JP2020071831A - Data collection device, data collection system, and data collection method - Google Patents

Abstract

To improve communication efficiency in an information collection related to a vehicle.SOLUTION: A data collection device includes a collection part, a collection condition setting part, and a calculation part. The collection part collects data related to each vehicle from an in-vehicle device mounted on the vehicle. The collection condition setting part sets conditions for compression of collection data. The calculation part calculates an estimated value of a data size that is related to the compression on the basis of the past collection data collected by the collection part.SELECTED DRAWING: Figure 2

Description

  The disclosed embodiments relate to a data collection device, a data collection system, and a data collection method.

  BACKGROUND ART Conventionally, there is known a data collection device that collects road information from an in-vehicle device mounted on each vehicle. Such a data collection device collects road information at a desired position by selecting vehicles for which road information is to be collected based on the position information of each vehicle (see, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2018-055581

  However, the above-described conventional technique has room for further improvement in improving communication efficiency in collecting information about a vehicle.

  Specifically, in data communication, various data compression techniques for increasing communication efficiency are known. There is differential compression as one of them, and in such differential compression, it is necessary to specify the data size of each of the base value transmitted for the first time and the differential value transmitted for the second time and thereafter.

  However, in collecting information about a vehicle that travels in a situation in which various dynamic factors are intertwined, there are various combinations of information collecting conditions, and it is difficult to easily determine the above data size that changes according to the collecting conditions. Therefore, it is difficult to improve the communication efficiency.

  One aspect of the embodiment is made in view of the above, and an object thereof is to provide a data collection device, a data collection system, and a data collection method that can improve communication efficiency in collecting information about a vehicle. ..

  A data collection device according to an aspect of the embodiment includes a collection unit, a collection condition setting unit, and a calculation unit. The collecting unit collects data regarding the vehicle from an on-vehicle device mounted on each vehicle. The collection condition setting unit sets a condition for compressing collected data. The calculation unit calculates a predicted value of the data size regarding the compression based on the past collection data collected by the collection unit.

  According to one aspect of the embodiment, it is possible to improve communication efficiency in collecting information about a vehicle.

FIG. 1A is a schematic explanatory diagram (part 1) of the data collection method according to the embodiment. FIG. 1B is a schematic explanatory diagram (part 2) of the data collection method according to the embodiment. FIG. 1C is a schematic explanatory diagram (part 3) of the data collection method according to the embodiment. FIG. 1D is a schematic explanatory diagram (Part 4) of the data collection method according to the embodiment. FIG. 1E is a schematic explanatory diagram (5) of the data collection method according to the embodiment. FIG. 1F is a schematic explanatory view (No. 6) of the data collection method according to the embodiment. FIG. 1G is a schematic explanatory view (No. 7) of the data collection method according to the embodiment. FIG. 1H is a schematic explanatory view (No. 8) of the data collection method according to the embodiment. FIG. 2 is a block diagram showing a configuration example of the data collection system according to the embodiment. FIG. 3A is a diagram (part 1) showing a specific example until the guidance information regarding the data size of the differential compression is displayed. FIG. 3B is a diagram (part 2) illustrating a specific example until the guidance information regarding the data size of the differential compression is displayed. FIG. 3C is a diagram (part 3) showing a specific example until the guidance information regarding the data size of the differential compression is displayed. FIG. 3D is a diagram (part 4) illustrating a specific example until the guidance information regarding the data size of the differential compression is displayed. FIG. 4 is a flowchart showing a processing procedure executed by the data collection system according to the embodiment.

  Hereinafter, embodiments of a data collection device, a data collection system, and a data collection method disclosed in the present application will be described in detail with reference to the accompanying drawings. The present invention is not limited to the embodiments described below.

  First, the outline of the data collection method according to the embodiment will be described with reference to FIGS. 1A to 1H. 1A to 1H are schematic explanatory diagrams (No. 1) to (No. 8) of the data collection method according to the embodiment. 1A to 1H will be described taking the data collection system 1 to which the data collection method according to the embodiment is applied as an example.

  As shown in FIG. 1A, a data collection system 1 according to an embodiment includes a data collection device 10 and vehicle-mounted devices 100-1 and 100-2 mounted on vehicles V-1, V-2, V-3, ... , 100-3 ... And the user terminal 200. In the following, the term "vehicle V" is used to refer to the whole vehicle, and the term "vehicle apparatus 100" is used to refer to the in-vehicle device in general.

  The data collection device 10 is configured as a cloud server that provides a cloud service via a network N such as the Internet or a mobile phone network, receives a vehicle data collection request from a data user, and based on the received collection request. , Collects vehicle data from each in-vehicle device 100 and provides it to the data user.

  The vehicle-mounted device 100 is a drive recorder having various sensors such as a camera, an acceleration sensor, a GPS (Global Positioning System) sensor, a storage device, and a microcomputer, and is a vehicle that responds to a collection request received by the data collection device 10. Data is collected from vehicle V.

  Further, the in-vehicle device 100 uploads the collected vehicle data to the data collection device 10 as needed. By using the drive recorder also as the in-vehicle device 100 in this way, the in-vehicle components mounted on the vehicle V can be made efficient. Note that the in-vehicle device 100 and the drive recorder may be separately configured without being shared.

  The user terminal 200 is a terminal used by a data user, and is, for example, a notebook PC (Personal Computer), a desktop PC, a tablet terminal, a PDA (Personal Digital Assistant), a smartphone, glasses-type or clock-type information processing. For example, a wearable device that is a terminal.

  Further, the data user is, for example, a developer who develops an automatic driving technique based on vehicle data provided from the data collection device 10. The data collection device 10 provides such a data user with a user interface (hereinafter referred to as “UI”) screen accessible via the user terminal 200.

  The data user specifies the vehicle data collection condition via the UI screen as shown in FIG. 1A (step S1). Then, the data collection device 10 that has received this delivers the collection conditions to each vehicle V in, for example, a file format (step S2).

  The collection condition includes various parameters regarding collection of vehicle data. The various parameters are, for example, "target vehicle", "data type", "collection trigger condition", "collection period", "presence / absence of differential compression", and the like.

  The "target vehicle" is identification information of the vehicle V to be collected. The “data type” is the type of data to be collected, in other words, the type of data collected from various sensors. As an example, an accelerator opening degree, a brake pressure, a steering angle, SOH (States Of Health), etc. included in CAN (Controller Area Network) information, an image taken by a camera, etc. The “collection trigger condition” is a condition that triggers collection, and is, for example, a case where the vehicle speed exceeds a predetermined speed.

  Further, “presence / absence of differential compression” is a designation item of whether or not to perform differential compression. For example, as shown in FIG. 1C, differential compression is designated as “present” on the UI screen displayed on the user terminal 200. In this case, it is necessary to set the data size of each of the difference compression base value and the difference value.

  As shown in FIG. 1D, the base value is data that is transmitted the first time for each different vehicle data in the differential compression, and the difference value is data that is transmitted the second time and thereafter. When the differential compression is “present”, the data size that needs to be specified is the size of each data buffer in which the base value and the differential value are stored.

  Returning to the description of FIG. 1A. Then, as shown in FIG. 1A, each vehicle-mounted device 100 appropriately uploads the vehicle data collected in each vehicle V to the data collection device 10 (step S3), and the data collection device 10 accumulates this (step S4). .. Then, the data user browses or downloads the vehicle data accumulated in the data collection device 10 through, for example, the above-mentioned UI screen (step S5) and uses it for analysis for development or the like.

  Although not shown in FIG. 1A, the vehicle data uploaded by the in-vehicle apparatus 100 includes actual data and tag data having characteristics as index data used for searching the actual data and grasping the outline.

  The tag data has a much smaller data capacity than the actual data. Therefore, each in-vehicle device 100 always uploads such tag data to the data collection device 10. Then, for example, the data user can browse the tag data via the user terminal 200 and cause the in-vehicle device 100 to upload only the actual data determined to be necessary to the data collection device 10. This can reduce the communication load. It is preferable that the tag data and the actual data that have been uploaded to the data collection device 10 be sequentially deleted from the vehicle-mounted device 100.

  In the following description, the vehicle data uploaded by the vehicle-mounted device 100 to the data collection device 10 is assumed to be actual data.

  By the way, when the data size in the above-mentioned differential compression is improper, as shown in FIG. 1E, when the circled data changes by an unexpected change amount, as shown in the left diagram of FIG. Defects occur. When such an event occurs, it is necessary to re-complement with the base value, as shown in the right diagram of the figure, which increases the amount of data.

  Therefore, in the data collection method according to the embodiment, when the vehicle data collection condition and the “presence” of the differential compression are designated, for example, the data collection in which the designated collection condition is applied to the collected data collected in the past is collected. It was decided to calculate the predicted value of the data size of each of the base value and the difference value under the specified collection condition based on this simulation.

  Further, in the data collection method according to the embodiment, it is decided to provide a UI screen that provides guidance for a data size setting operation based on the calculated predicted value.

Specifically, it is assumed that there is a collection condition including designation of collection at a cycle of 100 msec, and this is applied to past collection data to perform a data collection simulation. Then, as shown in FIG. 1G, it is assumed that a data string (X ₀ , X ₁ , X ₂ , X ₃ , X ₄ , X ₅ , ... X _n ) is obtained.

In the data collection method according to the embodiment, the predicted value of the data size of each of the base value and the difference value under the specified collection condition is calculated based on the simulation result. In the example of FIG. 1G, the maximum value X _max of the data string is calculated as the predicted value of the data size of the base value. Also, the data string of difference column _{(X 1 -X 0, X 2} -X 1, X 3 -X 2, ... X n -X n-1) the maximum value of as the predicted value of the data size of the differential value calculate.

  Then, in the data collection method according to the embodiment, as shown in FIG. 1H, for example, guidance information including the calculated predicted value is displayed on the UI screen of the user terminal 200 to set the data size for the data user. Guidance for operation. As shown in the figure, the predicted value is an average value for all vehicles in the past collected data, or an average value for a specific vehicle type such as “vehicle type A”. Good.

  As a result, the data user can set the data size while checking the guidance information. Further, since the guidance information is based on the collected data in the past, its accuracy can be ensured.

  The calculated predicted value may be automatically entered in the data size input field, instead of being simply presented. Such a specific example will be described later in the description using FIG. 3B.

  As described above, in the data collection method according to the embodiment, when the vehicle data collection condition and the “presence” of the differential compression are designated, for example, the designated collection condition is applied to the collected data collected in the past. A simulation of data collection was executed, and based on this, predicted values of the data sizes of the base value and the difference value under the specified collection conditions were calculated. In addition, based on the calculated predicted value, it is decided to provide a UI screen that guides the setting operation of the data size.

  Therefore, according to the data collection method of the embodiment, it is possible to appropriately assist the data user in the operation of setting the data size in the differential compression. And thereby, the communication efficiency in the information collection regarding the vehicle V can be improved. Hereinafter, a configuration example of the data collection system 1 according to the embodiment will be described more specifically.

  FIG. 2 is a block diagram showing a configuration example of the data collection system 1 according to the embodiment. It should be noted that FIG. 2 shows only the components necessary for explaining the features of the embodiment, and omits the description of general components.

  In other words, each component shown in FIG. 2 is functionally conceptual, and does not necessarily have to be physically configured as shown. For example, the specific form of distribution / integration of each block is not limited to that shown in the figure, and all or part of the block may be functionally or physically distributed / arranged in arbitrary units according to various loads and usage conditions. It can be integrated and configured.

  Further, in the description using FIG. 2, the description of the already described constituent elements may be simplified or omitted.

  As shown in FIG. 2, the data collection system 1 according to the embodiment includes a data collection device 10, an in-vehicle device 100, and a user terminal 200.

  First, the data collection device 10 will be described. The data collection device 10 includes a communication unit 11, a storage unit 12, and a control unit 13.

  The communication unit 11 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 11 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the vehicle-mounted device 100 and the user terminal 200 via the network N.

  The storage unit 12 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disc. In the example of FIG. , And the collection data DB 12b.

  The collection condition information DB 12a stores collection conditions specified by the user terminal 200 and set by a collection condition setting unit 13b described later. In addition, the collection condition information DB 12a includes a record of the collection conditions used for past data collection.

  The collection data DB 12b stores collection data collected from each in-vehicle device 100 by the collecting unit 13f described later. Further, the collection data DB 12b includes the actual results of the collection data collected in the past data collection.

  The control unit 13 is a controller, and various programs stored in a storage device inside the data collection device 10 are stored in a RAM as a work area by, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). It is realized by being executed as. Further, the control unit 13 can be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

  The control unit 13 includes a UI providing unit 13a, a collection condition setting unit 13b, a calculation unit 13c, a guidance generation unit 13d, a distribution unit 13e, and a collection unit 13f, and functions of information processing described below. To achieve or execute an action.

  The UI providing unit 13a generates various UI screens regarding data collection in addition to the collection condition setting screen and provides the UI screen to the user terminal 200 via the communication unit 11. A specific example of the UI screen will be described later with reference to FIGS. 3A and 3B. Also, the UI providing unit 13a provides the UI screen with the guidance information generated by the guidance generating unit 13d, which will be described later.

  The guidance information includes a predicted value of the data size based on a simulation in which the collection condition designated by the data user from the user terminal 200 is applied to the past collection data of the collection data DB 12b.

  The collection condition setting unit 13b receives the collection condition specified by the data user from the user terminal 200 and the presence / absence of differential compression via the communication unit 11. If the differential compression is “present”, the collection condition setting unit 13b accepts this. To the calculation unit 13c. Further, the collection condition setting unit 13b stores the collection condition specified by the data user in the collection condition information DB 12a.

  Further, when the collection condition setting unit 13b receives, for example, a collection condition whose condition has been changed by the data user who receives the guidance information, the collection condition setting unit 13b updates the corresponding collection condition in the collection condition information DB 12a.

  The calculation unit 13c extracts the relevant collection condition accepted by the collection condition setting unit 13b from the collection condition information DB 12a, and applies this to the past collection data of the collection data DB 12b to execute a data collection simulation. Further, the calculation unit 13c calculates the predicted value of the data size in the differential compression, based on the data string obtained as a result of the simulation. Further, the calculation unit 13c notifies the guidance generation unit 13d of the calculated predicted value.

  The guidance generation unit 13d generates guidance information regarding the data size in the differential compression based on the predicted value notified from the calculation unit 13c, and notifies the UI provision unit 13a. For example, the guidance generation unit 13d may calculate the average value of the data size when all the collected data of the past are targeted, or the specific vehicle type of the collected data of the past, as illustrated in FIG. 1H. The guidance information is generated so that the average value of the data size is displayed.

  Here, a specific example in which the data user sets the collection condition and the guidance information regarding the data size of the differential compression is displayed will be described with reference to FIGS. 3A to 3D. 3A to 3D are diagrams (No. 1) to (No. 4) showing specific examples until the guidance information regarding the data size of the differential compression is displayed.

  First, as shown in FIG. 3A, the UI providing unit 13a provides the user terminal 200 with a “collection condition setting screen” as a UI screen. The “collection condition setting screen” has items for which a plurality of collection conditions such as “upload condition” and “collection condition # 1” can be designated.

  Further, the “upload condition” and the “collection condition # 1” have a “trigger block” item capable of designating a conditional expression serving as a trigger for uploading vehicle data and starting or ending collection of vehicle data.

  In such items, “parameter” or “symbol” of the conditional expression can be selected from a drop-down list of GUI widget or the like. The "threshold value" can be specified by direct input, but like the "parameter" or "symbol", it may be specified by a drop-down list or the like.

  As shown in the figure, such a trigger block can be added by pressing the "+" button. Further, when added, the input parts of Boolean operators such as “and” and “or” are displayed, and the logical condition can be set (see the M0 part in the figure). Therefore, it is possible to detect the occurrence of the trigger under the complex condition.

  Further, as shown in the figure, in the "collection condition setting screen", it is possible to specify more detailed conditions for each collection data. For example, "normal" and "meta information" that can be selected with a radio button of a GUI widget correspond to the above-mentioned actual data and tag data. For the "data type", for example, the accelerator opening rate or the like can be selected from a drop-down list or the like.

  Then, as shown in the M1 part of the figure, the presence or absence of differential compression can be designated by a radio button or the like. Here, when "Yes" is designated, for example, the data size input field shown in the M2 part of FIG. For example, when the guidance information shown in FIG. 1H is displayed, the data user can directly input and specify the data size in the M2 part of FIG. 3A while referring to the guidance information.

  Note that the data size may be automatically input instead of being directly input by the data user. Such a case will be described with reference to FIG. 3B. As shown in FIG. 3B, it is assumed that the differential compression is designated as “present” in the M1 part of FIG.

  In such a case, for example, the M3 part in the figure becomes effective. In the M3 part, the simulation of the calculation of the predicted value of the data size related to the difference compression is performed on all past data by using a radio button or the like, or on the arbitrarily specified data of the past collected data. Can be specified.

  Here, when "arbitrary designation" is designated, for example, the M4 part in the figure becomes valid. In the M4 part, arbitrary detailed contents can be designated. For example, in "vehicle type", it is possible to specify a specific vehicle type such as "vehicle type A" or "vehicle type B". It should be noted that the vehicle types may be specified in a composite manner.

  Further, for example, in "collection period (msec)", it is possible to specify a specific period such as "100" or "200". Such a collection cycle corresponds to so-called resolution, and it is possible to calculate the predicted value of the data size according to the different resolution by a simulation in which the collection cycle is different.

As an example, consider the case where "200" is specified. In such a case, as a result of performing the simulation, as shown in FIG. 3C, the data string (X ₀ , X ₂ , X ₄ , X ₆ , X ₈ , X) is compared with the data string of 100 msec cycle shown in FIG. 1G. ₁₀ ... _Xn ) is obtained.

Then, in such a case, the calculation unit 13c calculates X _max , which is the maximum value of the data string, as a predicted value of the data size of the base value. Also, the data string of difference column _{(X 2 -X 0, X 4} -X 2, X 6 -X 4, ... X n -X n-2) the maximum value of as the predicted value of the data size of the differential value calculate.

Similarly, considering the case where "500" is specified, as a result of the simulation being executed, as shown in FIG. 3D, the data string (X ₀ , X ₅ , X ₁₀ , X ₁₅ , X ₂₀ , X ₂₅ , ... X _n ) are obtained.

Then, in such a case, the calculation unit 13c calculates X _max , which is the maximum value of the data string, as a predicted value of the data size of the base value. Also, the data string of difference column _{(X 5 -X 0, X 10} -X 5, X 15 -X 10, ... X n -X n-5) the maximum value of as the predicted value of the data size of the differential value calculate.

  By the way, the above description predicts the minimum data size that the difference value does not overflow by simulation, but in order to further improve communication efficiency, the data transmission capacity itself using such data size is calculated. It is more effective to perform a simulation.

  Such an example will be described. In the case of data transmission by differential compression, “data size of base value> data size of difference value” as described above. Therefore, as the number of times the base value is transmitted increases, the total transmission data capacity increases.

  Further, if the setting of the data size of the difference value is made small, the total transmission data capacity of the difference value can be made small, but the possibility of the above-mentioned overflow also increases. That is, when an overflow occurs, it is necessary to complement the base value (see FIG. 1F), which tends to increase the number of times the base value is transmitted.

  Therefore, it is preferable to set the data size of the difference value in a well-balanced manner. Specifically, the data size of the difference value is set to such an extent that overflow does not occur so much, that is, the increase in the data transmission capacity due to the transmission of the base value due to overflow can be well absorbed by reducing the data size of the difference value. Can be said to be preferable.

  Therefore, it is advisable to temporarily set the data size of the difference value, and in that state, perform a simulation of actual data transmission using past collected data to calculate the total transmission data capacity. That is, a simulation of converting the past collection data into transmission data according to the provisional data size and provisionally transmitting the transmission data is performed to predict the transmission data capacity. Then, such a simulation may be performed a plurality of times with the data sizes of some temporary difference values, and the data size that results in the smallest calculated transmission data capacity may be applied to the actual data transmission.

Specifically, when applied to the example shown in FIG. 3D, for example, calculation unit 13c, the data string of difference column _{(X 5 -X 0, X 10} -X 5, X 15 -X 10, ... X n The data size (M bits) capable of setting the maximum value of −X _n−5 ) is executed as the first simulation. Further, the calculation unit 13c executes a data size smaller by 1 bit than this as the second simulation, and a data size smaller by m bits as the (m-1) th simulation.

  Then, the calculation unit 13c calculates, as the optimum predicted value, the data size when the total transmission data capacity is the smallest among the results of the first to (m-1) th simulations.

It should be noted that the number of simulations may be determined as the predetermined number of times, with about half of the number of bits of the data size in which the maximum setting value (maximum difference value) of the simulation is included. Further, for example, the difference row _{(X 5 -X 0, X 10} -X 5, X 15 -X 10, ... X n -X n-5) of or may be determined based on the distribution. In this case, as an example, a determination method may be considered in which the simulation is executed from the one with a large difference to the data size with a difference value corresponding to the upper 3/4.

  Returning to the description of FIG. 3B. Further, in the M4 part of the figure, for example, "driving characteristics" can be designated. Here, for example, when "rough" is designated, past collected data whose driving characteristics are estimated to be rough are to be simulated. In addition, for example, when "gentle" is designated, past collected data whose driving characteristics are estimated to be calm are the targets of the simulation. Note that these may be designated in a composite manner.

  Such driving characteristics can be judged from indexes such as whether or not the accelerator opening, the brake pressure, and the steering angle change abruptly.

  Based on such designations in the M3 and M4 sections, past collected data to be simulated is narrowed down. Then, for example, by pressing the “automatic input” button M5, a simulation of data collection in which the collection condition specified in the “collection condition setting screen” of FIG. 3A is applied to the narrowed collection data is executed. It

  Then, as a result, the predicted value calculated by the calculation unit 13c is automatically input in the data size input field of the M2 part. The data user may use the automatically input predicted value as the set value as it is, or may change the predicted value to use the set value. The set value is determined, for example, by pressing a “decision” button (not shown) in FIG. 3A.

  Note that, here, the example in which the predicted value calculated by the calculation unit 13c is automatically input to the data size input field of the M2 part by pressing the “automatic input” button M5 has been described. The predicted value calculated by 13c may be automatically input to the M2 section as it is without using the "automatic input" button M5 or the like.

  Further, the predicted value calculated by the calculation unit 13c may be automatically set in the collection condition information DB 12a by the collection condition setting unit 13b and automatically distributed.

  Returning to the description of FIG. 2, the distribution unit 13e will be described next. The distribution unit 13e distributes the determined collection conditions stored in the collection condition information DB 12a to the target vehicle V, for example, in a file format via the communication unit 11. The collection unit 13f collects vehicle data uploaded from the vehicle-mounted apparatus 100 via the communication unit 11 and accumulates the collected vehicle data in the collection data DB 12b.

  Next, the in-vehicle apparatus 100 will be described. The in-vehicle device 100 includes a communication unit 101, a storage unit 102, and a control unit 103. Further, as described above, the vehicle-mounted device 100 is connected to the various sensors 150 such as a camera, an acceleration sensor, and a GPS sensor.

  Like the communication unit 11, the communication unit 101 is realized by, for example, a NIC or the like. The communication unit 101 is wirelessly connected to the network N, and transmits and receives information to and from the data collection device 10 via the network N. The communication unit 101 also receives output data from the various sensors 150.

  Like the storage unit 12, the storage unit 102 is realized by, for example, a semiconductor memory device such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. In the example of FIG. 2, the collection condition information 102a and the vehicle are stored. The data information 102b is stored.

  The collection condition information 102a is information including the collection conditions distributed from the data collection device 10. The vehicle data information 102b is information including vehicle data collected by the collecting unit 103c described later.

  Like the control unit 13, the control unit 103 is a controller, and is realized by, for example, a CPU, an MPU, or the like executing various programs stored in a storage device inside the vehicle-mounted apparatus 100 using a RAM as a work area. To be done. Further, the control unit 103 can be realized by, for example, an integrated circuit such as an ASIC or FPGA.

  The control unit 103 includes an acquisition unit 103a, a detection unit 103b, a collection unit 103c, and an upload unit 103d, and realizes or executes the information processing function and operation described below.

  The acquisition unit 103a acquires the collection condition distributed from the data collection device 10 and stores it in the collection condition information 102a. The detection unit 103b monitors the output data from the various sensors 150 and detects the occurrence of an event that triggers in the collection condition.

  For example, the detection unit 103b causes the collection unit 103c to collect the vehicle data when detecting the occurrence of an event that triggers collection of the vehicle data under the collection condition. Further, for example, the detection unit 103b causes the upload unit 103d to upload the vehicle data when detecting the occurrence of an event that triggers uploading of the vehicle data to the data collection device 10 under the collection condition.

  The collection unit 103c collects the vehicle data based on the output data of the various sensors 150 and stores the vehicle data in the vehicle data information 102b when the detection unit 103b detects the occurrence of the trigger for collecting the vehicle data. Further, the collection unit 103c stops the collection of vehicle data when the detection unit 103b detects the occurrence of the trigger for stopping the collection of vehicle data.

  The upload unit 103d uploads the vehicle data stored in the vehicle data information 102b to the data collection device 10 when the detection unit 103b detects the occurrence of the trigger for uploading the vehicle data.

  Next, a processing procedure executed by the data collection system 1 according to the embodiment will be described with reference to FIG. FIG. 5 is a flowchart showing a processing procedure executed by the data collection system 1 according to the embodiment.

  First, the data user specifies collection conditions from the user terminal 200 (step S101). Then, when there is a designation regarding differential compression (step S102, Yes), the calculation unit 13c of the data collection device 10 executes a simulation in which the designated collection condition is applied to past collection data (step S103).

  Then, the calculation unit 13c calculates the predicted value of the data size regarding the differential compression based on the simulation result (step S104). Then, the guidance generating unit 13d generates guidance information based on the predicted value, and the UI providing unit 13a inputs or automatically inputs the data size based on the guidance information (step S105).

  If there is no designation regarding differential compression in step S102 (No in step S102), the process proceeds to step S106.

  Then, it is determined whether or not the collection condition is determined (step S106). When the collection condition is determined (step S106, Yes), the distribution unit 13e distributes the collection condition to each in-vehicle device 100 (step S107). Then, the collection unit 13f collects vehicle data based on the distributed collection conditions (step S108).

  When the collection condition is not determined (step S106, No), the process from step S101 is repeated.

  In the above-described embodiment, the case where the compression method is differential compression has been described as an example, but the compression method is not limited. Therefore, the present embodiment can be applied to the case of designating the data size related to the compression method other than the differential compression.

  As described above, the data collection device 10 according to the embodiment includes the collection unit 13f, the collection condition setting unit 13b, and the calculation unit 13c. The collection unit 13f collects data regarding the vehicle V from the vehicle-mounted device 100 mounted on each vehicle V. The collection condition setting unit 13b sets a condition for compressing collected data. The calculation unit 13c calculates the predicted value of the data size regarding the compression based on the past collection data collected by the collection unit 13f.

  Therefore, the data collection device 10 according to the embodiment can improve communication efficiency in collecting information about the vehicle V.

  Further, the collection condition setting unit 13b sets a collection condition in response to a designation operation from a data user (corresponding to an example of a "user"), and the data collection device 10 according to the embodiment has a UI. The providing unit 13a (corresponding to an example of a "providing unit") is further included. The UI providing unit 13a provides a UI for guiding the data size to the data user based on the predicted value calculated by the calculating unit 13c.

  Therefore, according to the data collection device 10 according to the embodiment, it is possible to improve the operability regarding the designation of the data size.

  Further, the collection condition setting unit 13b sets the data size regarding compression based on the predicted value calculated by the calculation unit 13c.

  Therefore, according to the data collection device 10 according to the embodiment, the predicted value calculated by the calculation unit 13c can be automatically set and then automatically distributed to the in-vehicle device 100.

  Further, the calculation unit 13c executes a simulation of data collection in which the collection condition set by the collection condition setting unit 13b is applied to the past collection data, and calculates a predicted value based on the data obtained as a result of the simulation. To do.

  Therefore, according to the data collection device 10 according to the embodiment, it is possible to calculate a highly accurate predicted value based on the past results of data collection.

  In addition, the calculation unit 13c executes a simulation of converting the past collection data into transmission data and temporarily transmitting the transmission data according to the provisional data size, and predicts the transmission data capacity.

  Therefore, according to the data collection device 10 according to the embodiment, it is possible to improve the accuracy of improving communication efficiency by predicting not only the data size of the difference value but also the transmission data capacity itself.

  Further, the calculation unit 13c executes a plurality of simulations with a plurality of temporary data sizes.

  Therefore, according to the data collection device 10 according to the embodiment, the data size of the difference value is set to the extent that the overflow does not occur so much, that is, the increase in the data transmission capacity due to the transmission of the base value due to the overflow. It can contribute to setting a good balance so that it can be absorbed well by reduction.

  In addition, the calculation unit 13c sets the provisional data size when the transmission data capacity is the minimum among the execution results of the plurality of simulations as the optimum predicted value.

  Therefore, according to the data collection device 10 according to the embodiment, it is possible to optimize the predicted value based on the execution results of the plurality of simulations.

  Further, the UI providing unit 13a provides a UI capable of designating a parameter for extracting past collection data used in the simulation.

  Therefore, according to the data collection device 10 of the embodiment, it is possible to specify a more appropriate data size according to the parameter.

  Further, the UI providing unit 13a provides a UI that can specify at least the vehicle type of the vehicle V, the data resolution, and the driving characteristics of the vehicle V as parameters.

  Therefore, according to the data collection device 10 according to the embodiment, it is possible to specify a more appropriate data size according to at least the vehicle type of the vehicle V, the data resolution, and the driving characteristics of the vehicle V.

  The compression is differential compression.

  Therefore, according to the data collection device 10 according to the embodiment, it is possible to appropriately set the data size of the base value and the difference value when the differential compression is used as the compression method, and improve the communication efficiency in the information collection regarding the vehicle V. You can

  In the above-described embodiment, the data user is the developer of the autonomous driving technology or the like, but it is an example of the user, and is, for example, a corporate user such as a service provider or a general individual user. Good.

  Further effects and modifications can be easily derived by those skilled in the art. As such, the broader aspects of the present invention are not limited to the specific details and representative embodiments shown and described above. Accordingly, various modifications may be made without departing from the spirit or scope of the general inventive concept defined by the appended claims and their equivalents.

1 data collection system 10 data collection device 12a collection condition information DB
12b Collected data DB
13a UI provision section 13b Collection condition setting section 13c Calculation section 13d Guidance generation section 13e Delivery section 13f Collection section 100 In-vehicle device 102a Collection condition information 102b Vehicle data information 103a Acquisition section 103b Detection section 103c Collection section 103d Upload section 150 Various sensors 200 use Person terminal V vehicle

Claims (12)

A collection unit that collects vehicle-related data from an in-vehicle device mounted on each vehicle,
A collection condition setting section that sets the conditions for collecting data compression,
And a calculator that calculates a predicted value of the data size regarding the compression based on the past collected data collected by the collector. The collection condition setting unit sets a collection condition in response to a designation operation from a user,
The data collection device according to claim 1, further comprising: a providing unit that provides a user interface that provides a user with a data size guidance based on the predicted value calculated by the calculation unit. The collection condition setting unit,
The data collection apparatus according to claim 2, wherein the data size regarding the compression is set based on the predicted value calculated by the calculation unit. The calculation unit
A simulation of data collection in which a collection condition set by the collection condition setting unit is applied to past collection data, and a predicted value is calculated based on the data obtained as a result of the simulation. Item 2. The data collection device according to item 2 or 3. The calculation unit
The data collection device according to claim 2, 3 or 4, wherein a simulation of converting past collection data into transmission data according to the provisional data size and performing provisional transmission is performed to predict the transmission data capacity. The calculation unit
The data acquisition apparatus according to claim 5, wherein a plurality of simulations are executed with a plurality of temporary data sizes. The calculation unit
The data collection device according to claim 6, wherein a provisional data size when the transmission data capacity is the smallest among the execution results of the plurality of simulations is set as the optimum predicted value. The providing unit is
The data collection device according to claim 4, further comprising: a user interface capable of designating a parameter for extracting past collection data used in the simulation. The providing unit is
The data collection device according to claim 8, wherein a user interface capable of designating at least a vehicle type of the vehicle, a data resolution, and a driving characteristic of the vehicle is provided as a parameter. The data compression apparatus according to claim 1, wherein the compression is differential compression. A data collection device according to any one of claims 1 to 10,
The in-vehicle device,
A data collection system comprising: a terminal device used by a user. A collection process for collecting vehicle-related data from an in-vehicle device mounted on each vehicle,
A collection condition setting process that sets the conditions for collecting data compression,
And a calculation step of calculating a predicted value of the data size regarding the compression based on the past collection data collected by the collection step.

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