Rental vehicle operation management device

Abstract

To widely reflect a state of a vehicle on selecting a rental vehicle.SOLUTION: A first prediction section 433 predicts the height of a deterioration degree of each part of a vehicle 10 at a start point of time of one use schedule based on state information of each part of the vehicle 10 acquired by a first acquisition section 431 and use schedule information of the vehicle 10 acquired by a second acquisition section 432. A second prediction section 434 predicts, for each part, the height of a load level to be applied to the vehicle 10 in the one use schedule based on the use schedule information acquired by the second acquisition section 432. A third prediction section 435 predicts an inspection period of each part of the vehicle 10 based on the state information acquired by the first acquisition section 431 and the height of the deterioration degree predicted by the first prediction section 433. A selection section 436 selects a candidate vehicle from the vehicles 10 whose inspection period predicted by the third prediction section 435 does not come during a use period of the one use schedule among the vehicles 10 whose deterioration degree of the part where the load level is predicted as a higher level by the second prediction section 434 is predicted to be the lower degree by the first prediction section 433.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an operation management device for rental vehicles. [Background technology]

[0002] Patent Document 1 discloses an operation management system that selects vehicles for rental based on the degree of catalyst deterioration of the vehicle. The degree of catalyst deterioration used as a criterion takes into account the future deterioration of the catalyst predicted based on the user's planned use of the vehicle, and the future deterioration is predicted based on the details of use, including, for example, the mileage and number of passengers when the user plans to use the vehicle. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2021-140348 Summary of the Invention [Problem to be solved by the invention]

[0004] In the system of Patent Document 1, the condition of the vehicle other than the catalyst is not reflected in the selection of a vehicle for rental.

[0005] The present invention has been made in view of the above circumstances, and an object of the present invention is to widely reflect the condition of a vehicle when selecting a vehicle for rental. [Means for solving the problem]

[0006] In order to achieve the above object, one aspect of the present invention provides a rental vehicle operation management device that includes a first acquisition unit, a second acquisition unit, a first prediction unit, a second prediction unit, and a selection unit. The first acquisition unit acquires, for each vehicle, status information for each vehicle part detected by a sensor. The second acquisition unit acquires, for each planned use, vehicle usage schedule information for the user. The first prediction unit predicts, for each vehicle, the level of deterioration of each vehicle part at the start of each planned use based on the status information acquired by the first acquisition unit and the planned use information acquired by the second acquisition unit. The second prediction unit predicts, for each vehicle, the level of load applied to the vehicle during each planned use based on the planned use information acquired by the second acquisition unit for that planned use. The selection unit selects a candidate vehicle to be rented to a user of the planned use from one or more vehicles based on the level of deterioration predicted by the first prediction unit for parts whose load levels predicted by the second prediction unit are equal to or higher than a predetermined level. [Effects of the Invention]

[0007] According to the present invention, the condition of the vehicle can be widely reflected in the selection of vehicles for rental. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing a vehicle rental system including a rental vehicle operation management device according to one embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram showing an example of a schematic configuration of each element in the system of FIG. [Figure 3] FIG. 3 is a diagram showing predicted levels of deterioration of each part of the vehicle at the start of the planned use and the timing of inspection of each part for each vehicle. [Figure 4] FIG. 4 is a diagram showing predicted load levels that will be applied to each part of the vehicle depending on the user's planned use. [Figure 5] FIG. 5 is a diagram showing the relationship between the inspection timing of a certain part of a vehicle estimated from the predicted deterioration level and the period of use during which the user plans to use the vehicle. [Figure 6]FIG. 6 is a flowchart showing an example of a processing procedure of a rental vehicle operation management method executed by the controller of the operation management device of FIG. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present invention will be described with reference to the drawings. The same or equivalent parts or components are designated by the same reference numerals throughout the drawings. The embodiments shown below exemplify devices and the like that embody the technical concept of the present invention. The technical concept of the present invention does not limit the arrangement of each component to that described below.

[0010] [Vehicle rental system configuration] FIG. 1 is a diagram showing a vehicle rental system including a rental vehicle operations management device according to one embodiment of the present invention. The vehicle rental system 100 of this embodiment shown in FIG. 1 is mainly composed of a vehicle 10, a terminal device 20, a business operator terminal 30, and an operations management device 40 (rental vehicle operations management device). The vehicle 10, the terminal device 20, the business operator terminal 30, and the operations management device 40 are configured to be able to communicate with each other via a network. An example of the network is the Internet. The network may also use a mobile communication function such as 4G / LTE or 5G.

[0011] Vehicle 10 is a rental vehicle owned by a business that provides a vehicle rental service. As shown in FIG. 1, vehicle 10 is, for example, a rental power-assisted bicycle. Note that vehicle 10 may also be a rental electric kick scooter, an electric vehicle, or a bicycle or kick scooter without a power-assisted function. In the example shown in FIG. 1, one vehicle 10 is shown, but there may be multiple vehicles 10, and the number of vehicles 10 is not particularly limited.

[0012] The terminal device 20 is a terminal device carried by a user of the vehicle rental service. For example, as shown in FIG. 1, the terminal device 20 is a mobile terminal such as a smartphone. The terminal device 20 may also be a wearable device such as smart glasses. Although one terminal device is shown in the example shown in FIG. 1, there may be multiple terminal devices 20, and the number of terminal devices 20 is not particularly limited.

[0013] The business operator terminal 30 manages maintenance information indicating the maintenance status of the vehicle 10. The business operator terminal 30 is configured, for example, by a personal computer or the like installed at the business premises of a business operator that provides a vehicle rental service. The business operator terminal 30 is operated by the business operator.

[0014] The operation management device 40 selects a candidate vehicle to be rented to a user from one or more vehicles 10. The operation management device 40 is installed, for example, at the business premises of a business that provides a vehicle rental service.

[0015] In the vehicle rental system 100 of this embodiment, the operation management device 40 acquires usage schedule information input by the user of the vehicle 10 from the terminal device 20, and selects candidate vehicles 10 to be rented to the user based on the usage schedule in the acquired usage schedule information. The operation management device 40 acquires, for each vehicle 10, status information of each part of the vehicle 10 detected by a sensor group 15 (described later) of the vehicle 10, and predicts the inspection timing of each part of the vehicle 10 for each vehicle 10. The operation management device 40 selects candidate vehicles 10 to be rented to the user based on the predicted inspection timing of each part of the vehicle 10. In the following explanation, various components common to vehicle rental services will be omitted, and various components necessary for operation and management of rental vehicles will be explained.

[0016] FIG. 2 is a block diagram showing an example of a schematic configuration of each element in the vehicle rental system 100. The vehicle 10, terminal device 20, business operator terminal 30, and operation management device 40 of the vehicle rental system 100 each have a controller (not shown). The controller can be configured using, for example, a general-purpose microcontroller. The microcontroller has a CPU (Central Processing Unit) and memory. The memory includes a ROM (Read Only Memory) and RAM (Random Access Memory). The microcontroller can virtually construct multiple information processing circuits by having the CPU execute a program stored in the memory.

[0017] [Vehicle configuration] The vehicle 10 includes a communication unit 11 , a memory unit 12 , an input / output unit 13 , a battery 14 , a sensor group 15 , and a CPU 16 .

[0018] The communication unit 11 is configured to be able to communicate with the operator terminal 30 and the operation management device 40 via a network. The communication unit 11 receives predetermined data from the operator terminal 30 and the operation management device 40, and transmits predetermined data to the operator terminal 30 and the operation management device 40. The communication unit 11 may be a device equipped with a mobile communication function such as 4G / LTE or 5G, or may be a device equipped with a Wi-Fi (registered trademark) communication function.

[0019] The storage unit 12 includes a volatile or non-volatile memory (not shown). The storage unit 12 may be configured separately from the memory of a microcontroller that constitutes the controller of the vehicle 10, or a part or all of the storage unit 12 may be configured by the memory of the microcontroller. The storage unit 12 stores various programs executed by the CPU 16. The storage unit 12 stores, for example, information indicating a vehicle ID assigned to each vehicle 10. The storage unit 12 temporarily stores, for example, output signals from the sensor group 15. The storage unit 12 can be configured, for example, by an SSD (Solid State Drive). The storage unit 12 may also be configured using an eMMC (Embedded Multi Media Card) or an HDD (Hard Disk Drive).

[0020] The input / output unit 13 has various switches, buttons, monitors, etc. that can be operated by the user. The input / output unit 13 receives various information necessary for using the vehicle 10 from the user of the vehicle 10, and outputs various information corresponding to the user's operations. The input / output unit 13 receives, for example, input of planned use information necessary for using the vehicle 10 from the user. The planned use information includes, for example, the period of use of the vehicle 10, and the departure and destination of the trip using the vehicle 10.

[0021] The battery 14 supplies power to electrical components (not shown) of the vehicle 10 .

[0022] The sensor group 15 is installed on the vehicle 10 to detect the state of each part of the vehicle 10 and output a signal corresponding to the detected state to the CPU 16. The sensor group 15 includes, for example, an air pressure sensor that detects the pressure inside the tires of the vehicle 10, an acceleration sensor that detects impacts applied to various parts of the frame of the vehicle 10 as acceleration, and a sensor that detects a terminal voltage corresponding to the charge rate as the remaining charge of the battery 14. Changes in acceleration detected by the acceleration sensor can be used as an index for determining the application of brakes (not shown) and estimating the wear of brake pads. Any known method can be used as a method for each sensor of the sensor group 15 to detect the state of each part.

[0023] Each sensor of the sensor group 15 may detect not only deterioration of each part of the vehicle 10 over time, but also deterioration due to overstress applied to the vehicle 10 while it is in use. The overstress may be caused by environmental factors and human factors. There is a correlation between the sensor data indicated by the signal output by each sensor of the sensor group 15 and the amount of deterioration of the part corresponding to each sensor. However, the amount of deterioration and deterioration trend of each part of the vehicle 10 may differ for each part and for each vehicle 10. Furthermore, when multiple sensors of different types are arranged in the same part of the same vehicle 10, the amount of deterioration and deterioration trend of the corresponding part indicated by the sensor data may differ for each type of sensor.

[0024] The CPU 16 may be, for example, the CPU of a microcontroller constituting the controller of the vehicle 10. When the CPU 16 receives information necessary for starting use of the vehicle 10 input by the user to the input / output unit 13, the CPU 16 transitions the vehicle 10 to a usable state. In the case of the vehicle 10 of this embodiment, which is an electrically assisted bicycle, the transition to a usable state may involve, for example, the CPU 16 unlocking the wheels of the vehicle 10 and starting the supply of power from the battery 14 to the electrical components of the vehicle 10. When the CPU 16 receives information necessary for return input by the user to the input / output unit 13, it determines that the rental has ended and transitions the vehicle 10 to a use-end state. When the transition to the use-end state occurs, for example, the CPU 16 may transmit status information together with the vehicle ID to the operation management device 40 via the communication unit 11. The status information is information indicating the status of each part of the vehicle 10 detected by the sensor group 15, and the CPU 16 can transmit the status information to the operation management device 40 via the communication unit 11 based on the output signals of the sensor group 15 temporarily stored in the memory unit 12. When the output signals of the sensor group 15 are input, the CPU 16 may cause the communication unit 11 to transmit the status information to the operation management device 40 in real time.

[0025] [Terminal device configuration] The terminal device 20 includes a communication unit 21, an input unit 22, a display unit 23, and a CPU 24.

[0026] The communication unit 21 is configured to be able to communicate with the operator terminal 30 and the operation management device 40 via a network. The communication unit 21 receives predetermined data from the operator terminal 30 and the operation management device 40, and transmits predetermined data to the operator terminal 30 and the operation management device 40. The communication unit 21 may be a device equipped with a mobile communication function such as 4G / LTE or 5G, or may be a device equipped with a Wi-Fi communication function.

[0027] The input unit 22 has various switches, buttons, etc. that can be operated by the user. The input unit 22 may include, for example, a touchpad provided on the screen of the display unit 23, which will be described later. The input unit 22 accepts input of planned use information operated by the user of the vehicle 10. The planned use information includes, for example, the period of use of the vehicle 10, and the departure and destination of the trip using the vehicle 10.

[0028] The display unit 23 is, for example, a display, and displays various types of information. The display format of the information is not particularly limited.

[0029] The CPU 24 may be, for example, the CPU of a microcontroller constituting the controller of the terminal device 20. When the input unit 22 accepts the planned use information input by the user, the CPU 24 causes the communication unit 21 to transmit the accepted planned use information to the operation management device 40. When the communication unit 21 receives a notification from the operation management device 40, the CPU 24 causes the display unit 22 to display vehicles 10 that are candidates for rental according to the notification.

[0030] For example, a user can launch an app on the terminal device 20 or access a specified website from the terminal device 20, input planned usage information into the input unit 22, and transmit the planned usage information to the operation management device 40 via the communication unit 21.

[0031] [Configuration of operator terminal] The operator terminal 30 includes a communication unit 31, an input / output unit 32, a storage unit 33, and a CPU .

[0032] The communication unit 31 is configured to be able to communicate with the vehicle 10, the terminal device 20, and the operation management device 40 via a network. The communication unit 31 may be a device having a mobile communication function such as 4G / LTE or 5G, or may be a device having a Wi-Fi communication function.

[0033] The input / output unit 32 includes, for example, a keyboard, a mouse, a monitor, a touch panel, etc. The input / output unit 32 receives various types of information required to manage maintenance information of the vehicle 10, and outputs the various types of information.

[0034] The business operator inputs maintenance information for the vehicle 10 into the business operator terminal 30. For example, when the business operator collects the vehicle 10, the business operator can charge or replace the battery 14, disinfect and clean the vehicle 10. For example, the business operator inputs the maintenance information for the vehicle 10 together with the vehicle ID of the vehicle 10. The maintenance information includes, for example, the date and time when the battery 14 of the vehicle 10 was charged, the date and time when the battery 14 of the vehicle 10 was replaced, the date and time when the vehicle 10 was cleaned, the date and time when the vehicle 10 was disinfected, and the number of times the vehicle 10 has been used since cleaning, disinfection, or battery 14 replacement. Hereinafter, the number of times the vehicle 10 has been used will be simply referred to as the "number of uses." Note that the maintenance information for the vehicle 10 may be input manually by the business operator operating the input / output unit 32, or may be input via the communication unit 31 from another device that manages the maintenance information for the vehicle 10.

[0035] The storage unit 33 has a volatile or non-volatile memory (not shown). The storage unit 33 may be configured separately from the memory of a microcontroller that constitutes the controller of the business operator terminal 30, or a part or all of the storage unit 33 may be configured with the memory of the microcontroller. The storage unit 33 stores the maintenance information input to the business operator terminal 30 from the communication unit 31 or the input / output unit 32, linking it to the vehicle ID.

[0036] The CPU 34 may be, for example, the CPU of a microcontroller constituting the controller of the business operator terminal 30. When the communication unit 31 receives an instruction from the operation management device 40 requesting maintenance information for the vehicle 10, the CPU 34 causes the communication unit 31 to transmit the maintenance information together with the vehicle ID to the operation management device 40. The CPU 34 transmits, for example, data indicating the number of times the battery 14 has been charged, the time elapsed since disinfection, the time elapsed since cleaning, and the number of times the vehicle 10 has been used as maintenance information for the vehicle 10 to the operation management device 40. The number of times the battery 14 has been charged is the number of times the business operator has charged the battery 14 since replacing it, and is calculated based on the date and time the battery 14 of the vehicle 10 was charged and the date and time the battery 14 was replaced. The time elapsed since disinfection is the time elapsed since the business operator last disinfected the vehicle 10 and is calculated based on the date and time the vehicle 10 was disinfected. The time elapsed since cleaning is the time elapsed since the business operator last cleaned the vehicle 10 and is calculated based on the date and time the vehicle 10 was cleaned. The number of uses is the number of times the vehicle 10 has been used since the business operator disinfected, cleaned, or replaced the battery 14.

[0037] [Configuration of operation management device] The operation management device 40 includes a communication unit 41 , a storage unit 42 , and a CPU 43 .

[0038] The communication unit 41 is configured to be able to communicate with the vehicle 10, the terminal device 20, and the operator terminal 30 via a network. The communication unit 41 can receive status information from the vehicle 10. When the communication unit 41 receives user usage schedule information from the terminal device 20, it transmits an instruction to the operator terminal 30 requesting maintenance information for each vehicle 10. The communication unit 41 may be a device equipped with a mobile communication function such as 4G / LTE or 5G, or may be a device equipped with a Wi-Fi communication function.

[0039] The storage unit 42 has a volatile or non-volatile memory (not shown). The storage unit 42 stores the status information of the vehicle 10 received by the communication unit 41 together with the vehicle ID. The storage unit 42 also stores the user's planned use information received by the communication unit 41 for each planned use. The storage unit 42 also stores the maintenance information for each vehicle 10 input from the business operator terminal 30 in association with the vehicle ID. The storage unit 42 also stores, for each vehicle 10, the inspection timing of each part of the vehicle 10 predicted by the CPU 43 (described later) based on the status information and maintenance information. The storage unit 42 can be configured using, for example, an eMMC, an SSD, or an HDD.

[0040] The CPU 43 may be, for example, the CPU of a microcontroller that constitutes the controller of the operation management device 40. The microcontroller of the operation management device 40 includes a memory in addition to the CPU 43. The memory includes a ROM and a RAM. The microcontroller of the operation management device 40 can virtually construct multiple information processing circuits by having the CPU 43 execute a program stored in the memory. When the controller of the operation management device 40 is constructed using a microcontroller, the multiple information processing circuits constructed by the microcontroller inside the controller can be used to configure each of the units 431 to 435, which will be described later, in the operation management device 40.

[0041] In this embodiment, an example is shown in which multiple information processing circuits built in the controller of the operation management device 40 are realized by software. Of course, it is also possible to configure the information processing circuits by preparing dedicated hardware for executing each of the information processes described below. Also, the multiple information processing circuits may be configured by individual hardware.

[0042] The first acquisition unit 431 acquires the status information of each part of the vehicle 10 that is received together with the vehicle ID by the communication unit 41. The first acquisition unit 431 acquires the status information of each vehicle 10 that is received by the communication unit 41, thereby being able to acquire the status information of each vehicle 10 for each vehicle 10.

[0043] The second acquisition unit 432 acquires the usage schedule information of the vehicle 10 when the communication unit 41 receives the usage schedule information of the vehicle 10 transmitted from the terminal device 20. The second acquisition unit 432 can acquire the usage schedule information of the vehicle 10 for each usage schedule by acquiring the usage schedule information received by the communication unit 41 for each usage schedule.

[0044] The first prediction unit 433 causes the communication unit 41 to transmit an instruction requesting maintenance information for each vehicle 10 to the business operator terminal 30. When the communication unit 41 receives the maintenance information for each vehicle 10 transmitted by the business operator terminal 30 together with the vehicle ID in response to the instruction, the first prediction unit 433 acquires the maintenance information.

[0045] The first prediction unit 433 predicts the level of deterioration of each part of the vehicle 10 at the start of one planned use for each vehicle 10, based on the status information of each vehicle 10 acquired by the first acquisition unit 431 and the use schedule information acquired by the second acquisition unit 432. The start of one planned use is the start of the planned use related to the use schedule information acquired by the second acquisition unit 432. This start time can be identified by the start of the use period in the use schedule information acquired by the second acquisition unit 432. FIG. 3 shows an example of the level of deterioration of each part of the vehicle 10 predicted by the first prediction unit 433 for each vehicle 10 at the start of the planned use related to the use schedule information acquired by the second acquisition unit 432. In the example of FIG. 3, the first prediction unit 433 predicts the levels of deterioration of parts 1 to 3 of three vehicles 10, a to c, at the start of the planned use, using three levels: high, medium, and low.

[0046] Specifically, the first prediction unit 433 identifies the current deterioration level of each vehicle 10 for each part based on the status information acquired by the first acquisition unit 431. The first prediction unit 433 predicts the level of deterioration of each part of the vehicle 10 at the start of the usage period for each vehicle 10 based on the identified current deterioration level, the date and time of the acquired maintenance information, the number of uses, and the period elapsed from the present to the start of the usage period. Examples of parts whose deterioration levels are predicted include brakes, tires (air pressure, wear), the battery 14, the engine, the steering wheel, and lights. The deterioration level of each part of the vehicle 10 can be identified or estimated using a known method. Examples of known methods include those described in Japanese Patent Application Laid-Open Nos. 2002-370630, 2005-227141, 2015-41304, 2020-13374, and 2021-68104.

[0047] The second prediction unit 434 predicts the magnitude of the load level to be applied to the vehicle 10 for each part during one use schedule related to the use schedule information, based on the use schedule information acquired by the second acquisition unit 432. Fig. 4 shows an example of the magnitude of the load level to be applied to the vehicle 10 for each part during a use schedule related to the use schedule information acquired by the second acquisition unit 432, predicted by the second prediction unit 434. In the example of Fig. 4, the second prediction unit 434 predicts the load level to be applied to parts 1 to 3 of the vehicle 10 during use schedule 1 of user A into three levels: high level, medium level, and low level.

[0048] Specifically, the second prediction unit 434 identifies a driving route of the vehicle 10 from the departure point to the destination based on, for example, the departure point and the destination in the planned use information acquired by the second acquisition unit 432. Map data can be used to identify the driving route. The driving route may be identified by the second prediction unit 434 or by an external device such as a car navigation system. The second prediction unit 434 predicts the level of the load applied to the vehicle 10 due to traveling along the identified driving route for each part. The load level for each part due to traveling along the driving route can be predicted by referring to, for example, the characteristics of the driving route. As shown in FIG. 4 , the load level of each part of the vehicle 10 predicted by the second prediction unit 434 may be stored in the storage unit 42 in association with, for example, at least one of the characteristics of the driving route referenced when predicting the load level and the planned use period for which the load level was predicted.

[0049] Characteristics of the travel route include, for example, tunnels, intersections / railroad crossings, slopes, curves, rough roads, and straight roads. Lights must be turned on in tunnels, and vehicle 10 frequently accelerates, decelerates, stops, and starts at intersections / railroad crossings and roads with heavy traffic congestion. On slopes, vehicle 10 is subjected to loads due to incline, and on curves, it is subjected to loads due to centrifugal force. Rough roads, for example, are unpaved, uneven, and have uneven surfaces, and vehicle 10 is susceptible to loads due to vibrations, shocks, dust, and other factors. Even if the road surface is not unpaved, in bad weather, road conditions can be worse than in fair weather due to factors such as temperature and moisture, which can, for example, place loads on parts of vehicle 10 related to its braking function. Furthermore, on straight roads with little traffic and good visibility, vehicle 10 is more likely to travel at high speeds, and tire pressure loss can place loads on the tires. On roads with a high number of pedestrians and other people running out into the road, vehicle 10 is more likely to be subjected to loads due to sudden braking.

[0050] When the planned use information includes information about the purpose of use of the vehicle 10, if the purpose of use is sightseeing, it is expected that there will be many stops, and if the purpose of use is commuting, shopping, etc., it is expected that the same short route will be traveled repeatedly. This information may be referenced when identifying the characteristics of the travel route of the vehicle 10 and predicting the load level of each part of the vehicle 10.

[0051] When predicting the load level on each part of the vehicle 10 based on the characteristics of the travel route, a table may be used that associates the load level on each part of the vehicle 10 with each characteristic item. This table may be stored in the storage unit 42, for example. If the vehicle 10 is a micromobility vehicle such as a bicycle or kick scooter, it may travel on narrow roads or rough roads that are impassable or cannot be traveled by automobiles. The above table may have individual content for each type of vehicle that the vehicle 10 is intended to be.

[0052] For example, long-distance high-speed driving is likely to cause deformation of tires due to a drop in tire pressure, and if this continues for a long period of time, the tires may overheat and burst, or the tire surface may peel off. The second prediction unit 434 may predict a high tire load level for a driving route involving long-distance high-speed driving. For example, as in the present embodiment, when the vehicle 10 is a micromobility vehicle such as an electrically assisted bicycle, electrical equipment such as a man-machine interface for the user may be installed on the handlebars. When driving on rough roads, the electrical equipment installed on the handlebars may deteriorate due to impacts when the handlebars are pulled or vibrations transmitted from the road surface to the handlebars. The second prediction unit 434 may predict a medium load level for a driving route involving the vehicle 10 traveling on rough roads.

[0053] For example, when traveling downhill, braking operations are likely to be more frequent, which may increase the load on the brakes. The second prediction unit 434 may predict that the brake load level will be high for a traveling route that includes a downhill section. For example, when traveling at night or in a tunnel, the lights are turned on, which causes the lights to wear out quickly. The second prediction unit 434 may predict that the light load level will be high for a traveling route that includes traveling at night or in a tunnel.

[0054] The third prediction unit 435 predicts the inspection timing of each part for each vehicle 10 based on the condition information acquired by the first acquisition unit 431 and the level of deterioration predicted by the first prediction unit 433 at the start time of the planned use related to the planned use information acquired by the second acquisition unit 432. The inspection timing of each part can be, for example, the time when each part is expected to reach a level of deterioration that requires inspection.

[0055] The inspection referred to here does not refer to an inspection to check whether the basic performance of the vehicle 10 complies with legal safety standards, but rather an inspection to ensure and guarantee the safety and comfort of users during the planned period of use. The third prediction unit 435 predicts signs of deterioration that could lead to a breakdown of the vehicle 10 in order to inspect the vehicle 10 at an appropriate time, determine whether the vehicle 10 can be continued to be used, and perform necessary maintenance on the vehicle 10. The vehicle 10 can be driven even after the inspection period has passed, but driving the vehicle 10 after the inspection period increases the risks to safety and comfort.

[0056] The third prediction unit 435 can predict the inspection timing, for example, by using a method in which the first prediction unit 433 predicts the degree of deterioration of each part of each vehicle 10 at the start time of the scheduled use. The inspection timing of each part predicted for each vehicle 10 by the third prediction unit 435 may be stored in the storage unit 42 in association with the level of deterioration of each part at the start time of the scheduled use predicted by the first prediction unit 433 for each vehicle 10, for example, as shown in FIG.

[0057] The selection unit 436 selects a candidate vehicle to be rented to one prospective user from one or more vehicles 10 based on the level of deterioration predicted by the first prediction unit 433 for parts of the vehicle 10 where the high load level predicted by the second prediction unit 434 is equal to or higher than a predetermined level. In this embodiment, the parts where the high load level predicted by the second prediction unit 434 is equal to or higher than a predetermined level are considered to be parts where the high load level is higher than a predetermined level.

[0058] For example, the selection unit 436 may select a candidate vehicle from one or more vehicles whose level of deterioration predicted by the first prediction unit 433 is equal to or less than a predetermined value for a part of the vehicle 10 whose load level predicted by the second prediction unit 434 is high. In this embodiment, a part whose level of deterioration predicted by the first prediction unit 433 is low is defined as a part whose level of deterioration is equal to or less than a predetermined value.

[0059] The selection unit 436 may select a candidate vehicle based on the inspection timing predicted by the third prediction unit 435 for a part having a high load level predicted by the second prediction unit 434 and the usage period of the vehicle 10 in the usage schedule information of one usage schedule. Figure 5 illustrates, for each vehicle 10 that is an option for a candidate vehicle, the relationship between the usage period of the vehicle 10 in the usage schedule information acquired by the second acquisition unit 432 and the inspection timing predicted by the third prediction unit 435 for a certain part of the vehicle 10.

[0060] For example, when the selection unit 436 selects a candidate vehicle from vehicles 10 whose deterioration level is low as predicted by the first prediction unit 433 for a part of the vehicle 10 whose load level is high as predicted by the second prediction unit 434, the selection unit 436 may select the candidate vehicle as follows: The selection unit 436 can select a candidate vehicle from one or more vehicles 10 for which the inspection period for the part whose load level is high as predicted by the second prediction unit 434 does not fall during the usage period of the vehicle 10 in the usage schedule information of one usage schedule.

[0061] For example, if the route that user A plans to travel has many downhill slopes, the brake load level for that planned use is predicted to be high, as shown in location 1 in Fig. 4. The selection unit 436 selects candidate vehicles from vehicles 10 a to c, which have low levels of brake deterioration, as shown in Fig. 3. In the example of Fig. 5, the selection unit 436 can select candidate vehicles by selecting vehicles 10 a and d, among vehicles 10 a to d, whose inspection due date will not arrive during the period of use, as candidate vehicles, and excluding vehicles 10 b and c, whose inspection due date will arrive during the period of use, from the candidate vehicle options.

[0062] For example, the selection unit 436 can select, as a candidate vehicle option, a vehicle 10 whose deterioration level is low as predicted by the first prediction unit 433, even for a part of the vehicle 10 whose load level is medium or low as predicted by the second prediction unit 434. The selection unit 436 may also accept, as a candidate vehicle option, a vehicle 10 whose deterioration level is medium or high as predicted by the first prediction unit 433, for a part whose load level is medium or low. In the example of FIG. 5 , the selection unit 436 adds vehicles 10 b and c whose inspection time will arrive during the usage period to the candidate vehicle options. This addition of options is meaningful, for example, when the inspection time predicted by the third prediction unit 435 arrives during the planned usage period for all vehicles 10 whose parts whose load level is predicted to be medium or low are predicted to have low deterioration at the start of the usage period.

[0063] Vehicles 10 added to the candidate vehicle options may be limited to vehicles 10 whose inspection due date falls within a predetermined period going back from the end of the usage period. By limiting the vehicles 10 added to the candidate vehicle options to those whose inspection due date falls close to the end of the usage period, the risk of malfunctioning of parts whose inspection due date falls during the usage period can be reduced. If a vehicle 10 whose inspection due date falls during the usage period becomes a candidate vehicle, the inspection due date can be changed to immediately after the end of the usage period and managed. Vehicles 10 other than candidate vehicles can be inspected at the predicted inspection time.

[0064] The vehicles 10 to be added to the candidate vehicle options may include vehicles 10 whose inspection period will arrive within a predetermined period from the start of the usage period. By limiting the vehicles 10 to be added to the candidate vehicle options to those whose inspection period is close to the start of the usage period and shifting the inspection period to before the start of the usage period, it is possible to increase the number of vehicles 10 to be added to the candidate vehicle options while keeping the period for shifting the inspection period short.

[0065] The CPU 43 may notify the terminal device 20 of the user who will rent out the candidate vehicle, of the candidate vehicle selected by the selection unit 436, via the communication unit 41. In this case, the vehicle 10 to be rented out to the user may be finalized by the user performing an approval operation for the notified candidate vehicle on the terminal device 20.

[0066] [Vehicle rental system operation] An example of a processing procedure in the operation management method for rental vehicles executed by the controller of the operation management device 40 will be described below with reference to the flowchart of FIG.

[0067] The first acquisition unit 431 of the operation management device 40 acquires status information of each part of the vehicle 10 for each vehicle 10 (step S1). The second acquisition unit 432 of the operation management device 40 acquires planned use information of the vehicle 10 by the user for each planned use (step S3). The processing of steps S1 and S3 may be performed in parallel, or may be performed sequentially with a staggered timing.

[0068] The first prediction unit 433 of the operation management device 40 predicts the level of deterioration of each part of the vehicle 10 at the start of one use schedule for each vehicle 10 based on the status information acquired by the first acquisition unit 431 and the use schedule information acquired by the second acquisition unit 432 (step S5). The second prediction unit 434 predicts the level of the load level to be applied to the vehicle 10 during one use schedule for each part based on the use schedule information acquired by the second acquisition unit 432 for one use schedule (step S7). The processes of steps S5 and S7 may be performed in parallel or may be performed sequentially with a staggered timing. The third prediction unit 435 predicts the inspection time for each part of the vehicle 10 based on the status information acquired by the first acquisition unit 431 and the level of deterioration predicted by the first prediction unit 433 (step S9).

[0069] The selection unit 436 of the operation management device 40 selects a candidate vehicle to be rented to a user of one scheduled use from one or more vehicles 10 based on the degree of deterioration predicted by the first prediction unit 433 for parts for which the load level predicted by the second prediction unit 434 is at or above a predetermined level (step S11). In step S11, the selection unit 436 selects a candidate vehicle from vehicles 10 for which the degree of deterioration predicted by the first prediction unit 433 is low for parts for which the load level predicted by the second prediction unit 434 is high. In step S11, the selection unit 436 selects a candidate vehicle from vehicles 10 for which the degree of deterioration predicted by the first prediction unit 433 is low and for which the inspection period for each part predicted by the third prediction unit 435 does not fall during the usage period of one scheduled use.

[0070] [Action and effect] For example, in vehicle 10 rental services such as car rentals, shared cars, and micromobility, the vehicles 10 are shared by an unspecified number of users. As a result, the parts (components) that deteriorate and wear out of the vehicles 10, and the progress of the deterioration and wear, are not uniform. In order to rent each vehicle 10 to the next user in optimal condition, it is necessary to inspect (maintain) each vehicle 10 at a time appropriate to the degree of deterioration and wear. However, because the timing and content of vehicle 10 inspections vary for each vehicle 10 or for each part of the vehicle 10, if vehicle 10 inspections are not performed efficiently, the decrease in vehicle 10 utilization rate due to inspections may not match user demand, which may impair user convenience and the profitability of the rental company.

[0071] On the other hand, in this embodiment, the degree of deterioration of each part of the vehicle 10 at the start of the planned use is predicted by reflecting the state of each part of the vehicle 10 contained in the state information of the vehicle 10, and a vehicle 10 with a low degree of deterioration for parts with a predicted high load level during the planned use is selected as a candidate vehicle to be rented to the user. Therefore, the state of each part of the vehicle 10 contained in the state information of the vehicle 10 can be widely reflected in the selection of vehicles 10 for rental. This allows for integrated management of the state of deterioration and wear of the vehicle 10 and information regarding the planned use (rental) status, making it possible to efficiently select a vehicle 10 appropriate for the user's planned use as a candidate vehicle and rent it to the user.

[0072] In this embodiment, candidate vehicles are selected from among vehicles 10 with a low level of deterioration predicted by the first prediction unit 433, and from vehicles 10 for which the inspection times for each part predicted by the third prediction unit 435 do not fall within a single planned use period. However, even for vehicles 10 for which the inspection times for each part predicted by the third prediction unit 435 fall within a single planned use period, vehicles 10 that satisfy certain conditions regarding the relationship between the inspection times and the use period may be added to the options for candidate vehicles selected by the selection unit 436. Furthermore, the relationship between the inspection times and the use period may be excluded from the conditions for the selection of candidate vehicles by the selection unit 436. In this case, the third prediction unit 435 and the processing performed by the third prediction unit 435 can be omitted. When the relationship between the inspection times and the use period is excluded from the selection conditions for candidate vehicles, the selection unit 436 can select candidate vehicles based on the level of deterioration predicted by the first prediction unit 433 for parts for which the load level predicted by the second prediction unit 434 is equal to or greater than a predetermined level.

[0073] Although the embodiments of the present invention have been described above, the embodiments can be modified or varied based on the above disclosure. All components of the above embodiments and all features described in the claims may be individually extracted and combined, unless they contradict each other. [Explanation of symbols]

[0074] 10 vehicles 40 Operation management device 43 CPU 431 First acquisition part 432 Second Acquisition Department 433 First Prediction Section 434 Second Prediction Section 435 Third Prediction Department 436 Selection Section

Claims

1. a first acquisition unit that acquires state information of each part of the vehicle for each vehicle; a second acquisition unit that acquires vehicle use plan information by a user for each use plan; a first prediction unit that predicts the degree of deterioration of each part of the vehicle at the start time of one usage schedule for each vehicle based on the status information acquired by the first acquisition unit and the usage schedule information acquired by the second acquisition unit; a second prediction unit that predicts a level of a load applied to the vehicle for each part during the one use schedule based on the use schedule information acquired by the second acquisition unit for the one use schedule; a selection unit that selects a candidate vehicle to be rented to the one prospective user from one or more vehicles based on the level of deterioration predicted by the first prediction unit for a portion where the level of the load level predicted by the second prediction unit is equal to or higher than a predetermined level; and A rental vehicle operation management device comprising:

2. The rental vehicle operation management device described in claim 1, wherein the selection unit selects the candidate vehicle from one or more vehicles in which the level of deterioration predicted by the first prediction unit is below a predetermined value for parts where the load level predicted by the second prediction unit is above the predetermined level.

3. The rental vehicle operation management device of claim 1 further comprises a third prediction unit that predicts the inspection date for each part for each vehicle based on the condition information acquired by the first acquisition unit and the level of deterioration predicted by the first prediction unit, and the selection unit selects the candidate vehicle based on the inspection date predicted by the third prediction unit for parts where the load level predicted by the second prediction unit is equal to or higher than the predetermined level and the vehicle usage period in the usage schedule information for the one usage schedule.

4. The rental vehicle operation management device according to claim 3 , wherein the selection unit selects the candidate vehicle from one or more vehicles whose inspection due date does not arrive during the usage period.

5. The rental vehicle operation management device described in claim 1, wherein the second prediction unit predicts the level of load to be applied to the vehicle for each part during one usage schedule using a table that defines the level of load for each part for each item related to the vehicle's driving route in the usage schedule information.

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