In-vehicle device

Abstract

To provide a technique for determining the type of a charging facility at a site where the type of the charging facility is unknown.SOLUTION: A vehicle-mounted device according to a first aspect of the present disclosure acquires a captured image from a vehicle-mounted camera disposed so as to capture an image of an outside of a vehicle, determines a type of a charging facility shown in the captured image by performing image analysis on the acquired captured image, and outputs information related to a determination result of the charging facility.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to an in-vehicle device. [Background technology]

[0002] Patent Document 1 proposes a technique for searching for charging facilities included in a charging facility search range, selecting a charging facility close to a destination, and providing information on the selected charging facility. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-085685 Summary of the Invention [Problem to be solved by the invention]

[0004] One of the objectives of the present disclosure is to provide a technology for determining the type of charging equipment at a site where the type of charging equipment is unknown because, for example, the information on charging facilities registered in map information is out of date. [Means for solving the problem]

[0005] The in-vehicle device according to a first aspect of the present disclosure includes a control unit configured to acquire captured images from an in-vehicle camera positioned to capture images of the outside of the vehicle, determine the type of charging equipment shown in the captured images by analyzing the captured images, and output information related to the determination result of the charging equipment. [Effects of the Invention]

[0006] According to the present disclosure, it is possible to determine the type of charging equipment at a site where the type of charging equipment is unknown. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 schematically illustrates an example of a situation to which the present disclosure is applied. [Figure 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of the in-vehicle device according to the present disclosure. [Figure 3] FIG. 3 shows an example of a processing procedure of the in-vehicle device of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0008] [1 Application example] 1 schematically illustrates an example of a situation to which the present disclosure is applied. The in-vehicle device 1 according to this embodiment includes a control unit 11. The control unit 11 is configured to acquire captured images from an in-vehicle camera DC arranged to capture images of the outside of the vehicle M, perform image analysis on the acquired captured images, determine the type of charging equipment CE shown in the captured images, and output information related to the determination result.

[0009] As another form of the in-vehicle device 1 according to the above embodiment, one aspect of the present disclosure may be an information processing method or program that realizes all or part of the above components, or may be a storage medium that stores such a program and is readable by a machine such as a computer. A storage medium that is readable by a machine such as a computer is a medium that stores information such as a program by electrical, magnetic, optical, mechanical, or chemical action.

[0010] The vehicle M in this embodiment is equipped with a battery and a configuration for charging it externally, and is powered by electricity. The type of vehicle M (number of wheels, size, etc.) may be selected arbitrarily as long as it is equipped with a battery and a charging configuration. The vehicle M may be selected from, for example, a two-wheeled vehicle, a three-wheeled vehicle, a four-wheeled vehicle, etc. If the vehicle M is an automobile, the size of the vehicle M may be selected from large, medium, semi-medium, standard, large special, small special, etc. If the vehicle M is a two-wheeled vehicle, the size of the vehicle M may be selected from large, standard, etc. The user may be any person involved with the vehicle M. Typically, the user may be the driver.

[0011] (Type of charging equipment) There are many different types of charging equipment CE. For example, the types of charging equipment CE for charging a vehicle M can be broadly categorized into standard chargers and rapid chargers. Standard chargers come in different output powers, such as 3kW and 6kW. Similarly, rapid chargers come in different output powers, such as 30kW and 90kW. Each type of charger is installed in various facilities. Chargers can be distinguished by their appearance, such as size and markings. Furthermore, a recommended charging amount may be set depending on the type of charger.

[0012] The type of facility in which the charging equipment CE is installed is not particularly limited and may be determined arbitrarily. For example, the facility may include a detached house, an apartment building, a building, an outdoor parking lot, a car dealership, a convenience store, a supermarket, a hospital, a commercial facility, a leisure facility, an accommodation facility, a highway service area / parking area, a gas station, a roadside station, etc.

[0013] Information about facilities where charging facilities CE are installed (such as the type of charger) may be registered in advance in a map information database MDB. The map information database MDB may be managed and provided by a server S. The on-board device 1 may also be configured to be able to perform navigation (route guidance). In this case, the on-board device 1 may be configured to be able to check the location of the facility, the type, number, and operating status of the charging facilities CE on the navigation system. However, because the charging facilities CE may be frequently updated, the information about the charging facilities CE on the navigation system may be outdated, and the type of the charging facilities CE indicated by the information on the navigation system may differ from the actual type of the charging facilities CE. In this case, the actual charging time may differ from the expected charging time, which may cause inconvenience. Therefore, in order to keep the information about the charging facilities CE up to date, the vehicle M (on-board device 1) may be configured to provide the map information database MDB with the latest information by notifying the server S of feedback reporting the actual type of the charging facilities CE when the type of the actual charging facilities CE determined by the image analysis differs from the type indicated by the information on the navigation system.

[0014] Furthermore, when charging the vehicle M, it is desirable that charging settings 81 be set according to the type of charging facility CE. By identifying the type of charging facility CE and setting charging settings 81 according to that type, it is possible to optimize charging time and reduce battery deterioration. In this embodiment, the charging facility CE is imaged by the in-vehicle camera DC, the image is analyzed to determine the type of charging facility CE, and output (transmission to server S, change of charging settings 81) according to the determination result, thereby making it possible to automatically achieve the above objective.

[0015] (Image of charging equipment taken by an in-vehicle camera) The type of the on-board camera DC is not particularly limited as long as it can acquire an image from which the type of charging facility CE can be determined, and may be appropriately selected depending on the embodiment. The on-board camera DC is positioned to capture images of the outside of the vehicle M so that it can capture images of the charging facility CE.

[0016] (Image analysis) The image analysis method for the image of the charging facility CE captured by the in-vehicle camera DC is not particularly limited. The image analysis method may not necessarily be a method for determining the type of charging facility CE, and may be appropriately selected depending on the embodiment. In one example, the image analysis method may be a method for determining the type of charging facility CE by pattern matching. In another example, the image analysis method may be a method for determining the type of charging facility CE by using a trained machine learning model.

[0017] Image analysis using pattern matching may involve the control unit 11 referencing the charging equipment image 41 stored in advance in the storage unit 12 and applying a matching method. Examples of matching methods include template matching, feature point matching, and the like. Template matching is a method in which the control unit 11 calculates the similarity between a template image of charging equipment CE included in the charging equipment image 41 and a captured image of the charging equipment CE to determine whether the objects in the two images are the same. The similarity may be calculated by calculating a correlation coefficient, mean square error, or the like, to determine the degree of agreement between pixel values ​​in a region of the captured image of the charging equipment CE that corresponds to the template image. Feature point matching is a method in which the control unit 11 determines whether the objects in the two images are the same by examining the correspondence between feature points extracted from the template image and the captured image of the charging equipment CE. A feature point may be a point in an image showing an object, where a quantity that characterizes a pixel can be distinguished from surrounding pixels. The quantity that characterizes a pixel may be color, brightness, or the like.

[0018] In image analysis using a trained machine learning model, the control unit 11 determines the type of charging equipment CE shown in a captured image using a trained model 61 stored in the storage unit 12. The trained model 61 has one or more calculation parameters that can be adjusted by machine learning. The one or more calculation parameters are used for calculating the desired inference. The trained model 61 may be configured, for example, by a neural network, a support vector machine, a regression model, or other function formula (calculation model). The machine learning method may be appropriately selected depending on the machine learning model to be adopted (for example, backpropagation method, etc.).

[0019] When the trained model 61 includes a neural network, the structure of the neural network is not particularly limited and may be determined appropriately depending on the embodiment. The structure of the neural network may be specified, for example, by the number of layers from the input layer to the output layer, the type of each layer, the number of nodes (neurons) included in each layer, the connection relationships between the nodes in each layer, etc. The neural network may include any mechanism such as a recurrent structure, a self-attention mechanism, or an autoregressive model. The neural network may include any layer such as a fully connected layer, a convolutional layer, a pooling layer, a deconvolutional layer, an unpooling layer, a normalization layer, a dropout layer, or a long short-term memory (LSTM). The neural network may also include any type of model such as a diffusion model, a transformer model, or a generative model. The connection weights between each node included in the neural network and the threshold value of each node are examples of calculation parameters.

[0020] (Output of information about the judgment result) After determining the type of charging facility CE, the control unit 11 may be configured to output information related to the determination result. The content of the information related to the determination result may be determined appropriately depending on the embodiment. In one example, the control unit 11 may simply output the type of charging facility CE as the determination result. In another example, the control unit 11 may execute any information processing depending on the charging facility CE. The control unit 11 may output the result of the information processing as information related to the determination result. The output of the result of the information processing may include, for example, outputting a message such as a recommended charging amount or an estimated charging time, or transmitting the type of charging facility CE as the determination result to the server S.

[0021] The recommended charge amount indicates the charge amount (full charge, 80% charge, etc.) recommended for each charging facility CE. The estimated charge time indicates the charge time required to charge the vehicle M from its current charge amount to the recommended charge amount. The control unit 11 refers to the storage unit 12 and acquires the charging facility information 51 and the remaining charge amount 71, thereby being able to calculate these pieces of information.

[0022] The output destination of the determination result may be determined appropriately depending on the embodiment. For example, the output destination may be another computer such as RAM, the storage unit 12, the output device 15, the server S, or a user terminal. For example, when the determination result is output to the storage unit 12, the current charging setting 81 stored in the storage unit 12 is updated to a setting corresponding to the charging facility CE of the determination result. Furthermore, when the determination result is output to the server S, if the server S that has received the determination result determines that the information on the charging facility CE held in the map information database MDB differs from the information on the charging facility CE of the determination result, the server S can update the map information database MDB to keep the data on the charging facility CE up to date.

[0023] (Route guidance reconstruction) When route guidance includes charging at a charging facility CE, if the type of charging facility CE indicated in the navigation information differs from the actual type, inconveniences may occur in the route guidance. For example, a shortened charging time may cause the planned travel time to overlap with rush hour, increasing the possibility of getting caught in traffic. Therefore, the in-vehicle device 1 may reconstruct the route guidance (for example, extend the charging time, skip charging, and charge at another facility, etc.) depending on the determination result of the type of charging facility CE.

[0024] [2 Configuration Examples] FIG. 2 is a schematic diagram showing an example of the hardware configuration of the in-vehicle device 1 of the present disclosure. As shown in FIG. 2, the in-vehicle device 1 according to this embodiment is a computer to which a control unit 11, a storage unit 12, a communication interface 13, an external interface 14, and an output device 15 are electrically connected. The control unit 11 includes a CPU (Central Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), etc., and is configured to execute any information processing. do.

[0025] The storage unit 12 may be configured with, for example, a hard disk drive, a solid state drive, or the like. In this embodiment, the storage unit 12 stores a program 31, a charging facility image 41, charging facility information 51, a trained model 61, a remaining charge amount 71, and a charging setting 81. The program 31 is a program for causing the in-vehicle device 1 to execute information processing according to this embodiment. The program 31 includes a series of instructions for the information processing. The charging facility image 41 includes a reference image for each charging facility CE used for pattern matching. The charging facility information 51 includes various information such as a recommended charge amount for each charging facility CE. The trained model 61 is a model that has been trained in advance (adjusted calculation parameters) to determine the type of charging facility CE shown in the captured image. The remaining charge amount 71 indicates the remaining charge (kW) of the vehicle M. The charging setting 81 records various settings for charging the vehicle M and is set according to the type of charging facility CE.

[0026] The communication interface 13 is configured to perform wired or wireless data communication via a network. The communication interface 13 may be configured, for example, by a wired LAN (Local Area Network) module, a wireless LAN module, or the like. In this embodiment, the in-vehicle device 1 may use the communication interface 13 to perform data communication with another computer (e.g., a server S) via a network. The external interface 14 may be, for example, a USB (Universal Serial Bus) port, a dedicated port, a wireless communication port, or the like, and is configured to connect to an external device via a wired or wireless connection. In this embodiment, the in-vehicle device 1 may be connected to an in-vehicle camera DC via the external interface 14. The output device 15 is, for example, a device for outputting data to a display, a speaker, or the like.

[0027] It should be noted that, with regard to the specific hardware configuration of the in-vehicle device 1, components may be omitted, replaced, or added as appropriate depending on the embodiment. For example, the control unit 11 may include multiple hardware processors. The hardware processors may be a microprocessor, a field-programmable gate array (FPGA), a digital signal processor (DSP), a GPU, or the like. (Graphics Processing Unit), ASIC (application specific integrated circuit) ) etc.

[0028] [3 Example of operation] 3 shows an example of a processing procedure of the in-vehicle device 1 of the present disclosure. The following processing procedure is an example of an information processing method executed by a computer.

[0029] In step S101, control unit 11 acquires a captured image of charging facility CE captured by in-vehicle camera DC. In step S102, control unit 11 performs image analysis on the acquired captured image of charging facility CE to determine the type of charging facility CE. The image analysis method may be a pattern matching method using a template image included in charging facility image 41, or a method of determining charging facility CE using trained model 61. When determination of the type of charging facility CE by image analysis is completed, control unit 11 proceeds to step S103.

[0030] In step S103, the control unit 11 outputs the determination result of the type of charging facility CE obtained in step S102. The output content and output destination may be determined appropriately depending on the embodiment. In one example, the control unit 11 may output the type of charging facility CE determined as a result to the storage unit 12, and change the charging setting 81. In another example, the control unit 11 may execute at least one of outputting a message to the output device 15, such as a recommended charging amount and an estimated charging time, and notifying the server S of the type of charging facility CE. When this step is completed, the information processing according to this embodiment ends.

[0031] [Features] In this embodiment, in step S102, the control unit 11 determines the type of charging facility CE by analyzing the captured image of the charging facility CE. As a result, in step S103, the type of charging facility CE can be determined in a field where the type of charging facility CE is unknown, for example, because the information about the charging facility CE registered in the map information is outdated or multiple different types of charging facilities CE exist. Providing this determination result to the user is expected to improve the user's experience with the vehicle M. Furthermore, applying a charging setting 81 based on the determination result before actual charging enables appropriate charging of the vehicle M, thereby optimizing charging time and reducing battery degradation. Furthermore, if the type of charging facility CE registered in the map information database MDB differs from the determination result, the determination result can be notified to the server S, thereby updating the information about the charging facility CE in the map information database MDB to the latest version. This update is triggered by the actions of each user, rather than being actively performed by the administrator of the map information database MDB, which is expected to improve the efficiency of updating the map information database MDB.

[0032] [4 Variations] Although the embodiments of the present disclosure have been described in detail above, the above description is merely an example of the present disclosure in all respects. It goes without saying that various improvements or modifications can be made without departing from the scope of the present disclosure. The processes and means described in the present disclosure can be freely combined and implemented as long as no technical contradiction occurs. [Explanation of symbols]

[0033] 1. In-vehicle device, 11. Control unit, 12. Memory unit, 13. Communication interface, 14. External interface, 15. Output device, 31··Program, 41··Charging equipment image, 51··Charging facility information, 61··Trained model, 71...remaining charge amount, 81...charging settings, M··vehicle, CE··charging equipment, DC··In-vehicle camera, S··Server, MDB··Map Information Database

Claims

[Claim 1] Acquiring captured images from an on-board camera arranged to capture images outside the vehicle; Determining the type of charging equipment shown in the captured image by performing image analysis on the captured image; and outputting information regarding the determination result of the charging facility; a control unit configured to perform In-vehicle device.

Images