Vehicle management device, vehicle management method, vehicle management program

Abstract

The present invention relates to a vehicle management device, a vehicle management method, and a vehicle management program. The vehicle management device (1) for managing the state of a vehicle (2) having a drive system (7) for applying acceleration, a braking system (8) for applying deceleration, and a steering control system (9) for applying steering as basic functional systems (6) includes: an abnormality determination unit (100) that determines the presence or absence of a driving abnormality predicted to be related to a characteristic change of the basic functional systems (6) in a management target scenario (M) in which the driving direction changes in an autonomous driving mode during the driving scenario of the vehicle; and a designated output unit (120) that designates, from among a plurality of components constituting the basic functional systems (6), a replacement request component (X) that requests replacement according to the determined driving abnormality.

Description

[0001] Cross - reference to related applications

[0002] This application is based on Japanese Patent Application No. 2020 - 133994 filed in Japan on August 6, 2020, and Japanese Patent Application No. 2021 - 89555 filed in Japan on May 27, 2021, and the entire contents of the base applications are incorporated herein by reference. Technical field

[0003] The present disclosure relates to a vehicle management device, a vehicle management method, and a vehicle management program. Background art

[0004] Conventionally, in Patent Document 1, a vehicle motion control technique for suppressing a decrease in follow - up to a target trajectory in a vehicle has been proposed.

[0005] On the other hand, in Patent Document 2, a management system for replacing axle components of a vehicle has been proposed.

[0006] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2018 - 131042

[0007] Patent Document 2: Japanese Unexamined Patent Application Publication No. 2001 - 34405

[0008] In a technique such as that in Patent Document 1, in which an autonomous driving vehicle follows a target based on the actual driving position, there is a concern that problems may occur when the vehicle is traveling on a curved road or making a left - or right - hand turn where the driving direction of the vehicle changes. Regarding this problem, for example, during the follow - up control time such as the time to obtain the difference between the target trajectory and the actual trajectory, the time to estimate the actual driving position, the time to readjust the correction trajectory, or the time for the vehicle to follow the correction trajectory, there is a concern that the vehicle may travel on an actual trajectory that deviates from the target trajectory. In addition, during such follow - up control time, there is a concern that the ride comfort of the occupants may deteriorate due to a sudden change or oscillation of the actual trajectory.

[0009] Here, for example, in a driving environment where it is necessary to avoid collisions with vehicles or pedestrians, or in a driving environment with large restrictions on traffic flow, etc., improving the target follow - up performance becomes an important issue. In addition, for example, in a driving environment where there are traffic participants who act while predicting the movement direction of the vehicle, etc., there is also a concern that a sudden change or oscillation of the actual trajectory due to a decrease in target follow - up performance may cause traffic participants to misunderstand the vehicle movement prediction.

[0010] As a result of in-depth research in such a situation, the inventors found that in a vehicle in autonomous driving mode, it is difficult to grasp driving, braking, and steering operations through the five senses of the occupants. Therefore, when characteristic changes such as aging deterioration occur in the components constituting these three functions, it becomes a factor in reducing target followability.

[0011] Therefore, in the case of replacing components according to Patent Document 2, since it is impossible to trace the cause starting from the grasp by the five senses of the occupants in a vehicle in autonomous driving mode, it is difficult for the occupants themselves to specify replacement components suitable for eliminating the characteristic changes. In particular, since the components related to driving, braking, and steering operations involve multiple aspects, the number of combinations of replacement components corresponding to different characteristic changes becomes huge, and it is extremely difficult for the occupants to specify. Also, in a vehicle in autonomous driving mode where the opportunity to adjust the movement changes after replacement based on the five senses of the occupants is limited, the requirement for the fitness of the replacement components becomes strict.

[0012] Furthermore, in a vehicle in autonomous driving mode, not only regarding the update by replacing components related to driving, braking, and steering operations, but also regarding the update by setting and changing control parameters for controlling driving to control the driving state, braking state, and steering operation state, the requirement for the fitness after the update becomes strict. Summary of the Invention

[0013] Based on the above, the subject of the present disclosure is to provide a vehicle management device that appropriately manages the state of a vehicle in order to ensure target followability. Another subject of the present disclosure is to provide a vehicle management method that appropriately manages the state of a vehicle in order to ensure target followability. Still another subject of the present disclosure is a vehicle management program that appropriately manages the state of a vehicle in order to ensure target followability.

[0014] Hereinafter, the technical means of the present disclosure for solving the subject will be described.

[0015] The first aspect of the present disclosure is a vehicle management device that manages the state of a vehicle having a drive system that applies acceleration, a braking system that applies deceleration, and a steering system that applies steering as basic functional systems, and includes:

[0016] An abnormality determination unit that determines the presence or absence of a driving abnormality predicted to be related to a characteristic change of the basic functional system in a management target scenario of a driving direction change in autonomous driving mode in the driving scenario of the vehicle; and

[0017] A specified output unit that specifies and outputs a replacement request component that is requested to be replaced according to the determined driving abnormality from among a plurality of components constituting the basic functional system.

[0018] A second aspect of the present disclosure is a vehicle management method for managing the state of a vehicle that includes a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic functional systems, including:

[0019] In a management target scenario of a driving direction change in an autonomous driving mode in a driving scenario of the vehicle, an abnormality determination step of determining the presence or absence of a driving abnormality predicted to be related to a characteristic change of the basic functional system; and

[0020] A designated output step of designating, from among a plurality of components constituting the basic functional system, a replacement request component that requests replacement according to the determined driving abnormality.

[0021] A third aspect of the present disclosure is a vehicle management program including commands that cause a processor to execute in order to manage the state of a vehicle that includes a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic functional systems,

[0022] The commands include:

[0023] In a management target scenario of a driving direction change in an autonomous driving mode in a driving scenario of the vehicle, an abnormality determination step of determining the presence or absence of a driving abnormality predicted to be related to a characteristic change of the basic functional system; and

[0024] A designated output step of designating, from among a plurality of components constituting the basic functional system, a replacement request component that requests replacement according to the determined driving abnormality.

[0025] According to these first to third aspects, in a management target scenario of a driving direction change in an autonomous driving mode in a driving scenario of the vehicle, the presence or absence of a driving abnormality predicted to be related to a characteristic change of the basic functional system as a drive system, a braking system, and a steering control system is determined. Therefore, in the first to third aspects, from among a plurality of components constituting the basic functional system, a replacement request component that requests replacement according to the determined driving abnormality is designated and output. As a result, even if a driving abnormality related to a characteristic change of the basic functional system for left and right target followability occurs along with a driving direction change of the vehicle in an autonomous driving mode that requires target followability, it is possible to notify, by designated output, a replacement request component for eliminating the driving abnormality. Therefore, it is possible to appropriately manage the state of the vehicle in order to ensure target followability.

[0026] A fourth aspect of the present disclosure is a vehicle management device having a processor for managing the state of a vehicle that includes a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic functional systems,

[0027] The processor is configured to execute:

[0028] Determine the presence or absence of driving changes predicted to be related to changes in the characteristics of the basic function system in the autonomous driving mode of the vehicle; and

[0029] Apply a mitigation process to the vehicle to mitigate the driving changes by updating the basic function system that matches the determined driving changes.

[0030] The fifth aspect of the present disclosure is a vehicle management method executed by a processor to manage the state of a vehicle equipped with a drive system for applying acceleration, a braking system for applying deceleration, and a steering system for applying steering as basic function systems, including:

[0031] Determine the presence or absence of driving changes predicted to be related to changes in the characteristics of the basic function system in the autonomous driving mode of the vehicle; and

[0032] Apply a mitigation process to the vehicle to mitigate the driving changes by updating the basic function system that matches the determined driving changes.

[0033] The sixth aspect of the present disclosure is a vehicle management program stored in a storage medium and including commands executed by a processor for managing the state of a vehicle equipped with a drive system for applying acceleration, a braking system for applying deceleration, and a steering system for applying steering as basic function systems,

[0034] The commands include:

[0035] Determine the presence or absence of driving changes predicted to be related to changes in the characteristics of the basic function system in the autonomous driving mode of the vehicle; and

[0036] Apply a mitigation process to the vehicle to mitigate the driving changes by updating the basic function system corresponding to the determined driving changes.

[0037] According to these fourth to sixth aspects, in the autonomous driving mode of the vehicle, the presence or absence of driving changes predicted to be related to changes in the characteristics of the basic function systems of the drive system, the braking system, and the steering system is determined. Therefore, in the fourth to sixth aspects, a mitigation process for mitigating the driving changes is implemented on the vehicle by updating the basic function system that matches the determined driving changes. Thereby, in the autonomous driving mode that requires target followability, even if driving changes related to changes in the characteristics of the basic function systems for left and right target followability occur, a mitigation process can be performed to eliminate the driving changes. Therefore, the state of the vehicle can be appropriately managed to ensure target followability.

[0038] A seventh aspect of the present disclosure is a vehicle management device having a processor that manages the state of a vehicle having a drive system that applies acceleration, a braking system that applies deceleration, and a steering system that applies steering as basic functional systems.

[0039] The processor is configured to execute:

[0040] Determining whether there is a characteristic change in a basic functional system predicted to cause a driving change in the autonomous driving mode of the vehicle; and

[0041] Applying a mitigation process for mitigating driving changes to the vehicle by updating the basic functional system corresponding to the determined characteristic change.

[0042] An eighth aspect of the present disclosure is a vehicle management method executed by a processor for managing the state of a vehicle having a drive system that applies acceleration, a braking system that applies deceleration, and a steering system that applies steering as basic functional systems, including:

[0043] Determining whether there is a characteristic change in a basic functional system predicted to cause a driving change in the autonomous driving mode of the vehicle; and

[0044] Applying a mitigation process for mitigating driving changes to the vehicle by updating the basic functional system corresponding to the determined characteristic change.

[0045] A ninth aspect of the present disclosure is a vehicle management program stored in a storage medium and including commands executed by a processor for managing the state of a vehicle having a drive system that applies acceleration, a braking system that applies deceleration, and a steering system that applies steering as basic functional systems.

[0046] The commands include:

[0047] Determining whether there is a characteristic change in a basic functional system predicted to cause a driving change in the autonomous driving mode of the vehicle; and

[0048] Applying a mitigation process for mitigating driving changes to the vehicle by updating the basic functional system matching the determined characteristic change.

[0049] According to these seventh to ninth aspects, in the autonomous driving mode of the vehicle, it is determined whether there is a characteristic change predicted to cause a driving change in the basic functional systems of the drive system, the braking system, and the steering control system. Therefore, in the seventh to ninth aspects, a mitigation process for mitigating the driving change is applied to the vehicle by updating the basic functional systems in accordance with the determined characteristic change. Thus, in the autonomous driving mode that requires target following performance, even if a characteristic change occurs in the basic functional systems related to the left and right target following performance, a mitigation process can be performed to eliminate the driving change associated with the characteristic change. Therefore, it is possible to appropriately manage the state of the vehicle in order to ensure target following performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a block diagram showing the overall configuration of the vehicle management device according to the first embodiment.

[0051] Figure 2 is a schematic diagram showing the vehicle and the component parts of the basic functional systems on which the vehicle management device according to the first embodiment is mounted.

[0052] Figure 3 is a block diagram showing the functional configuration of the vehicle management device according to the first embodiment.

[0053] Figure 4 is a schematic diagram showing the management target scenarios of the vehicle management device according to the first embodiment.

[0054] Figure 5 is a schematic diagram showing the management target scenarios of the vehicle management device according to the first embodiment.

[0055] Figure 6 is a schematic diagram showing the management target scenarios of the vehicle management device according to the first embodiment.

[0056] Figure 7 is a schematic diagram showing the management target scenarios of the vehicle management device according to the first embodiment.

[0057] Figure 8 is a schematic diagram for explaining the track following abnormality of the vehicle management device according to the first embodiment.

[0058] Figure 9 is a schematic diagram for explaining the speed following abnormality of the vehicle management device according to the first embodiment.

[0059] Figure 10 is a schematic diagram for explaining the track following abnormality of the vehicle management device according to the first embodiment.

[0060] Figure 11It is a schematic diagram for explaining the track following abnormality of the vehicle management device of the first embodiment.

[0061] Figure 12 It is a schematic diagram for explaining the speed following abnormality of the vehicle management device of the first embodiment.

[0062] Figure 13 It is a schematic diagram for explaining the speed following abnormality of the vehicle management device of the first embodiment.

[0063] Figure 14 It is a schematic diagram for explaining the speed following abnormality of the vehicle management device of the first embodiment.

[0064] Figure 15 It is a flowchart for explaining the factor prediction of the vehicle management device of the first embodiment.

[0065] Figure 16 It is a schematic diagram for explaining the designated output of the vehicle management device of the first embodiment.

[0066] Figure 17 It is a schematic diagram for explaining the designated output of the vehicle management device of the first embodiment.

[0067] Figure 18 It is a flowchart for explaining the designated output of the vehicle management device of the first embodiment.

[0068] Figure 19 It represents Figure 18 a flowchart of a modified example of

[0069] Figure 20 It is a schematic diagram for explaining the designated output of the vehicle management device of the first embodiment.

[0070] Figure 21 It is a schematic diagram for explaining the designated output of the vehicle management device of the first embodiment.

[0071] Figure 22 It is a flowchart showing the vehicle management method of the first embodiment.

[0072] Figure 23 It is a block diagram showing the detailed structure of the vehicle management device of the second embodiment.

[0073] Figure 24 It is a schematic diagram for explaining the learning of the vehicle management device of the second embodiment.

[0074] Figure 25 It is a block diagram showing the functional structure of the vehicle management device of the third embodiment.

[0075] Figure 26 It is a flowchart showing the vehicle management method of the third embodiment.

[0076] Figure 27 It is a block diagram showing the functional structure of the vehicle management device of the fourth embodiment.

[0077] Figure 28 It is a flowchart showing the vehicle management method of the fourth embodiment.

[0078] Figure 29 It is a schematic diagram showing a modification example of the first to fourth embodiments. Detailed Embodiments

[0079] Hereinafter, a plurality of embodiments will be described based on the drawings. In addition, sometimes the same reference numerals are attached to corresponding components in each embodiment to omit redundant descriptions. In addition, when only a part of the configuration is described in each embodiment, the other parts of the configuration can be applied to the configurations of other previously described embodiments. Moreover, not only the combinations of the configurations explicitly shown in the description of each embodiment, but also the configurations of multiple embodiments can be partially combined with each other without particular hindrance even if not explicitly shown.

[0080] (First Embodiment)

[0081] Figure 1 The vehicle management device 1 of the first embodiment shown manages the state of the vehicle 2. The vehicle 2 is, for example, a passenger car, an industrial vehicle, an emergency vehicle, or a micro-mobility device. The vehicle 2 can stably or temporarily travel automatically in an autonomous driving mode based on autonomous driving control or highly automated driving assistance control. In particular, in the autonomous driving mode of the vehicle 2 based on autonomous driving control, when achieving a conditional autonomous driving level of level 3 or higher defined in the system for performing all dynamic driving tasks in a limited area, the vehicle management device 1 is preferred.

[0082] As Figure 2As shown in the figure, a drive system 7, a braking system 8, and a steering control system 9 are mounted on the vehicle 2 as basic functional systems 6. The drive system 7 is composed of components for accelerating the vehicle 2. The components constituting the drive system 7 are, for example, multiple types among a tire 60, a battery 61, an accelerator pedal 70, a drive motor 71, a drive engine, a start switch, a transmission, a shift unit, and the like. The braking system 8 is composed of components for decelerating the vehicle 2. The components constituting the braking system 8 are, for example, multiple types among a tire 60, a battery 61, a brake pedal 80, a friction braking unit 81, an oil pressure circuit, a regeneration motor, and the like. Here, the so-called friction braking unit 81 includes at least one of a brake shoe and a brake drum. The steering control system 9 is composed of components for steering the vehicle 2. The components constituting the steering control system 9 are, for example, multiple types among a tire 60, a battery 61, a steering wheel 90, a steering unit, a power steering motor, and the like.

[0083] In the above content, the components of each of the systems 7 to 9 constituting the basic functional system 6 can also be shared between at least two systems, such as the tire 60 and the battery 61 as described above. Here, the battery 61 includes, for example, a lead-acid battery or a lithium-ion battery. In addition, the components of each of the systems 7 to 9 constituting the basic functional system 6 can also be subdivided to the level of bolts, nuts, screws, or electrical wirings.

[0084] As Figure 1 , 3 shown in the figure, a sensor system 3 is mounted on the vehicle 2. The sensor system 3 acquires various information for driving control in the vehicle 2, such as for an autonomous driving mode. The sensor system 3 is configured to include an external sensor 30 and an internal sensor 31.

[0085] The external sensor 30 generates information on the external environment that is the surroundings of the vehicle 2. The external sensor 30 can also generate external information by detecting an object existing in the external environment of the vehicle 2. Such an object detection type external sensor 30 is, for example, at least one type among a camera, LiDAR (Light Detection and Ranging / Laser Imaging Detection and Ranging), radar, sonar, and the like. The external sensor 30 can also generate external information by receiving a signal from an artificial satellite of GNSS (Global Navigation Satellite System) or a roadside device of ITS (Intelligent Transport Systems) existing in the external environment of the vehicle 2. Such a signal reception type external sensor 30 is, for example, at least one type among a GNSS receiver and a telematics receiver.

[0086] The internal sensor 31 generates information on the internal environment that is the interior of the vehicle 2. The internal sensor 31 can also generate internal information by detecting a specific motion physical quantity in the interior of the vehicle 2. Such a physical quantity detection type internal sensor 31 is, for example, at least one type among a traveling speed sensor, an acceleration sensor, a Doppler speed sensor, a Bernoulli fluid speed sensor, a gyro sensor, a tire monitor, and a brake monitor. The internal sensor 31 can also generate internal information by detecting a specific state related to the occupant in the interior of the vehicle 2. Such an occupant state detection type internal sensor 31 is, for example, at least one type among a driver state monitor, an actuator sensor, and an in-vehicle machine sensor.

[0087] Here, the driver state monitor, for example, detects at least one type among the direction of the face, drowsiness, and posture as the state of the occupant driving the vehicle 2. The actuator sensor, for example, detects at least one type among the operation position of the pedals 70 and 80, the steering angle of the steering wheel 90, the on / off state of the start switch, and the shift position of the shift lever as the instruction state of the occupant related to the driving actuator of the basic function system 6 in the vehicle 2. The in-vehicle machine sensor, for example, detects at least one type among the operation state of the on / off switch, the operation state of the touch panel, and a gesture operation that can be non-contact recognized as the operation state of the occupant related to the in-vehicle machine.

[0088] A map unit 4 is mounted on the vehicle 2. The map unit 4 non-temporarily stores map information for driving control including an autonomous driving mode in the vehicle 2. The map unit 4 is configured to include at least one type of non-transitory tangible storage medium such as a semiconductor memory, a magnetic medium, and an optical medium. The map unit 4 may also be a database of a locator that estimates state quantities of the vehicle 2 including its own position. The map unit 4 may also be a database of a navigation unit that navigates a driving path of the vehicle 2. The map unit 4 may also be composed of a combination of multiple types of these databases or the like.

[0089] The map unit 4 obtains and stores the latest map information, for example, by wireless communication with the outside of the vehicle 2. Here, the map information is digitized two-dimensionally or three-dimensionally as information representing the driving environment of the vehicle 2. The map information may, for example, also include at least one type of road information such as the position, shape, and road surface condition of the road itself. The map information may, for example, also represent at least one type of identification information such as the position and shape of signs and dividing lines attached to the road. The map information may, for example, also include at least one type of structure information such as the position and shape of buildings and traffic lights facing the road.

[0090] An information presentation system 5 is mounted on the vehicle 2. The information presentation system 5 presents various types of information to the passengers of the vehicle 2. The information presentation system 5 is configured to include a visual presentation unit 50 and an auditory presentation unit 51.

[0091] The visual presentation unit 50 transmits presentation target information by stimulating the vision of the passengers. The visual presentation unit 50 is, for example, at least one type of HUD (Head-up Display), MFD (Multi Function Display), combination meter, and navigation unit. The auditory presentation unit 51 transmits presentation target information by stimulating the hearing of the passengers. The auditory presentation unit 51 is, for example, at least one type of speaker, buzzer, and vibration unit.

[0092] The information presentation system 5 may also be provided outside the vehicle 2, for example, by using wireless communication, separately from the mounting units 50 and 51 mounted on the vehicle 2. The installation location of the information presentation system 5 in this case is, for example, at least one of a repair shop, a dealership, and a remote assistance center. In addition, as the information presentation system 5, a mobile terminal that can perform visual presentation and auditory presentation and is separate from the mounting units 50 and 51 mounted on the vehicle 2 and owned by the passengers may also be added.

[0093] Figure 1The vehicle management device 1 shown, for example, is connected to the sensor system 3, the map unit 4, and the information presentation system 5 via at least one of a LAN (Local Area Network), a wiring harness, an in-vehicle bus, and the like. The vehicle management device 1 is configured to include at least one dedicated computer. The dedicated computer that constitutes the vehicle management device 1 may also be a drive control ECU (Electronic Control Unit) that implements drive control including an autonomous driving mode in the vehicle 2. The dedicated computer that constitutes the vehicle management device 1 may also be an actuator ECU that independently controls the drive actuators of the basic function system 6 in the vehicle 2. The dedicated computer that constitutes the vehicle management device 1 may also be a locator ECU that estimates the state quantity of the vehicle 2 including its own position. The dedicated computer that constitutes the vehicle management device 1 may also be a navigation ECU that navigates the travel path of the vehicle 2. The dedicated computer that constitutes the vehicle management device 1 may also be an HCU (HMI (Human Machine Interface) Control Unit) that controls the information presentation of the information presentation system 5.

[0094] The dedicated computer that constitutes the vehicle management device 1 each has at least one memory 10 and a processor 12. The memory 10 is a non-transitory physical storage medium such as at least one of a semiconductor memory, a magnetic medium, and an optical medium that non-temporarily stores computer-readable programs, data, and the like (non-transitory tangible storage medium). The processor 12 includes, for example, at least one of a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and a RISC (Reduced Instruction Set Computer)-CPU as a core.

[0095] The processor 12 executes a plurality of commands included in the vehicle program stored in the memory 10. Thereby, the vehicle management device 1 constructs a plurality of functional units (i.e., functional modules) for managing the state of the vehicle 2. Thus, in the vehicle management device 1, a plurality of functional units are constructed by causing the processor 12 to execute a plurality of commands by the vehicle management program stored in the memory 10 for managing the state of the vehicle 2. Among the plurality of functional units constructed by the vehicle management device 1, as Figure 3 shown, an abnormality determination unit 100 and a specified output unit 120 are included.

[0096] The abnormality determination unit 100 determines, in the driving scenario of the vehicle 2, such as Figures 4 - 7The presence or absence of a predicted driving anomaly in the management object scenario M as shown here. Here, the management object scenario M is defined, for example, as a driving scenario in a curved driving area where the driving direction in the autonomous driving mode changes according to the curvature shape of the driving road or when passing through an intersection, etc. Specifically, as Figures 4 - 6 shown, the management object scenario M includes a driving scenario in which the changed driving direction is inclined by 45 degrees or more with respect to the driving direction before the change. Additionally, particularly, as Figure 7 shown, the management object scenario M includes a driving scenario in which the number of lanes in the changed driving direction is multiple.

[0097] The so-called driving anomaly determined by the anomaly determination unit 100 means an anomaly predicted to be related to the characteristic changes caused in each of the systems 7 to 9 of the basic function system 6 in the management object scenario M. Additionally, the so-called characteristic changes related to such a driving anomaly mean that the characteristics (i.e., performance) of the components constituting each of the systems 7 to 9 vary from the initial characteristics, for example, due to aging deterioration, etc. In view of these meanings, the driving anomaly includes, for each characteristic change of each of the systems 7 to 9 in the assumed management object scenario M, or for each combination of two of these characteristic changes, candidates for anomalies that can be obtained from the results of analyzing past data such as big data and are pre-predicted. Therefore, as Figure 8 , 9 shown, the anomaly determination unit 100 determines the presence or absence of the driving anomaly by taking at least one of the following anomalies Rt and Rv as the driving anomaly.

[0098] As Figure 8 shown, the trajectory following anomaly Rt is an anomaly of the target following performance in which the difference Δ related to the target trajectory Tt of the vehicle 2 and the actual driving position Pr goes outside the allowable range. Therefore, the anomaly determination unit 100 that determines the trajectory following anomaly Rt obtains the target trajectory Tt based on the target value, that is, the target parameter, of the driving parameter that controls the driving of the vehicle 2 in the autonomous driving mode. Additionally, the anomaly determination unit 100 that determines the trajectory following anomaly Rt obtains the actual driving position Pr based on the acquired information from at least one of the object detection type and the signal reception type of the external sensor 30, or the matching of such acquired information with the map information of the map unit 4 (for example, including the result of self-position estimation, etc.).

[0099] The abnormality determination unit 100 determines the track following abnormality Rt based on the target track Tt and the actual traveling position Pr obtained in this way. At this time, the abnormality determination unit 100 may also use the sum or average of the differences Δ between the actual track Tr formed by interpolating multiple actual traveling positions Pr within the set interval and the target track Tt within the set interval for the determination of the track following abnormality Rt to improve the determination accuracy. Alternatively, the abnormality determination unit 100 may use the difference Δ between the actual traveling position Pr and the representative point corresponding to the actual traveling position Pr on the target track Tt for the determination of the track following abnormality Rt to save the determination operation resources.

[0100] The allowable range of the difference Δ for the track following abnormality Rt is defined as a range below the threshold value or less than the threshold value. Under this definition, the abnormality determination unit 100 makes a provisional determination of the existence of the track following abnormality Rt by the difference Δ going out of the allowable range, that is, exceeding the threshold value or being above the threshold value. At this time, as Figure 10 shown, it is also possible that if the difference Δ is outside the allowable range for each control timing, the abnormality determination unit 100 makes a provisional determination. Alternatively, as Figure 11 shown, it is also possible that if the difference Δ is outside the allowable range continuously or on average at multiple control timings, the abnormality determination unit 100 makes a provisional determination.

[0101] On the other hand, as Figure 9 shown, the speed following abnormality Rv is a target following abnormality different from the track following abnormality Rt in which the difference δ related to the target speed Vt and the actual traveling speed Vr of the vehicle 2 goes out of the allowable range. Therefore, the abnormality determination unit 100 that determines the speed following abnormality Rv obtains the target speed Vt based on the target parameters for controlling the driving of the vehicle 2 in the autonomous driving mode. In addition, the abnormality determination unit 100 that determines the speed following abnormality Rv obtains the actual traveling speed Vr based on the acquired information from the physical quantity detection type internal sensor 31.

[0102] The abnormality determination unit 100 determines the speed following abnormality Rv based on the target speed Vt and the actual traveling speed Vr obtained in this way. At this time, the abnormality determination unit 100 may also use the difference δ between the target speed Vt and the actual traveling speed Vr at one time series point for the determination of the track following abnormality Rt to save the determination operation resources. Alternatively, the abnormality determination unit 100 may use the difference δ between the values obtained by summing or averaging the target speed Vt and the actual traveling speed Vr for multiple time series points within the set interval for the determination of the speed following abnormality Rv to improve the determination accuracy.

[0103] The allowable range of the difference δ for the speed following abnormality Rv is defined as the range below the threshold value or less than the threshold value. Under this definition, the abnormality determination unit 100 makes a provisional determination of the existence of the speed following abnormality Rv when the difference δ goes outside the allowable range, that is, exceeds the threshold value or is equal to or greater than the threshold value. At this time, as Figure 12 shown, it is also possible that if the difference δ is outside the allowable range for each control timing, the abnormality determination unit 100 makes a provisional determination. Or, as Figure 13 shown, it is also possible that when the difference δ is outside the allowable range continuously or on average at multiple control timings, the abnormality determination unit 100 makes a provisional determination.

[0104] Here, the threshold value that determines the allowable range of the difference δ for the speed following abnormality Rv can also be set to a value corresponding to the magnitude relationship between the target speed Vt and the actual traveling speed Vr. For example, as Figure 14 shown, it is also possible to suppress the actual traveling speed Vr from being too large compared to the target speed Vt due to the characteristic change of the basic function system 6 by setting the threshold value for judging the case of Vr - Vt > 0 to be smaller than the threshold value for judging the case of Vr - Vt < 0.

[0105] In the case where at least one of the differences Δ and δ for judging the following abnormalities Rt and Rv, which is the attention difference for which a provisional determination has been made (refer to Figures 10 - 14 ) goes outside the allowable range, the abnormality determination unit 100 predicts whether this driving abnormality is related to other factors other than the characteristic change. As a result, when the prediction related to other factors is not established, the abnormality determination unit 100 determines the provisional determination of the existence of the driving abnormality. On the other hand, when the prediction related to other factors is established instead of the characteristic change of the basic function system 6, the abnormality determination unit 100 abandons the provisional determination.

[0106] Here, the so-called other factors include Figure 15 at least one type of the multiple factors A to E shown in the flow of. Specifically, factor A is a factor related to the distance traveled or the passage of time of the vehicle 2. Therefore, for example, when the traveling distance or traveling time from the start of use of each replacement request part X is below the judgment reference value or less than the judgment reference value, it is judged in S1 that the related prediction with factor A is established, and thus the provisional determination in the abnormality determination unit 100 is abandoned in S2.

[0107] Factor B is a temporary interference factor in the vehicle 2. Therefore, for example, when the attention difference at the same driving location is unstably outside the allowable range due to weather or road surface conditions, it is judged in S3 that the related prediction with factor B is established, and thus the provisional determination in the abnormality determination unit 100 is abandoned in S2.

[0108] Factor C is a structural factor of the driving road on which the vehicle 2 travels. Therefore, for example, in a case where the curvature of the driving road exceeds or is equal to a determination reference value, and thus it is easy to generate a concern difference outside the allowable range, etc., in S4, it is determined that the related prediction of Factor C is established, and thus in S2, the temporary determination in the abnormality determination unit 100 is abandoned.

[0109] Factor D is a generating factor of the target parameter in the vehicle 2. Therefore, for example, in a case where the time required from the generation of the target parameter related to the target trajectory Tt to entering the curved driving area in the management object scenario M exceeds or is equal to a determination reference value due to the presence of an obstacle or the loss of the destination, etc., in S5, it is determined that the related prediction of Factor D is established, and thus in S2, the temporary determination in the abnormality determination unit 100 is abandoned.

[0110] Factor E is a state factor of the sensor system 3 mounted on the vehicle 2. Therefore, for example, in a case where the deviation between the state estimation based on the acquired information of one sensor from the sensor system 3 and the state estimation based on the acquired information of other sensors from the system 3 exceeds or is above a determination reference value, etc., in S6, it is determined that the related prediction of Factor E is established, and thus in S2, the temporary determination in the abnormality determination unit 100 is abandoned. Here, the so-called state estimation can be performed, for example, using a Kalman filter, etc., on the position or speed of the vehicle 2.

[0111] In addition, when abandoning the temporary determination based on such factors A to E, for example, at least one of calibration or replacement of the sensor system 3, upgrade of the driving control program in the vehicle 2 or contact with the developer, update of the detection logic in the sensor system 3, and regeneration of the target trajectory Tt, etc. may also be executed together.

[0112] Figure 3 The designated output unit 120 shown designates and outputs the replacement request component X for replacement as shown from among the multiple components of each of the systems 7 to 9 constituting the basic function system 6, according to the driving abnormality for which the existence determination has been determined by the abnormality determination unit 100. In other words, when the abnormality determination unit 100 abandons the existence determination, the designated output unit 120 delays the designated output of the replacement request component X (refer to S2 in the example of Figure 16 above). Figure 15 The replacement request component X is designated by a combination of one component or multiple components that need to be replaced in order to restore the driving abnormality determined to exist to normal. Specifically, in the case where the driving abnormality is the trajectory following abnormality Rt, for example, as

[0113] shown. Figure 17As shown, during a turn, the rear part of the vehicle 2 moves outward in the turning direction compared to the target track Tt in the actual track Tr. In this case, for example, as Figure 16 shown, the combination of the brake shoe and the brake drum of the friction braking unit 81 that constitutes the braking system 8 is designated as the replacement request part X.

[0114] On the other hand, in the case where the driving abnormality is the speed following abnormality Rv, for example, as Figure 18 shown in the process, based on the deceleration condition of the vehicle 2 and the deterioration estimation of the basic function system 6, the components constituting the braking system 8 are designated as the replacement request part X. Specifically, in the Figure 18 example, when it is confirmed at the control timing during natural driving in S11 that there is a difference δ outside the allowable range caused by Vt < Vr (that is, a state where it is difficult to decelerate), the wear deterioration of the tire 60 is determined by the tire monitor as the internal sensor 31 in S12. As a result, when the wear deterioration of the tire 60 is confirmed, the tire 60 is designated as the replacement request part X in S13. In addition, as Figure 19 shown, the determination in S12 may not be executed. In addition, although not shown, the group of S11 to S13 may also be omitted.

[0115] Furthermore, in the Figure 18 example, when it is confirmed at the control timing during acceleration in S14 that there is a difference δ outside the allowable range caused by Vr < Vt (that is, a state where it is difficult to accelerate), the battery 61 is designated as the replacement request part X in S15. In addition, furthermore, in the Figure 18 example, when it is confirmed at the control timing during braking in S16 that there is a difference Δ outside the allowable range caused by Vt < Vr (that is, a state where it is difficult to brake), the wear deterioration of the brake shoe in the friction braking unit 81 is determined by the brake monitor as the internal sensor 31 in S17. As a result, when the wear deterioration of the brake shoe is confirmed, the brake shoe is designated as the replacement request part X in S18. In addition, as Figure 19 shown, the determination in S17 may not be executed. In addition, although not shown, at least one of the group of S14, S15 and the group of S16 to S18 may be omitted. Furthermore, although not shown, the battery 61 may also be designated as the replacement request part X when it is confirmed at the control timing during regenerative braking that there is a difference Δ outside the allowable range caused by Vt < Vr (that is, a state where it is difficult to decelerate).

[0116] The designation output unit 120 outputs after generating replacement information I related to the replacement request part X designated in this way. Here, for example, as Figure 20 、 21As shown, the replacement information I is at least one type among the part name, part number, replacement instruction, replacement order of the replacement request part X, the trained replacement consignment destination, precautions, vehicle model information, and the purchase or replacement history, etc.

[0117] As Figure 20 shown, the designated output unit 120 outputs the replacement information I by at least displaying it as a visual prompt among the information prompting methods of the information prompting system 5. Here, the replacement information I is displayed by at least one type among characters, marks, animations, and two-dimensional codes, etc. As the information prompting system 5 for displaying such replacement information I, it is necessary to be equipped with the visual prompting unit 50 mounted on the vehicle 2, but in addition to this, at least one of the setting unit outside the vehicle 2 and the mobile terminal of the occupant can also be used as described above.

[0118] In addition, for example, as Figure 21 shown in (a) and (b) of, the part number and two-dimensional code in the replacement information I can also be posted on the replacement request part X or its housing Y, etc. Thereby, incorrect replacement can be suppressed.

[0119] According to Figure 22 , the following will describe the process of the vehicle management method in which the vehicle management device 1 manages the state of the vehicle 2 through the combined action of the function units 100 and 120 described so far. In addition, each "S" in this process respectively means a plurality of steps executed by a plurality of commands included in the vehicle management program.

[0120] In S101, the abnormality determination unit 100 determines the presence or absence of a driving abnormality predicted to be related to the characteristic deterioration of the basic function system 6 in the management target scenario M in the driving scenario of the vehicle 2. As a result, when the attention difference, which is a driving abnormality that is at least one of the differences Δ and δ related to the following abnormalities Rt and Rv, deviates outside the allowable range, the abnormality determination unit 100 makes a temporary determination that there is a driving abnormality, and thus this process proceeds to S102.

[0121] In S102, the abnormality determination unit 100 predicts whether the temporarily determined driving abnormality is related to other factors other than characteristic changes. As a result, when the prediction that the driving abnormality is related to other factors does not hold, the abnormality determination unit 100 determines the temporary determination that there is a driving abnormality, and thus this process proceeds to S103.

[0122] In S103, the designated output unit 120 designates and outputs the replacement request part X that is requested to be replaced due to the driving abnormality for which the abnormality determination unit 100 has determined the presence of the driving abnormality from among the plurality of parts constituting the basic function system 6.

[0123] In the case where the prediction that the driving abnormality is related to other factors holds in S102, the abnormality determination unit 100 abandons the temporary determination of the existence of the driving abnormality, and thus this process proceeds to S104. In S104, the designated output unit 120 postpones the designated output of the replacement request component X.

[0124] After the execution of S104 and in the case where it is determined in S101 that there is no driving abnormality, the current execution of this process ends. Thus, in this process, S101 and S102 correspond to the abnormality determination process, and S103 and S104 correspond to the designated output process.

[0125] (Function and effect)

[0126] Hereinafter, the function and effect of the first embodiment described above will be described.

[0127] According to the first embodiment, in the management object scenario M of the driving direction change in the autonomous driving mode in the driving scenario of the vehicle 2, it is determined whether there is a driving abnormality predicted to be related to the characteristic change of the basic function system 6 including the drive system 7, the braking system 8, and the steering control system 9. Therefore, in the first embodiment, from among the multiple components constituting the basic function system 6, the replacement request component X that is requested to be replaced according to the determined driving abnormality is designated and output. Thus, even if a driving abnormality related to the characteristic change of the basic function system 6 for left and right target followability occurs along with the driving direction change of the vehicle 2 in the autonomous driving mode that requires target followability, it is possible to notify, through the designated output, the replacement request component X for eliminating this driving abnormality. Therefore, it is possible to appropriately manage the state of the vehicle 2 in order to ensure target followability.

[0128] According to the first embodiment, it is also possible to determine that the track following abnormality Rt in which the difference Δ between the target track Tt of the vehicle 2 and the actual driving position Pr goes out of the allowable range is a driving abnormality. In this case, even if a track following abnormality Rt indicating a decrease in the followability to the target track Tt occurs, it is possible to notify, through the designated output, the replacement request component X suitable for this followability abnormality Rt. Therefore, it is possible to appropriately manage the state of the vehicle 2 and urge the replacement of the component X required to ensure target followability.

[0129] According to the first embodiment, it is also possible to determine that a speed following abnormality Rv in which the difference δ related to the target speed Vt and the actual traveling speed Vr of the vehicle 2 goes outside the allowable range is a traveling abnormality. In this case, even when a speed following abnormality Rv that causes a decrease in the followability to the target trajectory Tt occurs due to deterioration of the turning maneuverability depending on the followability to the target speed Vt when the traveling direction of the vehicle 2 changes, it is possible to notify, by a specified output, the replacement request component X suitable for the followability abnormality Rv. Therefore, the state of the vehicle 2 can be appropriately managed and the replacement of the component X required to ensure the target followability can be urged.

[0130] According to the first embodiment, when at least one of the difference Δ related to the target trajectory Tt and the actual traveling position Pr and the difference δ related to the target speed Vt and the actual traveling speed Vr goes outside the allowable range, if it is predicted that the traveling abnormality is related to factors other than the characteristic change, the specified output of the replacement request component X is postponed. Here, in particular, the so-called other factors include at least one type among the factor A of the distance traveled by the vehicle 2 or the passage of time, the temporary disturbance factor B in the vehicle 2, the structural factor C of the traveling road on which the vehicle 2 travels, the generation factor D of the target parameter in the vehicle 2, and the state factor E of the sensor system 3 mounted on the vehicle 2. Thereby, the specified output of the replacement request component X can be limited to a traveling abnormality related to the characteristic change of the basic function system 6, making the specified output appropriate. Therefore, the reliability of the effect of appropriately managing the state of the vehicle 2 and urging the replacement of the component X required to ensure the target followability can be ensured.

[0131] According to the first embodiment, when the specified output of the replacement request component X is made, replacement information I related to the component X is generated. Thereby, it is possible to directly notify the replacement request component X by the display of the replacement information I. Therefore, the effect itself of appropriately managing the state of the vehicle 2 and urging the replacement of the component X required to ensure the target followability can be improved.

[0132] According to the first embodiment, the management target scenario M includes a traveling scenario of the vehicle 2 in which the changed traveling direction is inclined by 45 degrees or more with respect to the traveling direction before the change. Thus, in the management target scenario M that requires target followability, particularly when a traveling abnormality occurs in a traveling scenario where the influence caused by the characteristic change of the braking system 8 is large, it is possible to notify, by a specified output, the replacement request component X suitable for the traveling abnormality. Therefore, by appropriately managing the state of the vehicle 2 considering the safety accompanying the change in the traveling direction, the replacement of the component X required to ensure the target followability can be urged.

[0133] According to the first embodiment, a driving scenario of the vehicle 2 in which the number of lanes in the changed driving direction is plural is included. Thus, even in the management target scenario M that requires target followability, especially when a driving abnormality occurs in a driving scenario where it is easy for traffic participants to be misled because the destination has multiple lanes due to a change in the driving direction, it is possible to notify, by a designated output, the replacement request component X suitable for the driving abnormality. Therefore, through appropriate management of the state of the vehicle 2 considering traffic participants, it is possible to urge replacement of the component X required to ensure target followability.

[0134] (Second Embodiment)

[0135] The second embodiment is a modified example of the first embodiment.

[0136] Among the multiple functional units configured by the vehicle management device 1 of the second embodiment, in addition to the abnormality determination unit 100 and the designated output unit 120, as Figure 23 shown, a learning unit 2140 is included. The learning unit 2140 learns, based on the result of the driving, the control parameter, that is, the target parameter, for controlling the driving of the vehicle 2 in an arbitrary driving scenario including the management target scenario M. Here, for example, machine learning models such as neural networks are used to perform the learning. The timing of such learning is usually when the vehicle 2 is driving or stopped on the road, but for example, it can also be when the vehicle 2 is driving or stopped on a test track Z as Figure 24 shown after the replacement request component X is actually replaced.

[0137] (Function and Effect)

[0138] Hereinafter, the function and effect peculiar to the second embodiment described above will be described.

[0139] According to the second embodiment, the target parameter for controlling the driving of the vehicle 2 in the management target scenario M is learned based on the result of the driving. Thus, in the second embodiment where the replacement request component X for eliminating the driving abnormality is notified by a designated output in the same manner as the first embodiment, it is possible to suppress a situation where an inappropriate target parameter is learned without replacing the component X required to ensure target followability. Also, after the component X is actually replaced, it is possible to learn the target parameter suitable for the replaced component X.

[0140] (Third Embodiment)

[0141] The third embodiment is a modified example that combines the first embodiment and the second embodiment and further adds an execution function.

[0142] In vehicle 2, a control system for setting control parameters for controlling the driving of vehicle 2 and variably adjusting the driving state based on system 7 is also included in the drive system 7 of the basic function system 6. Similarly, in vehicle 2, a control system for setting control parameters for controlling the driving of vehicle 2 and variably adjusting the braking state based on system 8 is also included in the braking system 8 of the basic function system 6. Further, in vehicle 2, a control system for setting control parameters for controlling the driving of vehicle 2 and variably adjusting the steering state based on system 9 is also included in the steering system 9 of the basic function system 6. The control systems of these respective systems 7 to 9 can also be shared between at least two systems or can be independent of each other. Therefore, the control systems of respective systems 7 to 9 can also be constituted by at least one type among a driving control ECU, an actuator ECU, and ECUs other than them.

[0143] As Figure 25 shown, a prediction determination unit 3100, an update processing unit 3120, and a learning unit 2140 are included in a plurality of functional units constructed by the vehicle management device 1 of the third embodiment. An abnormality determination unit 3101 and an after-update determination unit 3102 are included in the prediction determination unit 3100 as a plurality of sub-functional units.

[0144] The abnormality determination unit 3101 determines the presence or absence of a driving abnormality related to a change in component characteristics such as aging deterioration in each of systems 7 to 9, and the presence or absence of other factors in the case of prediction, as a driving change predicted to be related to a characteristic change of the basic function system 6 in the automatic driving mode of vehicle 2. However, as the management target scenario M for which the abnormality determination unit 3101 determines a driving abnormality, in addition to a curved driving scenario at a curved driving location, for example, a parking scenario or a high-speed driving scenario (in the latter case, also including a combination with a curved driving) can also be monitored. Further, based on such an added management target scenario M, a following abnormality Rt, Rv, or a driving abnormality other than these abnormalities Rt, Rv can be determined.

[0145] After the update determination unit 3102 determines, as driving changes predicted to be related to characteristic changes in the basic function system 6 in the autonomous driving mode of the vehicle 2, whether there are driving changes caused by the updated characteristic changes in each of the systems 7 to 9. Here, the updates to the systems 7 to 9 may also be replacement of components constituting the systems 7 to 9, setting changes of control parameters of the control systems of the systems 7 to 9, or both of these replacement and setting changes. In addition, such updates to the systems 7 to 9 may include at least one type of update such as an update in setting changes based on the update process of the update processing unit 3120 described later or an update that accepts a specified output, an update that receives an instruction via communication from the outside, an update in a case where a specified condition is satisfied, and an update based on the user intention of the vehicle 2 that is not related to the update process of the update processing unit 3120, but may also be an update other than these. And, as the driving changes determined by the after-update determination unit 3102 after the update of any of the systems 7 to 9, the driving anomalies in the monitored management target scenario M are monitored according to the anomaly determination of the anomaly determination unit 3101.

[0146] The update processing unit 3120 includes a component specified output unit 3121, a risk determination unit 3122, a parameter setting change unit 3123, and a parameter specified output unit 3124 as a plurality of sub-function units. Among them, the component specified output unit 3121, the parameter setting change unit 3123, and the parameter specified output unit 3124 function to apply a mitigation process for mitigating the driving change to the vehicle 2 through an update of the basic function system 6 that matches the driving change determined by the prediction determination unit 3100. On the other hand, the risk determination unit 3122 functions to determine the risk level for selecting the optimal process among the respective mitigation processes based on the parameter setting change unit 3123 and the parameter specified output unit 3124.

[0147] The component specified output unit 3121, as an update that matches the driving anomaly, that is, the driving change, determined to exist by the anomaly determination unit 3101, specifies and outputs a replacement request component X that is requested to be replaced in order to mitigate the driving change according to the specified output unit 120 of the first embodiment. In other words, in the case where the existence determination is waived by the anomaly determination unit 3101, the component specified output unit 3121 defers the specified output of the replacement request component X according to the specified output unit 120 of the first embodiment.

[0148] In the component designation output unit 3121, the replacement request component X can, for example, output the component designation in larger units when the judgment materials such as the motion information of the vehicle 2 are insufficient, and on the other hand, output the component designation in smaller units when the judgment materials are sufficient or detailed. Here, in a specific example related to tires, when the judgment materials are insufficient, the entire tire is designated for output, and on the other hand, when the judgment materials are sufficient or detailed, the brake shoe is designated for output. In addition, for components that are symmetric left and right in the vehicle 2, even if only one side causes abnormal driving, the stability and ride comfort of the vehicle 2 can be improved by designating both sides as the replacement request component X. Here, in a specific example related to tires, when the left brake shoe causes abnormal driving, not only the left brake shoe but also the right brake shoe is designated for output.

[0149] The risk determination unit 3122 plans a setting change of the mitigation parameter required to mitigate the driving change in the control parameters of the control systems of the respective systems 7 to 9 as an addition update that matches the updated driving change determined by the post-update determination unit 3102. Therefore, the risk determination unit 3122 determines whether the risk level based on the planned setting change of the mitigation parameter is within the allowable range.

[0150] Specifically, the risk determination unit 3122 can make a determination that the risk level is within the allowable range when the change amount based on the setting change of the mitigation parameter is less than or equal to the threshold value, and on the other hand, make a determination that the risk level is outside the allowable range when the change amount is greater than or equal to the threshold value or exceeds the threshold value. At this time, the threshold value for the change amount towards the safe side can be set larger than the threshold value for the change amount towards the risk side. In addition, the risk determination unit 3122 can, for example, make a determination that the risk level is outside the allowable range when it is predicted that the influence on the view of driving safety increases due to a setting change of the mitigation parameter for controlling the vehicle 2 in response to the detection of a person. And the risk determination unit 3122 can also make a determination that the risk level based on the update is outside the allowable range during a period when the number of existence determinations by the post-update determination unit 3102 is small, for example, considering the possibility of misjudgment, and make a determination that the risk level is within the allowable range when the number of existence determinations increases.

[0151] When the risk level determined by the risk determination unit 3122 based on the presence determination by the updated determination unit 3102 is within the allowable range, the parameter setting change unit 3123 functions. When this condition is satisfied, the parameter setting change unit 3123 updates the mitigation parameter for which the setting change has been planned by the risk determination unit 3122. That is, the parameter setting change unit 3123 makes a setting change to the mitigation parameter for mitigating the driving change as an addition update that matches the driving change determined to be present by the updated determination unit 3102 among the control parameters of the control systems of each of the systems 7 to 9.

[0152] Specifically, in the update when the condition is satisfied, the parameter setting change unit 3123 may also restore the mitigation parameter to be changed, for example, to the initial value when the vehicle 2 leaves the assembly line. In the update when the condition is satisfied, the parameter setting change unit 3123 may also adjust to a value estimated or inversely calculated based on the characteristics of the replaced component when the previous update was a component replacement. In the update when the condition is satisfied, the parameter setting change unit 3123 may also make the setting change stepwise in order to suppress the driving change of the user of the vehicle 2 due to the update. In the update when the condition is satisfied, the parameter setting change unit 3123 may also, for example, during the driving or stopping of the vehicle 2 on the test track Z after the component replacement, make a setting change to the mitigation parameter based on the learning result of the mitigation parameter learned as a control parameter by the learning unit 2140.

[0153] Here, in particular, in the learning of the mitigation parameter for which the parameter setting change unit 3123 makes a setting change, the driving of the vehicle 2 may be controlled to change from straight driving to curved driving, thereby improving driving safety during learning. In the learning of the mitigation parameter, the vehicle 2 may be made to perform a curved driving in which the changed driving direction is more than 90 degrees different from the previous driving direction, so that the mitigation parameter particularly related to the braking system 8 is optimized for the deceleration scenario. In the learning of the mitigation parameter, the vehicle 2 may be made to perform a curved driving in which the changed driving direction is more than 45 degrees different from the previous driving direction, so that the mitigation parameter particularly related to the steering timing or steering amount of the steering system 9 is optimized.

[0154] When the risk level determined by the risk determination unit 3122 based on the presence determination by the updated determination unit 3102 is outside the allowable range, the parameter specification output unit 3124 functions. When this condition is satisfied, the parameter specification output unit 3124 outputs the mitigation parameter for which the setting change has been planned by the risk determination unit 3122. That is, the parameter specification output unit 3124 outputs, as an addition / update matching the driving change determined to be present by the updated determination unit 3102, the mitigation parameter that requests the setting change for mitigating the driving change, among the control parameters of the control systems of each of the systems 7 to 9.

[0155] In the case of the setting change process of the parameter setting change unit 3123 and the specification output process of the parameter specification output unit 3124, for example, the update target can be set to the upper control parameter when the judgment materials such as the motion information of the vehicle 2 are insufficient, while it can be set to the lower control parameter when the judgment materials are sufficient or detailed. Here, in a specific example, the target speed is set as the update target when the judgment materials are insufficient, while the braking amount and braking timing in a specific section are set as the update target when the judgment materials are sufficient or detailed. In the case of the setting change process of the parameter setting change unit 3123 and the specification output process of the parameter specification output unit 3124, for the control parameters set for the left and right of the vehicle 2, even if the necessity for update occurs only on one side, both can be set as the update target. Here, in a specific example, when the necessity for update occurs in the control parameter related to the lane change on the left side of the vehicle 2, the control parameter related to the lane change on the right side of the vehicle 2 is also set as the update target.

[0156] Next, according to Figure 26 , the process of the vehicle management method for the vehicle management device 1 to manage the state of the vehicle 2 through the combined action of the function units 3100 and 3120 described so far will be described. In addition, each "S" in this process also means multiple steps executed by multiple commands included in the vehicle management program.

[0157] In S3101, the updated determination unit 3102 of the prediction determination unit 3100 determines the presence or absence of a driving change predicted to be caused by the updated characteristic changes of each of the systems 7 to 9 as a driving change related to the characteristic change of the basic function system 6 in the automatic driving mode of the vehicle 2. As a result, when it is determined that there is no driving change, this process proceeds to S101. Thus, S101 and the subsequent S102 are executed by the abnormality determination unit 3101 of the prediction determination unit 3100 in accordance with the abnormality determination unit 100 of the first embodiment. Further, S103 and S104 branched from S102 are executed by the component designation output unit 3121 of the update processing unit 3120 in accordance with the designation output unit 120 of the first embodiment.

[0158] When it is determined in S3101 that there is a driving change, this process proceeds to S3102. In S3102, the risk determination unit 3122 plans a setting change of a mitigation parameter required to mitigate the driving change as an additional update matching the updated driving change determined to exist in S3101 among the control parameters of the control systems of each of the systems 7 to 9. In the subsequent S3103, the risk determination unit 3122 determines whether the risk level based on the planned setting change of the mitigation parameter is within the allowable range.

[0159] When it is determined in S3103 that the risk level is within the allowable range, this process proceeds to S3104. In S3104, the parameter setting change unit 3123 updates the mitigation parameter for which the setting change was planned in S30102. On the other hand, when it is determined in S3103 that the risk level is outside the allowable range, this process proceeds to S3105. In S3105, the parameter designation output unit 3124 designates and outputs the mitigation parameter for which the setting change was planned in S3102.

[0160] (Function and effect)

[0161] Hereinafter, the function and effect of the third embodiment described above will be described.

[0162] According to the third embodiment, the presence or absence of a driving change predicted to be related to the characteristic change of the basic function system 6, which is the drive system 7, the braking system 8, and the steering system 9, in the automatic driving mode of the vehicle 2 is determined. Therefore, in the third embodiment, by updating the basic function system 6 in accordance with the determined driving change, a mitigation process for mitigating the driving change is applied to the vehicle 2. Thus, in the automatic driving mode that requires target followability, even if a driving change related to the characteristic change of the basic function system 6 for left and right target followability occurs, a mitigation process can be performed to eliminate the driving change. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target followability.

[0163] According to the mitigation process of the third embodiment, among the multiple components constituting the basic function system 6, the replacement request component X that requests an update based on replacement to mitigate the judged driving change is specified for output. Thus, even when a driving change related to the characteristic change of the basic function system 6 for left and right target followability occurs in the autonomous driving mode, the replacement request component X for eliminating the driving change can be notified by the specified output. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target followability.

[0164] According to the mitigation process of the third embodiment, among the control parameters for controlling the driving of the vehicle 2 based on the basic function system 6, the mitigation parameter that requests an update based on setting change to mitigate the judged driving change is specified for output. Thus, even when a driving change related to the characteristic change of the basic function system 6 for left and right target followability occurs in the autonomous driving mode, the mitigation parameter for eliminating the driving change can be notified by the specified output. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target followability.

[0165] According to the mitigation process of the third embodiment, among the control parameters for controlling the driving of the vehicle 2 based on the basic function system 6, the mitigation parameter for mitigating the judged driving change is updated by setting change. Thus, even when a driving change related to the characteristic change of the basic function system for left and right target followability occurs in the autonomous driving mode, the setting of the mitigation parameter can be changed to eliminate the driving change. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target followability.

[0166] According to the mitigation process of the third embodiment, the risk level of the setting change based on the mitigation parameter for mitigating the driving change is judged. Therefore, when the judged risk level is within the allowable range, the mitigation parameter is updated by setting change. On the other hand, when the risk level is outside the allowable range, the mitigation parameter that requests an update based on setting change is specified for output. Thus, even when a driving change related to the characteristic change of the basic function system 6 for left and right target followability occurs in the autonomous driving mode, the setting change and the specified output can be switched according to the risk level of the setting change of the mitigation parameter for eliminating the driving change. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target followability.

[0167] According to the third embodiment, the relaxation parameter can also be set and changed according to the learning result based on the driving result of the vehicle 2. In such a case of setting change based on learning, even if driving fluctuations occur related to the characteristic change of the basic function system 6 of the left and right target followability in the autonomous driving mode, the relaxation parameter can be set and changed by learning to eliminate the driving fluctuations. Therefore, the state of the vehicle 2 can be appropriately managed to ensure the target followability.

[0168] (Fourth Embodiment)

[0169] The fourth embodiment is a modification of the third embodiment.

[0170] In Figure 27 In the fourth embodiment shown, the prediction determination unit 4100 includes an abnormality determination unit 3101 and an updated determination unit 4102 as a plurality of sub-function units.

[0171] The updated determination unit 4102 determines the presence or absence of updates to each of the systems 7 to 9 as a characteristic change of the basic function system 6 that is predicted to cause driving fluctuations in the autonomous driving mode of the vehicle 2. In the fourth embodiment, the update of the systems 7 to 9 may be a replacement of components constituting the systems 7 to 9, a setting change of the control parameters of the control systems of the systems 7 to 9, or both of these replacements and setting changes. In addition, such updates of the systems 7 to 9 may include at least one type of update in the setting change of the update process based on the update processing unit 4120 described later, or an update that accepts a specified output, an update that receives an instruction via communication from the outside, an update in a case where a specified condition is satisfied, and an update based on the user intention of the vehicle 2 that is independent of the update process of the update processing unit 4120, but may also be an update other than these.

[0172] Therefore, after such an update of the systems 7 to 9, at any part other than the updated part, for example, driving fluctuations may occur due to the balance with the updated part, etc. Therefore, the updated determination unit 4102 virtually determines the presence or absence of the previous update gate as a characteristic change of the systems 7 to 9. In addition, such a presence determination from the updated determination unit 4102 may be made after all updates, for example, may also be made only when the previous update that accepts the specified output of the update processing unit 4120 is accompanied by driving abnormalities caused by deteriorated components with a large difference Δ or difference δ, etc., when the necessity of adding an update becomes high.

[0173] In the fourth embodiment, the update processing unit 4120 includes a component specified output unit 3121, a risk determination unit 4122, a parameter setting change unit 4123, and a parameter specified output unit 4124 as a plurality of sub-function units.

[0174] The risk determination unit 4122 plans a setting change of a mitigation parameter required to mitigate driving fluctuations predicted to be caused by a previous update that matches the previous update as an additional update for a characteristic change determined to exist by the post-update determination unit 4102 among the control parameters of the control systems of the respective systems 7 to 9. Therefore, the risk determination unit 4122 determines whether the risk level based on the planned setting change of the mitigation parameter is within the allowable range. In addition, the specific determination process of the risk determination unit 4122 according to the fourth embodiment is performed according to the risk determination unit 3122 of the third embodiment.

[0175] When the risk level determined by the risk determination unit 4122 based on the existence determination of the post-update determination unit 4102 is within the allowable range, the parameter setting change unit 4123 of the fourth embodiment functions. The parameter setting change unit 4123 when this condition is satisfied updates the mitigation parameter for which the risk determination unit 4122 has planned a setting change. That is, the parameter setting change unit 4123 makes a setting change to the mitigation parameter for mitigating driving fluctuations predicted to be caused by a previous update that matches the previous update as an additional update for a characteristic change determined to exist by the post-update determination unit 4102 among the control parameters of the control systems of the respective systems 7 to 9. In addition, the specific setting change process of the parameter setting change unit 4123 according to the fourth embodiment is performed according to the parameter setting change unit 3123 of the third embodiment.

[0176] When the risk level determined by the risk determination unit 4122 based on the existence determination of the post-update determination unit 4102 is outside the allowable range, the parameter specification output unit 4124 of the fourth embodiment functions. The parameter specification output unit 4124 when this condition is satisfied specifies and outputs the mitigation parameter for which the risk determination unit 4122 has planned a setting change. That is, the parameter specification output unit 4124 specifies and outputs the mitigation parameter for which a setting change is requested to mitigate driving fluctuations predicted to be caused by a previous update that matches the previous update as an additional update for a characteristic change determined to exist by the post-update determination unit 4102 among the control parameters of the control systems of the respective systems 7 to 9. In addition, the specific specification output process of the parameter specification output unit 4124 according to the fourth embodiment is performed according to the parameter specification output unit 3124 of the third embodiment.

[0177] According to Figure 28 , the following describes the process of the vehicle management method in which the vehicle management device 1 manages the state of the vehicle 2 through the combined action of the functional units 4100 and 4120 described so far. In addition, each "S" in this process also means a plurality of steps executed by a plurality of commands included in the vehicle management program.

[0178] In S4101, the updated determination unit 4102 of the prediction determination unit 4100 determines the presence or absence of updates to each of the systems 7-9 as a characteristic change of the basic function system 6 that is predicted to cause a driving change in the automatic driving mode of the vehicle 2. As a result, in the case where it is determined that there is no update, this process proceeds to S101. Thus, S101 and the subsequent S102 are executed by the abnormality determination unit 3101 of the prediction determination unit 4100 in accordance with the abnormality determination unit 100 of the first embodiment. Further, S103 and S104 branched from S102 are executed by the component designation output unit 3121 of the update processing unit 4120 in accordance with the designation output unit 120 of the first embodiment.

[0179] In the case where it is determined in S4101 that there is an update, this process proceeds to S4102. In S4102, the risk determination unit 4122 plans a setting change of a mitigation parameter required to mitigate the driving change predicted to be caused by the previous update that is determined to exist in S4101 among the control parameters of the control systems of each of the systems 7-9. In the subsequent S4103, the risk determination unit 4122 determines whether the risk level based on the planned setting change of the mitigation parameter is within the allowable range.

[0180] In the case where it is determined in S4103 that the risk level is within the allowable range, this process proceeds to S4104. In S4104, the parameter setting change unit 4123 updates the mitigation parameter for which the setting change was planned in S40102. On the other hand, in the case where it is determined in S4103 that the risk level is outside the allowable range, this process proceeds to S4105. In S4105, the parameter designation output unit 4124 designates and outputs the mitigation parameter for which the setting change was planned in S4102.

[0181] (Function and effect)

[0182] Hereinafter, the function and effect unique to the fourth embodiment described above will be described.

[0183] According to the fourth embodiment, the presence or absence of a characteristic change of the basic function system 6 that is predicted to cause a driving change in the automatic driving mode of the vehicle 2 is determined as the drive system 7, the braking system 8, and the steering system 9. Therefore, in the fourth embodiment, a mitigation process for mitigating the driving change is applied to the vehicle 2 by updating the basic function system 6 that matches the determined characteristic change. Thus, in the automatic driving mode that requires target followability, even if a characteristic change of the basic function system 6 that causes left and right target followability occurs, a mitigation process can be performed to eliminate the driving change associated with the characteristic change. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target followability.

[0184] According to the fourth embodiment, after replacement of the replacement-request component, it is determined whether there is a characteristic change in the basic function system 6 that is predicted to cause a driving change in the autonomous driving mode of the vehicle 2. Therefore, in the fourth embodiment, a mitigation process for mitigating the driving change is applied to the vehicle 2 by adding and updating the basic function system 6 that matches the characteristic change determined after replacement. Thus, in the autonomous driving mode that requires target following, even if a characteristic change in the basic function system 6 related to left and right target following occurs due to the replacement of the replacement-request component, a mitigation process can be performed to eliminate the driving change associated with this characteristic change. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target following.

[0185] According to the fourth embodiment, after the setting of the mitigation parameter is changed, it is determined whether there is a characteristic change in the basic function system 6 that is predicted to cause a driving change in the autonomous driving mode of the vehicle 2. Therefore, in the fourth embodiment, a mitigation process for mitigating the driving change is applied to the vehicle 2 by adding and updating the basic function system 6 that matches the characteristic change determined after the setting change. Thus, in the autonomous driving mode that requires target following, even if a characteristic change in the basic function system 6 related to left and right target following occurs due to the change in the setting of the mitigation parameter, a mitigation process can be performed to eliminate the driving change associated with this characteristic change. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target following.

[0186] According to the mitigation process of the fourth embodiment, among the control parameters for controlling the driving of the vehicle 2 based on the basic function system 6, in order to mitigate the driving change predicted to be caused by the characteristic change determined for the basic function system 6, the mitigation parameter that requests an update based on the setting change is specified and output. Thus, even if a characteristic change in the basic function system 6 related to left and right target following occurs in the autonomous driving mode, the mitigation parameter for eliminating the driving change associated with this characteristic change can be notified by the specified output. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target following.

[0187] According to the mitigation process of the fourth embodiment, among the control parameters for controlling the driving of the vehicle 2 based on the basic function system 6, in order to mitigate the driving change predicted to be caused by the characteristic change determined for the basic function system 6, the mitigation parameter is updated by a setting change. Thus, even if a characteristic change in the basic function system related to left and right target following occurs in the autonomous driving mode, a setting change can be made to the mitigation parameter to eliminate the driving change associated with this characteristic change. Therefore, the state of the vehicle 2 can be appropriately managed to ensure target following.

[0188] According to the mitigation process of the fourth embodiment, the risk level based on the setting change of the mitigation parameter for mitigating driving variations is determined. Therefore, when the determined risk level is within the allowable range, the mitigation parameter is updated by the setting change. On the other hand, when the risk level is outside the allowable range, the mitigation parameter that requests an update based on the setting change is specified and output. Thus, even when a characteristic change occurs in the basic function system 6 of the left and right target following performance in the autonomous driving mode, the setting change and the specified output can be switched according to the risk level based on the setting change of the mitigation parameter for eliminating the driving variations associated with the characteristic change. Therefore, the state of the vehicle 2 can be appropriately managed to ensure the target following performance.

[0189] According to the fourth embodiment, the setting change of the mitigation parameter can also be performed based on the learning result of the driving result of the vehicle 2. Thus, even when a characteristic change occurs in the basic function system 6 of the left and right target following performance in the autonomous driving mode, the setting change of the mitigation parameter can be performed so as to eliminate the driving variations associated with the characteristic change by learning. Therefore, the state of the vehicle 2 can be appropriately managed to ensure the target following performance.

[0190] (Other embodiments)

[0191] As described above, multiple embodiments have been described, but the present disclosure is not limited to these embodiments for interpretation and can be applied to various embodiments and combinations without departing from the gist of the present disclosure.

[0192] In a modification, the dedicated computer constituting the vehicle management device 1 may also have at least one of a digital circuit and an analog circuit as a processor. Here, the digital circuit is, for example, at least one type among an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), an SOC (System on a Chip), a PGA (Programmable Gate Array), and a CPLD (Complex Programmable Logic Device). In addition, such a digital circuit may also have a memory storing a program.

[0193] In a modified example, the dedicated computer constituting the vehicle management device 1 may also be an external computer provided in at least one of a repair factory, a dealership, a remote assistance center, etc. and capable of wireless communication with the vehicle 2. Further, in this case, the designation output units 120, 3121 in S103 may also implement the designation output of the component X by wirelessly communicating the replacement information I related to the designated replacement request component X to such an external computer.

[0194] In a modified example, the abnormality determination units 100, 3101 may also determine the presence of a driving abnormality based on the attention difference in S101 by not performing the prediction of other factors in S102. Further, in this case, for example, as Figure 29 shown, the abnormality determination units 100, 3101 in S101 may also use the values of a plurality of segments a to d as thresholds for determining the attention difference.

[0195] Here, in the Figure 29 example, when the attention difference exceeds the threshold a or is outside the allowable range of the threshold a or more, and when the difference is below the threshold b or less than the threshold b, the corresponding one of the designation output in S103 and the postponement in S104 according to the usage condition is executed. Further, in the Figure 29 example, when the attention difference exceeds the thresholds a and b or is outside the allowable range of the thresholds a and b or more, and when the difference is below the threshold c or less than the threshold c, the postponement in S104 is executed together with the designation of the replacement period accompanied by the designation output in S103. Further, in the Figure 29 example, when the attention difference exceeds the thresholds a, b, and c or is outside the allowable range of the thresholds a, b, and c or more, and when the difference is below the threshold d or less than the threshold d, the designation output in S103 is executed together with the prohibition control of the autonomous driving mode.

[0196] Further, in the Figure 29 example, as an example of the case where the manual driving mode is assumed in addition to the autonomous driving mode in the driving control, when the attention difference exceeds all the thresholds or is outside the allowable range of all the thresholds or more, the designation output in S103 is executed together with the prohibition control of the full driving mode. Therefore, in the vehicle 2 that only implements the autonomous driving mode, this execution is not substantially required.

Claims

1. A vehicle management device is a vehicle management device that manages the state of a vehicle having a drive system that applies acceleration, a braking system that applies deceleration, and a steering control system that applies steering as basic functional systems, wherein, Comprising: An abnormality determination unit that determines the presence or absence of a driving abnormality predicted to be related to a characteristic change of the basic function system in a management target scenario of a driving direction change in an automatic driving mode in the driving scenario of the vehicle; And A specified output unit that specifies and outputs a replacement request component that requests replacement based on the determined driving abnormality from among a plurality of components constituting the basic function system, The abnormality determination unit determines the track following abnormality in which the difference between the target track and the actual driving position of the vehicle deviates outside the allowable range as the driving abnormality, When it is predicted that the driving abnormality is related to other factors other than the characteristic change when the difference deviates outside the allowable range, the specified output unit delays the specified output of the replacement request component.

2. A vehicle management device is a vehicle management device that manages the state of a vehicle having a drive system that applies acceleration, a braking system that applies deceleration, and a steering control system that applies steering as basic functional systems, wherein, Comprising: An abnormality determination unit that determines the presence or absence of a driving abnormality predicted to be related to a characteristic change of the basic function system in a management target scenario of a driving direction change in an automatic driving mode in the driving scenario of the vehicle; And A specified output unit that specifies and outputs a replacement request component that requests replacement based on the determined driving abnormality from among a plurality of components constituting the basic function system, The abnormality determination unit determines the speed following abnormality in which the difference between the target speed and the actual driving speed of the vehicle deviates outside the allowable range as the driving abnormality, When it is predicted that the driving abnormality is related to other factors other than the characteristic change when the difference deviates outside the allowable range, the specified output unit delays the specified output of the replacement request component.

3. The vehicle management device according to claim 1 or 2, wherein The other factors include at least one of the following factors: A factor of the passage of the distance or time traveled by the vehicle; A temporary interference factor in the vehicle; A structural factor of the driving road on which the vehicle travels; A factor for generating a target parameter in the vehicle; And A state factor of the sensor system mounted on the vehicle.

4. The vehicle management device according to claim 1 or 2, wherein The specified output unit generates replacement information displayed related to the replacement request component.

5. The vehicle management device according to claim 1 or 2, wherein The management target scenario includes a driving scenario of the vehicle in which the changed driving direction is inclined by 45 degrees or more with respect to the driving direction before the change.

6. The vehicle management device according to claim 1 or 2, wherein The management target scenario includes a driving scenario of the vehicle in which the number of lanes in the changed driving direction is plural.

7. The vehicle management device according to claim 1 or 2, further comprising: A learning unit that learns control parameters for controlling the driving of the vehicle in the management target scenario based on the result of the driving.

8. A vehicle management method for managing the state of a vehicle that has a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic functional systems, wherein, Including: An abnormality determination process for determining the presence or absence of a driving abnormality predicted to be related to a characteristic change of the basic function system in a management target scenario of a driving direction change in an automatic driving mode in the driving scenario of the vehicle; And Among the multiple components constituting the above basic function system, a designated output process for designating an output of a replacement request component that requests replacement based on the determined driving abnormality The above abnormality determination process determines an orbit following abnormality in which a difference between the target orbit and the actual driving position of the vehicle is deviated outside the allowable range as the above driving abnormality When it is predicted that the above driving abnormality is related to other factors than the above characteristic change in the case where the above difference is deviated outside the above allowable range, the above designated output process delays the designated output of the above replacement request component 9. A vehicle management method is a vehicle management method for managing the state of a vehicle that has a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic functional systems, wherein, Comprising: An abnormality determination process for determining the presence or absence of a predicted driving abnormality related to a characteristic change of the above basic function system in a management target scenario of a driving direction change in an automatic driving mode in the driving scenario of the above vehicle And Among the multiple components constituting the above basic function system, a designated output process for designating an output of a replacement request component that requests replacement based on the determined driving abnormality The above abnormality determination process determines a speed following abnormality in which a difference between the target speed and the actual driving speed of the vehicle is deviated outside the allowable range as the above driving abnormality When it is predicted that the above driving abnormality is related to other factors than the above characteristic change in the case where the above difference is deviated outside the above allowable range, the above designated output process delays the designated output of the above replacement request component 10. A non-transitory computer-readable storage medium containing instructions that cause a processor to execute for managing the state of a vehicle that includes a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as a basic function system. Among them, The above instructions include: An abnormality determination process for determining the presence or absence of a predicted driving abnormality related to a characteristic change of the above basic function system in a management target scenario of a driving direction change in an automatic driving mode in the driving scenario of the above vehicle And Among the multiple components constituting the above basic function system, a designated output process for designating an output of a replacement request component that requests replacement based on the determined driving abnormality The above abnormality determination process determines an orbit following abnormality in which a difference between the target orbit and the actual driving position of the vehicle is deviated outside the allowable range as the above driving abnormality When it is predicted that the above driving abnormality is related to other factors than the above characteristic change in the case where the above difference is deviated outside the above allowable range, the above designated output process delays the designated output of the above replacement request component 11. A non-transitory computer-readable storage medium containing instructions that cause a processor to execute for managing the state of a vehicle that includes a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as a basic function system. Among them, The above instructions include: An abnormality determination process for determining a predicted driving abnormality related to a characteristic change of the above basic function system in a management target scenario of a driving direction change in an automatic driving mode in the driving scenario of the above vehicle And From among a plurality of components constituting the above-described basic function system, specify a specifying output process for a replacement request component that requests replacement based on the determined driving abnormality. The above-described abnormality determination process determines the driving abnormality as the speed following abnormality in which the difference related to the target speed and the actual driving speed of the above-described vehicle deviates outside the allowable range. When it is predicted that the above-described driving abnormality is related to other factors than the above-described characteristic change in the case where the above-described difference deviates outside the above-described allowable range, the above-described specifying output process delays the specifying output of the above-described replacement request component.

12. A vehicle management device, which is a vehicle management device having a processor and managing the states of a vehicle that includes a drive system that applies acceleration, a braking system that applies deceleration, and a steering control system that applies steering as basic function systems. The above-described processor is configured to execute: Determine the presence or absence of driving fluctuations predicted to be related to characteristic changes in the above-described basic function system in the autonomous driving mode of the above-described vehicle; and Apply a mitigation process for mitigating the above-described driving fluctuations to the above-described vehicle by updating the above-described basic function system corresponding to the determined above-described driving fluctuations. Applying the above-described mitigation process includes: Among the control parameters for controlling the driving of the above-described vehicle in the above-described basic function system, specify an output of a mitigation parameter that requests an update based on a setting change in order to mitigate the above-described driving fluctuations. Applying the above-described mitigation process includes: In the control parameters for controlling the driving of the above-described vehicle in the above-described basic function system, update the mitigation parameter for mitigating the above-described driving fluctuations by changing the setting. Applying the above-described mitigation process includes: Determine the risk level of the setting change based on the above-described mitigation parameter; In the case where the determined above-described risk level is within the allowable range, update the above-described mitigation parameter by changing the setting; And In the case where the determined above-described risk level is outside the above-described allowable range, specify an output of the above-described mitigation parameter that requests an update based on a setting change.

13. The vehicle management device according to claim 12, wherein Applying the above-described mitigation process includes: Among a plurality of components constituting the above-described basic function system, specify an output of a replacement request component that requests an update based on replacement in order to mitigate the above-described driving fluctuations.

14. The vehicle management device according to claim 13, wherein The above-described processor is configured to further execute: After replacement of the above-described replacement request component, determine the presence or absence of characteristic changes in the above-described basic function system predicted to cause driving fluctuations in the autonomous driving mode of the above-described vehicle. Applying the above-described mitigation process includes: Apply the above-described mitigation process for mitigating the above-described driving fluctuations to the above-described vehicle by adding and updating the above-described basic function system corresponding to the characteristic changes determined after replacement.

15. A vehicle management device, which is a vehicle management device having a processor and managing the states of a vehicle that includes a drive system that applies acceleration, a braking system that applies deceleration, and a steering control system that applies steering as basic function systems. The above-described processor is configured to execute: Determine whether there is a characteristic change in the above basic function system predicted to cause a driving change in the above vehicle in the autonomous driving mode; and Apply a mitigation process to the above vehicle to mitigate the above driving change through an update of the above basic function system corresponding to the determined above characteristic change, Applying the above mitigation process includes: Among the control parameters of the above basic function system for controlling the driving of the above vehicle, specify an output of a mitigation parameter that requests an update based on a setting change in order to mitigate the above driving change, Applying the above mitigation process includes: Among the control parameters of the above basic function system for controlling the driving of the above vehicle, update the mitigation parameter for mitigating the above driving change through a setting change, Applying the above mitigation process includes: Determine the risk level of the setting change based on the above mitigation parameter; When the determined above risk level is within the allowable range, update the above mitigation parameter through a setting change; And When the determined above risk level is outside the above allowable range, specify an output of the above mitigation parameter that requests an update based on a setting change.

16. The vehicle management device according to claim 15, wherein Updating the above mitigation parameter includes: Perform a setting change on the above mitigation parameter based on the learning result of the driving result of the above vehicle.

17. The vehicle management device according to claim 15 or 16, wherein Determining whether there is the above characteristic change includes: Determine whether there is the above characteristic change after the setting change of the above mitigation parameter, Applying the above mitigation process includes: Apply the above mitigation process to mitigate the above driving change to the above vehicle through an additional update of the above basic function system corresponding to the above characteristic change determined after the setting change.

18. A vehicle management method is a vehicle management method executed by a processor for managing the state of a vehicle that has a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic functional systems, wherein, Includes: Determine whether there is a driving change predicted to be related to a characteristic change in the above basic function system in the autonomous driving mode of the above vehicle; and Apply a mitigation process to the above vehicle to mitigate the driving change through an update of the above basic function system corresponding to the determined above driving change, Applying the above mitigation process includes: Among the control parameters of the above basic function system for controlling the driving of the above vehicle, specify an output of a mitigation parameter that requests an update based on a setting change in order to mitigate the above driving change, Applying the above mitigation process includes: Among the control parameters of the above basic function system for controlling the driving of the above vehicle, update the mitigation parameter for mitigating the above driving change through a setting change, Applying the above mitigation process includes: Determine the risk level of the setting change based on the above mitigation parameter; When the determined above risk level is within the allowable range, update the above mitigation parameter through a setting change; And When the determined above risk level is outside the above allowable range, specify an output of the above mitigation parameter that requests an update based on a setting change.

19. A vehicle management method is a vehicle management method executed by a processor for managing the state of a vehicle having a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic functional systems, wherein, Includes: Determine whether there is a characteristic change in the above basic function system predicted to cause a driving change in the above vehicle in the autonomous driving mode; and Apply a mitigation process to the above vehicle to mitigate the above driving change through an update of the above basic function system corresponding to the determined above characteristic change, Applying the above-mentioned mitigation process includes: Among the control parameters for controlling the driving of the vehicle in the above-mentioned basic function system, specifying an output of a mitigation parameter that requests an update based on a setting change in order to mitigate the above-mentioned driving variation, Applying the above-mentioned mitigation process includes: Among the control parameters for controlling the driving of the vehicle in the above-mentioned basic function system, updating the mitigation parameter for mitigating the above-mentioned driving variation through a setting change, Applying the above-mentioned mitigation process includes: Determining the risk level of the setting change based on the above-mentioned mitigation parameter; When the determined above-mentioned risk level is within the allowable range, updating the above-mentioned mitigation parameter through a setting change; And When the determined above-mentioned risk level is outside the above-mentioned allowable range, specifying an output to request an update of the above-mentioned mitigation parameter based on a setting change.

20. A non-transitory computer-readable storage medium containing instructions stored in the storage medium and executed by a processor for managing the state of a vehicle having a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic function systems, wherein, The above-mentioned instructions include: Determining whether there is a driving variation predicted to be related to a characteristic change of the above-mentioned basic function system in the autonomous driving mode of the above-mentioned vehicle; and Applying a mitigation process for mitigating the above-mentioned driving variation to the above-mentioned vehicle through an update of the above-mentioned basic function system corresponding to the determined above-mentioned driving variation, Applying the above-mentioned mitigation process includes: Among the control parameters for controlling the driving of the vehicle in the above-mentioned basic function system, specifying an output of a mitigation parameter that requests an update based on a setting change in order to mitigate the above-mentioned driving variation, Applying the above-mentioned mitigation process includes: Among the control parameters for controlling the driving of the vehicle in the above-mentioned basic function system, updating the mitigation parameter for mitigating the above-mentioned driving variation through a setting change, Applying the above-mentioned mitigation process includes: Determining the risk level of the setting change based on the above-mentioned mitigation parameter; When the determined above-mentioned risk level is within the allowable range, updating the above-mentioned mitigation parameter through a setting change; And When the determined above-mentioned risk level is outside the above-mentioned allowable range, specifying an output to request an update of the above-mentioned mitigation parameter based on a setting change.

21. A non-transitory computer-readable storage medium containing instructions stored in the storage medium and executed by a processor for managing the state of a vehicle having a drive system for applying acceleration, a braking system for applying deceleration, and a steering control system for applying steering as basic function systems, wherein, The above-mentioned instructions include: Determining whether there is a characteristic change of the above-mentioned basic function system predicted to cause a driving variation in the autonomous driving mode of the above-mentioned vehicle; and Applying a mitigation process for mitigating the above-mentioned driving variation to the above-mentioned vehicle through an update of the above-mentioned basic function system corresponding to the determined above-mentioned characteristic change, Applying the above-mentioned mitigation process includes: Among the control parameters for controlling the driving of the vehicle in the above-mentioned basic function system, specifying an output of a mitigation parameter that requests an update based on a setting change in order to mitigate the above-mentioned driving variation, Applying the above-mentioned mitigation process includes: Among the control parameters for controlling the driving of the vehicle in the above basic function system, by setting a change to update a mitigation parameter for mitigating the above driving fluctuations, Applying the above mitigation process includes: Determining a risk level based on the setting change of the above mitigation parameter; When the determined above risk level is within the allowable range, updating the above mitigation parameter by setting a change; And When the determined above risk level is outside the above allowable range, specifying an output request for the above mitigation parameter updated based on the setting change.

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