Driving information display apparatus and method

Abstract

The invention discloses a driving information display apparatus and method. In a driving information display apparatus and method for providing charging station recommendation information by considering supply and demand, the driving information display apparatus includes: a processor configured to receive driving guide information and vehicle position information and perform control to output a guide screen corresponding to the driving guide information; and a storage unit configured to store the road information and an algorithm driven by the processor. The driving guidance information may include route information including charging station route guidance generated based on destination information, target remaining power information, and supply level information of one or more charging stations located on each of the plurality of areas on a route to the destination.

Description

[0001] Cross - reference to related applications

[0002] This application claims the priority of Korean Patent Application No. 10 - 2023 - 0176556, filed on December 7, 2023, the entire contents of which are incorporated herein by reference for all purposes. Technical Field

[0003] The present disclosure relates to a driving information display device and method for providing charging station recommendation information by considering supply and demand. Background Art

[0004] There are many cases where it is not possible to drive an electric vehicle smoothly due to characteristics such as long charging times and insufficient numbers of charging stations. Therefore, there is a need for a route guidance service that considers the battery state of the electric vehicle and guides it to a charging station.

[0005] In response thereto, U.S. Patent No. 9,170,118, named "Navigation System for Electric Vehicle", discloses a technique for changing a guidance route by considering the remaining battery power at each location while guiding an electric vehicle through its route. In this technique, a target remaining battery power is set for its destination such that when the vehicle reaches the destination, the vehicle can safely make the next trip, and route guidance for traveling via a charging station is provided to help achieve this goal.

[0006] However, in this prior art, charging stations are recommended only based on the vehicle's conditions and the driving route, such that there are problems in that charging demand may be concentrated in a specific area, resulting in long charging waiting times and inconvenience for the driver during charging. Therefore, there is a need for a technique that can predict as accurately as possible the time required to use an actual charging station and provide route guidance including a section via the charging station based on the predicted time.

[0007] The information included in this background of the present disclosure is only for enhancing the understanding of the general background of the present disclosure, and may not be regarded as an admission or suggestion in any form that this information forms the prior art known to those skilled in the art. Summary of the Invention

[0008] The present disclosure relates to a driving information display device and method for providing charging station recommendation information by considering supply and demand, and more particularly to a system and method for recommending an electric vehicle charging station based on information related to the demand and supply of electric vehicle charging stations in each area set based on geographical information.

[0009] Embodiments of the present disclosure can provide guidance on the optimal driving route by considering the charging waiting time and charging time of an electric vehicle.

[0010] Embodiments of the present disclosure can accurately predict the charging waiting time and charging time by analyzing the demand and supply of charging stations.

[0011] Embodiments of the present disclosure can accurately predict the charging waiting time and charging time in each region by using geographical information to analyze the status of one or more charging stations in each region.

[0012] Embodiments of the present disclosure can predict the total required time by additionally considering the time required to move to another charging station when the waiting time at a charging station is long, and provide route guidance aimed at reaching the destination as quickly as possible.

[0013] Embodiments of the present disclosure can set regions and cluster charging stations by using geographical information to facilitate the analysis of supply and demand.

[0014] The problems to be solved by the exemplary embodiments of the present disclosure are not necessarily limited to the above-mentioned problems, and those skilled in the art can clearly understand the solutions to other problems of the embodiments of the present disclosure from the following detailed description of the present disclosure.

[0015] According to various embodiments of the present disclosure, a driving information display device may include: a processor configured to receive driving guidance information and vehicle position information and perform control to output a guidance screen corresponding to the driving guidance information; and a storage unit configured to store road information and an algorithm driven by the processor; wherein, the driving guidance information may include route information, and the route information includes a charging station route guidance generated based on destination information, target remaining battery level information, and supply level information of one or more charging stations in each region located on the route to the destination in a plurality of regions.

[0016] The plurality of regions may be set such that the difference in the total road length within each region does not exceed a predetermined reference value. The supply level information of the charging stations in each region may include charging station density information obtained by dividing the number of charging stations existing in each region by the total road length in each region.

[0017] The supply level information of the charging stations in each region may include information related to the accessibility between charging stations obtained by reflecting real-time traffic information and calculating the driving time between the respective charging stations within each region.

[0018] The supply level information of the charging stations in each area may include information related to the accessibility obtained based on the driving time spent moving to the charging stations in nearby areas when there is only one charging station in each area.

[0019] The charging station route guidance can be generated by considering the estimated charging waiting time information for each area calculated based on the charging demand information for each area and the estimated charging time information for each area calculated based on the charging capacity information of the charging stations in each area.

[0020] The charging demand information for each area can be derived based on the route information and charging status information of multiple electric vehicles.

[0021] According to various embodiments of the present disclosure, a driving information management server may be equipped with a central processing unit and a memory. The driving information management server may include: a connection establishment unit configured to establish a connection to exchange information with the driving information display devices of multiple electric vehicles; a supply level information derivation unit configured to derive the supply level information of multiple charging stations in each area; a driving guidance information generation unit configured to receive destination information and target remaining battery level information from any one of the multiple electric vehicles through the established connection, and generate driving guidance information including a charging station route guidance using the received destination information, the received target remaining battery level information, and the supply level information of each area located on the route to the destination among multiple areas; and a driving guidance information sending unit configured to send the generated driving guidance information to the electric vehicle.

[0022] The multiple areas may be set such that the difference in the total road length within each area does not exceed a predetermined reference value. The supply level information of the charging stations in each area may include the charging station density information obtained by dividing the number of charging stations existing in each area by the total road length in each area.

[0023] The supply level information of the charging stations in each area may include information related to the accessibility between the charging stations obtained by reflecting real-time traffic information and calculating the driving time between the respective charging stations within each area.

[0024] The supply level information of the charging stations in each area may include information related to the accessibility obtained based on the driving time spent moving to the charging stations in nearby areas when there is only one charging station in each area.

[0025] The driving guidance information generation unit may also be configured to generate a charging station route guidance by considering the estimated charging waiting time information for each area calculated based on the charging demand information for each area and the estimated charging time information for each area calculated based on the charging capacity information of the charging stations in each area.

[0026] The charging demand information for each area can be obtained based on the route information and charging status information of multiple electric vehicles.

[0027] The methods and apparatuses of the various embodiments of the present disclosure may have other features and advantages, which will be apparent from or more specifically set forth in the accompanying drawings incorporated herein and the following detailed description, which together with the accompanying drawings and the following detailed description are used to explain certain principles of the exemplary embodiments of the present disclosure. Description of the Drawings

[0028] Figure 1 is a block diagram showing the internal configuration of a driving information display device according to various exemplary embodiments of the present disclosure;

[0029] Figure 2 is a block diagram showing the internal configuration of a driving information management server according to various exemplary embodiments of the present disclosure;

[0030] Figure 3 is a diagram showing an example in which a map is divided into multiple areas to generate route guidance information provided by a driving information display device according to various exemplary embodiments of the present disclosure;

[0031] Figure 4 is a diagram showing an example of calculating the supply amount for each area to generate route guidance information provided by a driving information display device according to various exemplary embodiments of the present disclosure;

[0032] Figure 5 is a diagram showing an example of calculating information related to the convenience (accessibility) of each area to generate route guidance information provided by a driving information display device according to various exemplary embodiments of the present disclosure;

[0033] Figure 6 is a diagram showing an example of selecting an optimal route from candidate routes provided by a driving information display device according to various exemplary embodiments of the present disclosure;

[0034] Figure 7 is a diagram showing the overall process of generating driving guidance information including route guidance in a driving information display device according to various exemplary embodiments of the present disclosure; and

[0035] Figure 8 is a flowchart showing the process of a driving information display method according to various exemplary embodiments of the present disclosure.

[0036] It will be appreciated that the drawings are not necessarily drawn to scale and present a somewhat simplified representation of various features that illustrate the basic principles of the exemplary embodiments of the present disclosure. Specific design features of the exemplary embodiments of the present disclosure as included herein (including, for example, specific dimensions, orientations, positions, and shapes) may be determined in part by the specific intended application and the use environment.

[0037] In the drawings, throughout several views of the drawings, reference numerals may refer to the same or equivalent components of the exemplary embodiments of the present disclosure. Detailed Description

[0038] Reference will now be made in detail to various exemplary embodiments of the present disclosure, which are illustrated in the drawings and described below. Although the present disclosure will be described in conjunction with the exemplary embodiments of the present disclosure, it should be understood that this specification is not intended to limit the present disclosure necessarily to those exemplary embodiments. On the other hand, the present disclosure is intended to cover not only the exemplary embodiments of the present disclosure, but also various alternatives, modifications, equivalents, and other embodiments that may be included within the spirit and scope of the present disclosure as defined by the appended claims.

[0039] Exemplary embodiments of the present disclosure will be described in detail below with reference to the drawings. In the following description of the exemplary embodiments of the present disclosure, when the detailed description of any relevant known configuration or function may obscure the gist of the present disclosure, the detailed description will be omitted. In addition, in the following description of the exemplary embodiments of the present disclosure, specific numerical values are merely examples, and the scope of the present disclosure need not be limited thereby.

[0040] In the following description of the components of the exemplary embodiments of the present disclosure, terms such as first, second, A, B, (a), (b), etc. may be used. These terms may be used only to distinguish the corresponding components from other components, and the nature, sequential position, and / or order of the corresponding components need not be limited by these terms. In addition, unless otherwise defined, all terms used herein (including technical or scientific terms) may include the same meanings as those commonly understood by those skilled in the art to which the exemplary embodiments of the present disclosure pertain. Terms such as those commonly defined in a dictionary should be interpreted as having a meaning consistent with the meaning in the context of the prior art, and should not be interpreted as having an ideal or overly formal meaning unless explicitly defined in this application.

[0041] Reference will now be made to Figures 1 to 8 describe in detail the exemplary embodiments of the present disclosure.

[0042] Figure 1 is a block diagram showing the internal configuration of a driving information display device 101 according to various exemplary embodiments of the present disclosure.

[0043] The driving information display device 101 according to an exemplary embodiment may be disposed inside a vehicle (such as a car), or may be implemented in a detachable form. The driving information display device 101 may generally include a vehicle navigation system; an audio, video, and navigation (AVN) system; a head-up display (HUD), etc., and may be implemented in the form of an application installed on a mobile phone terminal such as a smart phone.

[0044] The driving information display device 101 according to an exemplary embodiment may exist in the form of a server outside a vehicle (e.g., a car). The driving information display device 101 may be implemented to generate driving guidance information by processing a determination while existing outside the vehicle and output the driving guidance information to a display inside the vehicle. Different embodiments may be implemented. The scope of rights of the present disclosure need not be limited by the forms of these implementations.

[0045] The driving information display device 101 of an exemplary embodiment may be combined with the operation of a device for autonomous driving control, such as an advanced driver assistance system (ADAS), a smart cruise control (SCC) system, a forward collision warning (FCW) system, etc.

[0046] As shown in the figure, the driving information display device 101 according to an exemplary embodiment may include a processor 110, a storage unit 120, a communication unit 130, and an output unit 140.

[0047] The processor 110 may be configured to control the storage unit 120, the communication unit 130, and the output unit 140 to execute an application, process data according to an algorithm defined in the application, communicate with an external module, and provide a processing result to a user.

[0048] The processor 110 may refer to a chip for processing general algorithms (e.g., a central processing unit (CPU) or an application processor (AP)) or a collection of such chips. The processor 110 may refer to a chip optimized for floating-point arithmetic (e.g., general-purpose computing on a graphics processing unit (GPGPU)) to process artificial intelligence algorithms such as deep learning, or a collection of such chips. Alternatively, the processor 110 may refer to a module that executes algorithms and processes data in a connected and distributed manner using various types of chips.

[0049] The processor 110 may be electrically connected to the storage unit 120 (a storage medium) and the communication unit 130, may electrically control each component, may be a circuit that executes software commands, and may perform various types of data processing and determination described later. The processor 110 may be, for example, an electronic control unit (ECU), a microcontroller unit (MCU), or other low-level controller installed on a vehicle.

[0050] The storage unit 120 may be a storage medium that can store road information and algorithms executed by a processor. The road information may include map information, road traffic condition information, and the like. According to the configuration of the driving information display device 101 of the present disclosure, the form or amount of the road information stored inside the driving information display device 101 may vary.

[0051] In some cases, the storage unit 120 may store road information including map information and traffic condition information of all serviceable areas and provide services based on the road information. Alternatively, the storage unit 120 may temporarily store only road information related to the location where guidance is being performed and provide services based on the temporarily stored road information.

[0052] Depending on the form in which the driving information display device 101 of the exemplary embodiments of the present disclosure is implemented inside or outside the transportation system, the communication method used, the storage space of the storage unit 120, and / or the input / output speed, this may be implemented in different forms. This is part of what those skilled in the art can choose autonomously according to the implementation situation. The scope of the rights of the present disclosure need not be limited by such changes in the implementation.

[0053] The road information stored in the storage unit 120 may include not only general road information but also information for providing guidance on entrances, exits, parking positions, etc. within an indoor section such as an underground parking lot.

[0054] The road information stored in the storage unit 120 may include various types of display information to be displayed in the guidance information. The display information may include various types of information to be included in the guidance information displayed in the driving situation, such as intersections, traffic lights, sidewalks, destinations, and major landmarks. The display information included in the road information may include parking positions, entrance positions, ramps for moving between floors, indoor facilities, road information outside the indoor area connected to the exit, etc. for guiding within the indoor area. Such display information may each be composed of a combination of the name of the display information and information related to the position where the corresponding display information can be displayed, and the display information will be displayed as guidance information.

[0055] The storage unit 120 can have various forms and can be at least one type of storage medium, such as flash memory, hard disk, micro card (e.g., Secure Digital (SD) card), Extreme Digital (XD) card, Random Access Memory (RAM), Static RAM (SRAM), Read Only Memory (ROM), Programmable ROM (PROM), Electrically Erasable PROM (EPROM), Magnetic Random Access Memory (MRAM), magnetic disk or optical disk type storage medium, etc. or any combination thereof. For example, different types of storage media or combinations of different types of storage media can be selected according to the amount of data to be stored, processing speed, storage time, etc.

[0056] The algorithm stored in the storage unit 120 can be implemented as a computer program in an executable form and can be implemented to be stored in the storage unit 120 and then executed when needed. The algorithm stored in the storage unit 120 can be interpreted as including instructions temporarily loaded into volatile memory and instructing the processor to perform specific operations.

[0057] The communication unit 130 can receive information for driving guidance from outside the driving information display device 101 of the present disclosure through a wired / wireless communication network and send necessary information to an external module.

[0058] The communication unit 130 can receive road information, algorithms executed by the processor 110, etc. stored in the storage unit 120 from an external module and can transmit information related to the current state of the vehicle system to the outside to obtain necessary information related to the transmitted information. For example, the communication unit 130 can continuously receive traffic information from a traffic information server to check real-time traffic information and can be configured to send the position and route information of the vehicle system found by a module such as a Global Positioning System (GPS) receiver to the outside to obtain real-time traffic information of the area related to the position and route of the vehicle system.

[0059] The communication unit 130 is a hardware device implemented using various electronic circuits to transmit and receive signals through wireless or wired connections. In an exemplary embodiment of the present disclosure, the communication unit 130 may perform communication within the vehicle system using infrastructure vehicle network communication technology, and may perform vehicle-to-infrastructure (V2I) communication with a server, infrastructure, another vehicle system, etc. outside the vehicle system using wireless Internet access or short-range communication technology. Communication within the vehicle system may be performed using controller area network (CAN) communication, local interconnect network (LIN) communication, FlexRay communication, etc. as infrastructure vehicle network communication technology. Such wireless communication technologies may include wireless LAN (WLAN), wireless broadband (WiBro), Wi-Fi, worldwide interoperability for microwave access (WiMAX), etc. In addition, short-range communication technologies may include Bluetooth, ZigBee, ultra-wideband (UWB), radio frequency identification (RFID), infrared data association (IrDA), etc.

[0060] The output unit 140 may output augmented reality information controlled by executing an algorithm stored in the storage unit 120 by the processor 110. Augmented reality is a technology that enables relevant information to be provided by adding graphic information to an image or scene of the real world.

[0061] The output unit 140 may be implemented as a head-up display (HUD), cluster, audio, video, and navigation (AVN) system, human-machine interface (HMI), etc. The output unit 140 may include at least one of a liquid crystal display (LCD), thin film transistor liquid crystal display (TFT LCD), light emitting diode (LED) display, organic light emitting diode (OLED) display, active matrix OLED (AMOLED) display, flexible display, curved display, and three-dimensional (3D) display. Some of these displays may be implemented as transparent displays, which may be configured in a transparent or semi-transparent form to enable viewing of the outside. The output unit 140 may be provided as a touch screen including a touch panel, and may be used as both an input device and an output device.

[0062] In the present disclosure, a vehicle may be described based on a concept including various vehicle systems. In some cases, a vehicle may be interpreted based on a concept including not only various land vehicles (such as cars, motorcycles, trucks, and buses) traveling on roads but also various vehicle systems such as airplanes, drones, ships, etc.

[0063] Therefore, in the present disclosure, an electric vehicle may be interpreted based on a concept including various vehicle systems, in which the vehicle system stores electrical energy in a secondary battery and uses the secondary battery as a power source.

[0064] Based on the driving guidance information processed by the processor 110, the driving information display device 101 according to an embodiment of the present disclosure may have different exemplary embodiments. Accordingly, the generation of the driving guidance information received by the processor 110 and the information included in the driving guidance information will be described below by way of example.

[0065] As described above, the processor 110 may execute control to receive driving guidance information and information related to the position of the electric vehicle and output a guidance screen corresponding to the driving guidance information. The driving guidance information may include various types of information. When the driver sets a destination and wants to receive guidance information related to the destination through the screen, the driving guidance information may include information related to the destination and the route leading to the destination. Various other types of information for guiding the driving of the vehicle may be included in the driving guidance information.

[0066] Specifically, in the case of an electric vehicle, the driving distance may be short, the charging may take a long time, and there may not be a sufficient number of charging stations, such that it is important to provide guidance on the optimal route passing through a charging station during route guidance. Accordingly, the processor 110 may be configured to provide guidance on the optimal route along which the driver can safely drive to the destination by using the electric vehicle charging station information included in the map information stored in the storage unit 120 when charging of the electric vehicle is required at a point.

[0067] In the case of a conventional vehicle other than an electric vehicle, guidance on the fastest route among various routes that can reach the destination is generally provided. In the case of an electric vehicle, the driver may want to be guided along the fastest route to reach their destination. However, the charging time of an electric vehicle is longer than that of a conventional vehicle, and the difference in the total required time varies according to the standby state of the charging station, the charging speed, and the amount of power to be charged, making it difficult to find the fastest route.

[0068] In the case of a fossil fuel vehicle, the refueling time and waiting time at a gas station are generally short, such that regardless of which gas station the driver selects on his or her route to refuel the vehicle, the difference in the total required time attributable to the selection of the gas station is not significant. However, in the case of an electric vehicle, the waiting time and charging time can vary significantly depending on the charging station, and thus, when an inappropriate charging station is selected on the driving route, the total required time becomes significantly long. Therefore, it is necessary to provide route guidance including a path passing through a charging station to minimize the total time required for charging.

[0069] Specifically, in the case of long-distance driving, it is more difficult to predict the status of the charging stations that the electric vehicle will pass by, making it necessary to have a method for predicting the status of the charging stations as accurately as possible. For example, in the case of long-distance driving, when it takes about two hours to reach the electric vehicle charging station selected as the passing point, it is difficult to predict how long it will take to wait at the charging station selected as the passing point after two hours and how long it may take to charge the vehicle according to the demand and then drive again.

[0070] When the vehicle is crowded at the charging station selected as the passing point two hours later, the waiting time for charging will be longer. Specifically, the charging time of each electric vehicle is relatively long, making it take a long time to wait for the vehicle being charged to complete charging, which is incomparably longer than the waiting time for refueling a conventional vehicle.

[0071] When many electric vehicles are crowded at the charging station pre-selected as the passing point, resulting in a long waiting time, it may be desirable to move to another nearby charging station and charge the vehicle. However, since the vehicle has already driven for two hours before arrival, the charging stations that the vehicle can reach are inevitably limited. Therefore, in addition to predicting the waiting time and charging time of a specific charging station, by considering the possibility of selecting an alternative charging station according to the situation and the time required for the alternative charging station, the total time required can be accurately calculated. In other words, not only the individual charging stations need to be analyzed, but also the situations in the area around the charging stations need to be analyzed, especially the supply and demand of the charging stations and the possibility of moving to alternative charging stations, and the analysis results need to be used to generate route guidance.

[0072] The driving guidance information processed by the processor 110 may include route information, which includes destination information, target remaining battery level information, and a charging station route guidance generated based on the supply level information of each charging station located on the route to the destination among multiple regions. As described above, it is difficult to predict the accurate total time required and generate effective route information only by analyzing the situation of a single charging station.

[0073] Therefore, in an embodiment of the present disclosure, optimal route information can be generated by setting regions based on geographical information, clustering the charging stations within each region, and analyzing information related to the demand and supply of the charging stations and the accessibility between the charging stations within the corresponding region.

[0074] In an embodiment of the present disclosure, multiple regions can be set such that the difference in the total road length within each region does not exceed a predetermined reference value. There can be different ways to divide the overall map into multiple regions. The simplest way is to divide the map into grids and form the grids in a mosaic structure such that each cell has the same area.

[0075] However, when dividing the area in this way, the central area, mountain area, rural area, coastal area, etc. of the city are all divided into the same size. In one area, there may be complex roads and multiple charging stations, and in another area, there may not even be roads. It is impossible or difficult to effectively analyze the supply and demand of each area.

[0076] Therefore, in the embodiments of the present disclosure, the area can be set such that the difference in the total road length within each area does not exceed a predetermined reference value. The reference value can be determined in the form of a ratio. When the reference value is set to a lower value, the difference in the total road length within each area will be smaller, making efficient management possible, but it will take a lot of effort to divide the entire area into areas. On the contrary, when the reference value is set to a higher value, the entire area can be easily divided into areas, but the difference between areas can become serious, making effective analysis difficult.

[0077] For example, when the whole of South Korea is the target of the map, in the case where the urban roads in Seoul are dense, each area is set to a relatively small area, and in places where there are not many roads (such as rural or mountainous areas), each area is set to a relatively large area.

[0078] When setting the area based on the total road length, the total distance that an electric vehicle can travel within each area becomes the same. The same criteria can be used to compare the number of charging stations in each area, the number of electric vehicles entering each area, and the driving time required to move from one charging station to another within each area.

[0079] In order to divide the entire map into areas in such a way that the total road length is roughly the same, the entire map information and all road information may be required. Therefore, it is necessary to manage the area by constructing and continuously updating the geographic information database 202 including the map information and road information.

[0080] When there is map information and road information, the task of dividing the map into areas based on the map information and road information can be performed by applying various algorithms. Although each area can generally be formed in a rectangular shape, the embodiments of the present disclosure are not necessarily limited to a specific shape.

[0081] For each of the areas set in the above manner, supply level information and demand information are derived, and the derived supply level information and demand information can be used to calculate the charging waiting time and charging time required when an electric vehicle charges within the area. Therefore, the total time required can be calculated by adding the driving time to each area, the calculated charging waiting time, and the calculated charging time.

[0082] The charging station supply level information for each area can be information indicating how easily charging stations can be used within that area, and can be quantified and then provided in numerical form. When the density of charging stations in the area is higher, the supply level can be evaluated as higher. When it is easier to move between charging stations and find alternative charging stations, the supply level can be evaluated as higher.

[0083] First, the density of charging stations in the area can be calculated by dividing the total number of charging stations in the area by the total road length of each area. Thus, the density of charging stations can be determined as the number of charging stations per unit of road, and each area can be set to have a similar total road length such that the number of charging stations in the area actually represents the density of charging stations.

[0084] The number of charging stations refers to the number of chargers that can charge electric vehicles. In the case where the chargers capable of charging electric vehicles are limited according to the type of vehicle, the density of charging stations can be calculated as the number of chargers capable of charging electric vehicles using driving guidance information. In addition, it may be desirable to check status information such as the current availability of each charger and use the number of only available chargers to calculate the density of charging stations.

[0085] In the case of electric vehicle charging stations, the charging speed may be different. When the driver pre-specifies the minimum charging speed of the charging station to be used, the density of charging stations can be calculated only for the chargers in the charging station that have a charging speed higher than the specified minimum charging speed.

[0086] When there is an available time for each charging station, this can be checked, and the density of charging stations can be calculated only based on the chargers available in the charging station when the electric vehicle is expected to arrive in the corresponding area.

[0087] Therefore, the density of charging stations for each area may not be fixed, but can vary according to the type of electric vehicle, the personality of the driver, the usage time, etc., such that the density of charging stations can be calculated by checking the current situation when generating driving guidance information.

[0088] The information related to the supply level of charging stations in each area includes information related to the accessibility between charging stations, which can be obtained by calculating the driving time between each charging station in the area by reflecting the real-time traffic information between each charging station in the area. In other words, this can aim to determine how long it takes to move between charging stations in the area. When the electric vehicle can quickly move to an alternative charging station when the initial target charging station is unavailable when the electric vehicle arrives in the area, the area can be determined to have a high charging station supply level.

[0089] When there is only one charging station in a region, this can be used in the accessibility information obtained based on the driving time required to move to a charging station in a nearby region. In the case where there is only one charging station in a region but one charging station is unavailable, it may not be possible to move to another charging station in the region, and thus it may be necessary to find and move to another charging station in a nearby region. Therefore, the driving time required to move to a charging station in a nearby region can be used as information related to the accessibility between charging stations.

[0090] Specifically, the accessibility between charging stations can vary according to road conditions. In urban areas where traffic congestion may be severe and driving may take a long time, the accessibility between charging stations will be low (or relatively low). In quiet suburbs, the accessibility between charging stations will be high.

[0091] When calculating accessibility based only on congestion, the accessibility in urban areas may seem high, as above. However, in urban areas, there are many roads, so it can be expected that each region may be narrow and the density of charging stations will be high, resulting in a short time being likely to move to a nearby charging station.

[0092] In the suburbs, electric vehicles may move quickly per unit time, but the region will be relatively large and it is more likely that a long distance will need to be driven to find a charging station. Therefore, to determine this comprehensively, it would be desirable to calculate and utilize the time required to move between individual chargers by considering real-time traffic information.

[0093] A charging station route guidance included in route information can be generated by considering the estimated charging waiting time information for each region calculated based on the charging demand information for each region and the estimated charging time information for each region calculated based on the charging capacity information of one or more charging stations in each region. Even when the charging station supply level is high such that there are many chargers and it is convenient to move between chargers, when there are many electric vehicles using the chargers, the waiting time will inevitably be long. Therefore, the estimated charging time can be calculated by determining the charging demand information for each region and analyzing the speed at which the charging demand can be met in each region based on the charging demand information.

[0094] The charging demand information for each region can be derived based on the route information and charging status information of multiple electric vehicles. To this end, by receiving driving route information including destinations and waypoints from the driving information display device 101 of multiple electric vehicles, and then determining the number of electric vehicles planned to arrive at each region and each charging station within the region through statistical analysis of the driving route information, the charging demand information can be derived.

[0095] In order to derive accurate charging demand information, each area can be set as a destination or a passing point, the arrival time of electric vehicles expected to use the charging stations in the area can be predicted, and the number of electric vehicles arriving at the area at the expected arrival time of the electric vehicle for which driving guidance information will be displayed can be calculated.

[0096] By organizing the charging capacity information of one or more charging stations in the area into a database and then using the database, the charging time spent by electric vehicles charging in each area can be predicted.

[0097] For example, in the case where an electric vehicle capable of generating driving guidance information wants to reach a specific area within one hour and charge itself, when there is only one charging station in the area, there is one electric vehicle (the first vehicle) arriving 40 minutes later, and there is one electric vehicle (the second vehicle) arriving 50 minutes later. It can be predicted based on the charging capacity of the charging station in the area that the first vehicle will charge itself for 30 minutes and the second vehicle will charge itself for 20 minutes. When the electric vehicle that will generate driving guidance information arrives one hour later, it can be expected that the first vehicle needs to charge itself for an additional 10 minutes in the state where it has already charged itself for 20 minutes, and the waiting second vehicle needs to charge itself for an additional 20 minutes thereafter. Therefore, the arriving electric vehicle will wait for 30 minutes after arrival for charging and then charge itself for 30 minutes, so that it will spend a total of one hour at the charging station in the area.

[0098] When the time required to pass through another charging station in the nearby area is shorter than one hour, it may be desirable to provide route guidance so that the vehicle can charge itself in another area and then leave the area.

[0099] In this way, during the generation process of driving guidance information, candidate routes available for driving to the destination are derived, multiple areas that can be passed through are analyzed for each candidate route, and the total time required for the candidate route is calculated by adding the predicted charging station waiting time and charging time and the total driving time for charging in each area.

[0100] By comparing the total time required for each candidate route, the candidate route that requires the minimum time can be selected for route guidance included in the driving guidance information, and the output unit 140 can be controlled to output guidance information by using the route guidance.

[0101] In this way, when calculating the accurate charging time and accurate charging waiting time through the demand prediction analysis of each area, compared with simply providing guidance to minimize the driving time, the actual required time can be minimized, making efficient driving possible.

[0102] Figure 2 FIG. is a block diagram showing an internal configuration of a driving information management server according to various exemplary embodiments of the present disclosure.

[0103] The driving information management server 201 according to various exemplary embodiments of the present disclosure may be a server equipped with a central processing unit (CPU) and a memory, and may include a stand-alone server or a cloud. The driving information management server 201 is not limited to a specific configuration as long as the driving information management server 201 can obtain a target remaining battery level by processing information received from the driving information display device 101 via a wired or wireless communication network and transmit the target remaining battery level back to the driving information display device 101 via the communication network.

[0104] The driving information management server 201 according to an embodiment of the present disclosure may process calculations required to generate charging guidance information displayed on the driving information display device 101. Therefore, the process of generating the charging guidance information in the driving information display device 101 may be executed in the driving information management server 201. Therefore, the description of the process of generating the charging guidance information displayed on the driving information display device 101 may be applied to the driving information management server 201 without significant modification, and vice versa.

[0105] The driving information display device 101 may be connected to the driving information management server 201 via a communication network, may transmit destination information and driving-related information input by a driver to the driving information management server 201, and may display guidance information based on driving guidance information received from the driving information management server 201.

[0106] As Figure 2 shown, the driving information management server 201 according to an embodiment of the present disclosure may include a connection establishment unit 210, a supply level information derivation unit 220, a driving guidance information generation unit 230, and a driving guidance information transmission unit 240, and may further include a geographic information database 202 and a charging station information database 203 or be configured to operate in combination with the geographic information database 202 and the charging station information database 203 or any combination thereof. The geographic information database 202 and the charging station information database 203 may be multiple and may include multiple components.

[0107] The connection establishment unit 210 may establish a connection to exchange information with the driving information display devices 101 of multiple electric vehicles. The connection establishment unit 210 may establish a connection with the communication unit 130 of the driving information display device 101 via a wired or wireless communication network and is not limited to a specific type of communication.

[0108] The supply level information derivation unit 220 may derive the supply level information of the charging stations in each of a plurality of regions. The plurality of regions may be set such that the difference in the total road length within each region does not exceed a predetermined reference value. These regions may be set such that the total road lengths of the respective regions are similar to each other, such that the road lengths that an electric vehicle can travel within each region can be as similar to each other as possible, and supply and demand can be compared more accurately between these regions.

[0109] In order to set regions such that the total road lengths of the respective regions are similar to each other, map information and road information are required. For this purpose, the map information of the overall map and the road information on the map may be stored in the geographic information database 202, and the map may be divided into regions by using the stored map information and road information.

[0110] Various algorithms may be used to set regions such that the respective regions have similar total road lengths. The present disclosure need not be limited to a specific method. The respective regions may be formed in a rectangular shape, and may be formed by dividing or combining administrative regions. Various other variations are possible in combination with the shape of the regions.

[0111] As long as the regions are set such that the difference in the total road length of each region does not exceed a predetermined reference value, and thus the total road lengths within the respective regions are similar to each other, for example, variations including various region setting methods and various region shapes will also fall within the scope of the present disclosure.

[0112] The supply level of a charging station may refer to whether the charging station is supplied to be available to the driver of an electric vehicle within each region. Information related to the supply level of the charging station may include information related to the density of the charging stations and information related to the accessibility between the charging stations. The density of the charging stations may indicate how often a driver can encounter a charging station while driving within the region. The density of the charging stations can be obtained by dividing the number of charging stations in the region by the total road length in the region. For example, when the total road length in the region is 1 km and the number of charging stations is 5, the density of the charging stations may be 5 charging stations / km.

[0113] As described above, the regions are set such that the difference in the total road length of the respective regions is minimized, so that the density of the charging stations is actually determined according to the number of charging stations in the interval.

[0114] To store the charging station information for each area, information such as the location of the charging stations in all areas and the charging capabilities can be cumulatively stored in the charging station information database 203, and the stored information can be used to calculate the charging station information. The charging station information database 203 can obtain, process, and store the charging station information from various sources. In addition to the purpose of calculating the density of the charging stations, various types of charging station-related information can be stored for the purpose of providing driving information.

[0115] The information related to the supply level of the charging stations in each area derived by the supply level information derivation unit 220 may include information related to the accessibility between the charging stations derived by calculating the driving time between the charging stations in each area by reflecting the real-time traffic information between the respective charging stations in each area. For example, when there is only one charging station in a specific area, the information related to the supply level of the charging stations in each area can be derived by the supply level information derivation unit 220 and may include information related to the accessibility obtained based on the driving time to reach the charging stations in the nearby areas.

[0116] The fact that there are a high density of charging stations in an area does not guarantee that the driver can easily use the charging stations. For example, during peak hours in the central area of a city with severe traffic congestion, even when there are multiple charging stations in an area, it will inevitably take a lot of time to move when one charging station is in use, and thus it may be necessary or required to move to another charging station. The distance between the charging stations may be short because of the high density of the charging stations, but it may take a lot of time to move between the charging stations, so this is not a situation where the driver can smoothly use many charging stations.

[0117] Therefore, the information related to the supply level of the charging stations can include not only the density of the charging stations but also the accessibility between the charging stations. As described above, the information related to the accessibility between the charging stations can be obtained based on the time taken to move between the charging stations in the area. Based on the real-time traffic information or the traffic condition prediction information when the electric vehicle is expected to enter the area, the time taken to drive between the charging stations can be generated as the information related to the accessibility between the charging stations.

[0118] Even in the same area, the time taken to move between the charging stations will vary according to the time and traffic conditions, such that the information related to the accessibility between the charging stations needs to be continuously updated.

[0119] In this way, the information related to the supply level may include quantitative information indicating information related to the density of charging stations and the accessibility between charging stations. Since each element of the information related to the supply level may have a positive value, the area under discussion is more convenient for drivers to use the charging stations. For example, it can be determined that the supply level is higher because the information related to the density of charging stations has a higher value. In addition, it can be determined that the power supply level is higher when the information related to the accessibility between charging stations has a lower value.

[0120] To determine the supply level by using multiple parameters to determine whether a driver can conveniently use each area, the weight of each of the parameters can be calculated by using various types of regression analysis or artificial intelligence models.

[0121] The driving guidance information generation unit 230 can receive destination information and target remaining battery level information from any one of the multiple electric vehicles through the established connection, and use the received destination information, the received target remaining battery level information, and the information related to the supply level of each area located on the route to the destination among the multiple areas to generate driving guidance information including charging station route guidance.

[0122] Once the information related to the supply level has been calculated for each area constituting the map, the information related to the supply level can be used to generate driving guidance information for driving to the destination. Destination information and target remaining battery level information can be received, and a route can be set based on this information. The destination information and target remaining battery level information can be the information required to generate the driving route of an ordinary electric vehicle.

[0123] The driving guidance information generation unit 230 can first derive multiple candidate routes used to drive from the starting point to the destination. When the electric vehicle drives directly to the destination along each of the derived candidate routes, the expected remaining battery level at the destination can be determined. When this value is lower than the input target remaining battery level, the candidate route can be modified so that the electric vehicle can pass through a charging station along the candidate route for charging and moving.

[0124] The most effective route can be selected from the candidate routes set to pass through the charging station and then provided to the driver. The charging station supply level information of each area calculated previously can be used.

[0125] First, when moving along a candidate route, the supply level information of charging stations in the areas through which the driver passes along each candidate route can be used to select a candidate route where the driver can conveniently charge his or her electric vehicle, because when charging is needed, the supply level information of charging stations in the areas through which the driver passes is high. It can be recommended that when the driver moves along the candidate route, he or she fully charges his or her electric vehicle in an area with a high charging station supply level and then moves again.

[0126] The charging stations to be passed through can be determined by additionally considering various types of information related to the charging stations (such as the charging capacity, charging status, and driver preferences of the charging stations along the route), and the route including the charging stations can be calculated as the final route.

[0127] Compared with the conventional technology that does not consider the supply level, considering the charging station supply level information in the driving guidance information generation unit 230 in this way can maximize the charging convenience of the driver.

[0128] However, it may be desirable for the driving guidance information generation unit 230 to check not only the supply level information but also the demand information. Even when the supply level of charging stations in an area is high enough, when a large number of electric vehicles are crowded in the area for charging, the driver may have to wait a long time to charge.

[0129] For example, even in a case where the area has a high density of charging stations (5 per 1 km of road) and good accessibility between charging stations, when a large number of electric vehicles flock to the area to charge themselves and charge themselves in the area, it is usually more efficient to charge the electric vehicle in another area where the supply level information is not the best due to the low density of charging stations and poor accessibility between charging stations.

[0130] Therefore, the driving guidance information generation unit 230 can calculate the final route by checking the charging demand information as well as the supply level information. The charging demand information may include information related to the number of electric vehicles expected to arrive at each area for charging and the expected charging capacity (capacity) for each vehicle.

[0131] Based on the route information and charging status information of multiple electric vehicles, the charging demand information of each area can be calculated. The time when the electric vehicle for which the driving guidance information will be provided arrives at each area can be predicted, and the number of electric vehicles that will arrive at the area for charging at that time can be predicted. In addition, the charging capacity for which each electric vehicle will be charged in that area can be predicted.

[0132] Since the driving information management server 201 can be connected to the driving information display devices 101 of multiple electric vehicles and provide driving guidance information, it is possible to check the destination information, charging station information, charging target information of the charging stations, etc. of multiple electric vehicles. Therefore, based on this information, demand information related to the number of electric vehicles expected to arrive in each area and charge themselves within a specific time span and the capacity to be charged by each electric vehicle can be derived.

[0133] The driving guidance information generation unit 230 can generate a charging station route guidance by considering the estimated charging time information of each area calculated based on the estimated charging waiting time information of each area and the charging capacity information of the charging stations in each area calculated based on the charging demand information of each area.

[0134] The charging station information of each area stored in the charging station information database 203 can include various types of information related to one or more charging stations, such as the location and charging speed of the charging stations, etc. Therefore, the time taken for an electric vehicle to arrive and charge itself with the required charging capacity in each area can be calculated.

[0135] Therefore, the driving guidance information generation unit 230 can calculate the time spent waiting for charging due to the charging of earlier-arrived vehicles and the time taken for the electric vehicle providing the driving guidance information to complete charging when it arrives at each area.

[0136] When the charging waiting time and charging time are calculated in this way, the total time is determined by adding the calculated time to the total driving time on the candidate route. By calculating the total time required for each of the multiple candidate routes and selecting the route with the shortest required total time, a driving path guidance considering the actual required time (including the charging waiting time and charging time at the charging station) can be provided. The optimal driving guidance information can be generated by using both the above supply level information and charging demand information.

[0137] The supply level information and the charging demand information can be combined in various forms. For example, by using the required total time and supply level information (the density of charging stations and the accessibility between charging stations) derived from the charging demand information as parameters, the data of each driver's itinerary can be accumulated. An artificial intelligence model configured to derive the preferred route of each driver can be generated by using the accumulated data as training data, and the artificial intelligence model can be used to select the final route.

[0138] As another method, a statistical model or an artificial intelligence model can be generated, which allows calculating the required total time for generating the required total time using the charging demand information by receiving the supply level information and information such as the number of arriving vehicles and the charging capacity. The supply level information can be utilized to calculate the required total time. In the case of a high supply level, even when there is the same demand, the actual required time can be calculated as a lower value. Thus, in this way, the required total time is accurately predicted, and the final route is selected from multiple candidate routes based on the required total time.

[0139] As described above, by using the supply level information and the demand information alone or simultaneously, various modifications can be applied to derive the best route for the driver.

[0140] The driving guidance information transmitting unit 240 can transmit the generated driving guidance information to the electric vehicle. The communication unit 130 of the driving information display device 101 of the electric vehicle can transmit the transmitted driving guidance information to the processor 110, and the processor 110 can control the output unit 140 to output a guidance screen corresponding to the driving guidance information.

[0141] Figure 3 It is a view showing an example in which a map according to various exemplary embodiments of the present disclosure is divided into multiple regions to generate route guidance information provided by the driving information display device.

[0142] As described above, in the embodiments of the present disclosure, guidance on the best route is provided by analyzing the demand and supply information of each region. For this purpose, it is important to effectively set the regions.

[0143] When a method of setting regions into equal areas in a simple grid form can be used, urban areas with dense roads and mountainous or rural areas with few roads can be divided into regions using the same criteria, making it difficult to compare the supply and demand between the two regions. Therefore, in various exemplary embodiments of the present disclosure, the map can be divided into multiple regions such that the total road length within each region is set to a similar value. Additionally, it is preferable to divide the map into multiple regions in such a way that the total road length within each region is set to the same value, but it is actually difficult to divide the map in this way. Therefore, it is possible to ensure that the difference in the total road length of each region does not exceed a predetermined reference value so that the total road length of each region is as similar as possible.

[0144] As shown in the figure, the areas of region A 301 and region B 302 can be different from each other. On the other hand, region B 302 is an urban area with many roads, and region A 301 is a suburban area with sparse roads. Therefore, the total road lengths of region A 301 and region B 302 are set to approximately the same value.

[0145] Therefore, the supply and demand in each area can be evaluated based on the total road length using the same criteria. Thus, the best driving route can be selected, and the driver can be provided with guidance on the best driving route.

[0146] Various algorithms can be used to set the areas such that the total road lengths are similar to each other in this way. The simplest way may be to continue dividing the area in half based on the total road length. When the area is alternately divided into two halves with similar total road lengths along the X-axis and Y-axis, multiple areas with similar total road lengths can be generated.

[0147] The total road length in each area can be set to an appropriate size to analyze supply and demand. When each area is set too large, it may be difficult to accurately analyze the demand and supply at the area level. On the contrary, when the individual areas are too small, the amount of computation and data to be processed for each area will increase, making it difficult to perform efficient processing. Therefore, the size of each area can be determined from an operational perspective.

[0148] Figure 4 It is a diagram showing an example of calculating the supply level of each area according to various exemplary embodiments of the present disclosure to generate route guidance information provided by a driving information display device.

[0149] This figure is for checking Figure 3 An enlarged view of each area for checking the supply level information of the shown area A 301 and area B 302.

[0150] As described above, the supply level information of each area may include information related to the density of charging stations and information related to the accessibility between charging stations. The density of charging stations is obtained by dividing the number of charging stations in the area by the total road length in the area. In the drawing, as described above, area A 301 and area B 302 may be set such that their total road lengths are similar to each other. Therefore, the density of charging stations in each area is determined according to the number of charging stations in the area.

[0151] For example, when the total road length of each of area A 301 and area B 302 is set to 3 km, the density of charging stations in each of area A 301 and area B 302 is 3 / 3 km = 1 / km. Thus, although there are differences in the sizes of the areas, the density of charging stations in the two areas is determined to be the same.

[0152] Figure 5 It is a diagram showing an example of calculating information related to the accessibility of each area according to various exemplary embodiments of the present disclosure to generate route guidance information provided by a driving information display device.

[0153] This figure is an enlarged view of each area for checking the supply level information of area A 301 and area B 302 shown. Figure 3 In the figure, for example, the red road color can indicate that the corresponding road is in a congested traffic state, the yellow road color can indicate that the corresponding road is in a delayed traffic state, and the green road color can indicate that the corresponding road is in a smooth traffic state.

[0154] As previously discussed in connection with

[0155] As discussed previously in connection with Figure 4 Area A 301 and area B 302 have the same charging station density. However, as shown in the figure, in area A 301, the distance between charging stations is long, and the roads between charging stations are severely congested, resulting in a long time required to move between charging stations. In contrast, in area B 302, the charging stations are concentrated, and there is no traffic congestion on the roads between charging stations, enabling electric vehicles to move quickly between charging stations.

[0156] In other words, in area B 302, when it is difficult to charge an electric vehicle at the arriving charging station or the waiting time is long, the electric vehicle can be moved to another nearby charging station and charged quickly. In area A 301, it takes a long time to move to another charging station, resulting in a longer charging time for electric vehicles in this area.

[0157] Therefore, even though area A 301 and area B 302 have the same charging station density, it can be determined that area B has a higher charging station supply level. This is calculated as information related to the accessibility between charging stations and is included in the supply level information.

[0158] The information related to the accessibility between charging stations is obtained based on the expected time to drive to each charging station in the area. When there are multiple charging stations, it can be calculated as the average time spent moving from each charging station to a nearby charging station.

[0159] When there is no charging station in the area, the supply level will be set to the lowest value. When there is only one charging station in the area, the accessibility between charging stations is set based on the driving time to the nearest charging station in the nearby area, resulting in significantly poor charging station supply level information.

[0160] Figure 6 is a diagram showing an example of selecting the best route from candidate routes provided by a driving information display device according to various exemplary embodiments of the present disclosure.

[0161] As shown in the figure, route information provided by the driving information display device 101 is selected from multiple candidate routes.

[0162] In Figure 6 , it may be assumed that the best route is selected from two routes, candidate route A 601 and candidate route B 602. At this time, the travel time of candidate route A 601 is 104 minutes, which is longer than the travel time of candidate route B 602. Thus, in the prior art, since the charging waiting time and charging time of the charging station cannot be predicted, candidate route B 602 is determined to be a more appropriate route and is selected as the final route.

[0163] In contrast, when analyzing the actual charging station supply and demand information of each area using the embodiments of the present disclosure, for candidate route A 601, the charging waiting time is 0 minutes, but for candidate route B 602, the charging waiting time is 30 minutes. Therefore, for candidate route A 601, the total actual driving time required is 144 minutes, and for candidate route B 602, the total actual driving time required is 155 minutes.

[0164] Therefore, the driving information display device 101 of the embodiments of the present disclosure can provide guidance on candidate route A 601 as the final route, and the electric vehicle can actually reach the destination faster along candidate route A 601. This can allow the driver to select the route on which he or she can drive to the destination fastest.

[0165] When selecting the final route, various types of information, such as the driver's personality, charging cost, and other passing points, may be additionally considered, and the total required time can be used as one of the parameters to be considered.

[0166] Figure 7 is a diagram showing the overall flow of a process of generating driving guidance information including route guidance in a driving information display device according to various exemplary embodiments of the present disclosure.

[0167] As Figure 7 shown, when the vehicle enters the destination and requests route guidance, the vehicle can receive various driving-related information based on the input data, such as information related to the starting point and destination, electric vehicle information per area, driving distance information, and remaining battery level information.

[0168] An electric vehicle charging characteristic (EV characteristic) weight model can be generated by constructing the above various types of information into a statistical or artificial intelligence model. Through this, there are derived EV characteristic values for determining the charging station, charging time, and charging amount according to the situation.

[0169] As described above, it is possible to determine the supply level information and the charging demand information of the charging station cluster (area). As described above, it is possible to analyze the supply information and the charging demand information for each area set such that their total road lengths are similar to each other.

[0170] In the route design module (EV route planner), the final route is calculated by using the supply level and charging demand information for each charging station cluster (area) and the EV characteristic weight value.

[0171] The route design module can calculate the charging demand and supply level information for each area through which the candidate route passes, and calculate the charging station waiting time and charging time for each area based on the charging demand and supply level information.

[0172] The total required time can be calculated by adding the charging station waiting time and charging time calculated for each candidate route to the total driving time, and the candidate route that minimizes the total required time can be selected from all candidate routes as the final route. Therefore, in practice, a route that allows a driver to reach the destination fastest within the shortest time including the time spent on performing the overall charging process can be provided.

[0173] Figure 8 It is a flowchart showing the process of a driving information display method according to various exemplary embodiments of the present disclosure.

[0174] In the present exemplary embodiment, the driving information display method according to an embodiment of the present disclosure may be a method executed by a driving information display device 101 and a driving information management server 201 including a processor 110 and a storage unit 120. The components described above in connection with the operations of the driving information display device 101 and the driving information management server 201 can be applied to the driving information display method without significant modification. Therefore, by applying the above description of the driving information display device 101 and the driving information management server 201, those skilled in the art can even implement components not specifically described in connection with the following driving information display method.

[0175] In the supply level information derivation step S801, it is possible to derive the supply level information of the charging stations in each of the plurality of areas.

[0176] A plurality of areas may be set such that the difference in the total road length within each area does not exceed a predetermined reference value. The information related to the supply level of the charging stations in each area may include information related to the density of the charging stations obtained by dividing the number of charging stations existing in the area by the total road length of the area.

[0177] Information related to the supply levels of charging stations in each area exported in the supply information export step S801 may include information related to the accessibility between charging stations derived by reflecting real-time traffic information to calculate the driving time between individual charging stations within each area.

[0178] In the supply information export step S801, when there is only one charging station in an area, information related to accessibility may be derived based on the driving time taken to move to a charging station in a nearby area.

[0179] In the driving guidance information generation step S802, destination information and target remaining battery level information may be received from any one of a plurality of electric vehicles via the established connection, and driving guidance information including charging station route guidance may be generated using the received destination information, the received target remaining battery level information, and information related to the supply levels of each area located on the route to the destination among a plurality of areas.

[0180] In the driving guidance information generation step S802, a charging station route guidance may be generated by considering the estimated charging waiting time information for each area calculated based on area-based charging demand information and the estimated charging time information for the area calculated based on the charging capacity information of area-based charging stations. The charging demand information for each area may be derived based on the route information and charging status information of a plurality of electric vehicles.

[0181] In the guidance information output step S803, control may be performed to output guidance information corresponding to the generated driving guidance information to the screen. In the guidance information output step S803, the guidance information may be directly displayed on the display screen. A control signal may be sent such that a separate device displays the guidance information on the display screen.

[0182] Embodiments of the present disclosure may achieve the advantage of providing guidance on the optimal driving route by considering the charging waiting time and charging time of electric vehicles.

[0183] Embodiments of the present disclosure may achieve the advantage of accurately predicting the charging waiting time and charging time by analyzing the demand and supply of charging stations.

[0184] Embodiments of the present disclosure may achieve the advantage of accurately predicting the charging waiting time and charging time for each area by using geographical information to analyze the status of one or more charging stations in each area.

[0185] Embodiments of the present disclosure may achieve the following advantage: when the waiting time at a charging station is long, by additionally considering the time required to move to another charging station to predict the total time required, route guidance aimed at reaching the destination as quickly as possible is provided.

[0186] Embodiments of the present disclosure can achieve the advantage of promoting supply and demand analysis by using geographical information to set areas and aggregate charging stations.

[0187] In addition, throughout this specification, various advantages that can be directly or indirectly understood by those skilled in the art can be provided.

[0188] Although the present disclosure has been described with reference to exemplary embodiments, however, without departing from the spirit and scope of the present disclosure described in the appended claims, those skilled in the art can make various modifications and changes to the embodiments of the present disclosure.

[0189] The control device may be at least one microprocessor operated by a predetermined program, and the predetermined program may include a series of commands for executing the methods included in the above various exemplary embodiments of the present disclosure.

[0190] In various exemplary embodiments of the present disclosure, each of the above operations may be performed by the control device, and the control device may be configured by a plurality of control devices or an integrated single control device.

[0191] In various exemplary embodiments of the present disclosure, the memory and the processor may be provided as one chip or as separate chips.

[0192] In various exemplary embodiments of the present disclosure, the scope of the present disclosure may include software or machine-executable commands (e.g., operating systems, applications, firmware, programs, etc.) for enabling the operations of the methods according to different embodiments to be executed on a device or a computer, and non-transitory computer-readable media including such software or commands stored thereon and executable on the device or the computer.

[0193] In various exemplary embodiments of the present disclosure, the control device may be implemented in the form of hardware or software, or may be implemented in a combination of hardware and software.

[0194] Terms such as "unit" and "module" included in the specification may refer to a unit for processing at least one function or operation, which may be implemented by hardware, software, or a combination thereof.

[0195] In an exemplary embodiment of the present disclosure, a vehicle may be referred to based on the concept including various transportation systems. In some cases, a vehicle may be interpreted as based on not only various land transportation means (such as cars, motorcycles, trucks, and buses) traveling on roads but also various transportation systems such as airplanes, drones, and ships.

[0196] For ease of interpretation and accurate definition in the appended claims, the terms "upper", "lower", "inner", "outer", "upward", "downward", "upward", "downward", "front", "rear", "rear", "inner", "outer", "inward", "outward", "interior", "exterior", "interior", "exterior", "forward", and "backward" may be used to describe the features of the exemplary embodiments with reference to the positions of such features as shown in the accompanying drawings. It should be further understood that the term "connected" or its derivatives may refer to direct connection and indirect connection.

[0197] The term "and / or" may include combinations of multiple related listed items or any of the multiple related listed items. For example, "A and / or B" may include all three cases, such as "A", "B", and "A and B".

[0198] In this specification, unless otherwise stated, singular expressions may include plural expressions, unless the context clearly indicates otherwise.

[0199] In the exemplary embodiments of the present disclosure, "at least one of A and B" may refer to "at least one of A or B" or "at least one of a combination of at least one of A and B". In addition, "one or more of A and B" may refer to "one or more of A or B" or "one or more of a combination of one or more of A and B".

[0200] In the exemplary embodiments of the present disclosure, it should be understood that terms such as "comprising" or "having" are intended to specify the presence of the features, quantities, steps, operations, elements, components, or combinations thereof described in the specification, and do not preclude the possibility of adding or the presence of one or more other features, quantities, steps, operations, elements, components, or combinations thereof.

[0201] For purposes of illustration and description, the foregoing description of specific exemplary embodiments of the present disclosure has been presented. They are not intended to be exhaustive or to limit the present disclosure to the precise forms disclosed, and obviously many modifications and variations are possible in light of the above teachings. The exemplary embodiments were chosen and described to explain some principles of the present disclosure and its practical applications, so that others skilled in the art can make and utilize the various exemplary embodiments of the present disclosure and their various alternatives and modifications. The scope of the present disclosure is intended to be defined by the appended claims and their equivalents.

Claims

1. A driving information display device, comprising: one or more processors; as well as A storage medium configured to store road information and algorithms executed by the one or more processors, and to store computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to: receiving driving guidance information and vehicle location information; and Execute control to output a guidance screen corresponding to the driving guidance information; wherein the driving guidance information includes route information, and the route information includes a charging station route guidance generated based on destination information, target remaining power information, and supply level information of one or more charging stations in each area located on a route to the destination in multiple areas.

2. The driving information display device according to claim 1, in, The plurality of areas are set so that a difference in total road length within each area does not exceed a predetermined reference value; as well as The supply level information of the charging stations in each area includes charging station density information obtained by dividing the number of the charging stations existing in each area by the total road length in each area.

3. The driving information display device according to claim 2, wherein: The supply level information of the charging stations in each area includes first accessibility information related to accessibility between charging stations obtained by calculating driving times between respective charging stations in each area reflecting real-time traffic information.

4. The driving information display device according to claim 3, wherein: The supply level information of the charging station of each area includes second accessibility information related to accessibility obtained based on a driving time taken to move to a nearby charging station in a nearby area in response to only one charging station existing in each area.

5. The driving information display device according to claim 1, wherein: The charging station route guidance is generated by considering estimated charging waiting time information of each area calculated based on charging demand information of each area and estimated charging time information of each area calculated based on charging capability information of the charging station of each area.

6. The driving information display device according to claim 5, wherein: The charging demand information of each area is derived based on a plurality of route information and a plurality of charging status information of a plurality of electric vehicles.

7. A driving information management server, comprising: one or more processors; as well as A storage medium configured to store computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to: establishing a connection for exchanging information with driving information display devices of a plurality of electric vehicles; deriving supply level information for a plurality of charging stations in each of a plurality of regions; receiving destination information and target remaining power information from a designated electric vehicle among the plurality of electric vehicles through the established connection, and generating driving guidance information including charging station route guidance using the received destination information, the received target remaining power information, and the supply level information of each of the plurality of areas located on a route of the designated electric vehicle to the destination among the plurality of areas; as well as The generated driving guidance information is sent to the designated electric vehicle.

8. The driving information management server according to claim 7, in, The plurality of areas are arranged so that a difference in total road lengths within each of the plurality of areas does not exceed a predetermined reference value; as well as The supply level information of the charging stations in each of the plurality of areas includes charging station density information obtained by dividing the number of the charging stations existing in each of the plurality of areas by the total road length in each of the plurality of areas.

9. The driving information management server according to claim 8, wherein: The supply level information of the charging stations in each of the plurality of areas includes first accessibility information related to accessibility between charging stations obtained by calculating driving times between respective charging stations in each of the plurality of areas reflecting real-time traffic information.

10. The driving information management server according to claim 9, wherein: The supply level information of the charging station in each of the plurality of areas includes second accessibility information related to accessibility obtained based on a driving time taken to move to a nearby charging station in a nearby area when only one charging station exists in each of the plurality of areas.

11. The driving information management server according to claim 7, wherein: The computer-readable instructions, when executed by the one or more processors, further cause the one or more processors to generate the charging station route guidance by considering estimated charging waiting time information for each of the multiple areas calculated based on charging demand information for each of the multiple areas and estimated charging time information for each of the multiple areas calculated based on charging capability information of the charging station for each of the multiple areas.

12. The driving information management server according to claim 11, wherein: The charging demand information of each of the plurality of areas is derived based on a plurality of route information and a plurality of charging status information of the plurality of electric vehicles.

13. A driving information display method, the driving information display method comprising: deriving supply level information for charging stations in each of a plurality of regions; receiving destination information and target remaining power information from a designated electric vehicle among a plurality of electric vehicles, and generating driving guidance information including charging station route guidance using the received destination information, the received target remaining power information, and the supply level information of each area among the plurality of areas located on a route of the designated electric vehicle to the destination; as well as The generated driving guidance information is transmitted to the designated electric vehicle.

14. The driving information display method according to claim 13, further comprising: The plurality of areas are arranged so that a difference in total road length within each area does not exceed a predetermined reference value; obtaining charging station density information by dividing the number of charging stations existing in each area by the total road length in each area; and The supply level information of the charging stations in each area is obtained by including the charging station density information.

15. The driving information display method according to claim 14, wherein: The supply level information of the charging stations in each area includes first accessibility information related to accessibility between charging stations obtained by calculating first driving times between respective charging stations in each area reflecting real-time traffic information.

16. The driving information display method according to claim 15, wherein: The supply level information of the charging station in each area includes second accessibility information related to accessibility obtained based on a second driving time taken to move to a nearby charging station in a nearby area when there is only one charging station in each area.

17. The driving information display method according to claim 13, wherein: The generation of the driving guide information includes generating the charging station route guide by considering estimated charging waiting time information of each area calculated based on charging demand information of each area and estimated charging time information of each area calculated based on charging capacity information of the charging station of each area.

18. The driving information display method according to claim 17, wherein: The charging demand information of each area is derived based on a plurality of route information and a plurality of charging status information of the plurality of electric vehicles.

19. The driving information display method according to claim 13, further comprising: In response to a driver specifying a desired minimum charging speed of a charger, a charging station density for obtaining charging station density information is calculated including only the charging stations having chargers capable of providing the desired minimum charging speed. 20 . A non-transitory computer-readable storage medium storing a program, which, when executed by a processor, causes the processor to execute the driving information display method according to claim 13 .

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