Information display device, information display method, and program

Abstract

This information display device comprises: a first information acquisition means which acquires location information of an electric vehicle and situational information indicating a customer's situation; a second information acquisition means which acquires a congestion rate of charging stations or the charging rate of each battery at the charging stations within a predetermined distance which is based on the location information; and an output means which outputs information of a recommended charging station on the basis of the situational information, the congestion rate, or the charging rate.

Description

Information display device, information display method, and recording medium

[0001] The present disclosure relates to an information display device, an information display method, and a recording medium.

[0002] At charging stations for electric vehicles (EVs) and other electrically powered vehicles, customers may have to wait for charging or their operation rates may be low, placing a burden on operators. To solve these problems, there are technologies for leveling out the operation rates of charging stations. For example, Patent Literature 1 discloses a technology in which, when destination information is acquired from a vehicle, congestion information is acquired from a charging station adjacent to the destination among multiple charging stations, and incentive information is acquired from charging stations near the destination and transmitted to the vehicle.

[0003] Japanese Patent Application Laid-Open No. 2019-087142

[0004] However, the technology disclosed in Patent Document 1 can only present predetermined uniform measures, and has limitations in encouraging customers to use charging stations with low utilization rates.

[0005] An example of an objective of the present disclosure is to provide an information display device that can effectively encourage customers to use charging stations with low utilization rates.

[0006] An information display device in one aspect of the present disclosure includes a first information acquisition means that acquires location information of an electric vehicle and situation information indicating the customer's situation, a second information acquisition means that acquires the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of each battery at the charging station, and an output means that outputs information about recommended charging stations based on the situation information and the congestion rate or the charging rate.

[0007] In one aspect of the information display method of the present disclosure, a computer acquires situation information indicating the current location of an electric vehicle and the customer's situation, acquires the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of each battery at the charging station, and outputs information about recommended charging stations based on the situation information and the congestion rate or the charging rate.

[0008] In one aspect of the present disclosure, a recording medium stores a program that causes a computer to execute a process of acquiring status information indicating the current location of an electric vehicle and the customer's situation, acquiring the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of each battery at the charging station, and outputting information about recommended charging stations based on the status information and the congestion rate or the charging rate.

[0009] According to the present disclosure, it is possible to provide an information display device that can effectively encourage customers to use charging stations with low utilization rates.

[0010] FIG. 1 is a block diagram including an information display device according to the present disclosure. FIG. 2 is a diagram showing a hardware configuration in which the information display device according to the present disclosure is realized by a computer device and its peripheral devices. FIG. 3 is an example of a display of charging station information according to the present disclosure. FIG. 4 is another example of a display of charging station information according to the present disclosure. FIG. 5 is a flowchart showing the operation of an information display device according to the present disclosure. FIG. 6 is a block diagram including an information display device according to the present disclosure. FIG. 7 is an example of output of information on cost conditions for using each recommended charging station according to the present disclosure. FIG. 8 is a flowchart showing the operation of an information display device according to the present disclosure. FIG. 9 is an example of storage of correct answer data when a customer has used a charging station in the past according to the present disclosure. FIG. 10 is an example of storage of correct answer data when a customer has used a charging station in the past according to the present disclosure. FIG. 11 is an example of storage of correct answer data when a customer has used a charging station in the past according to the present disclosure. FIG. 12 is an example of storage of correct answer data when a customer has used a charging station in the past according to the present disclosure. FIG. 13 is a block diagram including an information display device according to the present disclosure. FIG. 14 is an example of a screen when an incentive is output according to the present disclosure. Fig. 15 is a flowchart showing the operation of the information display device according to the present disclosure. Fig. 16 is a diagram for explaining battery replacement according to the present disclosure. Fig. 17 is an example of outputting an incentive when a battery is replaced according to the present disclosure. Fig. 18 is a flowchart showing the operation of the information display device according to the present disclosure.

[0011] Hereinafter, with reference to the drawings, embodiments of an information display device, an information display method, and a non-transitory recording medium for recording a program according to the present disclosure will be described in detail. The disclosed technology is not limited to these embodiments.

[0012] [First Embodiment] Fig. 1 is a block diagram showing an information display device 100 according to this embodiment. The information display system 10 is a system for displaying the locations of charging stations for electric vehicles when a driving route to a destination is searched for. The information display system 10 includes the information display device 100 and a terminal device 200. As shown in Fig. 1 , the information display device 100 includes a first information acquisition unit 101, a second information acquisition unit 102, and an output unit 103.

[0013] In this embodiment, the electric vehicle is a vehicle that runs using the charged power of a battery installed in the electric vehicle, and includes, for example, an electric car, an electric motorcycle, an electric truck, an electric bicycle, and an electric kick scooter. The electric vehicle needs to move to a charging station to charge the battery before the battery runs out of charged power. The electric vehicle in this embodiment may also be equipped with a replaceable battery. In this case, the battery is replaced with a charged battery at the charging station.

[0014] The terminal device 200 is connected to the information display device 100 via a network. The terminal device 200 is a terminal carried by a customer or a car navigation system installed in an electric vehicle. A customer is a customer who uses a charging station, and includes the driver and passengers of the electric vehicle. In this embodiment, a navigation program for searching a driving route to a destination is pre-installed in the terminal device 200, and this navigation program displays charging stations near the driving route. Furthermore, this navigation program displays information about charging stations, for example, when there is insufficient charge to reach the destination or when the customer performs an operation to search for charging stations.

[0015] The storage device 505 of the information display device 100 stores map data for displaying a map on the information display device 100 and network data for searching for a driving route. When destination information for searching for a driving route is input to the navigation program installed in the terminal device 200, the navigation program searches for a driving route from the departure point or the current position to the destination using the map data stored in the storage device 505. The navigation program searches for a driving route using a known method such as the Dijkstra algorithm.

[0016] The map data includes information on charging stations and stores. The charging station information includes information on the congestion rate of charging stations located at positions on the map and the charging rate of batteries at the charging stations.

[0017] The congestion rate of a charging station is obtained by a known method, for example, by determining whether each charging equipment at the charging station is in use based on image data captured by a camera installed at the charging station, and storing the determination result. The congestion rate is, for example, an index showing the usage status of the charging equipment installed at each charging station, and is expressed as 100% when all charging equipment is in use. The lower the congestion rate, the higher the percentage of available charging stations.

[0018] The battery charging rate is stored in association with the ID of the battery managed by each charging station. Each battery is provided with an SOC (State Of Charge) detector that detects the SOC, which is a value indicating the state of charge of the battery, and a communication means, and the information display device 100 acquires the battery charging rate detected by the SOC detector via the network. The charging station congestion rate and battery charging rate are acquired at a predetermined interval, and the information stored in the storage device 505 is updated each time.

[0019] Store information is information about a store located at a position on the map, and includes, for example, information about products sold at the store, recommended products at the store, or coupons distributed at the store.

[0020] The network data includes nodes that represent specific points such as intersections and dead ends, and edges that represent roads connecting the nodes. The network data also stores an average transit time associated with each edge. The average transit time is the average time it takes for an electric vehicle to pass through an edge.

[0021] 2 is a diagram showing an example of a hardware configuration in which the information display device 100 according to the present disclosure is realized by a computer device 500 including a processor. As shown in FIG. 2, the information display device 100 includes a CPU (Central Processing Unit) 501, memories such as a ROM (Read Only Memory) 502 and a RAM (Random Access Memory) 503, a storage device 505 such as a hard disk for storing a program 504, a communication interface 508 for network connection, and an input / output interface 509 for inputting and outputting data. In the first embodiment, the information display device 100 is connected to each component via a bus 510.

[0022] The CPU 501 runs an operating system to control the entire information display device 100 according to the first embodiment of the present invention. The CPU 501 also reads programs and data into memory from a recording medium 506 mounted in, for example, a drive device 507. The CPU 501 also functions as the first information acquisition unit 101, the second information acquisition unit 102, and the output unit 103 in the first embodiment, and as part of these, and executes processing or commands in the flowchart shown in FIG. 5, which will be described later, based on the program.

[0023] The recording medium 506 is, for example, an optical disk, a flexible disk, a magneto-optical disk, an external hard disk, or a semiconductor memory. The semiconductor memory or the like that is part of the recording medium is a non-volatile storage device that stores the program. The program may also be downloaded from an external computer (not shown) that is connected to a communication network.

[0024] As described above, the first embodiment shown in Fig. 1 is realized by the computer hardware shown in Fig. 2. However, the means for realizing each unit of the information display device 100 in Fig. 1 is not limited to the configuration described above. Furthermore, the information display device 100 may be realized by a single physically coupled device, or may be realized by a system consisting of two or more physically separated devices connected by wire or wirelessly.

[0025] The first information acquisition unit 101 is a means for acquiring position information of the electric vehicle and situation information indicating the situation of the customer. The first information acquisition unit 101 acquires the current position obtained from a Global Positioning System (GPS) installed in the electric vehicle. In this embodiment, the situation information includes at least one of biometric information of the customer, driving information indicating the driving situation of the customer, and schedule information of the customer.

[0026] The first information acquisition unit 101 acquires biometric information, for example, from a biometric sensor of a wearable device worn by the customer. A known sensing technology is applied to the biometric sensor, and the first information acquisition unit 101 acquires biometric information that affects the customer's physical condition or emotions. The first information acquisition unit 101 acquires information such as pulse rate, blood pressure, blood glucose level, facial expression, and sweat rate as biometric information. The first information acquisition unit 101 acquires, for example, pulse rate from a pulse wave sensor, blood pressure from a blood pressure sensor, blood glucose level from a blood glucose level sensor, facial expression of the customer captured by a camera installed in the driver's seat, and sweat rate from a sensor that detects moisture or humidity in the palm of the customer's hand.

[0027] The first information acquisition unit 101 may acquire driving information indicating the driving status of the customer from an on-board camera or an on-board sensor mounted on the electric vehicle. The first information acquisition unit 101 acquires information regarding steering, accelerator, and brake operation as driving information, but any information may be acquired as long as it can estimate the customer's emotions or physical condition.

[0028] The first information acquisition unit 101 may acquire schedule information of the customer. The first information acquisition unit 101 acquires schedule information recorded in the customer's terminal device 200 or schedule information recorded in a schedule application program. The schedule information includes at least whether or not the customer has plans within a predetermined time period.

[0029] The second information acquisition unit 102 is a means for acquiring the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of batteries at the charging stations. For example, the second information acquisition unit 102 extracts information about charging stations within a predetermined distance from the current location, and acquires the congestion rate of each charging station or the charging rate of the batteries at the charging station from the storage device 505.

[0030] The output unit 103 is a means for outputting information about recommended charging stations that are recommended to the customer based on the status information and the congestion rate or the charging rate. In the present embodiment, when the customer's status information is normal, the output unit 103 extracts and displays charging stations within a predetermined distance from the current location of the electric vehicle that have a congestion rate equal to or lower than a predetermined threshold or that have a predetermined percentage or higher of charged batteries with a charging rate higher than the predetermined threshold. On the other hand, when the status information is abnormal, the output unit 103 outputs information about charging stations within the predetermined distance as is. However, this is merely one example of a method by which the output unit 103 outputs information about recommended charging stations based on the status information, and the method is not limited to the above example as long as the content of the recommended charging stations output based on the customer's status information is different.

[0031] In this embodiment, the output unit 103 determines that the biological information and driving information among the situation information are normal if the deviation from the normal value acquired when the customer is driving normally is less than a predetermined threshold, and determines that the biological information and driving information are abnormal if the deviation from the normal value acquired when the customer is driving normally is equal to or greater than the predetermined threshold. The normal value of the customer's situation information is stored in the storage device 505. Furthermore, the output unit 103 determines that the schedule information is normal if there are no plans within a predetermined time period, and abnormal if there are plans within the predetermined time period.

[0032] The output unit 103 may output information indicating the location of a recommended charging station, as well as information on the congestion rate or the number of charged batteries at the recommended charging station. In this case, the customer may use a charging station that is vacant or has an excess number of charged batteries, even if the charging station is far from the customer's current location.

[0033] 3 and 4 are examples of output of recommended charging stations in the present disclosure. The example in FIG. 3 is information about recommended charging stations that is output when the status information is abnormal. As shown in FIG. 3, the output unit 103 displays information about the positions on a map of charging stations within a predetermined distance from the current position of the electric vehicle. The example in FIG. 4 is information about recommended charging stations that is output when the status information is normal. As shown in FIG. 4, the output unit 103 extracts and displays charging stations that have a congestion rate below a predetermined threshold or a percentage of charged batteries above a predetermined percentage from among charging stations within a predetermined distance from the current position of the electric vehicle. The example in FIG. 4 displays only charging stations B, C, and F whose congestion rate is below a predetermined threshold. Furthermore, as shown in FIG. 4, the output unit 103 may display the congestion rate of each charging station.

[0034] 5 is a flowchart showing an outline of the operation of the information display device 100 according to the present disclosure. The process according to this flowchart may be executed based on program control by the processor described above. The process according to this flowchart is triggered, for example, by an operation to search for a charging station on an application program of the terminal device 200.

[0035] As shown in FIG. 5 , the first information acquisition unit 101 acquires the location information of the electric vehicle and status information indicating the customer's status (step S101). Next, the second information acquisition unit 102 acquires the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of each battery at the charging station (step S102). Next, if the status information is normal (S103; YES), the output unit 103 extracts and displays charging stations whose congestion rate is below a predetermined threshold or whose percentage of charged batteries is above a predetermined percentage (step S104). On the other hand, if the status information is not normal (S103; NO), the output unit 103 displays charging stations within a predetermined distance from the location information (step S105). This completes the processing of the information display device 100.

[0036] In the information display device 100 of this embodiment, when the status information is normal, the output unit 103 extracts charging stations whose congestion rate is below a predetermined threshold or whose percentage of charged batteries is above a predetermined percentage and displays them as recommended charging stations. In this case, for example, charging stations with low operation rates or many charged batteries are recommended only when the customer's emotions, physical condition, or time allowance are considered. This makes it possible to effectively encourage customers to use charging stations with low operation rates.

[0037] [Second Embodiment] Next, a second embodiment of the present disclosure will be described in detail with reference to the drawings. Below, the description of the second embodiment will be omitted to the extent that it does not make the description of the present embodiment unclear.

[0038] Fig. 6 is a block diagram including an information display device 110 according to the present disclosure. Fig. 6 is a diagram for explaining a management location in a second embodiment. As with the computer device shown in Fig. 2, the functions of the information display device 110 can be realized not only by hardware but also by a computer device or software based on program control.

[0039] 6, the information display device 110 includes a first information acquisition unit 111, a second information acquisition unit 112, a determination unit 113, and an output unit 114. In this embodiment, the configurations of the first information acquisition unit 111 and the second information acquisition unit 112 are similar to the first information acquisition unit 101 and the second information acquisition unit 102 in the first embodiment.

[0040] In this embodiment, customer information is stored in the storage device 505. The customer information includes attribute information such as the customer's gender or age, customer preference information, and purchase history information. The preference information is a customer's tendency to like food, entertainment, etc., estimated based on the customer's behavioral history. The purchase history information is information that can identify the content of a product or service, obtained from the customer's terminal device 210 that made the payment when purchasing the product or service.

[0041] The determination unit 113 is a means for determining the cost conditions for the customer's use of a recommended charging station based on the situation information and the congestion rate or charging rate of charging stations within a predetermined distance from the current location. The cost conditions include additional fees to be collected from the customer when using a specific charging station and rewards such as incentives to be given to the customer. In this embodiment, the situation information includes at least one of the customer's biometric information, driving information indicating the customer's driving status, and the customer's schedule information.

[0042] The determination unit 113 calculates the customer's degree of leeway based on at least one of the customer's emotions or physical condition estimated from the biometric information, the customer's emotions or physical condition estimated from the driving information, and the customer's degree of urgency estimated from the schedule information, and determines the cost conditions for the customer's use of the charging station based on the customer's degree of urgency. The degree of urgency is, for example, an index that indicates whether the customer is in a hurry depending on whether or not there is a schedule within a predetermined time period.

[0043] Generally, when a customer of an electric vehicle wants to charge or replace the battery, they often want to use a charging station near their current location. On the other hand, if the customer has enough emotion, physical condition, or time, they may be able to use a charging station that is farther away from their current location. Therefore, the determination unit 113 in this embodiment determines the cost conditions based on the customer's level of leeway calculated based on at least one of the emotion or physical condition estimated from biometric information, the emotion or physical condition estimated from driving information, and the level of urgency estimated from schedule information.

[0044] Here, a method by which the determination unit 113 determines the cost conditions will be described. First, a method for estimating the customer's emotions, physical condition, and urgency will be described. The determination unit 113 uses a known method to estimate whether the customer is feeling positive emotions, such as joy or happiness, or negative emotions, such as sadness, anxiety, or anger, based on biometric information or driving information. The determination unit 113 may also estimate the degree of positive or negative emotions based on the biometric information or driving information. The determination unit 113 may estimate the degree of positive or negative emotions using three levels, for example, weak, medium, and strong. For example, some customers may drive more recklessly than usual when they are angry. Therefore, the determination unit 113 estimates that the customer is angry when the driving information shows characteristics that are associated with reckless driving.

[0045] The determination unit 113 estimates the customer's physical condition based on the biometric information or the driving information. Specifically, the determination unit 113 estimates whether the customer's physical condition is good or bad based on the biometric information or the driving information using a known method. The determination unit 113 may also estimate the degree of good or bad physical condition based on the biometric information or the driving information, for example, in three levels: weak, medium, and strong. For example, some customers may drive slower than usual when they are not in good physical condition. Therefore, the determination unit 113 estimates that the customer's physical condition is not good when the driving information shows characteristics that are associated with slower driving.

[0046] The determination unit 113 may also estimate the customer's emotions or physical condition using a model that has learned, based on the biometric information, a combination of values ​​of the biometric information associated with a specific emotion or a specific poor physical condition through supervised machine learning. Similarly, the determination unit 113 may also estimate the customer's emotions or physical condition using a model that has learned, based on the values ​​of the driving information, a combination of values ​​of the driving information associated with a specific emotion or a specific poor physical condition through supervised machine learning. These models are stored in the storage device 505.

[0047] The determination unit 113 estimates the customer's degree of urgency based on the schedule information. In this embodiment, the schedule information includes at least the planned destination and the planned time. Specifically, based on the schedule information recorded in the customer's terminal device 210, the determination unit 113 estimates that the customer is in a hurry if the customer has an appointment within a predetermined time (e.g., within 30 minutes). On the other hand, the determination unit 113 estimates that the customer is not in a hurry if the customer does not have an appointment within the predetermined time. The predetermined time is a time that allows the customer to travel to the planned destination with ample time to spare, and may be determined based on the distance from the customer's current location to the destination.

[0048] The determination unit 113 may calculate the degree of slack by assigning points to the customer's emotions, physical condition, and level of urgency estimated from each piece of situation information as described above. The determination unit 113 may calculate the degree of slack by any method. For example, the determination unit 113 may add points when the emotion is positive and subtract points when the emotion is negative. The points added or subtracted by the determination unit 113 may be changed depending on the degree of positive or negative emotion. Furthermore, the determination unit 113 may add points when the physical condition is good and subtract points when the physical condition is poor. The points added or subtracted by the determination unit 113 may be changed depending on the degree of good or poor physical condition. The determination unit 113 may add points when the customer is not in a hurry and subtract points when the customer is in a hurry. The points added or subtracted by the determination unit 113 may be changed depending on the level of urgency. However, the above-described method of assigning points is merely an example of a method of calculating the degree of slack, and is not limited thereto. For example, the margin may be calculated using only one of the status information of the customer.

[0049] Next, the determination unit 113 determines the cost condition based on the calculated margin. Specifically, the determination unit 113 determines the cost condition such that the higher the margin, the higher the additional cost or the smaller the incentive to be provided. Conversely, the determination unit 113 determines the cost condition such that the lower the margin, the lower the additional cost or the larger the incentive to be provided.

[0050] Furthermore, when granting an incentive to a customer as a cost condition, the determination unit 113 may determine the content of the incentive to be granted based on preference information or purchase history information of the customer. The incentive may be a coupon that can be used at a charging station or a specific store.

[0051] The preference information is information about a customer's favorite stores or favorite products or services, which is inferred from the customer's behavior. The determination unit 113 acquires the preference information using a known method. For example, the determination unit 113 acquires information about stores that the customer has visited a predetermined number of times or more from the customer's location information history on a navigation program, and uses this information as the customer's favorite stores. The determination unit 113 also acquires information about the customer's favorite products or services, which is inferred from the customer's browsing history of a news app, television or on-demand content viewing history, preference information entered in a preliminary questionnaire, manually selected coupon information, or the content of posts that the customer has liked, retweeted, or followed on a social networking service (SNS).

[0052] The purchase history information is information related to products or services that a customer has purchased in the past. The determination unit 113 acquires information about products or services purchased at a store based on, for example, payment data from an electronic payment method.

[0053] The determination unit 113 determines the content of the incentive to be granted to the customer based on the preference information or purchase history information thus acquired. Specifically, the determination unit 113 may determine to grant a coupon that can be used at a store that the customer likes or a similar store. The determination unit 113 may also determine to grant a coupon that can be used for a product or service that the customer likes or a product or service similar thereto. The determination unit 113 may also determine to grant a coupon that can be used for a product or service that the customer has purchased a predetermined number of times or more or a product or service similar thereto.

[0054] When granting an incentive to a customer as a cost condition, the determination unit 113 may determine the content of the incentive to be granted based on the customer's emotions or physical condition. The determination unit 113 estimates the customer's emotions or physical condition by a known method based on the biometric information or driving information acquired by the first information acquisition unit 111, and determines the content of the incentive to be granted based on the customer's emotions or physical condition.

[0055] For example, if the determination unit 113 estimates that the customer's pulse rate or blood pressure is high and that the customer is feeling tense, excited, or angry, the determination unit 113 may issue a coupon for a place where the customer can rest, such as a cafe or a massage parlor, to encourage the customer to take a break. Furthermore, if the determination unit 113 estimates that the customer's facial expression indicates a sensitive emotion, such as sadness or loneliness, the determination unit 113 may issue a coupon that can be used at a place that soothes the customer, such as an animal cafe. Furthermore, if the determination unit 113 estimates that the customer's body temperature is higher than normal or that the customer has just exercised, the determination unit 113 may issue a coupon for purchasing a cold drink. Furthermore, if the determination unit 113 estimates that the customer's body temperature is lower than normal or that the customer is shivering, the determination unit 113 may issue a coupon that can be used at a restaurant. Furthermore, the determination unit 113 may estimate the customer's emotions, such as joy, anger, sadness, or happiness, and issue a coupon that can be used at a store that suits the customer's emotions. The above-mentioned examples are examples of the method for estimating the customer's physical condition or emotion by the determination unit 113 and the coupon to be issued in response to the estimated physical condition or emotion, but the method is not limited to these.

[0056] The determination unit 113 may issue a coupon for a product that is famous in the location or region where the customer is traveling. The determination unit 113 may also obtain the current time from a navigation system and issue a coupon for breakfast in the morning time zone and a coupon for lunch in the afternoon time zone. The determination unit 113 may also determine a coupon to be issued to a customer based on the weather or season of the day, such as issuing a coupon for a cold drink on a hot day.

[0057] The determination unit 113 may also acquire attribute information or situation information of the passenger and issue a coupon based on this information. For example, if the passenger has a child, the determination unit 113 may issue a coupon for food for the child.

[0058] Furthermore, the determination unit 113 may issue a coupon for a product or service that has been introduced a certain number of times on television, in online articles, or on social media, a coupon linked to a special feature on the radio, or a coupon with a time-limited discount amount. In this case, the customer is more likely to use the recommended charging station because they want to use the coupon.

[0059] The output unit 114 outputs information about the recommended charging stations, along with information about additional fees to be collected or incentives to be provided when using the recommended charging stations. FIG. 7 shows an example of output information about cost conditions for using each recommended charging station in the present disclosure. As shown in FIG. 7 , when a recommended charging station close to the current location is used, an additional fee is incurred. On the other hand, when a recommended charging station far from the current location or when the recommended charging station is to be used after a predetermined time from the current time, an incentive is provided.

[0060] 8 is a flowchart showing an outline of the operation of the information display device 110 according to the present disclosure. Note that the processing according to this flowchart may be executed based on program control by the processor described above.

[0061] As shown in Fig. 8, the first information acquisition unit 101 acquires location information of the electric vehicle and situation information indicating the customer's situation (step S201). Next, the second information acquisition unit 102 acquires the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of each battery at the charging station (step S202). Next, the determination unit 113 determines the cost conditions for the customer's use of the recommended charging station based on the situation information (step S203). Finally, the output unit 114 outputs the cost conditions of the determined recommended charging station (step S204). With this, the information display device 110 ends the processing.

[0062] In this embodiment, the determination unit 113 determines the cost conditions for when the customer uses a recommended charging station based on the situation information, and the output unit 114 outputs the determined cost conditions for the recommended charging station. In addition, in this embodiment, the situation information includes at least one of the customer's biometric information, driving information indicating the customer's driving status, and the customer's schedule information. This makes it possible to change the cost conditions for encouraging the use of a charging station with a low utilization rate based on the customer's level of slack, such as by increasing the incentive for encouraging the use of a charging station with a low utilization rate when the customer is emotionally, physically, or short on time. This makes it possible to encourage even customers with limited time to use a charging station with a low utilization rate.

[0063] [Variation of the Second Embodiment] In the second embodiment described above, the determination unit 113 determines the cost conditions for using a recommended charging station based on situation information. In contrast, in this variation, the determination unit 113 determines the cost conditions based on situation information using a model that has learned the customer's past usage history of charging stations. Some customers are willing to immediately use a charging station close to their current location even if it means paying a specific additional fee, while other customers are willing to charge at a charging station that is more than a certain distance away or even several hours later if they receive a specific incentive. Therefore, in this variation, the cost conditions are determined based on the customer's response to cost conditions presented when they previously used a charging station.

[0064] The model in this modification is a model that learns the correlation between past customer situation information, the conditions of the charging stations used, and the cost conditions used by the customer. More specifically, this model is, for example, a model that is generated by supervised machine learning to determine the correlation between the margin calculated based on past customer situation information, the conditions of the charging stations used, and the cost conditions used by the customer. This model may be generated using, for example, deep learning. This model is a model that, when inputting, for example, situation information and information on recommended charging stations, outputs cost conditions to be presented to the customer.

[0065] In this embodiment, correct answer data linking past customer situation information, conditions of the charging station to be used, and cost conditions of the customer's use, and a model generated from this correct answer data are stored in the storage device 505. The generation of the model may be performed by a component within the information display device 110 or by a device other than the information display device 110.

[0066] 9 and 10 show examples of stored correct answer data for when a customer has used a charging station in the past, according to the present disclosure. The examples in FIGS. 9 and 10 show cost conditions when a customer uses a charging station under specific conditions. In the examples in FIGS. 9 and 10, the margin of each customer is the same, with the margin of +5 in FIG. 9 and the margin of -5 in FIG. 10.

[0067] 9 and 10 show that customer A is the type who wants to charge immediately even if an additional cost is incurred, and that when the margin of safety is +5, he is willing to pay an additional cost of 100 yen, and when the margin of safety is -5, he is willing to pay an additional cost of 200 yen, and use a charging station five minutes later. Furthermore, it is shown that customers B and C would use a charging station several kilometers away or several hours later if they were given a coupon offering a few percent discount on the charging cost. Furthermore, it is shown that customer D would use a charging station for four hours if he were given a cafe coupon as an incentive.

[0068] Generally, when customers feel less comfortable or have less time, they want to charge immediately at a nearby charging station. Therefore, as shown in Figures 9 and 10, compared to the case in Figure 9 where the customer's margin is +5, the case in Figure 10 where the customer's margin is -5 tends to avoid using a charging station after a certain time or far from the current location unless the incentive amount is increased. Furthermore, compared to the case in Figure 9 where the customer's margin is +5, the case in Figure 10 where the customer's margin is -5 tends to avoid using a charging station within a certain time or far from the current location even if the additional fee is increased.

[0069] Another modified example will be described. In this modified example, the determination unit 113 determines cost conditions based on situation information and the battery charging rate using a model that has learned the customer's past usage history of charging stations. This model is a model that learns the correlation between past situation information, the battery charging rate of a specific electric vehicle, the conditions of the charging station to be used, and the cost conditions used by the customer. More specifically, this model is a model that has been generated by supervised machine learning to determine the correlation between the margin calculated based on the customer's past situation information, the battery charging rate of the electric vehicle, the conditions of the charging station to be used, and the cost conditions used by the customer. This model may be generated using, for example, deep learning. Furthermore, this model is a model that outputs cost conditions to be presented to a customer when, for example, situation information, the battery charging rate of the electric vehicle, and information on recommended charging stations are input.

[0070] In this modification, the first information acquisition unit 111 further acquires the charging rate of the battery of the electric vehicle. The first information acquisition unit 121 acquires the charging rate detected by the SOC detector of the electric vehicle via the network.

[0071] 11 and 12 show another example of storage of correct answer data from when a customer has used a charging station in the past in the present disclosure. The examples of FIGS. 11 and 12 show cost conditions when a recommended charging station is used at a specific battery charging rate. In the example of FIG. 11, the battery charging rate of each customer is 40%, and in the example of FIG. 12, the battery charging rate of each customer is 20%. In addition, in the examples of FIGS. 11 and 12, the margin of each customer is +5.

[0072] Generally, when the battery charge rate is low, customers want to charge immediately at a nearby charging station. Therefore, as shown in Figures 11 and 12, compared to the case of Figure 11 where the battery charge rate is 40%, in Figure 12 where the battery charge rate is 20%, customers tend not to use a charging station after a predetermined time or far from the current location unless a larger incentive is provided. Also, compared to the case of Figure 11 where the battery charge rate is 40%, in Figure 12 where the battery charge rate is 20%, customers tend to use a charging station within a predetermined time or nearby even if the additional fee collected is higher.

[0073] In this modification, the method of outputting the information about the charging station by the output unit 114 is the same as in the second embodiment. That is, the output unit 114 outputs, in addition to the charging station information, information about an additional fee to be collected or an incentive to be provided when the charging station is used.

[0074] In this modification, the determination unit 113 determines the cost conditions based on the situation information using a model that has learned the customer's past usage history of charging stations. As a result, by presenting similar cost conditions to a customer who has used a specific charging station under certain cost conditions with a specific margin, the probability that the customer will use the recommended charging station is increased.

[0075] In this modification, the determination unit 113 determines the cost conditions based on the situation information and the battery charging rate by using a model that has learned the customer's past usage history of the charging station. As a result, when a customer has used a specific charging station under certain cost conditions with a specific margin and battery charging rate, by presenting the customer with similar cost conditions, the probability that the customer will use the recommended charging station is increased.

[0076] [Third Embodiment] Next, a third embodiment of the present disclosure will be described in detail with reference to the drawings. Below, descriptions of content that overlaps with the above description will be omitted to the extent that the description of this embodiment is not unclear. This embodiment assumes that an incentive is provided to an electric vehicle that can travel to a destination even after replacing a battery with a low charging rate, and a request is made to replace the battery. Note that in this embodiment, a charging station having more than a predetermined number of uncharged batteries whose charging rate is below a predetermined threshold may be referred to as a "deficit station," and a charging station having more than a predetermined number of charged batteries whose charging rate is equal to or higher than a predetermined threshold may be referred to as a "surplus station."

[0077] Fig. 13 is a block diagram including an information display device 120 according to the present disclosure. Similar to the computer device shown in Fig. 2, the functions of the information display device 120 can be realized not only by hardware but also by a computer device or software based on program control.

[0078] Referring to FIG. 13, information display device 120 includes first information acquisition unit 121 , second information acquisition unit 122 , search unit 123 , extraction unit 124 , determination unit 125 , and output unit 126 .

[0079] The first information acquisition unit 121 further acquires the charging rate of the battery of the electric vehicle. The first information acquisition unit 121 acquires the charging rate detected by the SOC detector of the electric vehicle via the network.

[0080] The second information acquisition unit 122 acquires the charging rate of each battery at a charging station within a predetermined distance from the current location.

[0081] When the charging rate of the battery of the electric vehicle is equal to or higher than a predetermined threshold, the search unit 123 searches for shortage stations near the travel route to the set destination where the number of uncharged batteries with charging rates lower than the predetermined threshold is greater than a predetermined number. The search unit 123 searches for shortage stations where the number of uncharged batteries with charging rates lower than at least the charging rate of the battery of the electric vehicle is greater than a predetermined number, based on the charging rates of each battery in charging stations within a predetermined distance from the current position obtained from the second information acquisition unit 122. The search unit 123 may search for shortage stations with the highest proportion of uncharged batteries.

[0082] The extraction unit 124 is a means for extracting uncharged batteries capable of traveling to the destination from among the uncharged batteries in the searched shortage stations. The extraction unit 124 calculates the charging rate at which the distance from the shortage station to the destination can be traveled, and extracts uncharged batteries with a charging rate equal to or higher than the calculated charging rate from among the uncharged batteries in the searched shortage stations.

[0083] The determination unit 125 determines an incentive to be provided when the battery of the electric vehicle is replaced with one of the extracted uncharged batteries, based on the situation information. As in the second embodiment, the determination unit 125 may determine the content of the incentive based on preference information or purchase history information. Furthermore, the determination unit 125 may determine the incentive based on the situation information using a model that has learned the correlation between past situation information of the customer, the conditions of the charging station used, and the cost conditions under which the customer used the charging station. Furthermore, the determination unit 125 may determine the incentive based on the situation information and the battery charge rate using a model that has learned the correlation between past situation information of the customer, the charging rate of the battery of a specific electric vehicle, the conditions of the charging station used, and the cost conditions under which the customer used the charging station.

[0084] Furthermore, the determination unit 125 may determine the incentive based on the charging rate of the replaced uncharged battery. For example, the determination unit 125 may set the incentive to be greater as the charging rate of the replaced uncharged battery decreases. The determination unit 125 may also determine the incentive based on the distance from the current location to the location of the charging station where the battery is to be replaced. For example, the determination unit 125 may set the incentive to be greater as the distance from the current location to the charging station where the battery is to be replaced increases.

[0085] The output unit 126 outputs an incentive when the battery of the electric vehicle is replaced with one of the extracted uncharged batteries. FIG. 14 is an example of a screen used in the present disclosure when outputting incentives. As shown in FIG. 14 , information on incentives when the uncharged battery to be replaced is replaced with a candidate charging station is displayed. In the example of FIG. 14 , information on stations A to C, the identification number of the uncharged battery recommended for replacement, and coupon information that can be used at the destination as an incentive when the battery is replaced with an uncharged battery from a station farther from the current location are displayed. As shown in FIG. 14 , the discount rate of the coupon provided is larger when the uncharged battery is replaced with an uncharged battery from a station farther from the current location. Furthermore, when a charging station to be used is selected on the screen of FIG. 14 and route search is tapped, the output unit 126 may display a route to the destination that passes through the selected charging station.

[0086] 15 is a flowchart showing an outline of the operation of the information display device 120 according to the present disclosure. Note that the processing according to this flowchart may be executed based on program control by the processor described above.

[0087] As shown in FIG. 15 , the first information acquisition unit 121 acquires location information of the electric vehicle and situation information indicating the customer's situation (step S301). Next, the second information acquisition unit 122 acquires the charging rate of each battery at charging stations within a predetermined distance from the location information (step S302). Next, if the battery charging rate is equal to or greater than a predetermined threshold (step S303; YES), the search unit 123 searches for shortage stations near the travel route to the set destination where the number of uncharged batteries with a charging rate lower than the predetermined threshold is greater than a predetermined number (step S304). On the other hand, if the battery charging rate is less than the predetermined threshold (step S303; NO), the search unit 123 determines the cost conditions for the customer's use of recommended charging stations based on the situation information (step S305). Next, the output unit 126 outputs the cost conditions for the determined charging stations (step S306).

[0088] Next, the extraction unit 124 extracts uncharged batteries that are capable of traveling to the destination from among the uncharged batteries in the searched stations for battery shortage (step S307). Next, the determination unit 125 determines an incentive to be provided when the battery of the electric vehicle is replaced with one of the extracted uncharged batteries based on the situation information (step S308). Finally, the output unit 126 outputs the determined incentive (step S309). This completes the process of the information display device 120.

[0089] In this embodiment, when the battery's charging rate is equal to or higher than a predetermined threshold, the search unit 123 searches for shortage stations near the travel route to the set destination that have more than a predetermined number of uncharged batteries with charging rates lower than the predetermined threshold. The extraction unit 124 then extracts uncharged batteries that are capable of traveling to the destination from the uncharged batteries in the searched shortage stations, and the output unit 126 outputs a screen recommending the replacement of the electric vehicle's battery with one of the extracted uncharged batteries. By replacing a battery whose own charging rate is equal to or higher than the predetermined threshold with one of the uncharged batteries in a shortage station with many uncharged batteries, the average charging rate of the batteries in the shortage stations can be increased, and the average charging rates of batteries among multiple charging battery stations can be equalized.

[0090] Furthermore, in this embodiment, when the search unit 123 searches for a charging station with the highest proportion of uncharged batteries, the average charging rate of batteries among multiple charging battery stations can be efficiently equalized by exchanging a battery whose own charging rate is above a predetermined threshold with one of the uncharged batteries in the shortage station with the highest number of uncharged batteries.

[0091] In the third embodiment described above, the output means outputs a screen recommending replacement of either the battery of the electric vehicle with an uncharged battery. In contrast, in this modification, after the battery of the electric vehicle has been replaced with a charged battery, a screen is output recommending replacement of the replaced charged battery with the uncharged battery.

[0092] FIG. 16 is a diagram illustrating battery exchange in this modified example. As shown in FIG. 16 , in this modified example, a customer exchanges batteries at two charging stations along a route to a store C as a destination, thereby leveling the charging rates of the batteries among the multiple charging stations. First, the customer exchanges his or her own battery with a charged battery at station A, which is a surplus station where the number of charged batteries with charging rates equal to or higher than a predetermined threshold is greater than a predetermined number. In this case, it is assumed that the charging rate of the charged battery is higher than the customer's own battery. Next, the customer exchanges the charged battery exchanged at station A with the uncharged battery at station B, which is a shortage station where the number of uncharged batteries with charging rates below the predetermined threshold is greater than a predetermined number. The customer then drives to his or her destination with the uncharged battery.

[0093] Next, the function of each component will be described, focusing on differences from the third embodiment. The search unit 123 further searches for surplus stations near the travel route to the set destination where the number of charged batteries with a charging rate equal to or higher than a predetermined threshold is greater than a predetermined number. That is, the search unit 123 searches for candidates for station A in FIG. 16. Next, the extraction unit 124 extracts charged batteries at the searched charging stations. The extracted charged batteries are those in the candidate stations for station A. The extraction unit 124 may extract the battery with the highest charging rate among the charging stations.

[0094] In this modification, the method for searching for a candidate station B in Fig. 16 is the same as the configurations of the search unit 123 and the extraction unit 124 in the third embodiment. In this embodiment, the search unit 123 may search for each charging station so that the surplus station is closer to the current location than the shortage station. In this case, the customer can exchange an uncharged battery for a charged battery at the shortage station without having to turn back when driving to the destination.

[0095] The output unit 126 outputs an incentive when the battery of the electric vehicle is replaced with the extracted charged battery and then the replaced charged battery is replaced with an uncharged battery. FIG. 17 shows an example of outputting an incentive when a battery is replaced in the present disclosure. As shown in FIG. 17 , information about charging station A where a charged battery is located and information about charging station B where an uncharged battery is located are displayed. In addition, in the example of FIG. 17 , coupon information that can be used at the destination is displayed as an incentive when the battery is replaced at station A and station B. When route search is tapped on the screen of FIG. 17 , the output unit 126 may display a route to the destination that passes through charging station A and charging station B.

[0096] Fig. 18 is a flowchart showing an outline of the operation of information display device 120 according to the present disclosure. The flow of steps S311 to S313 in the flowchart in Fig. 18 is similar to the flow of steps S301 to S303 in the flowchart in Fig. 15. Furthermore, the processing according to this flowchart may be executed based on program control by the processor described above.

[0097] As shown in FIG. 18 , the first information acquisition unit 121 acquires information about the current location of the electric vehicle and status information indicating the customer's status (step S311). Next, the second information acquisition unit 122 acquires the charging rates of the batteries at charging stations within a predetermined distance from the current location (step S312). Next, if the battery charging rates are equal to or greater than a predetermined threshold (YES in S313), the search unit 123 searches for shortage stations, where the number of uncharged batteries with charging rates below the predetermined threshold is greater than a predetermined number, and surplus stations, where the number of charged batteries with charging rates above the predetermined threshold is greater than a predetermined number, near the travel route to the set destination (step S314). On the other hand, if the battery charging rates are less than the predetermined threshold (NO in S313), the search unit 123 determines the cost conditions for the customer's use of recommended charging stations based on the status information (step S315). Next, the output unit 126 outputs the cost conditions for the determined charging stations (step S316).

[0098] Next, the extraction unit 124 extracts uncharged batteries that can travel to the destination from among the charged batteries of the searched surplus stations and the uncharged batteries of the searched shortage stations (step S317). Next, the determination unit 125 determines an incentive for replacing the battery of the electric vehicle with the extracted charged battery, and then replacing the extracted uncharged battery with the replaced charged battery, based on the situation information (step S318). The output unit 126 outputs the determined incentive (step S319). This completes the processing of the information display device 120.

[0099] In this modification, when the battery's charging rate is equal to or higher than a predetermined threshold, the search unit 123 searches for surplus stations with more than a predetermined number of uncharged batteries with charging rates below the predetermined threshold and shortage stations with more than a predetermined number of charged batteries with charging rates equal to or higher than the predetermined threshold near the travel route to the set destination. The extraction unit 124 then extracts uncharged batteries that are capable of traveling to the destination from among the charged batteries in the searched surplus stations and the uncharged batteries in the shortage stations. The output unit 126 outputs an incentive for replacing the battery of the electric vehicle with the extracted charged battery and then replacing the extracted uncharged battery with the replaced charged battery based on the situation information. In this way, by exchanging uncharged batteries in surplus stations with charged batteries in shortage stations, the average charging rate of batteries among multiple charging stations can be equalized.

[0100] Although the present disclosure has been described above with reference to various embodiments, the present disclosure is not limited to the above embodiments. The configuration and details of each of the present disclosures may include embodiments to which various modifications that would be apparent to those skilled in the art are applied within the scope of the present disclosure. The present disclosure may also include embodiments in which the details described herein are appropriately combined or substituted as necessary. For example, details described using a particular embodiment may also be applied to other embodiments to the extent that no contradiction occurs. For example, although multiple operations are described in sequence in the form of a flowchart, the order of the descriptions does not limit the order in which the multiple operations are performed. Therefore, when implementing each embodiment, the order of the multiple operations may be changed as long as it does not interfere with the content.

[0101] Some or all of the above-described embodiments can be described as follows: However, some or all of the above-described embodiments are not limited to the following.

[0102] (Supplementary Note 1) An information display device comprising: a first information acquisition means that acquires location information of an electric vehicle and situation information that indicates the situation of a customer; a second information acquisition means that acquires the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of each battery at the charging station; and an output means that outputs information about recommended charging stations based on the situation information and the congestion rate or the charging rate.

[0103] (Supplementary Note 2) The information display device according to Supplementary Note 1, further comprising a determination means for determining a cost condition for the customer to use the recommended charging station based on the situation information, and the output means outputs the determined cost condition.

[0104] (Appendix 3) The information display device described in Appendix 2, wherein the situation information includes at least one of the customer's biometric information, driving information indicating the customer's driving status, and the customer's schedule information, and the determination means determines the cost conditions based on at least one of emotions or physical condition estimated from the biometric information, emotions or physical condition estimated from the driving information, and a degree of urgency estimated from the schedule information.

[0105] (Supplementary Note 4) In the information display device according to Supplementary Note 3, the determining unit determines the cost condition based on the situation information by using a model that has learned a past usage history of the customer when using a charging station.

[0106] (Supplementary Note 5) In the information display device described in Supplementary Note 3, the first information acquisition means further acquires a charging rate of the battery of the electric vehicle, and the determination means determines the cost condition based on the situation information and the charging rate of the battery using a model that has learned the past usage history of the customer when using a charging station.

[0107] (Appendix 6) An information display device according to any one of Appendices 3 to 5, wherein the determination means, when granting an incentive to the customer as the cost condition, determines the content of the incentive to be granted based on preference information or purchase history information of the customer.

[0108] (Supplementary Note 7) The information display device according to Supplementary Note 3 to 6, wherein when an incentive is to be given to the customer as the cost condition, the determination means determines the content of the incentive to be given based on the emotion or physical condition of the customer.

[0109] (Supplementary Note 8) The information display device according to Supplementary Note 1 further comprises: a search means for acquiring a charging rate of the battery of the electric vehicle; and, if the charging rate of the battery is equal to or higher than a predetermined threshold, searching for shortage stations near the travel route to the set destination where the number of uncharged batteries with a charging rate below the predetermined threshold is greater than a predetermined number; an extraction means for extracting uncharged batteries that can be used to travel to the destination from the uncharged batteries of the shortage stations found; and a determination means for determining an incentive to be given when the battery of the electric vehicle is replaced with any of the extracted uncharged batteries based on the situation information; and the output means outputs the determined incentive.

[0110] (Supplementary Note 9) The information display device according to Supplementary Note 8, wherein, when the charging rate of the battery is equal to or higher than a predetermined threshold, the search means searches for shortage stations near the travel route to the set destination, where the number of uncharged batteries with a charging rate below the predetermined threshold is greater than a predetermined number, and surplus stations where the number of charged batteries with a charging rate equal to or higher than the predetermined threshold is greater than a predetermined number; the extraction means extracts uncharged batteries that can be used to travel to the destination from among the charged batteries of the searched surplus stations and the uncharged batteries of the shortage stations; the determination means determines an incentive for exchanging the extracted uncharged battery for the replaced charged battery after exchanging the battery of the electric vehicle with the extracted charged battery; and the output means outputs the determined incentive.

[0111] (Supplementary Note 10) The information display device according to Supplementary Note 8 or Supplementary Note 9, wherein the search means searches for an insufficient charging station with the highest ratio of uncharged batteries.

[0112] (Appendix 11) An information display device as described in any of Appendices 8 to 10, wherein the situation information includes at least one of biometric information of the customer, driving information indicating the driving status of the customer, and schedule information of the customer, and the determination means determines the incentive based on at least one of emotions or physical condition estimated from the biometric information, emotions or physical condition estimated from the driving information, and a degree of urgency estimated from the schedule information.

[0113] (Supplementary Note 12) An information display method in which a computer acquires location information of an electric vehicle and situation information indicating the situation of a customer, acquires the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of each battery at the charging station, and outputs information on recommended charging stations based on the situation information and the congestion rate or the charging rate.

[0114] (Supplementary Note 13) A recording medium storing a program that causes a computer to execute a process of acquiring location information of an electric vehicle and situation information indicating the customer's situation, acquiring the congestion rate of charging stations within a predetermined distance from the location information or the charging rate of each battery at the charging station, and outputting information on recommended charging stations based on the situation information and the congestion rate or the charging rate.

[0115] 10, 11, 12 Information display system 100, 110, 120 Information display device 101, 111, 121 First information acquisition unit 102, 112, 122 Second information acquisition unit 103, 114, 126 Output unit 113, 125 Decision unit 123 Search unit 124 Extraction unit 200, 210, 220 Terminal device 500 Computer device 501 CPU 502 ROM 503 RAM 504 Program 505 Storage device 506 Recording medium 507 Drive device 508 Communication interface 509 Input / output interface 510 Bus

Claims

1. a first information acquisition means for acquiring position information of the electric vehicle and situation information indicating a situation of the customer; a second information acquisition means for acquiring a congestion rate of charging stations within a predetermined distance from the location information or a charging rate of each battery at the charging station; an output unit that outputs information about recommended charging stations based on the situation information and the congestion rate or the charging rate.

2. a determination unit that determines a cost condition in a case where the customer uses the recommended charging station based on the situation information; The information display device according to claim 1 , wherein said output means further outputs said determined cost condition.

3. the situation information includes at least one of biometric information of the customer, driving information indicating a driving situation of the customer, and schedule information of the customer; 3. The information display device according to claim 2, wherein the determining means determines the cost condition based on at least one of emotions or physical condition estimated from the biometric information, emotions or physical condition estimated from the driving information, and a degree of urgency estimated from the schedule information.

4. The information display device according to claim 3 , wherein the determining unit determines the cost condition based on the situation information by using a model that has learned a past usage history of the customer when the customer used a charging station.

5. The first information acquisition means further acquires a charging rate of a battery of the electric vehicle, 4. The information display device according to claim 3, wherein the determining means determines the cost condition based on the situation information and the charging rate of the battery using a model that has learned a past usage history of the customer when using a charging station.

6. 4. The information display device according to claim 3, wherein, when an incentive is to be given to the customer as the cost condition, the determining means determines the content of the incentive to be given based on the emotion or physical condition of the customer.

7. The first information acquisition means further acquires a charging rate of a battery of the electric vehicle, a search means for searching for shortage stations in the vicinity of a travel route to a set destination where the number of uncharged batteries with a charging rate below the predetermined threshold is greater than a predetermined number, when the charging rate of the battery is equal to or greater than a predetermined threshold; an extraction means for extracting uncharged batteries capable of traveling to the destination from among the uncharged batteries in the searched stations for shortage; a determination means for determining an incentive to be provided when the battery of the electric vehicle is replaced with any one of the extracted uncharged batteries based on the situation information; The information display device according to claim 1 , wherein the output means outputs the determined incentive.

8. When the charging rate of the battery is equal to or higher than a predetermined threshold, the search means searches for shortage stations in the vicinity of the travel route to the set destination, where the number of uncharged batteries with charging rates below the predetermined threshold is greater than a predetermined number, and for surplus stations in the vicinity of the travel route to the set destination, where the number of charged batteries with charging rates equal to or higher than the predetermined threshold is greater than a predetermined number, the extraction means extracts uncharged batteries capable of traveling to the destination from among the searched charged batteries of the surplus stations and the uncharged batteries of the shortage stations; the determination means determines an incentive for replacing the extracted uncharged battery with the replaced charged battery after replacing the battery of the electric vehicle with the extracted charged battery; The information display device according to claim 7 , wherein the output means outputs the determined incentive.

9. The computer Acquire location information of the electric vehicle and situation information indicating the customer's situation, Obtaining a congestion rate of charging stations within a predetermined distance from the location information or a charging rate of each battery at the charging station; An information display method that outputs information about recommended charging stations based on the situation information and the congestion rate or the charging rate.

10. Acquire location information of the electric vehicle and situation information indicating the customer's situation, Obtaining a congestion rate of charging stations within a predetermined distance from the location information or a charging rate of each battery at the charging station; A program that causes a computer to execute a process of outputting information about recommended charging stations based on the situation information and the congestion rate or the charging rate.