Detecting device, detecting system, detecting method, and detecting program

Abstract

This detecting device comprises: a first acquiring unit for acquiring, from a vehicle, vehicle information that is information including identification information of the vehicle and that relates to the vehicle; a second acquiring unit for acquiring collected results of the vehicle information obtained by the first acquiring unit; a third acquiring unit for acquiring an operating plan for the vehicle corresponding to the identification information; and a detecting unit for detecting an abnormality relating to the vehicle on the basis of the collected results and the operating plan.

Description

DETECTION DEVICE, DETECTION SYSTEM, DETECTION METHOD, AND DETECTION PROGRAM

[0001] This application claims priority from Japanese Patent Application No. 2022-163477, filed October 11, 2022, the disclosure of which is incorporated herein by reference in its entirety.

[0002] Japanese Patent Laid-Open Publication No. 2008-216113 (Patent Document 1) discloses the following defect information collection system: That is, in this defect information collection system, vehicle defect information is collected at a center, the vehicle has a vehicle driving information acquisition means for acquiring vehicle driving information, which is data related to the vehicle's driving conditions, a vehicle driving information transmission means for transmitting the vehicle driving information to the center, a voice communication means for enabling a call between the driver of the vehicle and an operator at the center, and a control means for initiating, based on an instruction from the driver, transmission of the vehicle driving information to the center by the vehicle driving information transmission means and a voice communication with the operator by the voice communication means, and the center has a vehicle driving information receiving means for receiving the vehicle driving information transmitted from the vehicle, a voice communication means for enabling a call between the driver of the vehicle and the operator at the center, and a defect information storage means for storing the received vehicle driving information in association with the content of the defect notified by the driver of the vehicle by the voice communication means.

[0003] Furthermore, Japanese Patent Laid-Open Publication No. 2014-081390 (Patent Document 2) discloses the following vehicle information storage device. In other words, the vehicle information storage device comprises a state information acquisition means for acquiring state information of the vehicle, a temporary storage means for temporarily storing the state information acquired by the state information acquisition means, a specified table storage means for storing a specified table that specifies information identification criteria for identifying verification information to be used to verify the cause of the malfunction from the state information stored in the temporary storage means, and a control means that identifies verification information to be used to verify the cause of the malfunction from the state information stored in the temporary storage means based on the information identification criteria specified in the specified table, and stores the identified verification information in a specified storage medium, wherein the specification table specifies the detection of a malfunction by a user and the corresponding type and range of the verification information as the information identification criteria, and when a malfunction is detected by a user as specified in the specification table, the control means identifies verification information of the corresponding type specified in the specification table within the range specified in the specification table, and stores the verification information of the identified type and range in the specified storage medium.

[0004] JP 2008-216113 A JP 2014-081390 A

[0005] The detection device of the present disclosure includes a first acquisition unit that acquires vehicle information related to the vehicle from the vehicle, the vehicle information including identification information of the vehicle, a second acquisition unit that acquires a collection history of the vehicle information by the first acquisition unit, a third acquisition unit that acquires an operation plan for the vehicle corresponding to the identification information, and a detection unit that detects an abnormality related to the vehicle based on the collection history and the operation plan.

[0006] One aspect of the present disclosure can be realized not only as a detection device including such a characteristic processing unit, but also as a semiconductor integrated circuit that realizes part or all of the detection device.

[0007] FIG. 1 is a diagram illustrating a configuration of a communication system according to an embodiment of the present disclosure. FIG. 2 is a diagram illustrating a configuration of a detection device according to an embodiment of the present disclosure. FIG. 3 is a diagram illustrating an example of information used by a detection device according to an embodiment of the present disclosure for anomaly detection. FIG. 4 is a diagram illustrating an example of configuration information and a data collection estimate used by a detection device according to an embodiment of the present disclosure for anomaly detection. FIG. 5 is a diagram illustrating an example of a data collection plan table used by a detection device according to an embodiment of the present disclosure for anomaly detection. FIG. 6 is a diagram illustrating an example of data collection results used by a detection device according to an embodiment of the present disclosure for anomaly detection. FIG. 7 is a diagram illustrating an example of types of anomalies detected by a detection device according to an embodiment of the present disclosure. FIG. 8 is a diagram illustrating an example of data collection results used by a detection device according to a first variation of the present disclosure for anomaly detection. FIG. 9 is a diagram illustrating an example of transmission location information used by a detection device according to a second variation of the present disclosure for anomaly detection. FIG. 10 is a diagram illustrating an example of list information created by a detection device according to a third variation of the present disclosure. FIG. 11 is a diagram illustrating a configuration of a detection device according to a fourth variation of the present disclosure. FIG. 12 is a diagram illustrating an example of a setting screen displayed by a detection device according to a fourth variation of the present disclosure. Fig. 13 is a diagram showing an example of a monitoring screen displayed by a fourth variation of a detection device according to an embodiment of the present disclosure. Fig. 14 is a flowchart defining an operational procedure when a detection device according to an embodiment of the present disclosure detects an abnormality in a vehicle. Fig. 15 is a flowchart defining an operational procedure when a detection device according to an embodiment of the present disclosure detects an abnormality in a vehicle. Fig. 16 is a flowchart defining an operational procedure when a third variation of a detection device according to an embodiment of the present disclosure creates list information.

[0008] Conventionally, techniques have been developed for detecting vehicle defects.

[0009] [Problem to be Solved by the Present Disclosure] Understanding abnormalities in a vehicle from a perspective different from the techniques described in Patent Documents 1 and 2 is useful in vehicle management.

[0010] The present disclosure has been made to solve the above-mentioned problems, and its purpose is to provide a detection device, a detection system, a detection method, and a detection program that can easily detect abnormalities related to a vehicle.

[0011] Effect of the Present Disclosure According to the present disclosure, an abnormality related to a vehicle can be easily detected.

[0012] [Description of Embodiments of the Present Disclosure] First, the contents of embodiments of the present disclosure will be listed and described. (1) A detection device according to an embodiment of the present disclosure includes a first acquisition unit that acquires vehicle information related to a vehicle from the vehicle, the vehicle information including identification information of the vehicle, a second acquisition unit that acquires a collection history of the vehicle information by the first acquisition unit, a third acquisition unit that acquires an operation plan for the vehicle corresponding to the identification information, and a detection unit that detects an abnormality related to the vehicle based on the collection history and the operation plan.

[0013] Unlike devices installed in factories, vehicles have periods when they do not transmit data even when in normal operation. Focusing on this point, a configuration that detects abnormalities based on the vehicle information collection record and the vehicle operation plan makes it possible to easily detect abnormalities related to vehicle data transmission using the data collection record from the vehicle. Therefore, abnormalities related to the vehicle can be easily identified.

[0014] (2) In the above (1), the detection device may further include a fourth acquisition unit that acquires setting information indicating the setting contents of the vehicle regarding the transmission of the vehicle information, and the detection unit may detect an abnormality regarding the vehicle based on the setting information, the collection history, and the operation plan.

[0015] In this way, by configuring the system to detect abnormalities using the settings regarding the transmission of vehicle information by the vehicle, it is possible to grasp the transmission status in more detail, regardless of whether or not vehicle information is being transmitted, and to more accurately detect abnormalities in the vehicle.

[0016] (3) In the above (2), the setting information may include at least one of a transmission cycle of the vehicle information by the vehicle and a type of the vehicle information transmitted by the vehicle.

[0017] In this way, by using the transmission cycle of vehicle information for abnormality determination, it is possible to easily determine abnormalities in the transmission of vehicle information based on the number of times the information is received. Also, by using the type of vehicle information for abnormality determination, it is possible to determine whether the amount of data is low because communication between the vehicle and the detection device is unstable, or because vehicle information of a specific data type has not been uploaded, etc.

[0018] (4) In (2) or (3) above, the setting information may include the type of vehicle information transmitted by the vehicle, and the detection device may further include a fifth acquisition unit that acquires transmission location information indicating the correspondence between the type and the transmission location of the vehicle information in the vehicle, and when the detection unit detects the abnormality, it may identify the location where the abnormality occurred based on the collection history, the type included in the setting information, and the transmission location information.

[0019] In this way, by using the type of vehicle information to determine an abnormality, it is possible to determine whether the amount of data is small because communication between the vehicle and the detection device is unstable, or whether the amount of data is small because vehicle information of a specific data type has not been uploaded, etc. Furthermore, since it is possible to grasp the collection history for each type of vehicle information, it is possible to identify the location of the abnormality in the vehicle and analyze the abnormality in more detail.

[0020] (5) In any of (1) to (4) above, the operation plan may be divided into a plurality of time intervals, and the detection unit may determine whether or not a deviation has occurred between the operation plan and the collected actual data for each time interval, and detect the abnormality based on the frequency of occurrence of the deviation in the plurality of time intervals.

[0021] This configuration makes it possible to analyze vehicle abnormalities in more detail over time, and to reduce the possibility of false detection of abnormalities due to temporary vehicle driving conditions, etc.

[0022] (6) In any of (1) to (5) above, the detection device may further include an analysis unit that calculates an index value of the deviation between the operation plan and the collected actual results, and creates a list of vehicles that require attention to the abnormality based on the index value.

[0023] With this configuration, for example, by sorting each vehicle by index value, it is possible to easily identify groups of vehicles in which similar abnormalities have occurred.

[0024] (7) In any of (2) to (4) above, the setting information may include the type of vehicle information transmitted by the vehicle, and the detection unit may perform processing to display on a screen content based on the type of vehicle information in which the abnormality occurred.

[0025] With this configuration, even if a malfunction occurs in a vehicle's retrofit device that transmits vehicle information, even an uninformed user can easily understand the abnormality in the device, which allows for efficient isolation of the cause of the malfunction and reduces the burden of, for example, recalling the retrofit device.

[0026] (8) A detection system according to an embodiment of the present disclosure includes an on-board device mounted on a vehicle and a detection device, wherein the on-board device transmits vehicle information relating to the vehicle, including identification information of the vehicle, to the detection device, and the detection device detects an abnormality relating to the vehicle based on the detection device's collection history of the vehicle information and the vehicle operation plan corresponding to the identification information.

[0027] Unlike devices installed in factories, vehicles have periods when they do not transmit data even when in normal operation. Focusing on this point, a configuration that detects abnormalities based on the vehicle information collection record and the vehicle operation plan makes it possible to easily detect abnormalities related to vehicle data transmission using the data collection record from the vehicle. Therefore, abnormalities related to the vehicle can be easily identified.

[0028] (9) A detection method according to an embodiment of the present disclosure is a detection method in a detection device, and includes the steps of acquiring vehicle information about the vehicle from the vehicle, the vehicle information including identification information of the vehicle, acquiring a collection history of the vehicle information by the detection device, acquiring an operation plan for the vehicle corresponding to the identification information, and detecting an abnormality related to the vehicle based on the collection history and the operation plan.

[0029] Unlike devices installed in factories, vehicles have periods when they do not transmit data even when in normal operation. Focusing on this point, a configuration that detects abnormalities based on the vehicle information collection record and the vehicle operation plan makes it possible to easily detect abnormalities related to vehicle data transmission using the data collection record from the vehicle. Therefore, abnormalities related to the vehicle can be easily identified.

[0030] (10) A detection program according to an embodiment of the present disclosure is a detection program used in a detection device, and causes a computer to function as a first acquisition unit that acquires vehicle information related to a vehicle from the vehicle, the vehicle information including identification information of the vehicle, a second acquisition unit that acquires the collection history of the vehicle information by the first acquisition unit, a third acquisition unit that acquires an operation plan for the vehicle corresponding to the identification information, and a detection unit that detects abnormalities related to the vehicle based on the collection history and the operation plan.

[0031] Unlike devices installed in factories, vehicles have periods when they do not transmit data even when in normal operation. Focusing on this point, a configuration that detects abnormalities based on the vehicle information collection record and the vehicle operation plan makes it possible to easily detect abnormalities related to vehicle data transmission using the data collection record from the vehicle. Therefore, abnormalities related to the vehicle can be easily identified.

[0032] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the drawings, identical or corresponding parts are designated by the same reference numerals, and their description will not be repeated. Furthermore, at least some of the embodiments described below may be combined in any manner.

[0033] 1 is a diagram illustrating a configuration of a communication system according to an embodiment of the present disclosure. Referring to FIG. 1 , a communication system 301 includes a detection device 101 and one or more in-vehicle devices 202. The detection device 101 and each in-vehicle device 202 can transmit and receive information via an external network 161 such as the Internet. The in-vehicle device 202 is mounted on a vehicle 10.

[0034] The detection device 101 is used, for example, by a business operator that manages the operation of the vehicle 10 or an individual (hereinafter collectively referred to as a user).

[0035] The detection device 101 collects vehicle information related to the corresponding vehicle 10 from one or more in-vehicle devices 202. Then, the detection device 101 detects an abnormality related to the vehicle 10, such as a malfunction of the vehicle 10, based on the collected vehicle information.

[0036] The in-vehicle device 202 transmits vehicle information related to the vehicle 10, which includes identification information of the vehicle 10, to the detection device 101. Specifically, for example, each in-vehicle device 202 receives position information of the corresponding vehicle 10 from a GPS (Global Positioning System) receiver (not shown) or the like in the vehicle 10, and transmits the received vehicle information including the position information, the ID of the vehicle 10, and the data type to the detection device 101 via the external network 161. Note that the vehicle information is not limited to position information, and may include, for example, measurement results of sensors mounted on the vehicle 10, or driving control information such as braking operation in the vehicle 10.

[0037] 2 is a diagram illustrating a configuration of a detection device according to an embodiment of the present disclosure. Referring to FIG. 2, the detection device 101 includes a communication unit 1, a detection unit 2, an analysis unit 3, and a storage unit 4. The communication unit 1, the detection unit 2, and the analysis unit 3 are partly or entirely realized by a processing circuit including one or more processors. The storage unit 4 is, for example, a non-volatile memory included in the processing circuit.

[0038] The communication unit 1 transmits and receives information to and from the in-vehicle device 202 via the external network 161. The communication unit 1 stores the information received from the in-vehicle device 202 in the storage unit 4.

[0039] The communication unit 1, as a first acquisition unit, acquires vehicle information from the vehicle 10. More specifically, the communication unit 1 receives the vehicle information from the in-vehicle device 202, creates a communication log including the received vehicle information and the time when the vehicle information was received, and stores the communication log in the storage unit 4.

[0040] FIG. 3 is a diagram illustrating an example of information used for anomaly detection by the detection device according to the embodiment of the present disclosure.

[0041] 3 , detection unit 2 serves as a third acquisition unit and acquires an operation plan for vehicle 10 corresponding to the identification information included in the vehicle information acquired by communication unit 1. More specifically, detection unit 2 acquires, for example, an operation plan table TB1 indicating an operation plan for each vehicle 10 from storage unit 4. Operation plan table TB1 is registered in advance in storage unit 4 by, for example, a user. Note that, when a clear operation plan is not formulated, operation plan table TB1 may be created based on, for example, acquired records of the on and off states of the ignition power of vehicle 10.

[0042] The operation plan is divided into a plurality of time intervals. In this example, the length of each time interval is four hours. In the operation plan table TB1 for a certain day "X" shown in FIG. 3 , the operation plans for the vehicles 10 with vehicle IDs "A" and "B" are "operating" from midnight to 12:00, "off" from 12:00 to 16:00, and "operating" from 16:00 to 20:00. The operation plan for the vehicle 10 with vehicle ID "C" is "operating" from midnight to 16:00, and "off" from 16:00 to 20:00.

[0043] The analysis unit 3 functions as a second acquisition unit and acquires the collection record of the vehicle information by the first acquisition unit. More specifically, for example, the analysis unit 3 periodically or irregularly creates a collection record table TB2 indicating the collection record of the vehicle information for each vehicle 10 based on the communication log of the vehicle information stored in the storage unit 4, and stores the created table in the storage unit 4.

[0044] The collection record is divided into multiple time intervals. In this example, the length of each time interval is four hours, similar to the operation plan. In the collection record table TB2 for a certain day "X" shown in FIG. 3, the collection record of the vehicle 10 with vehicle ID "A" is "Yes" from midnight to 12:00 and "No" from 12:00 to 20:00. The collection record of the vehicle 10 with vehicle ID "B" is "Yes" from midnight to 12:00, "No" from 12:00 to 16:00, and "Yes" from 16:00 to 20:00. The collection record of the vehicle 10 with vehicle ID "C" is "Yes" from midnight to 16:00 and "No" from 16:00 to 20:00.

[0045] The detection unit 2 detects an abnormality related to the vehicle 10 based on the collection record and the operation plan. Specifically, in the operation plan table TB1, the operation plan for vehicle ID "A" is "operating" from 4:00 PM to 8:00 PM, but in the collection record table TB2, the collection record for vehicle ID "A" is "none" from 4:00 PM to 8:00 PM. Therefore, the detection unit 2 determines that an abnormality has occurred in the vehicle 10 with the vehicle ID "A" because there is a time period during which vehicle information has not been received from the vehicle 10 that is in operation.

[0046] The detection unit 2 outputs the abnormality detection result. For example, the detection unit 2 stores the abnormality detection result in the storage unit 4 or notifies the abnormality detection result to a user.

[0047] [Another Example of Anomaly Detection] FIG. 4 is a diagram illustrating an example of setting information and data collection estimates used for anomaly detection by a detection device according to an embodiment of the present disclosure.

[0048] 4 , analysis unit 3, as a fourth acquisition unit, acquires setting information indicating settings of vehicle 10 related to the transmission of vehicle information. For example, the setting information includes a transmission cycle of vehicle information by vehicle 10 and a type of vehicle information transmitted by vehicle 10.

[0049] More specifically, the analysis unit 3 acquires the settings for the upload period, data type, and sampling period for each vehicle 10 from the storage unit 4, and calculates an estimate E of the amount of data per unit time of vehicle information to be transmitted from the vehicle 10 based on the acquired upload period and sampling period, and the predetermined amount of data for one sample of vehicle information. The analysis unit 3 then creates a transmission data table TB10 including the settings and the estimate E for each vehicle 10, and stores the transmission data table TB10 in the storage unit 4. Note that the analysis unit 3 is not limited to calculating the estimate E, and the amount of data per unit time may be registered in the storage unit 4 as setting information.

[0050] In the transmission data table TB10 shown in FIG. 4 , the vehicle 10 with the vehicle ID “A” has an upload period of 10 times per hour, uploads vehicle information of data types “ID1” and “ID2”, has a sampling period, i.e., a vehicle information generation period, of once every 10 seconds, and has an estimated value E of 10 megabytes per hour. The vehicle 10 with the vehicle ID “B” has an upload period of 10 times per hour, uploads vehicle information of data types “ID1” and “ID3”, has a sampling period of once every 10 seconds, and has an estimated value E of 15 megabytes per hour. The vehicle 10 with the vehicle ID “C” has an upload period of 20 times per hour, uploads vehicle information of data types “ID3” and “ID4”, has a sampling period of once every 5 seconds, and has an estimated value E of 20 megabytes per hour.

[0051] FIG. 5 is a diagram illustrating an example of a data collection schedule used for anomaly detection by a detection device according to an embodiment of the present disclosure.

[0052] Referring to FIG. 5, analysis unit 3 creates a collection plan for vehicle information from vehicle 10 based on the setting information and the operation plan.

[0053] More specifically, the analysis unit 3 creates a data collection plan table TB11 that shows a vehicle information collection plan for each vehicle 10 based on the transmission data table TB10 and operation plan table TB1 stored in the memory unit 4, and stores the data collection plan table TB11 in the memory unit 4.

[0054] The data collection plan table TB11 shown in FIG. 5 indicates the "vehicle information upload period / data type / amount of data to be uploaded" for each time interval.

[0055] In the data collection plan table TB11 for a certain day "X," the collection plan for vehicle 10 with vehicle ID "A" is "40 times / 2 items / 40 megabytes" from midnight to 12:00, "0 times / 0 items / 0 megabytes" from 12:00 to 16:00, and "40 times / 2 items / 40 megabytes" from 16:00 to 20:00. The collection plan for vehicle 10 with vehicle ID "B" is "40 times / 2 items / 60 megabytes" from midnight to 12:00, "0 times / 0 items / 0 megabytes" from 12:00 to 16:00, and "40 times / 2 items / 60 megabytes" from 16:00 to 20:00. The collection plan for vehicle 10 with vehicle ID "C" is "80 times / 2 items / 80 megabytes" from midnight to 16:00, and "0 times / 0 items / 0 megabytes" from 16:00 to 20:00.

[0056] FIG. 6 is a diagram illustrating an example of data collection results used for anomaly detection by a detection device according to an embodiment of the present disclosure.

[0057] 6 , analysis unit 3 functions as a second acquisition unit and acquires the collection record of vehicle information by the first acquisition unit. More specifically, analysis unit 3 periodically or irregularly creates a collection record table TB12 indicating the collection record of vehicle information for each vehicle 10 based on the communication log of vehicle information stored in storage unit 4, and stores the created collection record table in storage unit 4.

[0058] The collection record table TB12 shown in FIG. 6 indicates the "vehicle information upload period / data type / amount of data uploaded" for each time interval, similar to the data collection plan table TB11 shown in FIG.

[0059] In the collection record table TB12 for a certain day "X," the collection record of a vehicle 10 with a vehicle ID of "A" is "40 times / 1 item / 30 megabytes" from midnight to 12 noon, and "0 times / 0 items / 0 megabytes" from 12 noon to 8 p.m. The collection record of a vehicle 10 with a vehicle ID of "B" is "20 times / 2 items / 30 megabytes" from midnight to 12 noon, "0 times / 0 items / 0 megabytes" from 12 noon to 4 p.m., and "20 times / 2 items / 30 megabytes" from 4 p.m. to 8 p.m. The collection history of vehicle 10 with vehicle ID "C" is "80 times / 1 item / 5 megabytes" from midnight to 4:00, "80 times / 2 items / 80 megabytes" from 4:00 to 8:00, "80 times / 1 item / 75 megabytes" from 8:00 to 12:00, "80 times / 2 items / 80 megabytes" from 12:00 to 16:00, and "0 times / 0 items / 0 megabytes" from 16:00 to 20:00.

[0060] The detection unit 2 detects an abnormality related to the vehicle 10 based on the setting information, the operation plan, and the collection record. For example, the detection unit 2 compares the collection plan based on the setting information and the operation plan with the collection record, and detects an abnormality related to the vehicle 10 based on the comparison result. Specifically, the detection unit 2 detects an abnormality by comparing the data collection plan table TB11 with the collection record table TB12.

[0061] For example, the detection unit 2 calculates an index value of the deviation between the collection plan based on the setting information and the operation plan and the collection results, and detects an abnormality based on the index value.

[0062] Specifically, assuming that the operation plan at time t is Pt, the data collection record is Rt, and the threshold value is T, the detection unit 2 calculates Rt / Pt, and if Rt / Pt≦T, determines that the amount of collected vehicle information at time t is small. Rt / Pt is an example of the index value. The following explanation will be given assuming that the threshold value T is, for example, 50%.

[0063] [Example 1 of Abnormality Determination Criteria] The detection unit 2 determines whether an abnormality exists for each of the above-mentioned items "vehicle information upload cycle / data type / amount of uploaded data" individually. Specifically, for example, the detection unit 2 determines whether an abnormality exists when "upload cycle Rt in collection record / upload cycle Pt in operation plan≦0.5" is satisfied.

[0064] The detection unit 2 may make a determination regarding the "vehicle information upload period" and the "amount of data uploaded" for each data type, or may make a determination for multiple data types collectively.

[0065] [Example 2 of Abnormality Determination Criteria] The detection unit 2 determines an abnormality based on a combination of the above items of "vehicle information upload cycle / data type / amount of uploaded data." Specifically, for example, the detection unit 2 determines an abnormality when "number of data types in collection history Rt / number of data types in operation plan Pt≦0.5" and "amount of data in collection history Rt / amount of data in operation plan Pt≦0.5" are satisfied.

[0066] 6 shows a case where the detection unit 2 makes a collective determination of multiple data types as described above. In both cases of Example 1 and Example 2 of the abnormality determination criteria, the detection unit 2 determines that an abnormality has occurred in the vehicle 10 with the vehicle ID "A" from midnight to 12:00, in the vehicle 10 with the vehicle ID "B" from midnight to 12:00 and from 16:00 to 20:00, and in the vehicle 10 with the vehicle ID "C" from midnight to 4:00.

[0067] Furthermore, in the case of Example 1 of the abnormality determination criteria, the detection unit 2 determines that an abnormality occurs in the vehicle 10 with the vehicle ID "C" from 8:00 to 12:00. On the other hand, in the case of Example 2 of the abnormality determination criteria, the detection unit 2 determines that no abnormality occurs in the vehicle 10 with the vehicle ID "C" from 8:00 to 12:00 because the "amount of data uploaded" does not satisfy the condition.

[0068] In this way, by using index values, it is possible to prevent false detection of abnormalities in situations such as when vehicle information is not transmitted because the driver of vehicle 10 is taking a temporary break, or when vehicle information regarding the operation of hazard lights is not transmitted because vehicle 10 is traveling on a highway.

[0069] The data collection plan table TB11 and the collection record table TB12 are not limited to being configured to include the upload cycle, data type, and data volume of the vehicle information, but may be configured to include only a portion of the upload cycle, data type, and data volume. However, including the upload cycle makes it possible to easily determine abnormalities in the transmission of vehicle information based on the number of times the information is received. Furthermore, including the data type makes it possible to determine whether the data volume is low because communication between the vehicle 10 and the detection device 101 is unstable, or because vehicle information of a specific data type has not been uploaded.

[0070] [Modification 1: Determining the Type of Abnormality] The detection unit 2 may be configured to further determine the type of abnormality by comparing the data collection plan table TB11 with the collection record table TB12.

[0071] FIG. 7 is a diagram illustrating an example of types of abnormalities detected by the detection device according to the embodiment of the present disclosure.

[0072] Referring to Figure 7, the detection unit 2 can detect, for example, abnormality A1 in which the number of data types of vehicle information from vehicle 10 is always small, abnormality A2 in which the number of times vehicle information is uploaded from vehicle 10 is always small, abnormality A3 in which the amount of data of vehicle information from vehicle 10 is always small, abnormality A4 in which the number of data types of vehicle information from vehicle 10 is temporarily small, abnormality A5 in which the number of times vehicle information is uploaded from vehicle 10 is temporarily small, and abnormality A6 in which the amount of data of vehicle information from vehicle 10 is temporarily small.

[0073] FIG. 8 is a diagram illustrating an example of data collection results used for anomaly detection by the detection device according to the first modification of the embodiment of the present disclosure.

[0074] Referring to Figure 8, for example, the detection unit 2 may be configured to determine whether or not a deviation has occurred between the operation plan and the collected actual data for each time interval, and detect an abnormality based on the frequency of deviations occurring in multiple time intervals.

[0075] More specifically, the detection unit 2 sets the threshold for determining continuity as N, and when a time period satisfying Rt / Pt≦T occurs N or more times out of the most recent M times, the detection unit 2 determines that the time period corresponds to “always” described in Fig. 7, where M is an integer equal to or greater than 2, and N is an integer equal to or less than M and equal to or greater than 2.

[0076] 5 and 8, when M=3 and N=2, the detection unit 2 determines that an abnormality is "constantly" occurring in the vehicles 10 with vehicle IDs "A" and "B" from 0:00 to 12:00 on a certain day "X." The detection unit 2 also determines that an abnormality is "temporarily" occurring in the vehicle 10 with vehicle ID "B" from 16:00 to 20:00.

[0077] Furthermore, the detection unit 2 determines that an abnormality has "temporarily" occurred in the vehicle 10 with the vehicle ID "C" from midnight to 4 a.m. and from 8 a.m. to 12 p.m. As described above, in the case of Example 2 of the abnormality determination criteria, the detection unit 2 may determine that no abnormality has occurred in the vehicle 10 with the vehicle ID "C" from 8 a.m. to 12 p.m.

[0078] Furthermore, the detection unit 2 may be configured to determine that the condition "always" described in FIG. 7 applies when a time interval satisfying Rt / Pt≦T occurs a predetermined number of times or more in succession.

[0079] 8 shows a case where the detection unit 2 makes a collective judgment on multiple data types. In both judgment criterion example 1 and judgment criterion example 2, the detection unit 2 judges that in the vehicle 10 with vehicle ID "A," abnormalities A1 and A3 occur from midnight to 12:00, in the vehicle 10 with vehicle ID "B," abnormalities A2 and A3 occur from midnight to 12:00 and abnormalities A5 and A6 occur from 16:00 to 20:00, and in the vehicle 10 with vehicle ID "C," abnormalities A4 and A6 occur from midnight to 4:00.

[0080] Furthermore, in the case of judgment criterion example 1, the detection unit 2 determines that an abnormality A4 occurs from 8:00 to 12:00 in the vehicle 10 with the vehicle ID "C." On the other hand, in the case of judgment criterion example 2, the detection unit 2 determines that an abnormality does not occur from 8:00 to 12:00 in the vehicle 10 with the vehicle ID "C" because the amount of data does not satisfy the condition.

[0081] The detection unit 2 is not limited to a configuration that distinguishes between "always" and "temporarily" as types of abnormality as described in FIG. 7, but may be configured, for example, to determine that an abnormality has occurred if a time period that satisfies Rt / Pt≦T has occurred N times or more out of the most recent M times, and to determine that no abnormality has occurred if the time period has occurred less than N times.

[0082] [Modification 2: Identifying Location of Abnormality] FIG. 9 is a diagram illustrating an example of transmission location information used for abnormality detection by a detection device according to a modification 2 of the embodiment of the present disclosure.

[0083] Referring to FIG. 9 , detection unit 2 functions as a fifth acquisition unit to acquire transmission location information indicating a correspondence relationship between the type of vehicle information and the location in vehicle 10 .

[0084] Specifically, for example, the detection unit 2 acquires a transmission location table TB21 indicating the correspondence between data types and transmission locations of vehicle information from the storage unit 4. The transmission location table TB21 is created for each vehicle model, for example, and registered in the storage unit 4.

[0085] In the transmission location table TB21, vehicle information of data type "ID1" includes data transmitted over CAN (Controller Area Network) bus 1, vehicle information of data type "ID2" includes data transmitted over CAN bus 2, vehicle information of data type "ID3" includes data transmitted over LIN (Local Interconnect Network), and vehicle information of data type "ID4" includes data output from a camera connected via USB (Universal Serial Bus).

[0086] When the detection unit 2 detects an abnormality, it identifies the location where the abnormality has occurred based on the collection record, the type included in the setting information, and the transmission location information.

[0087] Specifically, in the collection record table TB12 shown in Fig. 6, the collection record for the vehicle 10 with the vehicle ID "A" is "40 times / 1 item / 30 megabytes" from midnight to 12 noon, which is less in terms of the data type and data amount compared to the data collection plan table TB11 shown in Fig. 5. Therefore, the detection unit 2 refers to the communication log and the data type settings in the memory unit 4, and if, for example, vehicle information of data type "ID2" is obtained from the vehicle 10 but vehicle information of data type "ID1" is not obtained, the detection unit 2 determines that an abnormality has occurred in the CAN bus 1 of the vehicle 10.

[0088] [Modification 3: Creation of List According to Deviation Index Value] FIG. 10 is a diagram illustrating an example of list information created by Modification 3 of the detection device according to the embodiment of the present disclosure.

[0089] Referring to Figure 10, the analysis unit 3 may be configured to calculate an index value of the deviation between the operation plan and the collected actual results, and create a list information of vehicles 10 that require attention to abnormalities based on the index value.

[0090] Specifically, the analysis unit 3 creates an index value table TB22 that indicates the index values ​​of each vehicle 10 in a desired time interval, and stores the created index value table TB22 in the storage unit 4. For example, the detection unit 2 associates the calculated Rt / Pt with the vehicle ID and the time interval in the collection record table TB12, and registers the calculated Rt / Pt in the collection record table TB12. The analysis unit 3 creates the index value table TB22 using the index value Rt / Pt in the collection record table TB12 that was registered by the detection unit 2.

[0091] The index value table TB22 shown in Figure 10 is a table that includes the upload period Rt / Pt, data type Rt / Pt, and data amount Rt / Pt for the time period from 0:00 to 4:00 on a certain day "X", and is sorted in ascending order according to data type and data amount.

[0092] This allows the user to easily understand that similar abnormalities have occurred in the vehicles 10 surrounded by the frame F1 and having vehicle IDs "A," "X," and "Y."

[0093] [Variation 4: Presentation of Detection Results to User] Fig. 11 is a diagram illustrating the configuration of Variation 4 of the detection device according to the embodiment of the present disclosure. Referring to Fig. 11, Variation 4 of the detection device 101 further includes a setting unit 5 compared to the detection device 101 illustrated in Fig. 2. Some or all of the communication unit 1, the detection unit 2, the analysis unit 3, and the setting unit 5 are realized, for example, by a processing circuit including one or more processors. The storage unit 4 is, for example, a non-volatile memory included in the processing circuit.

[0094] The setting unit 5 creates setting information indicating the settings of the vehicle 10 related to the transmission of vehicle information based on, for example, a user operation, and stores the information in the storage unit 4 .

[0095] FIG. 12 is a diagram illustrating an example of a setting screen displayed by the detection device according to the fourth modification of the embodiment of the present disclosure.

[0096] 12 , setting unit 5 creates a setting screen G1 for registering the contents of setting information and performs processing to display the setting screen G1 on a terminal device (not shown) such as a laptop PC (Personal Computer). More specifically, setting unit 5 creates screen information showing setting screen G1 and transmits it to the terminal device via communication unit 1 and external network 161. The terminal device displays setting screen G1 based on the screen information received from setting unit 5.

[0097] The setting screen G1 includes check boxes for inputting the type of vehicle information to be acquired, and the data collection period for each data. In the example shown in Fig. 12, the setting screen G1 showing the setting information for vehicle A allows the user to select CAN data transmitted via the CAN bus, LIN data transmitted via the LIN bus, and USB data transmitted via the USB for each bus. The setting screen G1 may also allow the user to input the data collection period for each data.

[0098] Specifically, in accordance with the user's operation, the terminal device transmits operation information to the detection device 101 indicating that it will collect CAN data 2 and 3 at a data collection period of 100 milliseconds, collect LIN data 2 and 3 at a data collection period of 200 milliseconds, collect USB data 1 at a data collection period of 100 milliseconds, and collect all data at a data collection period of 1000 milliseconds.

[0099] The setting unit 5 creates setting information based on operation information received from the terminal device via the external network 161 and the communication unit 1, and stores the created setting information in the storage unit 4. For example, when this setting information is registered in the in-vehicle device 202, the in-vehicle device 202 transmits vehicle information to the detection device 101 according to the setting contents indicated by the setting information. The setting information may be registered in the in-vehicle device 202 by a user, or may be registered by the detection device 101 transmitting the setting information to the in-vehicle device 202.

[0100] Furthermore, for example, the setting unit 5 calculates the estimated data volume of data to be uploaded from vehicle A, which is the vehicle 10, based on the created setting information, and displays the calculated volume on the setting screen G1. In the example shown in Fig. 12, the estimated data volume of vehicle information per upload sent from vehicle A is 100 kilobytes.

[0101] The terminal device may be configured to accept a user's input operation of an operation plan for vehicle 10. In this case, communication unit 1 receives operation information indicating the operation plan for vehicle 10 from the terminal device, creates operation plan table TB1 based on the received operation information, and stores the created operation plan table TB1 in storage unit 4.

[0102] FIG. 13 is a diagram illustrating an example of a monitoring screen displayed by the detection device according to the fourth modification of the embodiment of the present disclosure.

[0103] Referring to FIG. 13, the detection unit 2 performs a process of displaying on the screen the content based on the type of vehicle information in which an abnormality has occurred.

[0104] More specifically, the detection unit 2 creates a monitoring screen G2 that shows the abnormality detection results, and, similar to the setting screen G1, creates screen information showing the monitoring screen G2 and sends it to the terminal device, thereby displaying the monitoring screen G2 on the terminal device.

[0105] The monitoring screen G2 includes the date, the estimated upload data amount, i.e., the amount of vehicle information data estimated to be uploaded from the vehicle 10 per day, the actual upload data amount, i.e., the amount of vehicle information data actually uploaded from the vehicle per day, and data that may not have been uploaded. The monitoring screen G2 also includes the estimated cause of the abnormality and proposed countermeasures for the abnormality.

[0106] 13, the monitoring screen G2 showing the monitoring results of vehicle information from vehicle A displays that the expected upload data volume is 3.6 gigabytes, the actual upload data volume is 1.8 gigabytes, and there is a possibility that USB data 1 or CAN data 2 and 3 have not been uploaded. The monitoring screen G2 also displays that the cause of the abnormality is a poor connection in USB 1 or CAN bus 1, and that driver C of vehicle A should be contacted.

[0107] The detection unit 2 may be configured to display the estimated and actual upload data amounts per hour, for example, rather than on a daily basis, or may be configured to display the estimated and actual upload data amounts for the period up to the current point in time in a day.

[0108] In addition, if the detection unit 2 is configured to automatically notify the driver C of the vehicle A in which the abnormality has occurred of the abnormality detection result, the monitoring screen G2 may be configured to display, for example, a message that the driver C of the vehicle A has been contacted, or that an abnormality lamp on an equipment in the vehicle 10 has been turned on.

[0109] In the embodiments of the present disclosure including the fourth modification, the in-vehicle device 202 is, for example, a device that is retrofitted to the vehicle 10 after the vehicle 10 is shipped. Compared to existing devices, various malfunctions caused by the retrofitted device are expected. With the configuration for displaying the monitoring screen G2 as described above, even an uninformed user can easily grasp the abnormality of the in-vehicle device 202, for example, when a malfunction occurs in the retrofitted device. This allows the cause of the malfunction to be efficiently identified, and, for example, the number of retrofitted devices to be recalled can be reduced, thereby reducing the burden of recall work, etc.

[0110] [Operation Flow] Fig. 14 is a flowchart defining an operation procedure when the detection device according to the embodiment of the present disclosure detects an abnormality in a vehicle. Fig. 14 shows the process described using Fig. 3.

[0111] Referring to FIG. 14, first, the detection device 101 collects vehicle information from one or more vehicles 10, and creates and stores a communication log (step S1).

[0112] Next, the detection device 101 collects vehicle information until it has collected data for a certain period of time (NO in step S2), and if it has collected data for a certain period of time (YES in step S2), it creates a collection history table TB2 that shows the vehicle information collection history (step S3).

[0113] Next, the detection device 101 obtains the operation plan table TB1, which shows the operation plan of the vehicle 10, from the memory unit 4 (step S4), and detects abnormalities by comparing the collected performance table TB2 with the operation plan table TB1 (step S5).

[0114] When the detection device 101 determines that no abnormality has occurred (NO in step S6), the detection device 101 continues to collect vehicle information (step S1).

[0115] On the other hand, if the detection device 101 determines that an abnormality has occurred (YES in step S6), it outputs the detection result (step S7) and continues collecting vehicle information (step S1).

[0116] 15 is a flowchart illustrating an operation procedure when a detection device according to an embodiment of the present disclosure detects an abnormality in a vehicle. Fig. 15 illustrates another example of the abnormality detection process described above. Fig. 15 also includes the processes of Modifications 1 and 2.

[0117] Referring to FIG. 15, first, the detection device 101 collects vehicle information from one or more vehicles 10, and creates and stores a communication log (step S11).

[0118] Next, the detection device 101 collects vehicle information until it has collected data for a certain period of time (NO in step S12), and if it has collected data for a certain period of time (YES in step S12), it creates a collection history table TB12 that shows the vehicle information collection history (step S13).

[0119] Next, the detection device 101 acquires the setting information from the storage unit 4 (step S14), and calculates an estimated value E of the data amount based on the setting information (step S15).

[0120] Next, the detection device 101 obtains an operation plan table TB1 showing the operation plan of the vehicle 10 from the memory unit 4 (step S16), and creates a data collection plan table TB11 showing a plan for collecting vehicle information from the vehicle 10 based on the operation plan and setting information, specifically based on the operation plan table TB1 and the transmission data table TB10 (step S17).

[0121] Next, the detection device 101 compares the collection record table TB12 with the data collection plan table TB11 to detect an abnormality and determine the type of abnormality (step S18).

[0122] When the detection device 101 determines that no abnormality has occurred (NO in step S19), the detection device 101 continues to collect vehicle information (step S11).

[0123] On the other hand, if the detection device 101 determines that an abnormality has occurred (YES in step S19), it obtains the transmission location table TB21, which indicates the transmission location of the vehicle information, from the memory unit 4 (step S20), and identifies the location where the abnormality has occurred based on the settings of the collection history table TB12, the data type indicated in the transmission data table TB10, and the transmission location table TB21 (step S21).

[0124] Next, the detection device 101 outputs a detection result indicating, for example, the type of abnormality and the location where the abnormality has occurred (step S22), and continues collecting vehicle information (step S11). Note that the detection device 101 may also perform processing to display the above-mentioned monitoring screen G2 (step S22).

[0125] FIG. 16 is a flowchart defining an operation procedure when the detection device according to the third modification example of the embodiment of the present disclosure creates list information.

[0126] Referring to FIG. 16, first, the detection device 101 acquires the abnormality detection result of each vehicle 10 from the storage unit 4 (step S31).

[0127] Next, the detection device 101 obtains the index value Rt / Pt of the deviation between the collection plan based on the operation plan and the collection results for each vehicle 10 in which an abnormality has occurred, for example from the collection results table TB12 in the memory unit 4 (step S32).

[0128] Next, the detection device 101 uses the index value Rt / Pt in the collection record table TB12 to create list information, for example, an index value table TB22 as shown in FIG. 10, and stores it in the storage unit 4 (step S33).

[0129] Note that some or all of the functions of the detection device 101 may be provided by cloud computing. That is, the detection device according to the embodiment of the present disclosure may be a cloud server configured by a plurality of servers.

[0130] Each process (each function) in the above-described embodiments is realized by a processing circuit (circuitry) including one or more processors. The processing circuit may be configured as an integrated circuit or the like that combines one or more memories, various analog circuits, and various digital circuits in addition to the one or more processors. The one or more memories store programs (instructions) that cause the one or more processors to execute each of the processes. The one or more processors may execute each of the processes according to the program read from the one or more memories, or may execute each of the processes according to a logic circuit designed in advance to execute each of the processes. The processor may be any of various processors suitable for computer control, such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), and an ASIC (Application Specific Integrated Circuit). Note that the physically separated processors may cooperate with each other to execute the processes. For example, the processors installed in the physically separated computers may cooperate with each other via a network such as a LAN (Local Area Network), a WAN (Wide Area Network), or the Internet to execute the processes. The program may be installed into the memory from an external server device or the like via the network, or may be distributed in a state stored on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a semiconductor memory, and then installed into the memory from the recording medium.

[0131] The above-described embodiments should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims.

[0132] The above description includes the features noted below. [Supplementary Note 1] A detection device comprising: a first acquisition unit that acquires vehicle information related to a vehicle from a vehicle, the vehicle information including identification information of the vehicle; a second acquisition unit that acquires a collection history of the vehicle information by the first acquisition unit; a third acquisition unit that acquires an operation plan for the vehicle corresponding to the identification information; and a detection unit that detects an abnormality related to the vehicle based on the collection history and the operation plan, the detection device further comprising: an analysis unit that creates a collection plan for the vehicle information based on the setting information and the operation plan, and the detection unit compares the collection plan with the collection history and detects an abnormality related to the vehicle based on a comparison result.

[0133] [Supplementary Note 2] A detection device comprising a processing circuit, wherein the processing circuit: acquires vehicle information related to the vehicle from the vehicle, the vehicle information including identification information of the vehicle; acquires a collection record of the vehicle information by the first acquisition unit; acquires an operation plan for the vehicle corresponding to the identification information; and detects an abnormality related to the vehicle based on the collection record and the operation plan.

[0134] REFERENCE SIGNS LIST 1 Communication unit 2 Detection unit 3 Analysis unit 4 Storage unit 5 Setting unit 10 Vehicle 101 Detection device 102 On-board device 161 External network 202 On-board device 301 Communication system A1, A2, A3, A4, A5, A6 Abnormality F1 Frame TB1 Operation plan table TB10 Transmission data table TB11 Data collection plan table TB2, TB12 Collection result table TB21 Transmission location table TB22 Index value table

Claims

1. A first acquisition unit that acquires vehicle information related to the vehicle from a vehicle, the vehicle information including identification information of the vehicle; a second acquisition unit that acquires a collection record of the vehicle information by the first acquisition unit; A third acquisition unit that acquires an operation plan of the vehicle corresponding to the identification information; a detection unit that detects an abnormality regarding the vehicle based on the collected history and the operation plan.

2. The detection device further comprises: a fourth acquisition unit that acquires setting information indicating a setting content of the vehicle related to the transmission of the vehicle information; The detection device according to claim 1 , wherein the detection unit detects an abnormality related to the vehicle based on the setting information, the collection history, and the operation plan.

3. The detection device according to claim 2 , wherein the setting information includes at least one of a transmission period of the vehicle information by the vehicle and a type of the vehicle information transmitted by the vehicle.

4. the setting information includes a type of the vehicle information to be transmitted by the vehicle, The detection device further comprises: a fifth acquisition unit that acquires transmission location information indicating a correspondence relationship between the type and a transmission location of the vehicle information in the vehicle; The detection device according to claim 2 or 3, wherein when the detection unit detects the abnormality, the detection unit identifies a location where the abnormality has occurred based on the collection history, the type included in the setting information, and the transmission location information.

5. The operation plan is divided into a plurality of time periods, The detection device according to claim 1 , wherein the detection unit determines whether or not a deviation has occurred between the operation plan and the collected actual data for each time interval, and detects the abnormality based on a frequency of occurrence of the deviation in a plurality of the time intervals.

6. The detection device further comprises:

4. The detection device according to claim 1, further comprising an analysis unit that calculates an index value of a deviation between the operation plan and the collected results, and creates a list of the vehicles that require attention to the abnormality based on the index value.

7. the setting information includes a type of the vehicle information to be transmitted by the vehicle, The detection device according to claim 2 or 3, wherein the detection unit performs a process of displaying on a screen details based on a type of the vehicle information in which the abnormality has occurred.

8. An on-board device mounted in a vehicle; A detection device, the in-vehicle device transmits vehicle information regarding the vehicle, the vehicle information including identification information of the vehicle, to the detection device; The detection device detects an abnormality related to the vehicle based on a collection record of the vehicle information in the detection device and an operation plan of the vehicle corresponding to the identification information.

9. A detection method for a detection device, comprising: obtaining vehicle information from a vehicle, the vehicle information including an identification of the vehicle; acquiring a collection record of the vehicle information by the detection device; obtaining an operation plan for the vehicle corresponding to the identification information; and detecting an abnormality related to the vehicle based on the collected history and the operation plan.

10. A detection program for use in a detection device, Computer, A first acquisition unit that acquires vehicle information related to the vehicle from a vehicle, the vehicle information including identification information of the vehicle; a second acquisition unit that acquires a collection record of the vehicle information by the first acquisition unit; A third acquisition unit that acquires an operation plan of the vehicle corresponding to the identification information; A detection unit that detects an abnormality related to the vehicle based on the collected record and the operation plan; A detection program to function as a