Schedule setting device and schedule setting method

Abstract

The invention provides a schedule making device and a schedule making method. The schedule making device and the schedule making method provide a transport schedule and a charging schedule which are high in transport efficiency and easy to modify even if the schedule needs to be modified. The schedule formulating device formulates a schedule combination including a transport schedule and a charging schedule on the basis of the plurality of parameter values, evaluates the efficiency of transport and the ease of modifying the schedule for each of the formulated one or more schedule combinations, and outputs information on at least a portion of the schedule combination having relatively high efficiency and ease of modifying. For one or more restricting parameter value combinations, the restricting parameter value combination is a combination composed of a plurality of restricting parameter values corresponding to the plurality of restricting parameter names, respectively. The constraint parameter value of the at least one constraint parameter name affects the ease of modification.

Description

Technical Field

[0001] The present invention generally relates to techniques for creating schedules, and particularly to techniques for creating schedules for transportation performed by electric vehicles and schedules for charging electric vehicles. Background Art

[0002] When an electric vehicle is used as a transportation vehicle such as a truck, it is required to create a charging schedule in addition to the transportation schedule. As an electric vehicle, for example, there is an electric car. As a technique for creating a transportation schedule and a charging schedule for an electric vehicle, there is the technique described in Patent Document 1. In this publication, there is a description of "a battery charging system, characterized in that: the charging schedules of the respective electric vehicles are aggregated with the vehicle operation schedules of the respective electric vehicles, and after adjusting the respective schedules, they are determined."

[0003] Prior Art Documents

[0004] Patent Documents

[0005] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2010-231258 Summary of the Invention

[0006] Problems to be Solved by the Invention

[0007] In creating a transportation schedule and a charging schedule, multiple predicted parameter values are referred to. The "predicted parameter value" is a predicted value that serves as the basis for the transportation schedule and / or the charging schedule. As predicted parameter values, for example, there are the power consumption and the amount of goods of a building, etc. Based on multiple parameter values including multiple predicted parameter values, a transportation schedule and a delivery schedule are created on weekends or at night on the previous day, etc.

[0008] There may be a prediction error in at least one predicted parameter value. Considering the risk of a prediction error occurring, in order to make it unnecessary for the schedule maker to modify the temporarily created schedule, at least one predicted parameter value input for creating the schedule is set to a value with a margin. The value used as this margin is referred to as a "buffer value". The buffer value can also be referred to as the allowable degree of prediction error of the predicted parameter value.

[0009] Assuming that the prediction deviates in the direction of an increase in transportation load, by setting a larger buffer value for predicted parameter values such as the number of necessary vehicles and the operation time, it is possible to expect a schedule where it is unnecessary to modify the schedule even if the prediction deviates. However, since the number of necessary vehicles and the operation time, etc. are estimated to be large, this schedule is a schedule with low transportation efficiency.

[0010] In recent years, in the transportation industry, a shortage of workers has become a social problem, and there is a demand for increased efficiency. To improve efficiency, the buffer value can be reduced. However, when the buffer value is reduced, the necessity of modifying the schedule increases.

[0011] Technical solution for solving the problem

[0012] One of the representative embodiments of the present invention for solving at least one of the above problems is as follows. The schedule creation device creates a schedule combination including a transportation schedule and a charging schedule (a schedule based on the transportation schedule) based on a plurality of parameter values. The transportation schedule is for transporting a plurality of goods to a plurality of locations by a plurality of transportation vehicles including a plurality of electric vehicles that need to be charged, and the charging schedule is a schedule for charging the plurality of electric vehicles. The schedule creation device evaluates the efficiency of transportation and the ease of modifying the schedule for each of one or more schedule combinations, and outputs information on at least a part of the schedule combination with relatively high efficiency and ease of modification. The plurality of parameter values include a plurality of predicted parameter values and one or more combinations of constraint parameter values. Each predicted parameter value is a predicted value for a parameter name. Each of the plurality of constraint parameter names corresponds to one or more constraint parameter values. For each of one or more combinations of constraint parameter values, the combination of constraint parameter values is a combination composed of a plurality of constraint parameter values respectively corresponding to the plurality of constraint parameter names. At least one constraint parameter value affects the ease of modification.

[0013] Advantageous effects of the invention

[0014] According to one aspect of the present invention, it is possible to provide a transportation schedule and a charging schedule that are easy to modify even when the schedule needs to be modified and have high transportation efficiency. Problems, structures, and effects other than the above will be described through the following description of embodiments. Description of the drawings

[0015] Figure 1 FIG. is an example of the structure of the schedule creation system according to the embodiment and an example of the functional structure of the schedule creation device.

[0016] Figure 2 FIG. is an example of the hardware structure of the schedule creation system according to the embodiment.

[0017] Figure 3 FIG. is a flowchart showing an example of a series of processes performed in the embodiment.

[0018] Figure 4 FIG. is a diagram showing an example of the data structure of the prediction actual result information according to the embodiment.

[0019] Figure 5 FIG. is a diagram showing an example of the data structure of the parameter information according to the embodiment.

[0020] Figure 6 FIG. is a diagram showing an example of the data structure of the order information according to the embodiment.

[0021] Figure 7A diagram that is an example of a data structure representing vehicle information of an embodiment.

[0022] Figure 8 A diagram that is an example of a data structure representing location information of an embodiment.

[0023] Figure 9 A diagram that is an example of a data structure representing charger information of an embodiment.

[0024] Figure 10 A diagram that is an example of a data structure representing mobile cost information of an embodiment.

[0025] Figure 11 A diagram that is an example of a data structure representing evaluation information of an embodiment.

[0026] Figure 12 A diagram that is an example of a data structure representing transportation schedule plan information of an embodiment.

[0027] Figure 13 A diagram that is an example of a data structure representing charging schedule plan information of an embodiment.

[0028] Figure 14 A flowchart that is an example of a schedule creation process of an embodiment.

[0029] Figure 15 A flowchart that is an example of a schedule evaluation process of an embodiment.

[0030] Figure 16 A diagram that is an example of a transportation management screen of an embodiment.

[0031] Figure 17 A diagram that is an example of a charging management screen of an embodiment.

[0032] Figure 18 A diagram that is an example of a vehicle-oriented screen of an embodiment.

[0033] Figure 19 A diagram that is an example of a location-oriented screen of an embodiment. Detailed implementation manners

[0034] In the following description, the "interface device" may be one or more interface devices. The one or more interface devices may be at least one of the following.

[0035] ·One or more I / O (Input / Output) interface devices. The I / O (Input / Output) interface device is an interface device corresponding to at least one of the I / O device and the remote display computer. The I / O interface device corresponding to the display computer may be a communication interface device. At least one I / O device may be any one of a user interface device, such as an input device like a keyboard and a pointing device, and an output device like a display device.

[0036] ·One or more communication interface devices. One or more communication interface devices may be one or more communication interface devices of the same type (e.g., one or more NICs (Network Interface Cards)), or may be two or more communication interface devices of different types (e.g., a NIC and an HBA (Host Bus Adapter)).

[0037] In addition, in the following description, "memory" is one or more memory devices as an example of one or more storage devices, and typically may be a main storage device. At least one of the storage devices in the memory may be a volatile memory device or a non-volatile memory device.

[0038] In addition, in the following description, "persistent storage device" may be one or more persistent storage devices as an example of one or more storage devices. The persistent storage device is typically a non-volatile storage device (e.g., an auxiliary storage device), and specifically, for example, may be an HDD (Hard Disk Drive), an SSD (Solid State Drive), an NVME (Non-Volatile Memory Express) drive, or an SCM (Storage Class Memory).

[0039] In addition, in the following description, "storage device" may be at least the memory among the memory and the persistent storage device.

[0040] In addition, in the following description, a "processor" may be more than one processor device. Typically, at least one processor device may be a microprocessor device such as a CPU (Central Processing Unit), but may also be other types of processor devices such as a GPU (Graphic Processing Unit). At least one processor device may be single-core or multi-core. At least one processor device may also be a processor core. At least one processor device may also be a circuit that is an aggregate of gate arrays described in a hardware description language for performing part or all of the processing (e.g., a general processor device such as an FPGA (Field-Programmable Gate Array), a CPLD (Complex Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit)).

[0041] In addition, in the following description, the function is described using the expression "yyy unit", but the function may be implemented by executing one or more computer programs by a processor, may be implemented by one or more hardware circuits (e.g., an FPGA or an ASIC), or may be implemented by a combination thereof. When the function is implemented by executing a program by a processor, since appropriate processing is performed using a storage device and / or an interface device, etc., the function may also be regarded as at least part of the processor. The processing described with the function as the subject may be processing performed by the processor or a device having the processor. The program may be installed from a program source. The program source may be, for example, a program distribution computer or a computer-readable storage medium (e.g., a non-transitory storage medium). The description of each function is an example, and multiple functions may be combined into one function, or one function may be divided into multiple functions.

[0042] In addition, as information for identifying an element (identification information, identifier), any information (e.g., at least one of "ID", "name", and "number") may be adopted.

[0043] In addition, in the following description, the unit of "date and time" may be a coarser unit or a finer unit than month, day, hour, and minute.

[0044] Hereinafter, embodiments will be described with reference to the drawings. In this embodiment, the same reference numerals are attached to the same structures in principle, and repeated descriptions are omitted. In addition, it should be noted that this embodiment is only an example for implementing the present invention and does not limit the technical scope of the present invention.

[0045] Figure 1This is a diagram showing an example of the structure of the schedule creation system 1 for embodiments and an example of the functional structure of the schedule creation device 100.

[0046] The schedule creation system 1 includes a schedule creation device 100, an in-vehicle terminal 200 communicably connected to the schedule creation device 100 via a network 51, a schedule management terminal 300 at a location, and a charging control device 400. The schedule creation device 100, the in-vehicle terminal 200, the schedule management terminal 300, and the charging control device 400 may each include an interface device, a storage device, and a processor connected thereto.

[0047] The schedule creation device 100 has functions such as a storage unit 110, a control unit 130, an input unit 140, and an output unit 141 (for example, including the functions of at least one of a display unit 150 and a communication unit 160). These functions can be realized by the CPU 410 (refer to Figure 2 ) of the schedule creation device 100 executing a program.

[0048] The storage unit 110 stores prediction performance information 111, parameter information 112, order information 113, vehicle information 114, location information 115, charger information 116, movement cost information 117, evaluation information 118, transportation schedule plan information 119, and charging schedule plan information 120. The prediction performance information 111 is information on predictions and actual performances in past transportation schedules and charging schedules. The parameter information 112 is information on calculation parameters considered when creating a transportation schedule or a charging schedule. The order information 113 is order information for goods to be transported. The vehicle information 114 is information on vehicles that can be used when executing a schedule. The location information 115 is information on locations where at least one of pickup, delivery, and charging is performed. The charger information 116 is information on chargers installed at locations that are the objects of the charging schedule. The movement cost information 117 is information defining the cost required to move between two locations. The evaluation information 118 is information on parameters for evaluating the combination of the created transportation schedule plan and the charging schedule plan. The transportation schedule plan information 119 is information on the transportation schedule plan generated by the control unit 130. The charging schedule plan information 120 is information on the charging schedule plan generated by the control unit 130.

[0049] The control unit 130 includes a prediction error calculation unit 131, a schedule creation unit 132, and an evaluation unit 133. The prediction error calculation unit 131 calculates a buffer value of the input information using the prediction actual result information 111, and stores the calculated buffer value in the parameter information 112. The schedule creation unit 132 uses the parameter information 112, the order information 113, the vehicle information 114, the location information 115, the charger information 116, and the movement cost information 117 to generate a transportation schedule plan and a charging schedule plan, stores the transportation schedule plan in the transportation schedule plan information 119, and stores the charging schedule plan in the charging schedule plan information 120. The evaluation unit 133 uses the parameter information 112, the generated transportation schedule plan information 119, and the charging schedule plan information 120 to evaluate the modification cost of modifying the schedule from the viewpoints of transportation efficiency, the necessity of modifying the schedule, and the ease of modifying the schedule, and stores the combination of the optimal transportation schedule plan and the charging schedule plan as the optimal schedule.

[0050] The input unit 140 accepts the input operations of the user.

[0051] The output unit 141 outputs information. For example, the display unit 150 displays the transportation schedule and the charging schedule created by the control unit 130 on the display device 450 (refer to Figure 2 ). The communication unit 160 sends or receives information to and from the in-vehicle terminal 200, the schedule management terminal 300 at the location, and the charge control device 400.

[0052] The in-vehicle terminal 200 is an information processing terminal installed in an electric vehicle (such as an electric car) serving as a transportation vehicle. The in-vehicle terminal 200 has functions such as a communication unit 210, a control unit 220, and a display unit 230. The communication unit 210 sends the current status information of the vehicle (information indicating the current status of the vehicle) to the communication unit 160, or receives the vehicle-oriented information (such as information indicating the transportation schedule of the vehicle) sent from the communication unit 160 of the schedule creation device 100. "The vehicle" refers to the transportation vehicle having the in-vehicle terminal 200. When the vehicle is in autonomous driving, the control unit 220 controls the vehicle in such a way as to perform transportation in accordance with the transportation schedule indicated by the received vehicle-oriented information. When the driver drives the vehicle, the control unit 220 instructs the display unit 230 to display an alarm when there is a deviation of a certain amount or more between the transportation schedule indicated by the vehicle-oriented information and the actual result. The display unit 230 displays the transportation schedule indicated by the received vehicle-oriented information and the alarm indicated by the control unit 220 on the display screen of the in-vehicle terminal 200.

[0053] The schedule management terminal 300 is configured at each location. The schedule management terminal 300 has functions such as a communication unit 310, a control unit 320, and a display unit 330. The communication unit 310 receives location-oriented information for the local location (e.g., information indicating the transportation schedule and / or charging schedule for the local location) sent from the communication unit 160 of the schedule creation device 100. "The local location" refers to the location where the schedule management terminal 300 is configured. The control unit 320 determines whether the collection, delivery, or charging acceptance system is complete, and issues an operation instruction when it is not complete. The display unit 330 displays the transportation schedule and charging schedule indicated by the received location-oriented information on the display screen of the schedule management terminal 300.

[0054] The charging control device 400 is respectively configured at multiple (or one) charging locations among multiple locations. "The charging location" refers to a location where charging can be performed. The charging control device 400 has functions such as a communication unit 41 and a control unit 42. The communication unit 41 receives location-oriented information for the local charging location (e.g., information indicating the charging schedule in the local charging location) sent from the communication unit 160 of the schedule creation device 100. "The local charging location" refers to the charging location where the charging control device 400 is configured. The control unit 42 controls the charging of the charger and the vehicle according to the charging schedule indicated by the location-oriented information for the local charging location.

[0055] Figure 2 It is a block diagram showing an example of the hardware structure of the schedule creation system 1 according to the embodiment.

[0056] The schedule creation device 100 has a CPU (Central Processing Unit) 410, a RAM (Random Access Memory) 420, a ROM (Read Only Memory) 430, an auxiliary storage device 440, a display device 450, an input device 460, a medium reading device 470, and a communication device 480. The schedule creation device 100 can communicate with the in-vehicle terminal 200 of the vehicle 510 ( Figure 2 omitted), the schedule management terminal 300 at the location 520 for collection and charging ( Figure 2 omitted), and the charging control device 400 at the location 520 for charging ( Figure 2 omitted) via the communication device 480. The medium reading device 470 and the communication device 480 are examples of interface devices. The RAM 420 and the ROM 430 are examples of memories. The auxiliary storage device 440 is an example of a persistent storage device. The CPU 410 is an example of a processor.

[0057] The CPU 410 is a device that performs various operations. The RAM 420 is a memory that stores programs, data, etc. executed by the CPU 410. The ROM 430 is a memory that stores programs, etc. required for starting the schedule creation system. The auxiliary storage device 440 is a device such as an HDD (Hard Disk Drive), for example. The display device 450 is a device such as a liquid crystal display, for example. The input device 460 is a device such as a keyboard for a user to input information to the schedule creation device 100. The medium reading device 470 is a device that reads information from a removable storage medium such as a USB (Universal Serial Bus) memory (USB is a registered trademark). The communication device 480 is a device that transmits or receives information to / from an external device via the network 51. For example, Figure 1 The information 111 to 120 shown is stored in the RAM 420 or the like.

[0058] An in-vehicle terminal 200 is provided in the vehicle 510, and the in-vehicle terminal 200 communicates with the schedule creation device 100 via the network 51. In addition, a communication device 20 and a charge control device 400 that communicate via the network 51 are provided at a location 520 where charging is possible. The communication unit 41 of the charge control device 400 can communicate with the schedule creation device 100 via the communication device 20.

[0059] The schedule creation device 100 is a physical computer system (one or more computers) in the present embodiment, but may be changed to a logical computer system based on a physical computer system (for example, a system as a cloud computer service based on a cloud infrastructure). For example, instead of having the display device 450 and the input device 460, the schedule creation device 100 may communicate with a remote client computer having a display device and an input device via the communication device 480.

[0060] Figure 3 is a flowchart showing an example of a series of processes of the embodiment.

[0061] The input unit 140 acquires the information 111 to 118 (S100) in response to an input operation from at least one of the in-vehicle terminal 200, the schedule management terminal 300, and the input device 460. At least a part of the acquired information 111 to 118 may include the information input by the input operation.

[0062] Next, the prediction error calculation unit 131 calculates a buffer considered when creating a schedule, and saves the calculated buffer to the parameter information 112 (S200).

[0063] Next, the schedule creation unit 132 generates a transportation schedule plan and a charging schedule plan, saves the generated transportation schedule plan to the transportation schedule plan information 119, and saves the generated charging schedule plan to the charging schedule plan information 120 (S300).

[0064] Next, the evaluation unit 133 performs schedule evaluation processing (S400). The schedule evaluation processing is processing for evaluating the combination of the transportation schedule plan and the charging schedule plan and saving these schedule plans when a good evaluation is obtained.

[0065] Finally, the schedule is output (S500). Specifically, the display unit 150 displays the schedule on the display device 450. In addition, the communication unit 160 transmits vehicle-oriented information to the in-vehicle terminal 200 via the network 51, or transmits location-oriented information to the schedule management terminal 300, or transmits location-oriented information of the charging location to the charging control device 400.

[0066] S300 and S400 are performed for each combination of a plurality of (all types in this embodiment) constraint parameter values. The "constraint parameter value combination" is a combination composed of a plurality of constraint parameter values. For example, when the constraint parameter values of the constraint parameter name "A" are "a1" and "a2", and the constraint parameter values of the constraint parameter name "B" are "b1" and "b2", all types of constraint parameter value combinations are the four combinations of (a1, b1), (a2, b1), (a1, b2), and (a2, b2). The "constraint parameter value" is a parameter value that affects the ease of modifying the schedule. The "ease of modifying the schedule" is one of the evaluation items of the schedule. The details of the "constraint parameter value" and the "ease of modifying the schedule" are described later.

[0067] Hereinafter, Figure 3 each step of

[0068] In S100, the predicted actual information 111, the parameter information 112, the order information 113, the vehicle information 114, the location information 115, the charger information 116, the movement cost information 117, and the evaluation information 118 are acquired. Examples of the information 111 to 118 are described below. The structure of the information 111 to 118 (for example, the information included in the entries) is not limited to the following examples.

[0069] Figure 4 is a diagram showing an example of the data structure of the predicted actual information 111 showing the embodiment.

[0070] The predicted actual information 111 has entries for each group of prediction and actual. The entries include information such as the date 401, the item 402, the predicted score 403, and the error 404.

[0071] The date 401 represents the schedule object date (the date of the schedule as an object). "Item" represents an item as a prediction parameter name. The prediction score 403 is a prediction parameter value. The error 404 represents a prediction error, that is, the error between the prediction parameter value and the actual value (actual value) obtained on the schedule object date for the prediction parameter name. As the item 402 (prediction parameter name), for example, at least one of the electricity consumption of a building, the maximum demand target, the remaining power at the start of transportation, the power consumption, the electricity cost between locations, the delivery time, and the quantity of goods can be adopted.

[0072] Figure 5 It is a diagram showing an example of the data structure of the parameter information 112 of the embodiment.

[0073] The parameter information 112 has entries for each group of an item and a value. The entries include information such as the item 501 and the value 502.

[0074] The item 501 represents a constraint parameter name or a buffer name. The value 502 represents a constraint parameter value or a buffer value. Depending on the constraint parameter name (or buffer name), multiple constraint parameter values (or multiple buffer values) can be set as the value 502. Specifically, for example, regarding the constraint parameter name "lower limit value of the total time of staying at a location without charging", there are three constraint parameter values "0", "60", and "120".

[0075] Figure 6 It is a diagram showing an example of the data structure of the order information 113 of the embodiment.

[0076] The order information 113 has entries for each order. The entries include information such as the order number 601, the pickup location code 602, the delivery destination code 603, the quantity 604, the pickup date and time (start) 605, the pickup date and time (end) 606, the delivery date and time (start) 607, and the delivery date and time (end) 608.

[0077] The order number 601 represents the identification number of the order. The pickup location code 602 represents the identification code of the location of the pickup location. The delivery destination code 603 represents the identification code of the location of the delivery destination. The quantity 604 represents the number of goods. The pickup date and time (start) 605 and the pickup date and time (end) 606 represent the start date and time and the end date and time of the period during which pickup is possible. The delivery date and time (start) 607 and the delivery date and time (end) 608 represent the start date and time and the end date and time of the period during which delivery is possible. The value of the quantity 604 can be an example of the value of the quantity of goods, and the value of the quantity of goods can replace the number of goods or, in addition thereto, be expressed based on at least one of the value of the total weight of the goods and the value of the total volume of the goods. The expression of the period during which pickup is possible and the period during which delivery is possible can also be expressed by the combination of the start date and time and the period length from the start date and time.

[0078] Figure 7 It is a diagram showing an example of the data structure of vehicle information 114 of the embodiment.

[0079] Vehicle information 114 has entries for each vehicle. The entries include information such as vehicle name 701, upper limit of loading quantity 702, unit price of vehicle 703, unit price of operation 704, upper limit of charging quantity 705, lower limit of charging quantity 706, and power consumption 707.

[0080] Vehicle name 701 represents the identification name of the vehicle. The upper limit of loading quantity 702 represents the upper limit of the loading quantity of the vehicle (e.g., the upper limit of the number of goods). The unit price of vehicle 703 represents the arrangement cost for one vehicle. The unit price of operation 704 represents the usage fee of the vehicle per unit time of operation. The upper limit of charging quantity 705 represents the upper limit of the charging quantity for the vehicle. The lower limit of charging quantity 706 represents the lower limit of the charging quantity for the vehicle. Power consumption 707 represents the power consumption of the vehicle. The value of the upper limit of loading quantity 702 can represent, instead of or in addition to the upper limit value of the number of goods that can be loaded, at least one of the upper limit value of the weight that can be loaded and the upper limit value of the volume that can be loaded. In addition, the entry can have, instead of or in addition to at least a part of the information 702 to 707, information on "driver unit price" representing the personnel cost of the driver per unit time of operation of the vehicle, and can also have information on "carbon dioxide emission unit price" representing the carbon dioxide emission amount per unit consumption of electricity.

[0081] Figure 8 It is a diagram showing an example of the data structure of location information 115 of the embodiment.

[0082] Location information 115 has entries for each location. The entries include information such as location name 801, operation time 802, latitude 803, longitude 804, and upper limit of charging quantity 805.

[0083] Location name 801 represents the identification name of the location. Operation time 802 represents the time taken for the operation (loading or unloading) of one piece of goods at the location, i.e., the operation time. Latitude 803 represents the latitude of the location, and longitude 804 represents the longitude of the location. The upper limit of charging quantity 805 represents the upper limit of the amount of electricity that can be charged per unit time at the location. Operation time 802 can also be divided into information on "loading time" representing the time taken for loading one piece of goods and information on "unloading time" representing the time taken for unloading one piece of goods. Furthermore, the entry can have, instead of or in addition to at least a part of the information 802 to 805, information on "electricity consumption of buildings" representing the electricity consumption of the buildings at the location.

[0084] Figure 9 It is a diagram showing an example of the data structure of charger information 116 of the embodiment.

[0085] The charger information 116 has an entry for each charger. The entry has information such as the location name 901, charger number 902, charging amount 903, acceptance time (start) 904, acceptance time (end) 905, charging mode 906, and operation parallelizability flag 907.

[0086] The location name 901 represents the identification name of the location. The charger number 902 represents the identification number of the charger in the location. The charging amount 903 represents the charging amount per unit time that can be charged using the charger. The acceptance time (start) 904 represents the start date and time of the time period during which the charger can be used, and the acceptance time (end) 905 represents the end date and time of this time period. The charging mode 906 represents the charging mode that can be used in the charger. The operation parallelizability flag 907 represents whether charging and loading or unloading can be performed in parallel at the location. The entry may also have information on "electricity cost" indicating the electricity cost required for charging per unit time.

[0087] Figure 10 It is a diagram showing an example of the data structure of the movement cost information 117 of the embodiment.

[0088] The movement cost information 117 has an entry for each group of departure location and arrival location. The entry includes information such as the departure location 1001, arrival location 1002, movement time 1003, power consumption coefficient 1004, and movement distance 1005.

[0089] The departure location 1001 represents the identification name of the departure location (movement source location). The arrival location 1002 represents the identification name of the arrival location (movement destination location). The movement time 1003 represents the movement time from the departure location to the arrival location. The power consumption coefficient 1004 represents the ratio of the magnitude of the power consumption generated by moving from the departure location to the arrival location. The movement distance 1005 represents the movement distance from the departure location to the arrival location.

[0090] Figure 11 It is a diagram showing an example of the data structure of the evaluation information 118 of the embodiment.

[0091] The evaluation information 118 has an entry for each evaluation item. The entry has information such as the item 1101 representing the item name of the evaluation item and the value 1102 representing the evaluation value corresponding to the evaluation item. "Efficiency" is the efficiency of transportation, "necessity for modification" is the necessity for modifying the schedule, and "ease of modification" is the ease of modifying the schedule.

[0092] At Figure 3In S200, the prediction error calculation unit 131 uses the prediction actual result information 111, order information 113, vehicle information 114, location information 115, charger information 116, and moving cost information 117 to calculate a buffer value used in schedule creation and stores it in the parameter information 112.

[0093] In the prediction actual result information 111, the prediction score 403 is a predicted parameter value calculated by a predetermined method for the predicted parameter name indicated by the item 402. For example, the prediction score 403 corresponding to the item 402 "electricity consumption of a building" is set to the maximum electricity consumption at the time of the schedule target date and time indicated by the date 401. The error 404 is the difference between the prediction score 403 and the actual value calculated by the same method as the prediction score 403. The prediction error calculation unit 131 determines the buffer value of the prediction score 403 based on at least a part of the group of the prediction score 403 and the error 40, order information 113, vehicle information 114, location information 115, charger information 116, and moving cost information 117. The input unit 140 receives at least one of weather information (for example, information indicating the weather at each location during a period including the schedule target date and time) and congestion information (for example, information indicating the degree of congestion between each location during a period including the schedule target date and time) from the outside, and the prediction error calculation unit 131 can use at least a part of the group of the prediction score 403 and the error 40, order information 113, vehicle information 114, location information 115, charger information 116, and moving cost information 117, and at least one of weather information and congestion information to determine the buffer value.

[0094] In S300, the schedule creation unit 132 creates a transportation schedule plan and a charging schedule plan based on at least a part of the parameter information 112, order information 113, vehicle information 114, location information 115, charger information 116, and moving cost information 117, stores the transportation schedule plan in the transportation schedule plan information 119, and stores the charging schedule plan in the charging schedule plan information 120. As the constraint parameter name of the parameter information 112, for example, at least one of "upper limit of the usage time of fast chargers", "lower limit of the staying time at a location without charging", "peak power", "upper limit of the number of simultaneously staying vehicles during business hours", "upper limit of the number of vehicles with a large ratio of driving distance to cruising distance", "upper limit of the number of operations with a short length of the continuous operable time period", and "lower limit of the difference between the operation end time and the operation deadline" can be adopted. For example, when the value 502 of the item 501 "peak power" is "240 kW", even if the charging amount upper limit 805 stored in the location information 115 is "300 kW", the schedule plan must be created in such a way that the peak power is 240 kW or less.

[0095] Figure 12 It is a diagram showing an example of a data structure of the transportation schedule plan information 119 of the embodiment.

[0096] The transportation schedule plan information 119 has information representing one or more transportation schedule plans. Figure 12 The transportation schedule plan information 119 illustrated as an example in [it] represents one transportation schedule plan. The information representing the transportation schedule plan has entries for each event related to transportation. The entries include information such as vehicle name 1201, location name 1202, status 1203, order number 1204, quantity 1205, time (start) 1206, and time (end) 1207.

[0097] The vehicle name 1201 represents the identification name of the vehicle. The location name 1202 represents the identification name of the location. The status 1203 represents the operation performed at the location. The order number 1204 represents the identification number of the order for the operation target. The quantity 1205 represents the quantity of the goods for the operation target. The time (start) 1206 represents the start date and time of the time when the operation is performed, and the time (end) 1207 represents the end date and time of the time when the operation is performed. The value of the quantity 1205 can be an example of the value of the quantity of goods, and the value of the quantity of goods can replace the quantity of goods or, in addition, be expressed based on at least one of the value of the total weight of the goods and the value of the total capacity of the goods.

[0098] Figure 13 It is a diagram showing an example of a data structure of the charging schedule plan information 120 of the embodiment.

[0099] The charging schedule plan information 120 has information representing one or more charging schedule plans. Figure 13 The charging schedule plan information 120 illustrated as an example in [it] represents one charging schedule plan. The information representing the charging schedule plan has entries for each event related to charging. The entries include information such as location name 1301, charger number 1302, vehicle name 1303, charging amount 1304, time (start) 1305, and time (end) 1306.

[0100] The location name 1301 represents the identification name of the charging location. The charger number 1302 represents the identification number of the charger at the location. The vehicle name 1303 represents the identification name of the vehicle to be charged. The charging amount 1304 represents the charging amount per unit time. The time (start) 1305 represents the start date and time of the time when the charging operation is performed, and the time (end) 1306 represents the end date and time of that time. In the entries, for example, if the charger numbers between all locations are unique, the location name 1301 may not be present.

[0101] Figure 14It is a flowchart showing an example of the schedule creation process of the embodiment.

[0102] At the start of the process, the schedule creation unit 132 reads the parameter information 112, order information 113, vehicle information 114, location information 115, charger information 116, and movement cost information 117 (S310).

[0103] The schedule creation unit 132 generates a transportation schedule plan according to the combination of constraint parameter values in the parameter information 112 read in S310 (S320). For one combination of constraint parameter values, multiple transportation schedule plans can be generated. The transportation schedule plan is generated, for example, by exhaustive search or simulation.

[0104] The schedule creation unit 132 generates a charging schedule plan for charging during the time of staying at a chargeable location among the multiple locations represented by the transportation schedule plan generated in S320 according to the combination of constraint parameter values in the parameter information 112 read in S310 (S330). For one transportation schedule plan, multiple charging schedule plans can be generated. The charging schedule plan is generated, for example, by exhaustive search or simulation.

[0105] The schedule creation unit 132 stores the transportation schedule plan generated in S320 in the transportation schedule plan information 119, and stores the charging schedule plan generated in S330 in the charging schedule plan information 120 (S340). In the transportation schedule plan information 119, for each transportation schedule plan, information identifying the charging schedule plan corresponding to the transportation schedule plan can also be stored. And / or in the charging schedule plan information 120, for each charging schedule plan, information identifying the transportation schedule plan corresponding to the charging schedule plan can also be stored.

[0106] Return Figure 3 An explanation is given. In S400, the evaluation unit 133 uses the vehicle information 114, location information 115, evaluation information 118, and one schedule plan combination (a combination of a transportation schedule plan and the charging schedule plan corresponding to the transportation schedule plan) generated in S300 to perform schedule evaluation processing. As the value of item 1101 of the evaluation information 118, at least "efficiency" indicating the efficiency in the schedule and "easiness of modification" indicating the easiness of modifying the schedule are adopted. As the value of item 1101, "necessity of modification" indicating the necessity of modifying the schedule can also be further adopted.

[0107] Figure 15 It is a flowchart showing an example of the schedule evaluation process of the embodiment.

[0108] At the start of processing, the evaluation unit 133 reads one of the transportation schedule plans stored in the vehicle information 114, location information 115, evaluation information 118, transportation schedule plan information 119, and one of the charging schedule plans stored in the charging schedule plan information 120 (S410). The read transportation schedule plan and charging schedule plan are corresponding plans to each other.

[0109] The evaluation unit 133 evaluates the efficiency of the schedule (S420). For example, the evaluation unit 133 evaluates the efficiency based on at least one of the number of vehicles with low remaining battery or depleted battery, the amount of goods that cannot be transported, the number of vehicles used, transportation costs, transportation time, power consumption during transportation, electricity costs required for charging, and the amount of carbon dioxide emitted due to transportation. Specifically, for example, the evaluation unit 133 can calculate the number of vehicles with low remaining battery or depleted battery by counting the number of vehicles with a remaining battery below a threshold value based on the evaluation information 118, transportation schedule plan information 119, and charging schedule plan information 120. The efficiency of the schedule is calculated using a weighted sum, for example, as shown in the following formula (1).

[0110] <Formula (1)>

[0111] Efficiency

[0112] = (Weight α × Number of vehicles with low remaining battery or depleted battery)

[0113] × (Weight β × Amount of goods that cannot be transported)

[0114] × (Weight γ × Transportation costs)

[0115] × (Weight δ × Electricity costs required for charging)

[0116] Here, each weight can be stored in the evaluation information 118. In addition, each weight can also be a value set inherently for the schedule creation device 100.

[0117] The evaluation unit 133 evaluates the necessity of modifying the schedule (S430). For example, the evaluation unit 133 evaluates the necessity of modifying the schedule based on at least one of the tolerance of the prediction error of the electricity consumption of the building, the tolerance of the prediction error of the maximum demand target, the tolerance of the prediction error of the initial remaining battery, the tolerance of the prediction error of the power consumption, the tolerance of the prediction error of the power consumption cost between locations, the tolerance of the prediction error of the delivery time, and the tolerance of the prediction error of the amount of goods. Specifically, for example, the tolerance of the prediction error of the power consumption can be determined by using the vehicle information 114, transportation schedule plan information 119, charging schedule plan information 120, and calculating to what extent the power consumption can increase while still being able to operate without modifying the transportation schedule plan information 119 and charging schedule plan information 120.

[0118] The necessity of modifying the schedule is calculated using a weighted sum as shown, for example, in the following formula (2).

[0119] <Formula (2)>

[0120] Necessity of modification

[0121] = (Weight ε × Buffer value of prediction error of maximum demand target)

[0122] × (Weight ζ × Buffer value of prediction error of power consumption)

[0123] × (Weight η × Buffer value of prediction error of cargo volume)

[0124] Here, each weight can be stored in the evaluation information 118. Additionally, each weight can also be a value set inherently for the schedule creation device 100.

[0125] The evaluation unit 133 evaluates the ease of modifying the schedule (S440). For example, the evaluation unit 133 evaluates the ease of modifying the schedule based on at least one of the total usage time of the fast - charge chargers, the time of staying at a location without charging, the difference between the contract power and the predicted peak power, the maximum number of simultaneously parked vehicles during business hours, the number of vehicles with a large ratio of driving distance to cruising range, the maximum value of the number of operations with a short length of consecutive operable time periods, and the magnitude of the difference between the operation end time and the operation deadline. Specifically, for example, the total usage time of the fast - charge chargers can be determined using the charger information 116 and the charging schedule plan information 120. The ease of modifying the schedule is calculated using a weighted sum as shown, for example, in the following formula (3).

[0126] <Formula (3)>

[0127] Ease of modification

[0128] = (Weight θ × Total usage time of fast - charge chargers)

[0129] × (Weight ι × Maximum number of simultaneously parked vehicles during business hours)

[0130] × (Weight κ × Number of vehicles with a large ratio of driving distance to cruising range)

[0131] × (Weight λ × Magnitude of the difference between the operation end time and the operation deadline)

[0132] Here, each weight can be stored in the evaluation information 118. Additionally, each weight can also be a value set inherently for the schedule creation device 100.

[0133] The evaluation unit 133 uses the evaluation information 119, the evaluation value of the efficiency calculated in S420, the evaluation value of the necessity for modification calculated in S430, and the evaluation value of the ease of modification calculated in S440, and calculates the evaluation value of the schedule using a weighted sum as shown in the following formula (4), and determines whether the evaluation value is better than the evaluation value as the tentative solution (S450). When it is determined that the evaluation value is good (the evaluation value is better than the tentative solution) (S450: Yes), the evaluation unit 133 saves the combination of the transportation schedule plan and the charging schedule plan as the tentative solution (S460). In formula (4), the "parameter value" can be a value indicating the level of the evaluation value, for example, it can also be the normalized value of the evaluation value. In formula (4), one or both of the evaluation value and the parameter value can be replaced by weights or in addition to this.

[0134] <Formula (4)>

[0135] Schedule evaluation value

[0136] =(Efficiency parameter value × Evaluation value of efficiency)

[0137] ×(Necessity for modification parameter value × Evaluation value of necessity for modification)

[0138] ×(Ease of modification parameter value × Evaluation value of ease of modification)

[0139] Return Figure 3 An explanation will be given. Finally, in S500, the display unit 150 outputs the tentative solution. In addition, the communication unit 160 transmits vehicle-oriented information (for example, information including the transportation schedule) to the in-vehicle terminal 200 via the network 51, transmits location-oriented information (for example, information including the transportation schedule and the charging schedule) to the schedule management terminal 300 at the location, and transmits the charging schedule to the charging control device 400.

[0140] Figure 16 It is a diagram showing an example of the transportation management screen 600 of the embodiment.

[0141] The transportation management screen 600 is displayed on the display device 450. The transportation management screen 600 includes information such as the transportation schedule 610 of the vehicle, the transportation route 620 of the vehicle, and the evaluation result 630 of the schedule. The transportation schedule and the result of the evaluation of the transportation schedule can be confirmed using the transportation management screen 600.

[0142] The transportation schedule 610 of the vehicle represents the transportation schedule in the optimal schedule combination (for example, the schedule combination with the highest total evaluation value 1631 or evaluation parameter value 1632 (the corresponding transportation schedule and charging schedule)). Specifically, for example, for each transportation-related event, the vehicle name 1601, location name 1602, status 1603, order number 1604, quantity 1605, time (start) 1606, and time (end) 1607 are displayed. The information 1601 to 1607 corresponds to the information 1201 to 1207 of the transportation schedule plan information 119. Furthermore, the transportation volume of the order can also be displayed. The status 1603 can be at least one of departure, loading, unloading, charging, and arrival. The transportation volume can also be displayed, and the transportation volume can be based on the quantity of goods, total weight, total volume, or a combination thereof. The time (start) 1606 and time (end) 1607 can also be the time periods during which the vehicle stays at the location instead of the time periods for performing the operations. The transportation schedule can be visualized (not shown) as a Gantt chart with time on the horizontal axis and each vehicle on the vertical axis.

[0143] The transportation route 620 of the vehicle can represent the transportation route of each vehicle, or can represent the transportation route 1620 of the vehicle selected using a tool such as the drop-down menu 1630. Figure 16 In this case, the transportation route 1620 is the transportation route of vehicle A. The transportation route 620 of the vehicle can have an object 1611 representing each location. The position of the object 1611 of each location can be determined based on the latitude 803 and longitude 804 in the location information 115. The transportation route of each vehicle is determined based on the vehicle name 1201, location name 1202, and status 1203 of each entry in the transportation schedule plan information 119.

[0144] The evaluation result 630 of the schedule represents the evaluation results of the efficiency, necessity for modification, and ease of modification of the displayed transportation schedule (optimal schedule combination), and for each evaluation item, at least one of the evaluation value 1631 and the evaluation parameter value 1632 can be displayed. For each evaluation item, the value of the evaluation value 1631 and the value of the evaluation parameter value 1632 can be the values used in the above formula (4). Furthermore, at least one of the total transportation cost, total transportation distance, total transportation time, and total power consumption can also be displayed.

[0145] Figure 17 It is a diagram showing an example of the charging management screen 700 of the embodiment.

[0146] The charging management screen 700 is displayed on the display device 450. The charging management screen 700 includes a charging schedule 710 and an evaluation result 720 of the schedule. The charging schedule and the result of the evaluation of the charging schedule can be confirmed using the charging management screen 700.

[0147] The charging schedule 710 represents the charging schedule in the optimal schedule combination. Specifically, for each charging event, the location name 1701 (the identification name of the charging location), charger number 1702, vehicle name 1703, charging amount 1704, time (start) 1705, and time (end) 1706 are displayed. The information 1701 to 1706 corresponds to the information 1301 to 1306 of the charging schedule scenario information 120.

[0148] The evaluation result 720 of the schedule represents the evaluation result of the displayed charging schedule (the best schedule combination), and the information 1711 and 1712 are the same as Figure 16 the information 1631 and 1632 in the evaluation result 630 shown.

[0149] Figure 18 FIG. is an example of a vehicle-oriented screen 800 showing an embodiment.

[0150] In the vehicle-oriented screen 800, the transportation schedule of the vehicle 510 having the in-vehicle terminal 200 that provides the vehicle-oriented screen 800 is displayed. Specifically, for each transportation event, the information 1801 to 1806 about the vehicle 510 and the information indicating the progress of the operation represented by the status 1802, i.e., the progress 1807, are displayed. The transportation schedule and the progress status of the transportation can be confirmed using the vehicle-oriented screen 800. The information 1801 to 1806 is the same as Figure 16 the information 1602 to 1607 shown. In the vehicle-oriented screen 800, the charging schedule of the vehicle 510 can also be further displayed. In addition, the value of the progress 1807 can be automatically updated according to the status detected by the in-vehicle terminal 200 or can be updated manually.

[0151] Figure 19 FIG. is an example of a location-oriented screen 900 showing an embodiment.

[0152] In the location-oriented screen 900, a schedule of operations related to transportation and charging performed at location 520 is displayed. Specifically, for each event related to transportation or charging, the order number 1901 (identification number of the order for the operation target), time (start) 1902, and time (end) 1903 (time period of the operation), charger number 1904 (identification number of the charger), status 1905 (type of operation), and quantity 1906 (quantity of goods) are displayed. The information 1901 to 1906 is obtained based on the information of the entries corresponding to the location 520 in the transportation schedule scenario information 119 and the charging schedule scenario information 120. The value of the status 1905 can be at least any one of pick-up, delivery, and charging. The schedules of pick-up and delivery operations and the charging schedule can also be displayed separately. The schedule operation person in charge and the operation staff can confirm the schedules of operations related to transportation and charging performed at each location using the location-oriented screen 900.

[0153] As described above, the schedule creation system according to the embodiment of the present invention has been described. According to such a schedule creation system, in the transportation business performed by electric vehicles, by adopting a schedule with ease instead of a schedule that does not require modification, efficiency can be improved while reducing the modification workload of the schedule person in charge.

[0154] One embodiment of the present invention has been described, but this embodiment is presented as an example and is not intended to limit the scope of the invention. The present invention can be implemented in various other ways, and various omissions, substitutions, and changes can be made without departing from the gist of the invention. This embodiment is included in the scope and gist of the invention and includes the invention described in the claims and its equivalent scope. For example, both the transportation schedule and the charging schedule can be chronological times (e.g., what is done where from when to when) during the schedule object period (e.g., time period, day, or week, etc.).

[0155] For example, the above description can be summarized as follows. In addition, the following summary may include supplementary explanations and descriptions of modification examples of the above description.

[0156] The schedule creation device 100 includes an input unit 140, a schedule creation unit 132, an evaluation unit 133, and an output unit 141.

[0157] The input unit 140 inputs a plurality of parameter values. The plurality of parameter values are used to formulate schedule combinations. The schedule combinations include a transportation schedule and a charging schedule based on the transportation schedule. The transportation schedule is a schedule for transporting a plurality of goods to a plurality of locations using a plurality of transportation vehicles. The "plurality of transportation vehicles" includes a plurality of electric vehicles that need to be charged. The plurality of transportation vehicles may also include transportation vehicles other than the electric vehicles that need to be charged. The charging schedule includes a schedule for charging the plurality of electric vehicles.

[0158] The schedule formulation unit 132 formulates one or more schedule combinations based on the plurality of input parameter values.

[0159] The evaluation unit 133 evaluates the efficiency (transportation efficiency) and the modifiability (ease of modifying the schedule) for each of the one or more formulated schedule combinations. For example, the evaluation unit 133 calculates evaluation values regarding efficiency and modifiability for each of the one or more formulated schedule combinations.

[0160] The output unit 141 outputs information based on at least a part of the target schedule combination among the one or more schedule combinations. The target schedule combination is a schedule combination with relatively high efficiency and modifiability.

[0161] The plurality of parameter values for formulating the schedule combination include a plurality of predicted parameter values and one or more combinations of constraint parameter values. Each predicted parameter value is a predicted value regarding a parameter name. For a plurality of constraint parameter names, there is one or more constraint parameter values respectively. For one or more combinations of constraint parameter values, the combination of constraint parameter values is respectively a combination composed of a plurality of constraint parameter values corresponding to the plurality of constraint parameter names respectively. The constraint parameter value of at least one constraint parameter name affects the modifiability (the evaluation value of modifiability).

[0162] In this way, an evaluation item (evaluation perspective) of modifiability is prepared, a constraint parameter name that affects the modifiability is prepared, and one or more combinations of constraint parameter values are included in the plurality of parameter values for formulating the schedule combination. Thus, it is possible to expect to provide a transportation schedule and a charging schedule that are easy to modify even when the schedule needs to be modified and have high transportation efficiency.

[0163] In addition, the "plurality of parameter values" may include at least a part of information elements such as cargo information (e.g., order information 113) regarding the cargo to be transported, vehicle information 114 regarding the plurality of transportation vehicles, location information 115 (e.g., may include information on movement between locations) regarding the locations of the mobile source / mobile destination (e.g., departure location, arrival location, transfer location, charging location, etc.) as the transportation vehicles, and charger information 116 regarding the chargers that can charge the electric vehicles installed at the locations where charging is possible as parameter values.

[0164] In addition, "efficiency" can be, for example, whether transportation can be carried out without waste, and at least one of the following can be adopted as a factor affecting efficiency.

[0165] · Whether the number of vehicles is small (for example, it is required to avoid formulating a schedule with a large number of vehicles and formulating a schedule for electric vehicles that cannot transport all goods or runs out of power, and a new transport vehicle is required on the schedule target day (the current day)).

[0166] · Whether the cost required for transportation is small.

[0167] · Whether the amount of power consumed and the electricity cost during transportation are small.

[0168] · Whether the amount of carbon dioxide emitted during transportation is small.

[0169] In addition, "modifiability" can be the degree to which a formulated schedule can be modified with a small amount of work (the degree to which the modification cost can be small). As a factor affecting modifiability, at least one of the following can be adopted. The "modification cost" can be obtained based on the amount of work required for modification, the time required for modification, or a combination thereof.

[0170] · Whether it is possible to modify only the charging schedule without modifying the transportation schedule.

[0171] · Whether it is possible to not modify the relationship between the transport vehicle and the goods to be transported.

[0172] For one or more schedule combinations, the evaluation unit 133 can also evaluate the necessity of modifying the schedule, that is, the modification necessity, in addition to efficiency and modifiability. The multiple parameter values can include buffer values respectively associated with one or more of the multiple prediction parameter values. At least one buffer value can affect the modification necessity. The target schedule combination can be a schedule combination with relatively high efficiency and modifiability and relatively low modification necessity. Thus, it is possible to provide a schedule combination in which even if the efficiency is high and the modification necessity is low, but due to an error exceeding the buffer value or other reasons, the schedule needs to be modified, and the modification cost of the schedule can be relatively small.

[0173] In addition, "modification necessity" can be the degree of prediction error that occurs and still the schedule does not need to be modified. As a factor affecting the modification necessity, at least one of the following can be adopted.

[0174] · To what extent the cargo volume can increase compared to the prediction and still be able to continue transportation without modifying the formulated schedule.

[0175] · To what extent the electricity consumption of the building can increase compared to the prediction and still be able to continue transportation without modifying the formulated schedule.

[0176] One or more prediction parameter values associated with each buffer value may be at least one of the electricity consumption of a building at a location where charging can be performed, a maximum demand target, the remaining battery level of an electric vehicle at the start of transportation, power consumption (distance that can be traveled per unit of electricity), electricity consumption between locations, the departure date and time of a location, the arrival date and time of a location, and the amount of goods. Thereby, an improvement in the evaluation accuracy of the necessity for modification can be expected.

[0177] The schedule creation unit 132 can create one or more schedule combinations for each combination of one or more constraint parameter values. Thereby, at least one schedule combination is created for each combination of constraint parameter values, and it can be expected that each created schedule combination is a schedule combination with high efficiency and ease of modification within the range that conforms to the combination of constraint parameter values corresponding to the schedule combination.

[0178] The plurality of constraint parameter values may include one or more first constraint parameter values that affect the modification cost of the charging schedule in order to minimize the modification cost of the transportation schedule when modifying the schedule combination and preferentially modify the charging schedule. Thereby, even when the schedule needs to be modified, it can be expected that the efficiency conforming to the transportation schedule is not reduced as much as possible and the schedule can be modified at a small modification cost.

[0179] In addition, the one or more first constraint parameter values may include at least one of an upper limit value of the total usage time of chargers whose charging mode is fast charging, a lower limit value of the total time of the stay times of one or more vehicles staying at a location without charging, a lower limit value of the difference between the maximum demand target and the predicted peak power, an upper limit value of the number of vehicles staying at a location simultaneously during business hours, and an upper limit value of the number of electric vehicles whose ratio of the driving distance to the cruising range is above a threshold value. Thereby, an improvement in the evaluation accuracy of ease of modification can be expected. For example, a schedule combination can be created or an evaluation value of ease of modification can be calculated based on the difference between the constraint parameter value and the parameter value of the parameter having the same parameter name as the constraint parameter name. In addition, for example, at least one of the following may tend to have a high evaluation value of ease of modification.

[0180] · The total time of the stay times of one or more vehicles staying at a location without charging is long.

[0181] · The total usage time of fast chargers is short.

[0182] · The difference between the maximum demand target and the predicted peak power is large.

[0183] · The number of vehicles staying at a location simultaneously during business hours is small.

[0184] · The number of electric vehicles whose ratio of the driving distance to the cruising range is above a threshold value is small.

[0185] The plurality of constraint parameter values may include one or more second constraint parameter values that affect the modification cost of the transportation schedule. The one or more second constraint parameter values may include at least one of an upper limit value of the number of operations in which the length of a consecutive pickup or delivery time period is below a threshold, and a lower limit value of the difference between the end date and time of a pickup or delivery operation and the pickup or delivery deadline. Thus, it is possible to expect a schedule combination that can modify the transportation schedule with a small modification cost even when the schedule needs to be modified. For example, at least one of the following may tend to have a small modification cost for the transportation schedule.

[0186] · The number of operations in which the length of a consecutive pickup or delivery time period is below a threshold is small.

[0187] · The difference between the end date and time of a pickup or delivery operation and the pickup or delivery deadline is large.

[0188] One or more parameter values that affect efficiency, which are included in the plurality of parameter values or obtained from at least a part of the above-mentioned plurality of parameter values, may be at least one of the number of electric vehicles with low remaining battery or depleted battery, the amount of goods that cannot be transported, the number of vehicles used, the transportation cost, the transportation time, the power consumption during transportation, the carbon dioxide emissions generated during transportation, and the electricity cost required for charging. Thus, it is possible to expect an improvement in the evaluation accuracy of efficiency.

[0189] The target schedule combination may be a schedule combination in which efficiency and ease of modification (e.g., its evaluation value) are Pareto optimal, or a schedule combination with the optimal evaluation of efficiency and ease of modification (e.g., a schedule combination with the optimal schedule evaluation value determined based on its evaluation value). Thus, it is possible to expect to adopt a schedule combination that is preferable at least from the viewpoints of efficiency and ease of modification.

[0190] The output unit 141 may perform at least one of the following (a) to (d). Thus, it is possible to provide optimal information to the output destination. For example, according to (d), it is possible to expect automatic charging control that conforms to the charging schedule.

[0191] (a) The output unit 141 displays the transportation schedule and / or the charging schedule in the target schedule combination on the display device 450 or a remote computer.

[0192] (b) For at least one transportation vehicle among the plurality of transportation vehicles, the output unit 141 sends information indicating the transportation schedule part and / or the charging schedule part corresponding to the transportation vehicle in the above-mentioned target schedule combination to the information processing terminal of the transportation vehicle. The "information processing terminal" may be, for example, an in-vehicle device of a transportation vehicle or a mobile terminal held by a person riding in the transportation vehicle.

[0193] (c) The output unit 141 sends information indicating the transportation schedule part and / or the charging schedule part corresponding to a location among the multiple locations to the information processing terminal at that location. The "information processing terminal" can be, for example, a fixed or mobile personal computer or smartphone at the location.

[0194] (d) The output unit 141 sends charging control information corresponding to the charging schedule part for at least one chargeable location among the multiple locations to the charging control device that controls the charger at that location. The "charging control information" can be information on when and to what extent charging is performed in which charger, or it can be a control instruction sent according to the charging schedule part.

[0195] In addition, functions such as the input unit 140, the prediction error calculation unit 131, the schedule creation unit 132, the evaluation unit 133, and the output unit 141 can exist in one device or be distributed among multiple devices. For example, there can be a first device having functions such as the input unit 140, the prediction error calculation unit 131, and the schedule creation unit 132, and a second device having functions such as the evaluation unit 133 and the output unit 141. The first device can output information indicating one or more created schedule combinations, and the second device can evaluate one or more schedule combinations indicated by this information respectively and output information based on the evaluation results.

[0196] Explanation of Reference Numerals

[0197] 1... Schedule creation system, 100... Schedule creation device, 110... Storage unit, 111... Prediction actual result information, 112... Parameter information, 113... Order information, 114... Vehicle information, 115... Location information, 116... Charger information, 117... Movement cost information, 118... Evaluation information, 119... Transportation schedule plan information, 120... Charging schedule plan information, 130... Control unit, 131... Prediction error calculation unit, 132... Schedule creation unit, 133... Evaluation unit, 140... Input unit, 141... Output unit, 150... Display unit, 160... Communication unit, N... Network, 200... On-vehicle terminal, 210... Communication unit, 220... Control unit, 230... Display unit, 300... Schedule management terminal at location, 310... Communication unit, 320... Control unit, 330... Display unit, 400... Charging control device, 41... Communication unit, 42... Control unit.

Claims

1. A timetable making device, characterized in that: include: an input section for inputting a plurality of parameter values ​​for formulating a schedule combination including a transport schedule and a charging schedule, wherein the transport schedule is for transporting a plurality of goods to a plurality of locations by a plurality of transport vehicles including a plurality of electric vehicles that need to be charged, and the charging schedule is a schedule for charging the plurality of electric vehicles and is a schedule based on the transport schedule; a schedule formulation unit for formulating one or more schedule combinations based on the plurality of parameter values; an evaluation unit for evaluating efficiency and modifiability of the one or more schedule combinations, respectively, wherein the efficiency is the efficiency of transportation, and the modifiability is the ease of modifying the schedule; and an output unit for outputting information about at least a portion of the target schedule combination, The multiple parameter values ​​include multiple prediction parameter values ​​and one or more constraint parameter value combinations, Each predicted parameter value is the predicted value for the parameter name. Each of the multiple constraint parameter names corresponds to one or more constraint parameter values. For each of the one or more constraint parameter value combinations, the constraint parameter value combination is a combination consisting of a plurality of constraint parameter values ​​corresponding to the plurality of constraint parameter names, respectively. a constraint parameter value of at least one constraint parameter name affecting said modifiability, The target schedule combination is a schedule combination having relatively high efficiency and easy modifiability.

2. The timetable making device according to claim 1, characterized in that: For the one or more schedule combinations, the evaluation unit evaluates the necessity of modification as the necessity of modifying the schedule in addition to the efficiency and the ease of modification, The plurality of parameter values ​​include buffer values ​​respectively associated with at least one of the plurality of predicted parameter values, at least one buffer value influences said necessity of modification, The target schedule combination is a schedule combination in which the efficiency and the ease of modifiability are relatively high and the necessity for modification is relatively low.

3. The timetable making device according to claim 2, characterized in that: The one or more predicted parameter values, each associated with a buffer value, are at least one of the power consumption of a building capable of charging, a maximum demand target, the remaining power of the electric vehicle at the start of transportation, power consumption, power consumption between locations, the departure date and time of a location, the arrival date and time of a location, and the amount of cargo.

4. The timetable making device according to claim 1, characterized in that: The schedule creation unit creates one or more schedule combinations for each of the one or more constraint parameter value combinations.

5. The timetable making device according to claim 1, characterized in that: The plurality of constraint parameter values ​​include one or more first constraint parameter values ​​that affect the modification cost of the charging schedule in order to prioritize the modification cost of the transportation schedule to be as small as possible if the schedule combination needs to be modified.

6. The timetable making device according to claim 5, characterized in that: The one or more first constraint parameter values ​​include at least one of an upper limit value of the total usage time of a charger whose charging mode is fast charging, a lower limit value of the total stay time of one or more vehicles staying at a location without charging, a lower limit value of the difference between the maximum demand target and the predicted peak power, an upper limit value of the number of vehicles staying at a location at the same time during business hours, and an upper limit value of the number of electric vehicles for which the ratio of driving distance to cruising distance is above a threshold.

7. The timetable making device according to claim 1, characterized in that: The plurality of constraint parameter values ​​include one or more second constraint parameter values ​​affecting a modified cost of the transportation schedule, The one or more second constraint parameter values ​​include at least one of an upper limit value of the number of consecutive collection or delivery operations with a length of time period below a threshold, and a lower limit value of the difference between the end date and time of the collection or delivery operation and the collection or delivery deadline.

8. The timetable making device according to claim 1, characterized in that: One or more parameter values ​​affecting the efficiency, included in the multiple parameter values ​​or obtained from at least a part of the multiple parameter values, are at least one of the number of electric vehicles with little remaining power or exhausted power, the amount of cargo that cannot be transported, the number of vehicles used, the transportation cost, the transportation time, the amount of electricity used for transportation, the amount of carbon dioxide emissions generated by transportation, and the electricity cost required for charging.

9. The timetable making device according to claim 1, characterized in that: The target schedule combination is a schedule combination in which the efficiency and the modifiability are Pareto optimal, or a schedule combination in which the evaluation of the efficiency and the modifiability is optimal.

10. The timetable making device according to claim 1, characterized in that: The output unit performs at least one of the following (a) to (d): (a) displaying the transport schedule and / or charging schedule in the object schedule combination on a display device or a remote computer, (b) for at least one of the plurality of transport vehicles, sending information indicating a transport schedule portion and / or a charging schedule portion in the target schedule combination corresponding to the transport vehicle to an information processing terminal of the transport vehicle, (c) for at least one of the plurality of locations, sending information indicating a transportation schedule portion and / or a charging schedule portion of the target schedule combination corresponding to the location to an information processing terminal of the location, (d) For at least one charging-enabled spot among the plurality of spots, charging control information that matches a portion of the charging schedule corresponding to the spot in the target schedule combination is transmitted to a charging control device that controls a charger at the spot.

11. A timetable making method, characterized in that: Execute on a computer: a process for inputting a plurality of parameter values ​​for formulating a schedule combination including a transport schedule for transporting a plurality of goods to a plurality of locations by a plurality of transport vehicles including a plurality of electric vehicles that need to be charged, and a charging schedule that is a schedule for charging the plurality of electric vehicles and is a schedule based on the transport schedule, a process of formulating one or more schedule combinations based on the plurality of parameter values, a process of evaluating efficiency and modifiability respectively for the one or more schedule combinations, wherein the efficiency is the efficiency of transportation, and the modifiability is the ease of modifying the schedule, a process of outputting information about at least a portion of a target schedule combination among the one or more schedule combinations, The multiple parameter values ​​include multiple prediction parameter values ​​and one or more constraint parameter value combinations. Each predicted parameter value is the predicted value for the parameter name. Each of the multiple constraint parameter names corresponds to one or more constraint parameter values. Regarding the one or more constraint parameter value combinations, the constraint parameter value combination is a combination consisting of a plurality of constraint parameter values ​​corresponding to the plurality of constraint parameter names, respectively. a constraint parameter value of at least one constraint parameter name affecting said modifiability, The target schedule combination is a schedule combination having relatively high efficiency and easy modifiability.

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