Detection device, detection system, detection method, and detection program

Abstract

A detection device is provided with: a first acquisition unit that acquires, from a vehicle, vehicle information relating to the vehicle, which is information including identification information of the vehicle; a second acquisition unit that acquires the collection performance of the vehicle information acquired by the first acquisition unit; a third acquisition unit that acquires an operation plan of the vehicle corresponding to the identification information; and a detection unit that detects an abnormality related to the vehicle on the basis of the collection performance and the operation plan.

Description

Technical Field

[0001] The present disclosure relates to a detection device, a detection system, a detection method and a detection program.

[0002] This application claims the benefit of priority based on Japanese patent application No. 2022-163477, filed on October 11, 2022, and incorporates herein all the contents disclosed. Background Art

[0003] Japanese Patent Application Laid-Open No. 2008-216113 (Patent Document 1) discloses a system for centralizing bad condition information of vehicles. That is, a system for centralizing bad condition information of vehicles at a center, wherein the vehicle comprises: a vehicle driving information acquisition unit for acquiring data on the driving condition of the vehicle, namely, vehicle driving information; a vehicle driving information transmission unit for transmitting the vehicle driving information to the center; a voice call unit for enabling the driver of the vehicle to communicate with an operator at the center; and a control unit for starting, based on an instruction from the driver, the transmission of the vehicle driving information to the center by the vehicle driving information transmission unit and the voice call with the operator by the voice call unit, wherein the center comprises: a vehicle driving information reception unit for receiving the vehicle driving information transmitted from the vehicle; a voice call unit for enabling the driver of the vehicle to communicate with the operator at the center; and a bad condition information storage unit for storing the received vehicle driving information in association with the content of the bad condition notified by the driver of the vehicle through the voice call unit.

[0004] In addition, Japanese Patent Application Laid-Open No. 2014-081390 (Patent Document 2) discloses the following vehicle information storage device. That is, the vehicle information storage device comprises: a state information acquisition unit, which acquires the state information of the vehicle; a temporary storage unit, which temporarily stores the state information acquired by the state information acquisition unit; a prescribed table storage unit, which stores a prescribed table of prescribed information determination criteria, wherein the information determination criteria is used to determine the verification information that should be used for verifying the cause of the malfunction from the state information stored in the temporary storage unit; and a control unit, which determines the verification information that should be used for verifying the cause of the malfunction from the state information stored in the temporary storage unit based on the information determination criteria specified in the prescribed table, and stores the determined verification information in a predetermined storage medium, wherein the detection of the malfunction performed by the user and the corresponding category and range of the verification information are specified as the information determination criteria, and when the control unit performs the detection of the malfunction specified in the prescribed table and performed by the user, the control unit determines the verification information of the corresponding category specified in the prescribed table according to the range specified in the prescribed table, and stores the verification information of the determined category and range in the predetermined storage medium.

[0005] Prior art literature

[0006] Patent Literature

[0007] Patent Document 1: Japanese Patent Application Publication No. 2008-216113

[0008] Patent Document 2: Japanese Patent Application Publication No. 2014-081390 Summary of the invention

[0009] The detection device disclosed in the present invention comprises: a first acquisition unit, which acquires information including identification information of the vehicle, i.e., vehicle information related to the vehicle, from a vehicle; a second acquisition unit, which acquires the collection performance of the vehicle information acquired by the first acquisition unit; a third acquisition unit, which acquires an operation plan of the vehicle corresponding to the identification information; and a detection unit, which detects abnormalities related to the vehicle based on the collection performance and the operation plan.

[0010] 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 realizing a part or all of the detection device. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a diagram showing the structure of a communication system involved in an embodiment of the present disclosure.

[0012] Figure 2It is a diagram showing the structure of a detection device according to an embodiment of the present disclosure.

[0013] Figure 3 This is a diagram showing an example of information used for abnormality detection by the detection device according to the embodiment of the present disclosure.

[0014] Figure 4 This is a diagram showing an example of setting information and data collection estimation used for abnormality detection by the detection device involved in the embodiment of the present disclosure.

[0015] Figure 5 This is a diagram showing an example of a data collection schedule table used for abnormality detection by the detection device according to the embodiment of the present disclosure.

[0016] Figure 6 This is a diagram showing an example of data collection results for abnormality detection by the detection device according to the embodiment of the present disclosure.

[0017] Figure 7 This is a diagram showing an example of the types of abnormalities detected by the detection device according to the embodiment of the present disclosure.

[0018] Figure 8 This is a diagram showing an example of data collection results for abnormality detection in Modification 1 of the detection device according to the embodiment of the present disclosure.

[0019] Fig. 9 This is a diagram showing an example of transmission location information used for abnormality detection in Modification 2 of the detection device involved in the embodiment of the present disclosure.

[0020] Fig.10 This is a diagram showing an example of list information created by Modification 3 of the detection device according to the embodiment of the present disclosure.

[0021] Fig.11 It is a diagram showing the structure of Modification 4 of the detection device according to the embodiment of the present disclosure.

[0022] Fig.12 This is a diagram showing an example of a setting screen displayed in Modification 4 of the detection device according to the embodiment of the present disclosure.

[0023] Fig.13 This is a diagram showing an example of a monitoring screen displayed by Modification 4 of the detection device according to the embodiment of the present disclosure.

[0024] Fig.14 This is a flowchart that defines the operation process when the detection device according to the embodiment of the present disclosure detects an abnormality in a vehicle.

[0025] Fig.15This is a flowchart that defines the operation process when the detection device according to the embodiment of the present disclosure detects an abnormality in a vehicle.

[0026] Fig.16 This is a flowchart that specifies the operation procedure when creating list information in Modification 3 of the detection device according to the embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] Conventionally, technologies for understanding vehicle failures have been developed.

[0028] [Technical Problems to be Solved by the Present Disclosure]

[0029] Understanding abnormalities related to a vehicle from a different perspective from the techniques described in Patent Documents 1 and 2 is useful in vehicle management.

[0030] The present disclosure is made to solve the above-mentioned technical problems, and its object is to provide a detection device, a detection system, a detection method, and a detection program that can easily grasp abnormalities related to a vehicle.

[0031] [Effects of the present disclosure]

[0032] According to the present disclosure, abnormality related to the vehicle can be easily grasped.

[0033] [Description of Embodiments of the Present Disclosure]

[0034] First, the contents of the embodiments of the present disclosure are listed and described.

[0035] (1) The detection device involved in the embodiment of the present disclosure comprises: a first acquisition unit, which acquires information including identification information of the vehicle, i.e., vehicle information related to the vehicle, from a vehicle; a second acquisition unit, which acquires the collection performance of the vehicle information acquired by the first acquisition unit; a third acquisition unit, which acquires an operation plan of the vehicle corresponding to the identification information; and a detection unit, which detects an abnormality related to the vehicle based on the collection performance and the operation plan.

[0036] Unlike equipment installed in factories, vehicles have periods where data is not transmitted even in normal conditions. With this in mind, a structure that detects abnormalities based on vehicle information collection results and vehicle operation plans can easily detect abnormalities related to vehicle data transmission using vehicle data collection results. As a result, abnormalities related to the vehicle can be easily grasped.

[0037] (2) In the above (1), the detection device may further include a fourth acquisition unit, which acquires setting information representing setting contents of the vehicle related to the sending of the vehicle information, or the detection unit may detect an abnormality related to the vehicle based on the setting information, the collection performance and the operation plan.

[0038] In this way, according to the configuration for detecting abnormality using the setting contents related to the transmission of vehicle information by the vehicle, it is possible to grasp a more detailed transmission status, not just the presence or absence of transmission of vehicle information, and more accurately detect abnormality of the vehicle.

[0039] (3) In the above (2), the setting information may include at least one of a transmission cycle of the vehicle information transmitted by the vehicle and a type of the vehicle information transmitted by the vehicle.

[0040] In this way, according to the structure of using the transmission cycle of vehicle information for abnormality determination, it is possible to simply determine the abnormality related to the transmission of vehicle information based on the number of receptions. In addition, according to the structure of using the type of vehicle information for abnormality determination, it is possible to determine whether the amount of data is small due to unstable communication between the vehicle and the detection device or because the vehicle information of a specific data type has not been uploaded.

[0041] (4) In the above (2) or (3), the setting information may include the type of the vehicle information sent by the vehicle, or the detection device may further include a fifth acquisition unit, and the fifth acquisition unit may acquire transmission location information indicating the correspondence between the type and the transmission location of the vehicle information in the vehicle. Or, when the detection unit detects the abnormality, it may determine the occurrence location of the abnormality based on the collection performance, the type included in the setting information, and the transmission location information.

[0042] In this way, according to the structure of using the type of vehicle information for abnormality determination, it is possible to determine whether the amount of data is small due to unstable communication between the vehicle and the detection device or the amount of data is small due to the fact that vehicle information of a specific data category has not been uploaded. In addition, since the collection performance can be grasped for each type of vehicle information, the location of the abnormality in the vehicle can be determined, and the abnormality can be analyzed in more detail.

[0043] (5) In any of the above (1) to (4), the operation plan may be divided into a plurality of time intervals, or the detection unit may determine whether a deviation between the operation plan and the collected performance has occurred for each of the time intervals, and detect the abnormality based on the frequency of occurrence of the deviation in the plurality of time intervals.

[0044] According to such a configuration, it is possible to analyze the abnormality of the vehicle in more detail in terms of time, or to reduce the possibility of erroneous detection of abnormality due to temporary driving conditions of the vehicle, etc.

[0045] (6) In any one of the above (1) to (5), the detection device may further include an analysis unit, which calculates an index value of the deviation between the operation plan and the collected performance, and creates an overview information of the vehicle that needs to respond to the abnormality based on the index value.

[0046] According to such a configuration, for example, by sorting the vehicles according to the index value, it is possible to easily grasp the group of vehicles in which similar abnormalities have occurred.

[0047] (7) In any of the above (2) to (4), the setting information may include the type of the vehicle information sent by the vehicle, or the detection unit may perform processing to display the content of the type of the vehicle information in which the abnormality has occurred on the screen.

[0048] According to such a structure, for example, when a malfunction occurs in the after-installed equipment of the vehicle that sends the vehicle information, even an inexperienced user can easily understand the abnormality of the equipment. Thus, the cause of the malfunction can be efficiently distinguished, for example, the burden of the recovery operation of the after-installed equipment can be reduced.

[0049] (8) The detection system involved in the embodiment of the present disclosure includes a vehicle-mounted device mounted on a vehicle, and a detection device, wherein the vehicle-mounted device sends information including identification information of the vehicle, that is, vehicle information related to the vehicle, to the detection device, and the detection device detects abnormalities related to the vehicle based on the collection performance of the vehicle information in the detection device and the operation plan of the vehicle corresponding to the identification information.

[0050] Unlike equipment installed in factories, vehicles have periods where data is not transmitted even in normal conditions. With this in mind, a structure that detects abnormalities based on vehicle information collection results and vehicle operation plans can easily detect abnormalities related to vehicle data transmission using vehicle data collection results. As a result, abnormalities related to the vehicle can be easily grasped.

[0051] (9) The detection method involved in the embodiment of the present disclosure is a detection method in a detection device, comprising: a step of acquiring information including identification information of the vehicle, i.e., vehicle information related to the vehicle, from a vehicle; a step of acquiring the collection performance of the vehicle information acquired by the detection device; a step of acquiring an operation plan of the vehicle corresponding to the identification information; and a step of detecting an abnormality related to the vehicle based on the collection performance and the operation plan.

[0052] Unlike equipment installed in factories, vehicles have periods where data is not transmitted even in normal conditions. With this in mind, a structure that detects abnormalities based on vehicle information collection results and vehicle operation plans can easily detect abnormalities related to vehicle data transmission using vehicle data collection results. As a result, abnormalities related to the vehicle can be easily grasped.

[0053] (10) The detection program involved in the embodiment of the present disclosure is a detection program used in a detection device, and is a program for causing a computer to function as the following components: a first acquisition unit, which acquires information including identification information of the vehicle, i.e., vehicle information related to the vehicle, from a vehicle; a second acquisition unit, which acquires the collection performance of the vehicle information acquired by the first acquisition unit; a third acquisition unit, which acquires an operation plan of the vehicle corresponding to the identification information; and a detection unit, which detects an abnormality related to the vehicle based on the collection performance and the operation plan.

[0054] Unlike equipment installed in factories, vehicles have periods where data is not transmitted even in normal conditions. With this in mind, a structure that detects abnormalities based on vehicle information collection results and vehicle operation plans can easily detect abnormalities related to vehicle data transmission using vehicle data collection results. As a result, abnormalities related to the vehicle can be easily grasped.

[0055] The following is an explanation of the embodiments of the present disclosure using the accompanying drawings. It should be noted that the same or equivalent parts in the drawings are marked with the same reference numerals, and their descriptions are not repeated. In addition, at least a part of the embodiments described below may be arbitrarily combined.

[0056] Figure 1 1 is a diagram showing a configuration of a communication system according to an embodiment of the present disclosure. Figure 1 The communication system 301 includes a detection device 101 and one or more vehicle-mounted devices 202. The detection device 101 and each vehicle-mounted device 202 can transmit and receive information via an external network 161 such as the Internet. The vehicle-mounted device 202 is mounted on the vehicle 10.

[0057] The detection device 101 is used by, for example, a company or an individual (hereinafter collectively referred to as a user) who manages the operation of the vehicle 10 .

[0058] The detection device 101 collects vehicle information related to the corresponding vehicle 10 from one or more vehicle-mounted devices 202. The detection device 101 detects abnormalities related to the vehicle 10, such as a malfunction of the vehicle 10, based on the collected vehicle information.

[0059] The vehicle-mounted device 202 sends information including identification information of the vehicle 10, that is, vehicle information related to the vehicle 10, to the detection device 101. Specifically, for example, each vehicle-mounted device 202 receives the position information of the corresponding vehicle 10 from a GPS (Global Positioning System) receiver (not shown) in the vehicle 10, and sends the vehicle information including the received position information, the ID of the vehicle 10, and the data category to the detection device 101 via the external network 161. It should be noted that the vehicle information is not limited to the position information, and may include, for example, the measurement results of the sensors mounted on the vehicle 10, and may also include driving control information such as the braking operation in the vehicle 10.

[0060] Figure 2 2 is a diagram showing the structure of a detection device according to an embodiment of the present disclosure. Figure 2 The detection device 101 includes a communication unit 1, a detection unit 2, an analysis unit 3 and a storage unit 4. Part or all of the communication unit 1, the detection unit 2 and the analysis unit 3 are implemented by a processing circuit (Circuitry) including one or more processors. The storage unit 4 is, for example, a non-volatile memory included in the above-mentioned processing circuit.

[0061] The communication unit 1 transmits and receives information to and from the vehicle-mounted device 202 via the external network 161. The communication unit 1 stores the information received from the vehicle-mounted device 202 in the storage unit 4.

[0062] The communication unit 1 as a first acquisition unit acquires vehicle information from the vehicle 10. More specifically, the communication unit 1 receives vehicle information from the vehicle-mounted 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.

[0063] Figure 3 This is a diagram showing an example of information used for abnormality detection by the detection device according to the embodiment of the present disclosure.

[0064] Reference Figure 3, the detection unit 2, as a third acquisition unit, acquires the operation plan of the vehicle 10 corresponding to the identification information included in the vehicle information acquired by the communication unit 1. More specifically, for example, the detection unit 2 acquires the operation plan table TB1 representing the operation plan of each vehicle 10 from the storage unit 4. The operation plan table TB1 is pre-registered in the storage unit 4 by the user, for example. It should be noted that the operation plan table TB1 may be created, for example, based on the acquisition results of the on state and the off state of the ignition power of the vehicle 10 without formulating a clear operation plan.

[0065] The operation plan is divided into multiple time intervals. In this example, the length of the time interval is 4 hours. Figure 3 In the operation plan table TB1 of a certain day "X" shown, the operation plans of the vehicles 10 with vehicle IDs "A" and "B" are: "operation" from 0:00 to 12:00, "rest" from 12:00 to 16:00, and "operation" from 16:00 to 20:00. The operation plan of the vehicle 10 with vehicle ID "C" is: "operation" from 0:00 to 16:00, and "rest" from 16:00 to 20:00.

[0066] The analysis unit 3, as a second acquisition unit, acquires the collection performance of the vehicle information acquired by the first acquisition unit. More specifically, for example, the analysis unit 3 regularly or irregularly creates a collection performance table TB2 indicating the collection performance of the vehicle information of each vehicle 10 based on the communication log of the vehicle information stored in the storage unit 4, and stores it in the storage unit 4.

[0067] The collection performance is divided into multiple time periods. In this example, the length of the time period is 4 hours, just like the operation plan. Figure 3 In the collection performance table TB2 of a certain day "X" shown, the collection performance of the vehicle 10 with the vehicle ID "A" is: "Yes" from 0:00 to 12:00, and "No" from 12:00 to 20:00. The collection performance of the vehicle 10 with the vehicle ID "B" is: "Yes" from 0:00 to 12:00, "No" from 12:00 to 16:00, and "Yes" from 16:00 to 20:00. The collection performance of the vehicle 10 with the vehicle ID "C" is: "Yes" from 0:00 to 16:00, and "No" from 16:00 to 20:00.

[0068] The detection unit 2 detects an abnormality related to the vehicle 10 based on the collection results and the operation plan. Specifically, in the operation plan table TB1, although the operation plan of the vehicle ID "A" is "operation" from 16:00 to 20:00, in the collection results table TB2, the collection results of the vehicle ID "A" are "none" from 16:00 to 20:00. Therefore, since there is a time period in which the vehicle information cannot be received from the operating vehicle 10, the detection unit 2 determines that an abnormality related to the vehicle 10 with the vehicle ID "A" has occurred.

[0069] 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 user of the abnormality detection result.

[0070] [Other examples of anomaly detection]

[0071] Figure 4 This is a diagram showing an example of setting information and data collection estimation used for abnormality detection by the detection device involved in the embodiment of the present disclosure.

[0072] Reference Figure 4 The analyzing unit 3 as a fourth acquiring unit acquires setting information indicating setting contents of the vehicle 10 related to the transmission of vehicle information. For example, the setting information includes a transmission cycle of the vehicle information transmitted by the vehicle 10 and a type of the vehicle information transmitted by the vehicle 10.

[0073] More specifically, the analysis unit 3 obtains the setting contents of the upload cycle, data type, and sampling cycle of each vehicle 10 from the storage unit 4, and calculates the estimated value E of the data volume per unit time of the vehicle information transmitted from the vehicle 10 based on the obtained upload cycle and sampling cycle, and the predetermined data volume of one sample volume of the vehicle information. Then, the analysis unit 3 creates a transmission data table TB10 including the above-mentioned setting contents and the estimated value E of each vehicle 10, and stores it in the storage unit 4. It should be noted that the analysis unit 3 is not limited to the structure of calculating the estimated value E, and the above-mentioned data volume per unit time can also be registered in the storage unit 4 as setting information.

[0074] exist Figure 4 In the transmission data table TB10 shown, the upload cycle of the vehicle 10 with vehicle ID "A" is 10 times / hour, and the vehicle information of the data categories "ID1" and "ID2" is uploaded. The sampling cycle, that is, the generation cycle of the vehicle information is once every 10 seconds, and the estimated value E is 10 megabytes / hour. The upload cycle of the vehicle 10 with vehicle ID "B" is 10 times / hour, and the vehicle information of the data categories "ID1" and "ID3" is uploaded. The sampling cycle is once every 10 seconds, and the estimated value E is 15 megabytes / hour. The upload cycle of the vehicle 10 with vehicle ID "C" is 20 times / hour, and the vehicle information of the data categories "ID3" and "ID4" is uploaded. The sampling cycle is once every 5 seconds, and the estimated value E is 20 megabytes / hour.

[0075] Figure 5 This is a diagram showing an example of a data collection schedule table used for abnormality detection by the detection device according to the embodiment of the present disclosure.

[0076] Reference Figure 5 The analyzing unit 3 creates a plan for collecting vehicle information from the vehicle 10 based on the setting information and the operation plan.

[0077] More specifically, the analysis unit 3 creates a data collection plan table TB11 indicating a collection plan of vehicle information for each vehicle 10 based on the transmission data table TB10 and the operation plan table TB1 stored in the storage unit 4 , and stores the data collection plan table TB11 in the storage unit 4 .

[0078] Figure 5 The data collection schedule table TB11 shown indicates "vehicle information upload cycle / data type / uploaded data volume" in each time zone.

[0079] In the data collection plan table TB11 of a certain day "X", the collection plan of vehicle 10 with vehicle ID "A" is: "40 times / 2 / 40 megabytes" from 0 o'clock to 12 o'clock, "0 times / 0 / 0 megabytes" from 12 o'clock to 16 o'clock, and "40 times / 2 / 40 megabytes" from 16 o'clock to 20 o'clock. The collection plan of vehicle 10 with vehicle ID "B" is: "40 times / 2 / 60 megabytes" from 0 o'clock to 12 o'clock, "0 times / 0 / 0 megabytes" from 12 o'clock to 16 o'clock, and "40 times / 2 / 60 megabytes" from 16 o'clock to 20 o'clock. The collection plan of vehicle 10 with vehicle ID "C" is: "80 times / 2 / 80 megabytes" from 0 o'clock to 16 o'clock, and "0 times / 0 / 0 megabytes" from 16 o'clock to 20 o'clock.

[0080] Figure 6 This is a diagram showing an example of data collection results for abnormality detection by the detection device according to the embodiment of the present disclosure.

[0081] Reference Figure 6 The analysis unit 3, as a second acquisition unit, acquires the collection performance of the vehicle information acquired by the first acquisition unit. More specifically, the analysis unit 3 creates a collection performance table TB12 representing the collection performance of the vehicle information of each vehicle 10 based on the communication log of the vehicle information stored in the storage unit 4 on a regular or irregular basis, and stores it in the storage unit 4.

[0082] Figure 6 The collection performance table TB12 shown is Figure 5 The data collection schedule table TB11 shown similarly indicates “vehicle information upload cycle / data type / uploaded data volume” in each time zone.

[0083] In the collection performance table TB12 of a certain day "X", the collection performance of the vehicle 10 with the vehicle ID "A" is: "40 times / 1 item / 30 megabytes" from 0:00 to 12:00, and "0 times / 0 items / 0 megabytes" from 12:00 to 20:00. The collection performance of the vehicle 10 with the vehicle ID "B" is: "20 times / 2 items / 30 megabytes" from 0:00 to 12:00, "0 times / 0 items / 0 megabytes" from 12:00 to 16:00, and "20 times / 2 items / 30 megabytes" from 16:00 to 20:00. The collection performance of vehicle 10 with vehicle ID "C" is: from 0 o'clock to 4 o'clock is "80 times / 1 / 5 megabytes", from 4 o'clock to 8 o'clock is "80 times / 2 / 80 megabytes", from 8 o'clock to 12 o'clock is "80 times / 1 / 75 megabytes", from 12 o'clock to 16 o'clock is "80 times / 2 / 80 megabytes", and from 16 o'clock to 20 o'clock is "0 times / 0 / 0 megabytes".

[0084] The detection unit 2 detects abnormalities related to the vehicle 10 based on the setting information, the operation plan, and the collection results. For example, the detection unit 2 compares the collection plan based on the setting information and the operation plan with the collection results, and detects abnormalities related to the vehicle 10 based on the comparison result. Specifically, the detection unit 2 detects abnormalities by comparing the data collection plan table TB11 with the collection results table TB12.

[0085] 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 actual collection performance, and detects an abnormality based on the index value.

[0086] Specifically, if the operation plan at time t is set to Pt, the data collection performance is set to Rt, and the threshold is set to T, the detection unit 2 calculates Rt / Pt. When Rt / Pt≤T, it is determined that the amount of vehicle information collected at time t is small. Rt / Pt is an example of the above-mentioned index value. Assuming that the threshold T is, for example, 50%, the following description is given.

[0087] [Example 1 of abnormality judgment criteria]

[0088] The detection unit 2 performs an abnormality determination for each of the above-mentioned "upload cycle of vehicle information / data type / amount of uploaded data". Specifically, for example, if "upload cycle Rt in collection performance / upload cycle Pt in operation plan ≤ 0.5" is satisfied, the detection unit 2 determines that it is abnormal.

[0089] It should be noted that regarding the “upload cycle of vehicle information” and the “amount of uploaded data”, the detection unit 2 may make a determination for each data category, or may make a determination for a plurality of data categories at once.

[0090] [Example 2 of abnormality judgment criteria]

[0091] The detection unit 2 makes an abnormality determination based on the combination of the items of "upload cycle of vehicle information / data category / amount of uploaded data". Specifically, for example, if "the number of data categories in the collection results Rt / the number of data categories in the operation plan Pt≤0.5" and "the amount of data in the collection results Rt / the amount of data in the operation plan Pt≤0.5" are satisfied, the detection unit 2 determines that it is abnormal.

[0092] Figure 6 The case where the detection unit 2 uniformly determines multiple data categories as described above is shown. In either of the examples 1 and 2 of the abnormality determination criteria, the detection unit 2 determines that an abnormality occurred from 0:00 to 12:00 in the vehicle 10 with the vehicle ID "A", an abnormality occurred from 0:00 to 12:00 in the vehicle 10 with the vehicle ID "B", an abnormality occurred from 16:00 to 20:00, and an abnormality occurred from 0:00 to 4:00 in the vehicle 10 with the vehicle ID "C".

[0093] In the case of example 1 of the abnormality determination criterion, the detection unit 2 determines that an abnormality occurred from 8 o'clock to 12 o'clock in the vehicle 10 whose vehicle ID is "C". On the other hand, in the case of example 2 of the abnormality determination criterion, in the vehicle 10 whose vehicle ID is "C", since the "amount of data uploaded" does not satisfy the condition, the detection unit 2 determines that no abnormality occurred from 8 o'clock to 12 o'clock.

[0094] In this way, according to the structure of the usage index value, in a state where vehicle information is not sent because the driver of vehicle 10 is temporarily resting, or a state where vehicle information related to the operation of the hazard warning lights is not sent because vehicle 10 is traveling on a highway, it is possible to suppress false detection of abnormalities.

[0095] It should be noted that the data collection schedule table TB11 and the data collection performance table TB12 are not limited to the structure including the upload cycle, data category and data volume of the vehicle information, and may also be a structure including a part of the upload cycle, data category and data volume. Among them, according to the structure including the upload cycle, it is possible to simply judge the abnormality related to the transmission of the vehicle information according to the number of receptions. In addition, according to the structure including the data category, it is possible to judge whether the data volume is small due to unstable communication between the vehicle 10 and the detection device 101 or the data volume is small due to the failure to upload the vehicle information of a specific data category, etc.

[0096] [Variation 1: Identification of abnormality type]

[0097] The detection unit 2 may be configured to further distinguish the type of abnormality by comparing the data collection plan table TB11 with the collection performance table TB12 .

[0098] Figure 7 This is a diagram showing an example of the types of abnormalities detected by the detection device according to the embodiment of the present disclosure.

[0099] Reference Figure 7 For example, the detection unit 2 can detect an anomaly A1 that the data category of the vehicle information from the vehicle 10 is always small, an anomaly A2 that the number of uploads of the vehicle information from the vehicle 10 is always small, an anomaly A3 that the data volume of the vehicle information from the vehicle 10 is always small, an anomaly A4 that the data category of the vehicle information from the vehicle 10 is temporarily small, an anomaly A5 that the number of uploads of the vehicle information from the vehicle 10 is temporarily small, and an anomaly A6 that the data volume of the vehicle information from the vehicle 10 is temporarily small.

[0100] Figure 8 This is a diagram showing an example of data collection results for abnormality detection in Modification 1 of the detection device according to the embodiment of the present disclosure.

[0101] Reference Figure 8 For example, the detection unit 2 may determine whether a deviation between the operation plan and the collected results occurs for each time interval, and detect an abnormality based on the frequency of occurrence of the deviation in a plurality of time intervals.

[0102] More specifically, the threshold for continuous determination is set to N, and when the time interval satisfying Rt / Pt≤T occurs N times or more in the most recent M times, the detection unit 2 determines that it is equivalent to Figure 7 Here, M is an integer greater than or equal to 2, and N is an integer less than or equal to M and greater than or equal to 2.

[0103] exist Figure 5 and Figure 8 In the example shown, when M=3 and N=2, the detection unit 2 determines that a "constant" abnormality has occurred in the vehicle 10 with the vehicle ID "A" or "B" from 0:00 to 12:00 on a certain day "X". In addition, the detection unit 2 determines that a "temporary" abnormality has occurred in the vehicle 10 with the vehicle ID "B" from 16:00 to 20:00.

[0104] In addition, the detection unit 2 determines that a "temporary" abnormality occurs in the vehicle 10 with the vehicle ID "C" from 0:00 to 4:00 and from 8:00 to 12:00. It should be noted that, as described above, in the case of Example 2 of the abnormality determination criterion, the detection unit 2 may determine that no abnormality occurs in the vehicle 10 with the vehicle ID "C" from 8:00 to 12:00.

[0105] In addition, the detection unit 2 is not limited to the above configuration. For example, when the time interval satisfying Rt / Pt≤T is continuous for more than a predetermined number of times, it may be determined that the detection unit 2 is equivalent to Figure 7 The structure of "always" described in .

[0106] Figure 8 The figure shows a case where the detection unit 2 makes a unified judgment on multiple data categories. In either case of the judgment criteria example 1 or example 2, the detection unit 2 judges that abnormalities A1 and A3 occurred from 0:00 to 12:00 in the vehicle 10 with vehicle ID "A", abnormalities A2 and A3 occurred from 0:00 to 12:00 in the vehicle 10 with vehicle ID "B", abnormalities A5 and A6 occurred from 16:00 to 20:00, and abnormalities A4 and A6 occurred from 0:00 to 4:00 in the vehicle 10 with vehicle ID "C".

[0107] In addition, in the case of example 1 of the judgment criterion, the detection unit 2 determines that the abnormality A4 occurred from 8 o'clock to 12 o'clock in the vehicle 10 whose vehicle ID is "C". On the other hand, in the case of example 2 of the judgment criterion, in the vehicle 10 whose vehicle ID is "C", the data amount does not meet the condition, so the detection unit 2 determines that no abnormality occurred from 8 o'clock to 12 o'clock.

[0108] It should be noted that the detection unit 2 is not limited to the determination Figure 7 The structure in which "always" and "temporarily" are used as the types of abnormalities may be, for example, a structure in which an abnormality is determined when a time interval satisfying Rt / Pt≤T occurs N times or more in the most recent M times, and a structure in which no abnormality occurs when it occurs less than N times.

[0109] [Variant 2: Identification of the abnormality occurrence site]

[0110] Fig. 9 This is a diagram showing an example of transmission location information used for abnormality detection in Modification 2 of the detection device involved in the embodiment of the present disclosure.

[0111] Reference Fig. 9 The detection unit 2 as a fifth acquisition unit acquires the transmission location information indicating the correspondence between the type of vehicle information and the location in the vehicle 10 .

[0112] Specifically, for example, the detection unit 2 acquires a transmission location table TB21 indicating a correspondence relationship 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 and registered in the storage unit 4, for example.

[0113] In the transmission location table TB21, the vehicle information of data category "ID1" includes data transmitted in CAN (Controller Area Network) bus 1, the vehicle information of data category "ID2" includes data transmitted in CAN bus 2, the vehicle information of data category "ID3" includes data transmitted in LIN (Local Interconnect Network), and the vehicle information of data category "ID4" includes data output from a camera connected to a USB (Universal Serial Bus).

[0114] When detecting an abnormality, the detection unit 2 specifies the location where the abnormality occurred based on the collection results, the type included in the setting information, and the transmission location information.

[0115] Specifically, in Figure 6 In the collection performance table TB12 shown, the collection performance of the vehicle 10 with the vehicle ID "A", namely, "vehicle information upload cycle / data type / uploaded data volume", is "40 times / 1 item / 30 megabytes" from 0:00 to 12:00, which is different from Figure 5 Therefore, the detection unit 2 refers to the communication log and the data category settings in the storage unit 4, and when, for example, vehicle information of data category "ID2" is obtained from the vehicle 10 but vehicle information of data category "ID1" is not obtained, it is determined that an abnormality has occurred in the CAN bus 1 in the vehicle 10.

[0116] [Variant 3: Creation of a list corresponding to divergent index values]

[0117] Fig.10 This is a diagram showing an example of list information created by Modification 3 of the detection device according to the embodiment of the present disclosure.

[0118] Reference Fig.10 Alternatively, the analyzing unit 3 may calculate an index value of the deviation between the operation plan and the collected results, and create a list of vehicles 10 that need to be dealt with abnormally based on the index value.

[0119] Specifically, the analysis unit 3 creates an index value table TB22 indicating the index value of each vehicle 10 in the desired time interval and stores it in the storage unit 4. For example, the detection unit 2 additionally registers the calculated Rt / Pt in the collection performance table TB12 in correspondence with the vehicle ID and the time interval in the collection performance table TB12. The analysis unit 3 creates the index value table TB22 using the index value Rt / Pt in the collection performance table TB12 registered by the detection unit 2.

[0120] Fig.10 The index value table TB22 shown includes Rt / Pt of upload cycle, Rt / Pt of data type and Rt / Pt of data amount in the time period from 0:00 to 4:00 on a certain day "X", and is sorted in ascending order with respect to data type and data amount.

[0121] This allows the user to easily understand that similar abnormalities have occurred in the vehicles 10 whose vehicle IDs are “A”, “X”, and “Y” and are enclosed by the frame F1 .

[0122] [Variant 4: Prompting the user to see the test result]

[0123] Fig.11 2 is a diagram showing a configuration of a fourth modification of the detection device according to the embodiment of the present disclosure. Fig.11 , the variation 4 of the detection device 101 and Figure 2 Compared with the detection device 101 shown in the figure, it further includes a setting unit 5. The communication unit 1, the detection unit 2, the analysis unit 3 and part or all of the setting unit 5 are implemented by a processing circuit including one or more processors. The storage unit 4 is, for example, a nonvolatile memory included in the above processing circuit.

[0124] The setting unit 5 creates setting information indicating setting contents of the vehicle 10 related to transmission of vehicle information, for example, based on a user's operation, and stores the setting information in the storage unit 4 .

[0125] Fig.12 This is a diagram showing an example of a setting screen displayed in Modification 4 of the detection device according to the embodiment of the present disclosure.

[0126] Reference Fig.12 The setting unit 5 creates a setting screen G1 for registering the setting information, and displays it on a terminal device (not shown) such as a notebook PC (Personal Computer). More specifically, the setting unit 5 creates screen information representing the setting screen G1, and transmits it to the terminal device via the communication unit 1 and the external network 161. The terminal device displays the setting screen G1 based on the screen information received from the setting unit 5.

[0127] The setting screen G1 includes check boxes for inputting data types of vehicle information to be acquired, and data collection cycles for each data. Fig.12 In the example shown, in the setting screen G1 showing the setting information of the vehicle A, CAN data transmitted in the CAN bus, LIN data transmitted in the LIN bus, and USB data transmitted in the USB can be selected for each bus. It should be noted that the data collection period of each data can also be input in the setting screen G1.

[0128] Specifically, the terminal device sends operation information to the detection device 101 according to the user's operation. The operation information indicates that CAN data 2 and 3 are collected with a data collection cycle of 100 milliseconds, LIN data 2 and 3 are collected with a data collection cycle of 200 milliseconds, USB data 1 is collected with a data collection cycle of 100 milliseconds, and all data are collected with a data collection cycle of 1000 milliseconds.

[0129] The setting unit 5 creates setting information based on the operation information received from the terminal device via the external network 161 and the communication unit 1, and stores it in the storage unit 4. For example, by registering the setting information in the vehicle-mounted device 202, the vehicle-mounted device 202 sends the vehicle information to the detection device 101 according to the setting content indicated by the setting information. The setting information can be registered in the vehicle-mounted device 202 by the user, or the detection device 101 can send the setting information to the vehicle-mounted device 202 for registration.

[0130] In addition, for example, the setting unit 5 calculates the assumed data volume of data uploaded from the vehicle A as the vehicle 10 based on the created setting information, and displays the calculated data volume on the setting screen G1. Fig.12 In the example shown, the assumed data size of each uploaded vehicle information sent from vehicle A is 100 kilobytes.

[0131] It should be noted that the terminal device may receive an input operation of the operation plan of the vehicle 10 by the user. In this case, the communication unit 1 receives operation information indicating the operation plan of the vehicle 10 from the terminal device, creates an operation plan table TB1 based on the received operation information, and stores it in the storage unit 4.

[0132] Fig.13 This is a diagram showing an example of a monitoring screen displayed by Modification 4 of the detection device according to the embodiment of the present disclosure.

[0133] Reference Fig.13 The detection unit 2 performs processing to display the content based on the type of vehicle information in which the abnormality has occurred on the screen.

[0134] More specifically, the detection unit 2 creates a monitoring screen G2 indicating the abnormality detection result, and displays the monitoring screen G2 on the terminal device by creating screen information indicating the monitoring screen G2 and sending it to the terminal device, for example, similarly to the setting screen G1.

[0135] The monitoring screen G2 includes the date, the assumed upload data volume, i.e., the assumed vehicle information volume uploaded from the vehicle 10 every day, the actual upload data volume, i.e., the actual vehicle information volume uploaded from the vehicle every day, and data that may not have been uploaded. In addition, the monitoring screen G2 includes the estimated cause of the abnormality and the countermeasures for the abnormality.

[0136] exist Fig.13 In the example shown, the monitoring screen G2 showing the monitoring result of the vehicle information from the vehicle A shows that the assumed uploaded data amount is 3.6 gigabytes, the actual uploaded data amount is 1.8 gigabytes, and there is a possibility that the USB data 1 or the CAN data 2, 3 may not be uploaded. In addition, the monitoring screen G2 shows that the poor connection in the USB 1 or CAN bus 1 is the cause of the abnormality, and that the driver C of the vehicle A should be contacted.

[0137] It should be noted that the detection unit 2 is not limited to a day as a unit. For example, it can be a structure that displays the assumed upload data volume and the actual upload data volume per hour, or it can be a structure that displays the assumed upload data volume and the actual upload data volume for a period up to the current time of the day.

[0138] In addition, when the detection unit 2 is configured to automatically notify the driver C of the vehicle A where the abnormality has occurred of the abnormality detection result, the monitoring screen G2 may display, for example, the meaning of contacting the driver C of the vehicle A, or the meaning of lighting the abnormality light of the machine in the vehicle 10.

[0139] In the embodiments of the present disclosure including Modification 4, the vehicle-mounted device 202 is, as an example, a device that is installed on the vehicle 10 after the vehicle 10 leaves the factory. Compared with conventional devices, various faults caused by the after-market devices are assumed in the after-market devices, and according to the configuration of displaying the monitoring screen G2 as described above, for example, when a fault occurs in the after-market device, even an inexperienced user can easily grasp the abnormality of the vehicle-mounted device 202. As a result, the cause of the fault can be efficiently distinguished, for example, the after-market devices that are the object of recycling can be reduced, and the burden of recycling work can be reduced.

[0140] [Action flow]

[0141] Fig.14 This is a flowchart that defines the operation process when the detection device according to the embodiment of the present disclosure detects an abnormality in a vehicle. Fig.14 Shows the use of Figure 3 Description of the process.

[0142] Reference Fig.14 ,First, the detection device 101 collects vehicle information from one or more vehicles 10, creates and saves a communication log (step S1).

[0143] Next, the detection device 101 collects vehicle information until data for a certain period is collected ("No" in step S2). When data for a certain period is collected ("Yes" in step S2), a collection performance table TB2 showing the collection performance of vehicle information is created (step S3).

[0144] Next, the detection device 101 acquires the operation plan table TB1 indicating the operation plan of the vehicle 10 from the storage unit 4 (step S4 ), and detects abnormality by comparing the collection performance table TB2 with the operation plan table TB1 (step S5 ).

[0145] When the detection device 101 determines that no abnormality has occurred (No in step S6 ), it continues to collect vehicle information (step S1 ).

[0146] On the other hand, when the detection device 101 determines that an abnormality has occurred (YES in step S6 ), it outputs the detection result (step S7 ) and continues to collect vehicle information (step S1 ).

[0147] Fig.15 This is a flowchart that defines the operation process when the detection device according to the embodiment of the present disclosure detects an abnormality in a vehicle. Fig.15 Another example of the above abnormality detection process is shown. Fig.15 The processing of Modifications 1 and 2 is also included.

[0148] Reference Fig.15 ,First, the detection device 101 collects vehicle information from one or more vehicles 10, creates and saves a communication log (step S11).

[0149] Next, the detection device 101 collects vehicle information until data for a certain period is collected ("No" in step S12). When data for a certain period is collected ("Yes" in step S12), a collection performance table TB12 indicating the collection performance of vehicle information is created (step S13).

[0150] 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 ).

[0151] Next, the detection device 101 obtains the operation plan table TB1 representing the operation plan of the vehicle 10 from the storage unit 4 (step S16), and creates a data collection plan table TB11 representing the collection plan of vehicle information from the vehicle 10 based on the operation plan and setting information, specifically, based on the operation plan table TB1 and the sending data table TB10 (step S17).

[0152] Next, the detection device 101 detects an abnormality and determines the type of abnormality by comparing the collection performance table TB12 with the data collection plan table TB11 (step S18 ).

[0153] When the detection device 101 determines that no abnormality has occurred (No in step S19 ), it continues to collect vehicle information (step S11 ).

[0154] On the other hand, when the detection device 101 determines that an abnormality has occurred ("Yes" in step S19), it obtains the transmission location table TB21 indicating the transmission location of the vehicle information from the storage unit 4 (step S20), and determines the location where the abnormality occurred based on the setting content of the data category shown in the collection performance table TB12 and the sending data table TB10 and the transmission location table TB21 (step S21).

[0155] Next, the detection device 101 outputs the detection result indicating the type of abnormality and the location of the abnormality (step S22), and continues to collect vehicle information (step S11). It should be noted that the detection device 101 may also display the monitoring screen G2 (step S22).

[0156] Fig.16 This is a flowchart that specifies the operation procedure when creating list information in Modification 3 of the detection device according to the embodiment of the present disclosure.

[0157] Reference Fig.16 First, the detection device 101 acquires the abnormality detection result of each vehicle 10 from the storage unit 4 (step S31).

[0158] Next, the detection device 101 acquires 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 storage unit 4 (step S32 ).

[0159] Next, the detection device 101 uses the index value Rt / Pt in the collection performance table TB12 to create a summary information, such as Fig.10 The index value table TB22 shown is stored in the storage unit 4 (step S33).

[0160] It should be noted that part or all of the functions of the detection device 101 may be provided by cloud computing. In other words, the detection device according to the embodiment of the present disclosure may be a cloud server composed of a plurality of servers.

[0161] Each process (function) of the above-mentioned embodiment is implemented by a processing circuit (Circuitry) including one or more processors. It is also possible that the above-mentioned processing circuit is composed of an integrated circuit that combines one or more memories, various analog circuits and various digital circuits in addition to the above-mentioned one or more processors. The above-mentioned one or more memories store programs (commands) that enable the above-mentioned one or more processors to perform the above-mentioned processes. The above-mentioned one or more processors can perform the above-mentioned processes according to the above-mentioned programs read from the above-mentioned one or more memories, or according to the logic circuits pre-designed to perform the above-mentioned processes. The above-mentioned processor can be a CPU (Central Processing Unit: Central Processing Unit), GPU (Graphics Processing Unit: Graphics Processing Unit), DSP (Digital Signal Processor: Digital Signal Processor), FPGA (Field Programmable Gate Array: Field Programmable Gate Array) and ASIC (Application Specific Integrated Circuit: Application Specific Integrated Circuit) and other various processors suitable for computer control. It should be noted that it is also possible that the above-mentioned multiple processors separated physically cooperate with each other to perform the above-mentioned processes. For example, the processors installed in physically separated computers may cooperate with each other via a network such as a LAN (Local Area Network), a WAN (Wide Area Network), and the Internet to perform the above-mentioned processing. The above-mentioned program may be installed in the above-mentioned memory from an external server device or the like via the above-mentioned network, or may be circulated in a state stored in a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), and a semiconductor memory, and installed in the above-mentioned memory from the above-mentioned recording medium.

[0162] The above embodiments should be considered in all respects as illustrative rather than restrictive. The scope of the present invention is indicated by the claims rather than the above description, and is intended to include all modifications within the meaning and scope equivalent to the claims.

[0163] The above description includes the following additional features.

[0164] [Note 1]

[0165] A detection device, comprising:

[0166] A first acquisition unit, which acquires information including identification information of the vehicle, that is, vehicle information related to the vehicle, from the vehicle;

[0167] a second acquisition unit, which acquires the collection performance of the vehicle information acquired by the first acquisition unit;

[0168] a third acquisition unit, which acquires an operation plan of the vehicle corresponding to the identification information; and

[0169] a detection unit that detects an abnormality related to the vehicle based on the collected performance and the operation plan,

[0170] The detection device further comprises:

[0171] an analyzing unit, the analyzing unit creating a collection plan for the vehicle information based on the setting information and the operation plan,

[0172] The detection unit compares the collection plan and the actual collection performance, and detects an abnormality related to the vehicle based on a comparison result.

[0173] [Note 2]

[0174] A detection device, comprising a processing circuit,

[0175] The processing circuit

[0176] acquiring information including identification information of the vehicle, that is, vehicle information related to the vehicle, from the vehicle;

[0177] acquiring the collection performance of the vehicle information acquired by the first acquisition unit,

[0178] acquiring an operation plan of the vehicle corresponding to the identification information,

[0179] Based on the collected results and the operation plan, abnormality related to the vehicle is detected.

[0180] Description of Reference Numerals

[0181] 1 Ministry of Communications

[0182] 2. Detection Department

[0183] 3. Analysis Department

[0184] 4 Storage

[0185] 5. Setting section

[0186] 10 Vehicles

[0187] 101 Detection Device

[0188] 102 Vehicle-mounted devices

[0189] 161 External Network

[0190] 202 Vehicle-mounted device

[0191] 301 Communication System

[0192] A1, A2, A3, A4, A5, A6 abnormal

[0193] F1 box

[0194] TB1 Operation Schedule

[0195] TB10 Send Data Table

[0196] TB11 Data Collection Schedule

[0197] TB2, 12 Collection Performance Table

[0198] TB21 Transmission Location Table

[0199] TB22 indicator value table.

Claims

1. A detection device comprising: A first acquisition unit, which acquires information including identification information of the vehicle, that is, vehicle information related to the vehicle, from the vehicle; a second acquisition unit, which acquires the collection performance of the vehicle information acquired by the first acquisition unit; a third acquiring unit, which acquires an operation plan of the vehicle corresponding to the identification information; as well as The detection unit detects an abnormality related to the vehicle based on the collected performance and the operation plan.

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

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

4. The detection device according to claim 2 or 3, wherein: The setting information includes the type of the vehicle information sent by the vehicle, The detection device further comprises: a fifth acquisition unit that acquires transmission location information indicating a correspondence between the type and a transmission location of the vehicle information in the vehicle, When the abnormality is detected, the detection unit specifies a location where the abnormality has occurred based on the collection performance, the type included in the setting information, and the transmission location information.

5. The detection device according to any one of claims 1 to 4, wherein: The operation plan is divided into multiple time intervals. The detection unit determines whether a deviation between the operation plan and the collected results has occurred for each of the time periods, and detects the abnormality based on the occurrence frequency of the deviation in a plurality of the time periods.

6. The detection device according to any one of claims 1 to 5, wherein: The detection device further comprises: An analyzing unit calculates an index value of a deviation between the operation plan and the collected results, and creates a list of the vehicles that need to deal with the abnormality based on the index value.

7. The detection device according to any one of claims 2 to 4, wherein: The setting information includes the type of the vehicle information sent by the vehicle, The detection unit performs a process of displaying, on a screen, content based on the type of the vehicle information in which the abnormality has occurred.

8. A detection system comprising: On-vehicle device, mounted on a vehicle; and Detection device, The vehicle-mounted device sends information including identification information of the vehicle, that is, vehicle information related to the vehicle, to the detection device. The detection device detects an abnormality related to the vehicle based on the collection performance of the vehicle information in the detection device and an operation plan of the vehicle corresponding to the identification information.

9. A detection method is a detection method in a detection device, the detection method comprising the following steps: Acquiring information including identification information of the vehicle, that is, vehicle information related to the vehicle, from the vehicle; Acquiring the collection performance of the vehicle information acquired by the detection device; acquiring an operation plan of the vehicle corresponding to the identification information; as well as An abnormality related to the vehicle is detected based on the collected results and the operation plan.

10. A detection program is a detection program used in a detection device, The detection program is used to make the computer function as the following components: A first acquisition unit, which acquires information including identification information of the vehicle, that is, vehicle information related to the vehicle, from the vehicle; a second acquisition unit, which acquires the collection performance of the vehicle information acquired by the first acquisition unit; a third acquiring unit, which acquires an operation plan of the vehicle corresponding to the identification information; as well as The detection unit detects an abnormality related to the vehicle based on the collected performance and the operation plan.

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