference in the acceleration distribution regarding two moving objects referring to the above <Example 1> as an example. FIG. 15 is an example comparing the acceleration distributions for a certain month and the previous month regarding the driving of a vehicle by a certain driver. As shown in FIG. 15, in addition to each region being represented by a density corresponding to the magnitude of the difference value, it is in a recognizable manner which of the two comparison targets has a higher occurrence frequency. For example, region 601 is shown with vertical lines and high density, which indicates that the frequency of the acceleration corresponding to this region occurred much higher in that month compared to the previous month. On the contrary, region 602 is shown with diagonal lines and high density, which indicates that the frequency of the acceleration corresponding to this region became much lower in that month compared to the previous month. By showing the results of comparing the acceleration distributions in this way, a relative driving evaluation can be performed from viewpoints such as time, region, person, etc.

[0074] Also, FIG. 16 shows an example of adding the acceleration distributions regarding a plurality of moving objects referring to the above <Example 3> as an example. FIG. 13 is the result of adding the acceleration distributions regarding the driving in a certain week in a plurality of moving objects managed by a certain department. Similar to FIG. 8, in FIG. 16, each region is represented by a density corresponding to the magnitude of the added value obtained by adding them up. That is, the darker the density, the higher the frequency of the acceleration corresponding to that region occurred.

[0075] Furthermore, with respect to the content shown in FIGS. 15 and 16, the user may specify limiting conditions and display the results when corresponding limitations are applied (S1105). FIG. 17 is a distribution diagram of acceleration when the moving objects are limited to those with a driving score in the top 20% as a limiting condition, and further, the target area is limited to the vicinity of YY, XX City. In the distribution diagram shown in FIG. 17, based on the fact that it is a set of moving objects with a high driving score, it can be understood that the acquisition frequency of acceleration corresponding to sudden steering, sudden acceleration, and sudden deceleration is lower than that in FIG. 16. Also, since the density of area 801 and its surrounding sections remains high, even in the set of moving objects with a high driving score, a large amount of acceleration corresponding to area 801 occurs in this target area, and it is presumed that there is some background (for example, there is a road with poor visibility and sudden braking is likely to occur, etc.). Therefore, it is displayed in a manner distinguishable from other sections as a section worthy of attention.

[0076] Thereafter, the user can specify any section to be analyzed to identify the moving object information related to the analysis process. The analysis process, although details will be described later, derives, for example, whether there is a correlation such as their tendencies and common points among the specified group of moving object information, and if so, what those tendencies and common points are. When specifying a section, it is possible to select an arbitrary range including one or more sections. For example, area specification as shown in FIG. 18 can be performed. FIG. 18A designates a section where the scalar value of acceleration in all directions is greater than a predetermined value. FIG. 18B designates the section with the largest value in all sections. As described above, it may be displayed in a manner different from other sections as a section worthy of attention. FIG. 18C designates a section where the scalar value of acceleration in the forward direction is greater than a predetermined value. FIG. 18D designates a section in the forward direction regardless of the magnitude of the scalar value of acceleration. FIG. 18E designates a section where the magnitude of the value is within the top 10% in a section where the scalar value of the acceleration is greater than a predetermined value. As a section to be noted, it may be displayed in a manner different from other sections. FIG. 18F is an area arbitrarily designated by a user operation. For example, it is designated by an operation of filling in with a finger on a tablet or a smartphone. The section designated thereby may be a section having at least one pixel in common with this area, or may be a section having a predetermined number or more (for example, 50% or more of the size of the section) of pixels in common with this area, and the relationship between the area and the section is not particularly limited.

[0077] Thereby, the server 230 specifies the section area designated by the user (S1106). For example, when the area 803 in the example of FIG. 17 is designated, in addition to the map information and the route information in the vicinity of the position where the acceleration corresponding to the area 803 is acquired being displayed, the server 230 analyzes the situation where such acceleration is acquired, and derives and outputs tendencies, common points, etc. (S1107).

[0078] FIG. 19 is an example of a screen output when a certain acceleration area is selected and displayed on the user terminal. As shown in FIG. 19, information regarding tendencies is output for the following items as examples. · Time zone For example, it is distinguished as early morning (from 4:00 to 8:00), morning (from 8:00 to 12:00), afternoon (from 12:00 to 16:00), evening (from 16:00 to 20:00), night (from 20:00 to 24:00), late night (from 24:00 to 4:00), etc. When the frequency in a certain time zone when such acceleration is acquired is greater than a predetermined value (for example, 30% or more of the whole. Here, the ratio of the frequency of acquisition of such acceleration to the whole is referred to as the tendency degree), it is set as a display target as having a large tendency degree in that time zone. · Weather When the frequency in a certain weather is higher than a predetermined value, it is considered that the degree of tendency is large and is set as a display target. Note that since driving is likely to be difficult in some weather conditions such as rain and snow, it may be appropriate to display information about the degree of tendency only when the degree of tendency is large in those weather conditions. · Loading capacity (ratio to the maximum loading capacity) The loading capacity information is obtained from a loading capacity acquisition unit (not shown) provided in the moving body or the data processing device 210, or by the user inputting for each driving unit, for example. In FIG. 19, the loading capacity information shows the ratio of the loading capacity to the maximum loading capacity, but it may also be targeted at the loading capacity (in kilograms, etc.). Based on these acquired loading capacity information and the corresponding acceleration information, information about the loading capacity with a high degree of tendency is displayed. Here, similar to the case of weather, since driving is likely to become difficult due to a large maximum loading capacity ratio or loading capacity, it may be appropriate to display information about the degree of tendency only when it is equal to or greater than a predetermined loading capacity ratio or loading capacity. · Continuous driving time When there is a time amount with a large tendency to the selected acceleration in the time amount of the difference between the time when the situation occurred and the time when the last break was taken, it is considered that the degree of tendency is large and is set as a display target. · Vehicle type · Vehicle class For a specific vehicle type or vehicle class, when the tendency for the selected acceleration to occur is high, it is considered that the degree of tendency is large and is set as a display target.

[0079] Among these information, the information about the time zone and the continuous driving time can be calculated from the corresponding time information, and the information about the weather is acquired in the server 230 via the Internet or the like based on the corresponding time information and the position information. The information about the loading capacity and the information about the vehicle type and vehicle class are acquired by the user inputting at the user terminal.

[0080] The content of the information on the tendency is, for example, as shown in FIG. 19, information on the most frequent element and the ratio that the frequency occupies. However, the content of the information on the tendency is not limited to this, and it is not particularly limited as long as it is information that can confirm the tendency in some form.

[0081] Similarly, by selecting the region 701 in the example of FIG. 16 or the region 601 in the example of FIG. 15 before applying the limiting conditions, the tendency may be calculated and output in the same manner as in the example of FIG. 19. In addition, when a certain region is selected as a result of comparing two acceleration distributions, the situation regarding both of the two comparison targets may be displayed, or only the situation with the higher frequency or only the situation with the lower frequency may be displayed. Alternatively, it may be displayed in a manner that distinguishes between the higher frequency side and the lower frequency side (for example, arranging the higher frequency side on the left and the lower frequency side on the right).

[0082] [Modification Example] A modification example of the above-described embodiment will be described. In the lower part of FIG. 1, the collection result of the acceleration in the reference plane RP is shown. However, when the acceleration is also acquired in the direction perpendicular to the reference plane RP (that is, the vertical direction (for example, the up-and-down direction of the vehicle) orthogonal to both the traveling direction (FR-RR direction) and the lateral direction (LS-RS direction)), the angle from this vertical direction may also be used to plot the position in polar coordinates or spherical coordinates.

[0083] The magnitude of the acceleration may be calculated three-dimensionally including the vertical direction, and the plotting may be performed in the reference plane RP which is a two-dimensional plane.

[0084] The data processing device 210 stores the acquired moving body information for a predetermined time or a predetermined travel distance in the storage unit 232, and when a predetermined communication becomes possible during travel (for example, when passing near a roadside unit installed beside the road and capable of data communication with the moving body using a predetermined communication protocol), all or part of the stored moving body information may be transmitted to the server 230 or to a temporary data storage server (not shown) that performs temporary data accumulation and stored there. In this way, when the moving body information is accumulated in the temporary data storage server, the server 230 appropriately accesses (for example, every hour) the temporary data storage server, extracts the moving body information, and stores it in the storage unit 232.

[0085] In the above description, an example has been described in which the data processing device 210 acquires acceleration information and position information, associates time information with these, and transmits and stores them as moving body information. However, the configuration of the moving body information is not limited to this. For example, speed information may be used instead of acceleration information. In this case, what is obtained by associating position information and time information with the speed information is transmitted to the server 230 as moving body information and stored, and the same processing as in the case of acceleration information is performed. Also in this case, the data processing device 210 includes a speed information acquisition unit that acquires the speed information of the vehicle. Alternatively, angular velocity information may be used instead of acceleration information. Similarly in this case, what is obtained by associating position information and time information with the angular velocity information is transmitted to the server 230 as moving body information and stored, and the same processing as in the case of acceleration information is performed. Also in this case, the data processing device 210 includes an angular velocity information acquisition unit that acquires the angular velocity information of the vehicle. Also, for example, the moving body information may further include at least one of the following. · Information regarding the load capacity · Information regarding the charge amount in an electric vehicle (for example, remaining capacity, SOC, SOH, etc.) · Information regarding the temperature of the cargo compartment in a temperature control vehicle · Information regarding the engine speed · Information regarding the gear during travel In this case, the data processing device 210 is provided with corresponding means (i.e., the loading amount information acquisition unit, the charge amount information acquisition unit, the temperature information acquisition unit, the engine rotation speed information acquisition unit, and the gear information acquisition unit), and the acquired information is transmitted to and stored in the server 230.

[0086] In the above description, an example of inserting the data processing device 210 into the socket of an automobile has been described, but the present embodiment is not limited to this. The present embodiment is applicable also when the data processing device 210 is connected to the vehicle via a connection terminal other than the cigarette socket, when it is configured integrally with the vehicle, or when it is not fixedly connected to the vehicle but simply arranged on the dashboard in the vehicle, etc.

[0087] In the above description, it is assumed that the data processing device 210 includes the acceleration information acquisition unit 211 and the position information acquisition unit 214, but it is not limited to this mode. For example, the acceleration information acquisition unit 211 may be provided in a device different from the data processing device 210, and the acquired acceleration information may be transmitted to the data processing device 210, and the acceleration information and the position information may be associated in the data processing device 210. Conversely, the position information acquisition unit 214 may be provided in a device different from the data processing device 210, and the acquired position information may be transmitted to the data processing device 210, and the acceleration information and the position information may be associated in the data processing device 210. Thus, each element of the data processing device 210 does not necessarily have to be configured integrally, and separate devices may be provided with elements and transmit the acquired information to the data processing device 210 for aggregation and association. Or, it may be aggregated and associated in the server 230.

[0088] In the above description, a vehicle is exemplified as the moving body, but the scope to which the present invention is applicable is not limited to vehicles. For example, it is applicable to all moving bodies such as motorcycles, bicycles, airplanes, helicopters, drones, ships, etc.

[0089] In the above description, an aspect of displaying information on a situation related to an acceleration identified in an acceleration distribution for a moving body has been shown, but it is not limited to this aspect. For example, it may be possible to specify an arbitrary area on the map information and display the acceleration information of the vehicle in that area. In this case, for example, when the "display acceleration distribution in the area" button in FIG. 10 is pressed, the acceleration information of the vehicles that have passed through such an area is collected and an acceleration distribution as shown in FIG. 8 is displayed.

[0090] In the above description, addition, subtraction, division, and multiplication have been shown as examples of the synthesis method, but the synthesis method is not limited to these, and any synthesis method can be applied. For example, it may be a synthesis method in a combined form of these. When synthesizing A and B of the moving body information set, for A, the frequency value in each section is tripled, and for B, the frequency value in each section is quadrupled, and the difference between them is calculated (that is, 3×A - 4×B). This is effective, for example, when the moving body information set A has an information volume for 4 months and the moving body information set B has an information volume for 3 months, and the difference is obtained assuming the annual information volume of both. Furthermore, it may be possible to output an acceleration distribution calculated with a multiple by an arbitrary number or an arbitrary number as the divisor.

[0091] Furthermore, as an example of another synthesis method, comparison operations and logical operations may be performed. For example, it is also possible to perform an operation of comparing values for each section and outputting 1 as true if the first value is smaller than the second value, and 0 as false if the first value is greater than or equal to the second value. Similarly, whether the first value is less than or equal to the second value, whether the first value is greater than the second value, whether the first value is greater than or equal to the second value, whether the first value is equal to the second value (in this case, it may also be a determination of whether it is within a predetermined range with a certain width), whether the first value is not equal to the second value, whether both the first value and the second value are 1 (or a predetermined value) or more, whether either the first value or the second value is 1 (or a predetermined value) or more, whether the first value and the second value are different (or whether the difference value is a predetermined value or more), whether either one of the first value and the second value is 1 (or a predetermined value) or more and both are not 1 or more, etc. It is also possible to perform an operation of outputting 1 or 0 (or any numerical value) according to such criteria.

[0092] In the above description, the moving body information set to be synthesized is specified based on information such as the driver, driving period, driving area, weather, etc., but the specifying method is not limited to this. For example, the average of the acceleration distributions corresponding to the moving body set for a plurality of drivers may be used as the synthesis target, or further, the average of all the moving body information in a certain area collected over a certain period may be used as the area average and used as the synthesis target. In this case, these average acceleration distributions may be obtained by the processing from step S1100 to step S1104. At this time, a method such as calculating a weighted average can also be applied.

[0093] In the above description, synthesis processing is performed on the acceleration information or speed information included in the moving body information, but the target of the synthesis processing is not limited to these. The target of the synthesis processing may be any feature quantity information related to the movement of the moving body, for example, jerk, angular velocity, angular acceleration, etc. Also, for each of the plurality of moving object information to be synthesized, distributions of a plurality of types of feature quantity information may be prepared and synthesized by a specified synthesis method. For example, for each of the plurality of moving object information to be synthesized, an acceleration distribution based on a first section and a speed distribution based on a second section are prepared, synthesis processing is performed on the plurality of acceleration distributions by a specified synthesis method, and synthesis processing is performed on the plurality of speed distributions by the same synthesis method, and output is performed for each of them.

[0094] In the above description, a plurality of moving object information to be synthesized is assigned to two-dimensional sections, and synthesis processing is performed based on the two-dimensional sections. However, the sections to be assigned are not limited to this mode. The sections to be assigned may be based on one dimension, or may be based on three or more dimensions, and the number of dimensions is not particularly limited. Also, the form of the sections is not particularly limited. For example, for the purpose of finely analyzing the acceleration generated in a specific direction (for example, the right direction), the sections in the specific direction may be made finer than the sections in other directions. Note that the user may be allowed to select the sections to which a plurality of moving object information to be synthesized is assigned. In this case, the sections themselves that are displayed by default may be changed to such sections, or the default may be left as it is and only the output may be performed in such sections. For example, the user may be allowed to select before and after selecting the synthesis method.

[0095] In the above description, moving object information is assigned to predetermined sections, and the frequencies in each section are acquired and used as the synthesis target. However, the information acquired as the synthesis target in the predetermined sections is not limited to the frequencies. For example, the occurrence probability calculated based on the frequencies in each section may be acquired and used as the synthesis target. In this case, even if there are differences in the components of the plurality of moving object information to be synthesized, there is an effect that comparison becomes easy. Also, from this background, it is preferable that synthesis methods such as subtraction and division are recommended.

[0096] Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited to the above embodiments. Further, various improvements and modifications are possible within the scope not departing from the gist of the present invention. Also, the above embodiments and modifications can be combined.

Explanation of Reference Numerals

[0097] 210 Data processing device 211 Acceleration information acquisition unit 212 Processing unit 213 Communication unit 214 Position information acquisition unit 220 Mobile terminal 230 Server 231 Communication unit 232 Storage unit 233 Processing unit

Claims

1. A data processing system, comprising: a storage unit that associates and stores time-series moving object information with time information; a synthesis method specifying unit that specifies a synthesis method; a moving object information specifying unit that specifies a plurality of pieces of moving object information related to synthesis processing from the stored moving object information; an assignment unit that assigns feature quantity information included in each of the plurality of pieces of moving object information related to the synthesis processing based on a predetermined classification; an acquisition unit that acquires the frequency or occurrence probability of the feature quantity information for each of the predetermined classifications for each of the plurality of pieces of moving object information related to the synthesis processing; a synthesis result acquisition unit that acquires a synthesis result obtained by applying the specified synthesis method to the frequency or occurrence probability of the feature quantity information for each of the predetermined classifications acquired for each of the plurality of pieces of moving object information related to the synthesis processing; an output unit that outputs the acquired synthesis result; and the moving object information specifying unit specifies a part of the plurality of pieces of moving object information related to the synthesis processing, the synthesis method specifying unit specifies at least one candidate synthesis method related to the synthesis processing based on a part of the specified plurality of pieces of moving object information, the moving object information specifying unit specifies candidates for the remaining moving object information of the plurality of pieces of moving object information related to the synthesis processing based on each of the specified at least one candidate synthesis method and the specified part of the plurality of pieces of moving object information, the moving object information specifying unit and the synthesis method specifying unit specify, from combinations of the specified at least one synthesis method and the corresponding specified candidates for the remaining moving object information, a combination of candidates selected by user input as the synthesis method related to the synthesis processing and the remaining moving object information of the plurality of pieces of moving object information.

2. A data processing method in a data processing system, comprising: associating and storing time-series moving object information with time information; specifying a synthesis method; specifying a plurality of pieces of moving object information related to synthesis processing from the stored moving object information; assigning feature quantity information included in each of the plurality of pieces of moving object information related to the synthesis processing based on a predetermined classification; and acquiring the frequency or occurrence probability of the feature quantity information for each of the predetermined classifications for each of the plurality of pieces of moving object information related to the synthesis processing; Obtaining a synthesis result by applying the identified synthesis method to the frequency or occurrence probability of the feature amount information for each predetermined category in each of the plurality of moving body information related to the synthesis process; Outputting the obtained synthesis result; including; Identifying the moving body information includes identifying a part of the plurality of moving body information related to the synthesis process; Identifying the synthesis method includes identifying at least one candidate synthesis method related to the synthesis process based on a part of the identified plurality of moving body information; The data processing method is Identifying candidates for the remaining moving body information of the plurality of moving body information related to the synthesis process based on each of the identified at least one candidate synthesis method and a part of the identified plurality of moving body information; Further including identifying, from combinations of the identified at least one synthesis method and the corresponding identified candidates for the remaining moving body information, a combination of candidates selected by user input as the synthesis method related to the synthesis process and the remaining moving body information of the plurality of moving body information.

3. In a data processing system, Storing the moving body information acquired in time series in association with time information; Identifying a synthesis method; Identifying a plurality of moving body information related to the synthesis process from the stored moving body information; Assigning the feature amount information included in each of the plurality of moving body information related to the synthesis process based on a predetermined category; For each of the plurality of moving body information related to the synthesis process, obtaining the frequency or occurrence probability of the feature amount information for each predetermined category; Obtaining a synthesis result by applying the identified synthesis method to the frequency or occurrence probability of the feature amount information for each predetermined category in each of the plurality of moving body information related to the synthesis process; Outputting the obtained synthesis result; A program for causing the above to be executed, Identifying the moving body information includes identifying a part of the plurality of moving body information related to the synthesis process; Identifying the synthesis method includes identifying at least one candidate synthesis method related to the synthesis process based on a part of the identified plurality of moving body information; The program is Based on each of the candidates of the at least one specified synthesis method and a part of the specified plurality of moving object information, specifying candidates for the remaining moving object information of the plurality of moving object information related to the synthesis process; From among the combinations of the specified at least one synthesis method and the corresponding candidates for the remaining moving object information, specifying, as the synthesis method and the remaining moving object information of the plurality of moving object information related to the synthesis process, the combination of candidates selected by user input.

4. A data processing system, a storage unit that stores moving object information acquired in time series in association with time information; a synthesis method specifying unit that specifies a synthesis method; a moving object information specifying unit that specifies a plurality of moving object information related to a synthesis process from the stored moving object information; an assignment unit that assigns the feature amount information included in each of the plurality of moving object information related to the synthesis process based on a predetermined classification; an acquisition unit that acquires the occurrence probability of the feature amount information for each of the predetermined classifications for each of the plurality of moving object information related to the synthesis process; a synthesis result acquisition unit that acquires a synthesis result obtained by applying the specified synthesis method to the occurrence probability of the feature amount information for each of the predetermined classifications in each of the plurality of moving object information related to the synthesis process; an output unit that outputs the acquired synthesis result; comprising: The synthesis method specifying unit specifies candidates for at least one synthesis method based on the plurality of moving object information related to the specified synthesis process, and specifies, as the synthesis method related to the synthesis process, the candidate for the synthesis method selected by user input from among the specified candidates for the at least one synthesis method.

5. A data processing method in a data processing system, storing moving object information acquired in time series in association with time information; specifying a synthesis method; specifying a plurality of moving object information related to a synthesis process from the stored moving object information; assigning the feature amount information included in each of the plurality of moving object information related to the synthesis process based on a predetermined classification; acquiring the occurrence probability of the feature amount information for each of the predetermined classifications for each of the plurality of moving object information related to the synthesis process; For each of the plurality of moving object information related to the synthesis process, obtaining a synthesis result by applying the specified synthesis method to the occurrence probability of the feature amount information for each of the obtained predetermined sections; Outputting the obtained synthesis result; including; Specifying the synthesis method includes specifying at least one candidate synthesis method based on the plurality of moving object information related to the specified synthesis process, and selecting, from among the specified at least one candidate synthesis method, the candidate synthesis method selected by user input as the synthesis method related to the synthesis process.

6. A data processing system, a storage unit that stores moving object information acquired in time series in association with time information; a synthesis method specifying unit that specifies a synthesis method; a moving object information specifying unit that specifies a plurality of moving object information related to a synthesis process from the stored moving object information; an assignment unit that assigns the feature amount information included in each of the plurality of moving object information related to the synthesis process based on a predetermined section; an acquisition unit that acquires the occurrence probability of the feature amount information for each of the predetermined sections for each of the plurality of moving object information related to the synthesis process; a synthesis result acquisition unit that obtains a synthesis result by applying the specified synthesis method to the occurrence probability of the feature amount information for each of the obtained predetermined sections in each of the plurality of moving object information related to the synthesis process; an output unit that outputs the obtained synthesis result; comprising; the moving object information specifying unit specifies a part of the plurality of moving object information related to the synthesis process, the synthesis method specifying unit specifies a synthesis method based on a part of the specified plurality of moving object information, the moving object information specifying unit specifies the remaining moving object information of the plurality of moving object information related to the synthesis process based on a part of the specified plurality of moving object information and the specified synthesis method.

7. A data processing method in a data processing system, storing moving object information acquired in time series in association with time information; specifying a synthesis method; specifying a plurality of moving object information related to a synthesis process from the stored moving object information; assigning the feature amount information included in each of the plurality of moving object information related to the synthesis process based on a predetermined section; acquiring the occurrence probability of the feature amount information for each of the predetermined sections for each of the plurality of moving object information related to the synthesis process; For each of a plurality of pieces of moving body information related to the synthesis process, obtaining a synthesis result by applying the identified synthesis method to the occurrence probability of the feature quantity information for each predetermined section of the acquired feature quantity information; outputting the obtained synthesis result; comprising: Identifying the moving body information includes identifying a part of a plurality of pieces of moving body information related to the synthesis process; Identifying the synthesis method is performed based on a part of the identified plurality of pieces of moving body information; Identifying the moving body information includes identifying the remaining moving body information of a plurality of pieces of moving body information related to the synthesis process based on a part of the identified plurality of pieces of moving body information and the identified synthesis method.

8. A data processing system, comprising: a storage unit that stores moving body information acquired in a time series in association with time information; a synthesis method identification unit that identifies a synthesis method; a moving body information identification unit that identifies a plurality of pieces of moving body information related to a synthesis process from the stored moving body information; an allocation unit that allocates the feature quantity information included in each of the plurality of pieces of moving body information related to the synthesis process based on a predetermined section; an acquisition unit that acquires the occurrence probability of the feature quantity information for each predetermined section for each of the plurality of pieces of moving body information related to the synthesis process; a synthesis result acquisition unit that obtains a synthesis result by applying the identified synthesis method to the occurrence probability of the feature quantity information for each predetermined section of the acquired feature quantity information for each of the plurality of pieces of moving body information related to the synthesis process; an output unit that outputs the obtained synthesis result; comprising: The synthesis method identification unit identifies at least one candidate synthesis method related to the synthesis process, and identifies, from among the identified at least one candidate synthesis method, the candidate synthesis method selected by user input as the synthesis method related to the synthesis process; The moving body information identification unit identifies at least one candidate for the remaining moving body information of a plurality of pieces of moving body information related to the synthesis process based on a part of the identified plurality of pieces of moving body information and the identified synthesis method, and identifies, from among the identified at least one candidate for the remaining moving body information, the candidate for the remaining moving body information selected by user input as the remaining moving body information of a plurality of pieces of moving body information related to the synthesis process.

9. A data processing method in a data processing system, comprising: storing moving body information acquired in a time series in association with time information; Specifying a synthesis method, Specifying a plurality of moving body information related to the synthesis process from the stored moving body information, Assigning the feature quantity information included in each of the plurality of moving body information related to the synthesis process based on a predetermined classification, For each of the plurality of moving body information related to the synthesis process, obtaining the occurrence probability of the feature quantity information for each of the predetermined classifications, For each of the plurality of moving body information related to the synthesis process, obtaining a synthesis result obtained by applying the specified synthesis method to the occurrence probability of the feature quantity information for each of the obtained predetermined classifications, Outputting the obtained synthesis result, including, Specifying the synthesis method includes specifying at least one candidate synthesis method related to the synthesis process, and specifying, from among the specified at least one candidate synthesis method, the candidate synthesis method selected by user input as the synthesis method related to the synthesis process. Specifying the moving body information includes specifying at least one candidate remaining moving body information of the remaining moving body information in the plurality of moving body information related to the synthesis process based on a part of the specified plurality of moving body information and the specified synthesis method, and specifying, from among the specified at least one candidate remaining moving body information, the candidate remaining moving body information selected by user input as the remaining moving body information in the plurality of moving body information related to the synthesis process.

10. The data processing system according to any one of Claims 1, 4, 6, and 8, further includes a limiting condition specifying unit that specifies a limiting condition for the synthesis result, and the output unit outputs a result obtained by applying the specified limiting condition to the synthesis result.

11. A data processing system according to any one of Claims 1, 4, 6, and 8, wherein the output unit outputs the synthesis result in such a manner that a classification satisfying a predetermined criterion for the feature quantity information for each of the predetermined classifications is distinguishable from a classification not satisfying the predetermined criterion.

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