Navigation method, electronic equipment and vehicle

Abstract

The embodiment of the invention provides a navigation method, electronic equipment and a vehicle, and relates to the technical field of navigation. The method comprises the following steps: acquiring electric quantity information and position information of a vehicle; generating elements of an energy channel according to the electric quantity information and the position information, wherein the energy channel is used for visually displaying a reachable area range and an unreachable area range of the vehicle; rendering the energy channel in the map according to the elements of the energy channel; wherein the generation of the elements of the energy channel according to the electric quantity information and the position information comprises the following steps: correcting the energy consumption parameter according to the obtained road slope data and / or congestion state data of the current road to obtain the corrected energy consumption parameter; and generating elements of the energy channel according to the corrected energy consumption parameters, the electric quantity information and the position information. By rendering the energy channel, the reachable area range and the unreachable area range can be intuitively understood without converting the residual electric quantity or the geographical range covered by the electric quantity residual mileage by the user, and the effect of relieving the electric quantity anxiety of the user is achieved.

Description

Technical Field

[0001] This application relates to the field of navigation technology, and more particularly to a navigation method, electronic device, and vehicle. Background Technology

[0002] With the increasing popularity of new energy vehicles, users' demands for range and charging convenience are growing. However, new energy vehicles often face the problem of "range anxiety" during actual driving.

[0003] For example, when a vehicle's battery is low, users find it difficult to intuitively determine whether the current charge is sufficient to reach their destination or the nearest charging station, leading to increased psychological stress and even dangerous driving behaviors such as sudden acceleration and frequent checks of the dashboard. This is especially true in complex road conditions such as mountainous or congested areas, or when driving in unfamiliar environments, where users have a lower perception of remaining battery power and reachable areas, further amplifying battery anxiety.

[0004] Current navigation methods, when displaying remaining battery power, can only show the remaining mileage that the remaining battery power can support. This information is relatively limited, increasing the difficulty for users to understand distances and failing to alleviate their battery anxiety. Therefore, there is an urgent need for a more comprehensive navigation method to reduce the difficulty for users to understand distances and effectively alleviate their battery anxiety. Summary of the Invention

[0005] This application provides a navigation method, electronic device, and vehicle that provide richer information during vehicle navigation, enabling users to intuitively understand the range that the vehicle can and cannot reach with its current battery level, thereby reducing users' battery anxiety.

[0006] In a first aspect, embodiments of this application provide a navigation method, the method comprising:

[0007] Obtain vehicle battery level and location information;

[0008] The elements of the energy channel are generated based on the battery level and location information. The energy channel is used to visualize the accessible and inaccessible areas of the vehicle.

[0009] Render the energy channels on the map based on their elements;

[0010] The elements for generating energy channels based on power and location information include:

[0011] Based on the obtained current road slope data and / or congestion status data, the energy consumption parameters are corrected to obtain the corrected energy consumption parameters;

[0012] The elements of the energy channel are generated based on the corrected energy consumption parameters, power information, and location information.

[0013] In one possible implementation, rendering energy channels in the map includes:

[0014] The reachable and unreachable areas in the energy channel are rendered using different colors.

[0015] In one possible implementation, the reachable area range includes an energy-saving reachable area range and an energy-free reachable area range. The energy-saving reachable area range includes the area range corresponding to the vehicle after energy-saving control is implemented, and the energy-free reachable area range includes the area range corresponding to the vehicle without energy-saving settings.

[0016] In one possible implementation, after rendering the energy channels in the map, the method further includes:

[0017] Based on the preset energy consumption model and terrain data, the elements of the energy channel are updated to obtain the updated elements;

[0018] Based on the updated features, adjust the coverage areas of reachable and inaccessible areas, and update the rendering energy channels;

[0019] And / or,

[0020] After obtaining the vehicle's battery and location information, the method also includes:

[0021] Acquire user behavior data, which is used to characterize user actions related to vehicle battery level during driving;

[0022] Anxiety index is determined based on user behavior data and battery information. The anxiety index is used to characterize the user's level of anxiety about the vehicle's battery level.

[0023] Switch map display modes based on anxiety level.

[0024] In one possible implementation, the display mode includes an emergency mode, which switches the map display mode according to the anxiety index, including:

[0025] When switching the map to emergency mode based on the anxiety index, receive voice commands and / or gesture commands;

[0026] Map operation and control are performed based on voice commands and / or gesture commands.

[0027] In one possible implementation, after rendering the energy channels in the map, the method further includes:

[0028] Based on the acquired charging point information, multiple charging plans are generated;

[0029] Perform timeline animation simulations of multiple charging schemes;

[0030] Display timeline animations of multiple options on a split-screen display on the map.

[0031] In one possible implementation, after generating multiple charging schemes, the method further includes:

[0032] Based on the anxiety index, the recommended priority of multiple charging options is determined;

[0033] And / or, update the route planning for multiple charging options based on terrain data.

[0034] In one possible implementation, after displaying timeline animations of multiple scenarios in a split-screen format on the map, the method further includes:

[0035] Update the navigation path on the map based on the user's chosen charging option among multiple charging options;

[0036] The system monitors vehicle battery levels in real time and periodically updates and renders the energy channels on the map.

[0037] Secondly, embodiments of this application provide a navigation device, the device comprising:

[0038] The acquisition module is used to acquire the vehicle's battery level and location information;

[0039] The generation module is used to generate elements of the energy channel based on power and location information. The energy channel is used to visually display the accessible and inaccessible areas of the vehicle.

[0040] The rendering module is used to render energy channels on the map based on the elements of the energy channels;

[0041] The generation module is specifically used for:

[0042] Based on the obtained current road slope data and / or congestion status data, the energy consumption parameters are corrected to obtain the corrected energy consumption parameters;

[0043] The elements of the energy channel are generated based on the corrected energy consumption parameters, power information, and location information.

[0044] In one possible implementation, the rendering module is specifically used for:

[0045] The reachable and unreachable areas in the energy channel are rendered using different colors.

[0046] In one possible implementation, the reachable area range includes an energy-saving reachable area range and an energy-free reachable area range. The energy-saving reachable area range includes the area range corresponding to the vehicle after energy-saving control is implemented, and the energy-free reachable area range includes the area range corresponding to the vehicle without energy-saving settings.

[0047] In one possible implementation, the apparatus further includes an update module, which is used to:

[0048] Based on the preset energy consumption model and terrain data, the elements of the energy channel are updated to obtain the updated elements;

[0049] Based on the updated features, adjust the coverage areas of reachable and inaccessible areas, and update the rendering energy channels;

[0050] And / or,

[0051] The acquisition module is also used for:

[0052] Acquire user behavior data, which is used to characterize user actions related to vehicle battery level during driving;

[0053] Anxiety index is determined based on user behavior data and battery information. The anxiety index is used to characterize the user's level of anxiety about the vehicle's battery level.

[0054] Switch map display modes based on anxiety level.

[0055] In one possible implementation, the display mode includes an emergency mode, and the acquisition module is specifically used for:

[0056] When switching the map to emergency mode based on the anxiety index, receive voice commands and / or gesture commands;

[0057] Map operation and control are performed based on voice commands and / or gesture commands.

[0058] In one possible implementation, the device further includes a display module, which is used for:

[0059] Based on the acquired charging point information, multiple charging plans are generated;

[0060] Perform timeline animation simulations of multiple charging schemes;

[0061] Display timeline animations of multiple options on a split-screen display on the map.

[0062] In one possible implementation, the display module is also used for:

[0063] Based on the anxiety index, the recommended priority of multiple charging options is determined;

[0064] And / or, update the route planning for multiple charging options based on terrain data.

[0065] In one possible implementation, the display module is also used for:

[0066] Update the navigation path on the map based on the user's chosen charging option among multiple charging options;

[0067] The system monitors vehicle battery levels in real time and periodically updates and renders the energy channels on the map.

[0068] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0069] Fourthly, embodiments of this application provide a vehicle that includes electronic equipment as described in the third aspect.

[0070] Fifthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0071] Sixthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0072] The navigation method, electronic device, and vehicle provided in this application combine vehicle battery information with location information to generate elements of an energy channel and render the energy channel on a map. This solves the problem in existing technologies where users find it difficult to intuitively determine the reachable and inaccessible areas corresponding to the remaining battery level. This method increases the richness and intuitiveness of navigation information. By rendering the energy channel, users can intuitively understand the specific situation of reachable and inaccessible areas without having to calculate the remaining battery level or the geographical area covered by the remaining range. This helps users make correct driving decisions and alleviates battery anxiety. Furthermore, by combining road gradient data and / or congestion data to correct energy consumption parameters, the accuracy of battery prediction under complex road conditions is improved. This enhances the reliability of energy channel prediction in mountainous or congested road sections, allowing users to more accurately perceive energy channels and plan routes more rationally, thus improving the user experience. Attached Figure Description

[0073] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0074] Figure 1 A flowchart illustrating the navigation method provided in an embodiment of this application;

[0075] Figure 2 A schematic diagram of an energy channel provided for an embodiment of this application;

[0076] Figure 3 A flowchart illustrating the navigation method provided in the embodiments of this application;

[0077] Figure 4 This is a schematic diagram of the structure of the navigation device provided in the embodiments of this application;

[0078] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0079] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0080] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0081] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of the relevant data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, have taken necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation access points for users to choose to authorize or refuse.

[0082] Furthermore, the technical solution involved in this application, which involves big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.) and the use of artificial intelligence technology for automated decision-making, and makes decisions that have a significant impact on personal rights based on the results of automated decision-making, provides users with corresponding operation entry points for users to choose to agree to or reject the results of automated decision-making; if the user chooses to reject, the process will proceed to the expert decision-making process.

[0083] The following is an explanation of some terms used in the embodiments of this application:

[0084] Augmented Reality (AR): A technology used to overlay virtual information onto real-world scenes.

[0085] Battery State of Charge (SOC): Indicates the remaining percentage of energy in an energy storage device.

[0086] Energy Corridor: A visual navigation method, such as in AR mode, which uses different colors to distinguish between accessible and / or inaccessible areas of a vehicle.

[0087] Anxiety Index: This index represents the level of anxiety based on factors such as battery level, user behavior, and environment. For example, the Anxiety Index ranges from 0 to 100 points, with higher scores indicating higher levels of anxiety and vice versa.

[0088] In this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0089] In the embodiments of this application, the use of terms such as "first" and "second" is to distinguish between identical or similar items that have essentially the same function and effect. For example, "first electronic device" and "second electronic device" are merely used to distinguish different electronic devices and do not limit their order of execution. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different.

[0090] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following associated objects have an "or" relationship.

[0091] In practical applications, existing new energy vehicle navigation systems generally use a traditional map overlaid with remaining mileage figures. Their core functions include basic navigation, charging station marking, and battery level monitoring. Existing navigation systems typically present information as a static map overlaid with remaining mileage figures, failing to dynamically reflect the user's current battery anxiety, such as frequent battery checks or route switching. Furthermore, they lack decision support for low-battery scenarios, such as comparing multiple charging options.

[0092] Therefore, there is an urgent need for a navigation method that can combine user behavior, vehicle status and environmental factors, intuitively present the reachable area through augmented reality technology, dynamically adjust the interface complexity, provide multiple scenario simulations and terrain perception prediction, so as to alleviate users' battery anxiety, optimize route planning and improve driving safety.

[0093] In existing technologies, basic navigation provides route planning based on location and displays remaining mileage and estimated arrival time. Charging station marking marks the locations of charging stations on a map, and some vehicle systems provide information such as charging station distance and price. Battery monitoring displays the current battery SOC through the dashboard or a separate interface, and some vehicle systems provide an estimate of remaining mileage, which is mostly calculated based on the vehicle's average energy consumption.

[0094] The existing vehicle navigation systems mentioned above have many shortcomings, including unintuitive information presentation, neglect of user status, lack of decision support, and insufficient prediction accuracy.

[0095] For example, the lack of intuitive information presentation is mainly reflected in the fact that navigation only displays the remaining mileage as a number, such as simply showing "remaining mileage xx kilometers". This makes it difficult for users to quickly determine "where they can go and where they can't go", especially in areas with a high concentration of charging stations, making it difficult to quickly identify the best option.

[0096] Ignoring user status is mainly manifested in the following ways: the navigation interface has a fixed complexity, always displaying the same complex interface regardless of the battery level. The types of information in these interfaces remain unchanged and do not change dynamically. When the battery is low, information overload can actually exacerbate user anxiety and tension.

[0097] The lack of decision support is mainly manifested in the fact that when there are multiple charging options (such as fast charging / slow charging / energy-saving direct charging), only distance and price are provided. Users need to weigh multiple factors such as time, cost, and risk of insufficient power, which makes it difficult for users to make decisions and increases anxiety.

[0098] The lack of prediction accuracy is mainly reflected in the fact that energy consumption calculation is based on the average energy consumption on flat roads, without fully considering actual road conditions such as road slope, traffic congestion, and weather. This results in a large error in the calculation of the remaining mileage (for example, around ±15%), which will reduce users' trust in navigation and affect the user experience.

[0099] While existing technologies can achieve basic navigation functions, they have many obvious shortcomings in dynamically adapting to user status, visualizing reachability, comparing multiple solutions, and making accurate predictions, making it difficult to meet users' deeper needs regarding the battery anxiety of new energy vehicles.

[0100] In summary, static mileage figures fail to intuitively reflect whether a user's current battery level is sufficient to cover the target area, resulting in unintuitive information presentation. This is especially problematic in areas with dense charging stations, where users struggle to quickly identify the optimal route, increasing the error rate in route planning. Furthermore, if user status is not dynamically adapted and interface complexity remains constant, information overload during low battery periods can exacerbate anxiety, highlighting the lack of a dynamic adjustment mechanism for user behavior (such as frequent battery checks).

[0101] Charging option comparisons only provide a single dimension (such as distance or price), offering insufficient support for navigation decision-making. Users must weigh multiple factors such as time, cost, and risk themselves, resulting in low decision-making efficiency and a high likelihood of choosing a suboptimal option. Furthermore, because energy consumption calculations do not incorporate actual road conditions such as gradients and congestion, significant errors in remaining mileage and large deviations in prediction accuracy occur, gradually reducing user trust in navigation systems.

[0102] These issues are particularly prominent in complex road conditions or emergency low battery scenarios, directly impacting the user's driving experience. Furthermore, if the user's anxiety reaches a certain level, it can also negatively affect driving safety.

[0103] Starting from the root causes of users' battery anxiety, the inventors identified shortcomings in existing technologies in several aspects, including information presentation, user adaptation, decision support, and prediction accuracy. To address these issues, the solutions in this application propose the following technical concepts.

[0104] Dynamic perception and correlation. For example, vehicle battery level, location, and user behavior data (such as battery level check frequency) can be obtained in real time through the Controller Area Network (CAN) bus. Combined with terrain data (slope, congestion) in the cloud, a comprehensive anxiety index can be generated to achieve dynamic correlation between user status and environmental factors.

[0105] AR visualization innovation. For example, by introducing an energy channel, using three-color areas such as green / yellow / red to intuitively display the reachable range supported by the remaining battery power, instead of abstract mileage numbers, it improves the user's spatial cognitive efficiency.

[0106] Adaptive interface settings. For example, automatically switch between three display modes based on anxiety level, such as normal mode, alert mode, and emergency mode. When the battery is low, simplify the interface and provide visual / voice reassurance to avoid information overload that could exacerbate the user's battery anxiety.

[0107] The combination of multi-scenario simulation and terrain perception. For example, split-screen animations can be used to compare the time, cost, and power risks of different charging options, and combined with energy consumption calculations corrected for road slope, the accuracy of predictions can be significantly improved.

[0108] Based on this, the inventors integrated the above-mentioned technical concepts and determined a complete and effective visual navigation solution. Through dynamic data collection, AR visualization, adaptive interface and intelligent decision-making, the systemic relief of battery anxiety in new energy vehicles was achieved.

[0109] In view of this, embodiments of this application provide a navigation method that dynamically senses user behavior, vehicle status, and environmental data, and combines augmented reality technology to construct an adaptive visual navigation method to alleviate battery anxiety and optimize route decisions for new energy vehicle users. Specifically, the method dynamically correlates user anxiety states (such as battery tension and behavioral anxiety) with environmental factors (such as road gradient and traffic congestion), and intuitively presents reachable ranges, charging schemes, and energy consumption predictions through AR visualization (such as energy channels and multi-scheme simulation animations), ultimately achieving a comprehensive goal of adaptive interface, intuitive information, and intelligent decision-making.

[0110] The navigation method provided in this application can be applied to various navigation systems, such as in-vehicle navigation systems for new energy vehicles or application (App) navigation systems for mobile terminals, such as map app navigation systems. The navigation method provided in this application can be applied to various driving scenarios for new energy vehicles, especially for long-distance driving, unfamiliar environments, or emergency low battery scenarios.

[0111] The method in this application embodiment can be implemented by a navigation system including vehicle-side hardware (such as CAN bus, display screen, communication module) and cloud server (storing terrain data, charging station information), or it can be implemented based on electronic devices for data acquisition and data processing.

[0112] For example, based on the navigation system, users can obtain AR navigation information in real time through the in-vehicle display or mobile device. The navigation system reads data such as vehicle battery level (SOC) and location via the CAN bus, and dynamically generates the navigation interface by combining cloud map slope, congestion data, and user behavior (such as the frequency of battery level checks). Under complex road conditions (such as mountainous areas or congested roads) or triggered by user anxiety (such as frequent battery level checks), the navigation system can automatically switch to alert mode or emergency mode, providing a simplified interface display, visual reassurance, and comparison of multiple charging options, thereby reducing user anxiety and improving driving safety.

[0113] The technical solutions of this application will be described in detail below with reference to specific embodiments. The specific embodiments described below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0114] Figure 1 This is a flowchart illustrating the navigation method provided in an embodiment of this application. The executing entity of this method can be an electronic device with corresponding data storage and computing capabilities, such as a vehicle or an in-vehicle controller. The electronic device may include one processor unit, or it can be understood to include multiple processor units. For example, the electronic device may include one processor chip, or it may include multiple processor chips.

[0115] Taking in-vehicle electronic devices as an example, when executing this method, the in-vehicle electronic devices can perform the method through coordinated data processing among processor units such as the Vehicle Control Unit (VCU), Electronic Control Unit (ECU), and Telematics Box (T-BOX). It should be understood that the embodiments of this application do not limit the specific form of the electronic device.

[0116] like Figure 1 As shown, the method includes steps S101, S102 and S103.

[0117] S101, obtains the vehicle's battery level and location information.

[0118] For example, battery information can be understood as data representing the state of charge (SOC) of a vehicle's battery, such as the remaining percentage of charge or the remaining battery capacity. For instance, if the obtained battery information is SOC=20%, it means the vehicle's battery has 20% of its maximum capacity remaining. Location information can be understood as the geographic coordinates of the vehicle's current location. For example, the latitude and longitude coordinates of the vehicle obtained through satellite positioning, such as XX.XX° North latitude and YY.YY° East longitude.

[0119] For example, taking an electronic device including a vehicle controller as an example, when acquiring vehicle battery power information and location information, the VCU can read the vehicle's battery SOC data in real time through the vehicle's onboard CAN bus to obtain vehicle battery power information. The VCU can also acquire the vehicle's geographic coordinate data collected by the satellite positioning module to obtain location information. The satellite positioning module is a functional module that implements satellite positioning, and may include, for example, a Global Positioning System (GPS) module and / or a BeiDou Navigation Satellite System (BDS) module, etc.

[0120] S102, generate elements of the energy channel based on battery level information and location information. The energy channel is used to visually display the accessible and inaccessible areas of the vehicle. The elements for generating the energy channel based on battery level information and location information include: correcting energy consumption parameters based on acquired road slope data and / or congestion status data to obtain corrected energy consumption parameters; and generating the elements of the energy channel based on the corrected energy consumption parameters, battery level information, and location information.

[0121] For example, the energy channel can be understood as a visual navigation method used to visually display the vehicle's reachable and inaccessible areas. The reachable area can be understood as the geographical range that the vehicle's remaining battery power can support the vehicle's travel to; the inaccessible area can be understood as the geographical range that the vehicle's remaining battery power is insufficient to support the vehicle's travel to.

[0122] The elements of an energy channel can be understood as the components required to demonstrate the energy channel, such as geographical location parameters including the reachable and inaccessible areas, coverage range, coverage area, and distance values ​​between vehicles and the boundaries of the area.

[0123] When generating the elements of an energy channel based on battery and location information, the maximum achievable distance of the vehicle can be calculated using the battery's state of charge and vehicle energy consumption. This maximum distance can be considered one of the elements for generating the energy channel. Based on this maximum distance, the specific coordinates of the reachable area and the inaccessible area can also be determined on the navigation map.

[0124] These coordinate values ​​can discretely represent multiple reachable and multiple inaccessible locations. Connecting the reachable locations forms a closed reachable region. Connecting the inaccessible locations also forms a closed inaccessible region. These coordinate values ​​can form one or more coordinate sets, each representing a specific coordinate within the reachable and inaccessible regions. These coordinate values ​​or coordinate sets can also be understood as elements that generate energy channels.

[0125] For example, if the dynamic relationship between road slope and vehicle speed is not considered when generating the elements of the energy channel, the remaining mileage and other elements in mountainous or complex road conditions may have large errors, affecting the accuracy of the energy channel. Therefore, the method in this application embodiment generates the energy channel by combining the current road terrain data. A high-resolution digital elevation model (HR-DEM) and a road slope layer can be used, and the energy consumption coefficient can be dynamically corrected by combining real-time vehicle speed data. This can improve the accuracy of the energy channel elements, thereby enhancing the overall accuracy of the energy channel.

[0126] Among them, HR-DEM can use a combination of "elevation data + spatial location" to present real-world terrain (such as mountains, valleys, plains, river terraces, etc.) in the form of computer-recognizable grids or point clouds, which can be used for real-time navigation, terrain analysis, environmental simulation and other scenarios. For example, on uphill sections (slope > 5%), the energy consumption multiplier can be adjusted (e.g., from 0.18 kWh / km to 0.25 kWh / km) based on the combination of slope and vehicle speed (e.g., vehicle speed < 30 km / h). In addition, the terrain database can be updated in real time via the cloud.

[0127] Based on the obtained road slope data and / or congestion status data, the energy consumption parameters are corrected to obtain the corrected energy consumption parameters; based on the corrected energy consumption parameters, power information, and location information, the elements of the energy channel are generated.

[0128] For example, both road slope data and congestion status data can be understood as terrain data. Road slope data can be understood as representing the uphill and downhill slope information of a road, which can be used to adjust energy consumption calculations. For instance, if the slope of the current road segment obtained through a terrain map or road angle detection device is 8%, and since it is greater than a preset slope threshold (such as 5%), the current road segment can be determined to be uphill.

[0129] Congestion status data can be understood as representing the current traffic congestion level of a road, and can be used to adjust energy consumption calculations. For example, if there are preset traffic congestion levels 1, 2, and 3, by detecting the current traffic flow and traffic ratio on the road, it can be determined that the current road segment's congestion level is level 2, which can be understood as moderate congestion.

[0130] When generating energy channel elements, road slope data is read and combined with road slope data (e.g., energy consumption of uphill sections multiplied by 1.3) or congestion status data (e.g., energy consumption of congested sections multiplied by 1.2) to dynamically adjust energy consumption parameters. For example, on uphill sections in mountainous areas, the system can automatically add energy consumption parameters (e.g., energy consumption coefficient), thus correcting preset fixed energy consumption parameters. Then, by combining the corrected energy consumption parameters, power consumption information, and location information, the system can calculate the specific distance values ​​of the reachable area, thereby generating energy channels that conform to the current road conditions, thus more realistically reflecting the actual reachable and inaccessible areas.

[0131] Congestion data can also reflect the current vehicle speed range. By upgrading the terrain perception model from static slope correction to dynamic multi-dimensional parameter (slope + vehicle speed) correction, the prediction bias caused by neglecting the impact of vehicle speed on energy consumption in traditional models that calculate drivable mileage can be solved.

[0132] A high-precision terrain layer is constructed based on a high-precision digital elevation model, and by combining it with real-time vehicle speed data, energy consumption parameters can be dynamically adjusted (e.g., energy consumption increases significantly when climbing hills at low speeds). For example, when driving at low speeds in mountainous areas, the navigation system can provide an advance warning that "the current combination of slope and vehicle speed leads to increased energy consumption, and it is recommended to switch to energy-saving driving mode," thereby mitigating the risk of users running out of battery due to prediction errors. Compared to calculation methods that rely solely on average energy consumption to determine the elements of the energy channel, the method in this application improves prediction reliability under complex road conditions, enabling users to plan routes more accurately and reducing the probability of missing charging stations due to misjudgment.

[0133] For example, if vehicle energy consumption is always calculated based on flat roads (e.g., a fixed 0.18 kWh / km), the calculation error of energy channel elements will be large due to the gradient of mountain roads. Based on the method of this application embodiment, road gradient data of the current road can be obtained from a map database. For example, if it is an uphill section, the energy consumption coefficient is multiplied by 1.3 (e.g., corrected to 0.23 kWh / km); if it is a downhill section (gradient less than -3%), the energy consumption coefficient is multiplied by 0.7 (including energy recovery, becoming 0.13 kWh / km); if it is a congested section, the energy consumption coefficient is multiplied by 1.2. After obtaining the corrected energy consumption parameters, the total energy consumption, the maximum reachable distance, and the estimated remaining power can be calculated comprehensively. For example, the interface can display "Considering gradient and road conditions, the estimated remaining power is 8%".

[0134] After generating energy channels based on the corrected energy consumption parameters, the routes can be optimized. For example, when the battery is low, an energy-saving route that "avoids steep slopes and congestion" can be automatically planned, and it can display "Choosing this route can save about 3% of the battery".

[0135] By combining road slope data and / or congestion data to correct energy consumption parameters, the accuracy of power consumption prediction under complex road conditions is improved, enhancing the reliability of energy channel prediction in mountainous or congested road sections. This allows users to perceive energy channels more accurately and plan routes more rationally, thus improving the user experience.

[0136] S103, renders the energy channels on the map based on the elements of the energy channels.

[0137] For example, the map can be any electronic map that can overlay virtual display information, such as an augmented reality map or an AR-renderable in-vehicle navigation map. Based on the coordinate values ​​and coordinate sets of the reachable and inaccessible areas in the energy channel, the corresponding locations can be rendered on the map to visually display the reachable and inaccessible areas. During rendering, at least one of the following methods can be used: animation, graphics, text, etc.

[0138] In one possible implementation, rendering energy channels in a map includes rendering the reachable and inaccessible areas of the energy channels using different colors.

[0139] For example, the different colors can be any number of different colors; for instance, reachable areas can be rendered in green, while unreachable areas can be rendered in red.

[0140] In this embodiment of the application, by rendering the reachable and unreachable areas in the energy channel with different colors, the reachable and unreachable areas can be displayed more intuitively, reducing the difficulty for users to identify them and improving the applicability of the scenario.

[0141] In one possible implementation, the reachable area range includes an energy-saving reachable area range and an energy-free reachable area range. The energy-saving reachable area range includes the area range corresponding to the vehicle after energy-saving control is implemented, and the energy-free reachable area range includes the area range corresponding to the vehicle without energy-saving settings.

[0142] For example, the energy-efficient reachable area can be understood as the area that a vehicle can reach after management and control operations that limit its energy consumption. For instance, by limiting the start of the air conditioner, limiting the air conditioner's operating power, or limiting entertainment functions, the geographical range that the vehicle can travel to can be supported. The energy-efficient reachable area can also be understood as "the area that can barely be reached".

[0143] The energy-efficient accessible area can be understood as the normally accessible area, which is the geographical range that a vehicle can reach without any energy consumption restrictions. For example, it is a geographical range that can be reached without restrictions on the use of air conditioning, audio and video playback, seat heating, and other functions.

[0144] When rendering reachable and unreachable areas using different colors, energy-efficient reachable areas, energy-saving reachable areas, and unreachable areas can be rendered using a variety of different colors.

[0145] Figure 2 A schematic diagram of the energy channel provided in the embodiments of this application, as shown below. Figure 2 As shown, the map interface displays the vehicle's current location information, indicating its geographical location and direction. The map also shows the currently traveled road and other surrounding roads. Energy-efficient accessible areas are rendered in green, energy-efficient accessible areas in yellow, and inaccessible areas in red. Areas outside the accessible areas are rendered in the color of inaccessible areas. Preset transparency settings can be used to overlay rendered areas. This provides a clear visual representation of "where you can go, where you can barely go, and where you can't go," replacing abstract mileage figures.

[0146] For example, the three colored map areas corresponding to the energy-saving accessible area, energy-saving accessible area, and inaccessible area in the energy channel can be overlaid on the road in the navigation map through the in-vehicle display screen.

[0147] For example, when displaying the color of a road, the road lines are shown in green within the energy-efficient accessible area; in the energy-efficient accessible area, the road lines are shown in yellow; and in the inaccessible area, the road lines are shown in red. Of course, other colors can be used to indicate accessibility in addition to green, yellow, and red to indicate road congestion.

[0148] In this embodiment, the reachable area is subdivided into energy-saving reachable area and energy-free reachable area based on whether energy-saving control is applied to the vehicle. This increases the granularity of the reachable area division, enhances the diversity of reachable area representation, and provides users with a more intuitive and visual navigation service that maps battery level and accessibility.

[0149] For example, in implementing the above Figure 1In the method of the illustrated embodiment, after obtaining the vehicle's battery level and location information, the range that the vehicle can travel with the current battery level can be calculated based on the battery level and location information, combined with a preset energy consumption model (such as energy consumption per unit distance) and terrain data (such as slope and congestion status). The energy-efficient accessible area is rendered as green (normally accessible), the energy-efficient accessible area as yellow (energy-efficient accessible), and the inaccessible area as red (inaccessible), thus forming an energy channel on the augmented reality map.

[0150] By overlaying the three-color areas of the energy channel onto an augmented reality map, it can be displayed to users via in-vehicle displays or mobile devices. The augmented reality map uses cameras to capture real-world scenes in real time and merges the virtual energy channel information with the real-world environment, allowing users to intuitively see the reachable and inaccessible areas from their current location. This transforms abstract mileage into colored areas on the map (green = reachable, yellow = reachable with energy saving, red = inaccessible), enabling a visually intuitive display of reachable areas using AR. It also implements a region-based map navigation mode, reducing the difficulty of understanding navigation and improving navigation efficiency.

[0151] The entire process described above can also be accomplished through collaborative computing between the vehicle and the cloud, enabling the generation and rendering of energy channels to respond in real time to changes in vehicle status and environment. For example, the cloud can provide terrain data to the vehicle, while the vehicle can execute the rendering of energy channels.

[0152] The navigation method provided in this application combines vehicle battery information with location information to generate a color-coded energy channel, which is then dynamically rendered on an augmented reality map. This solves the problem in the prior art where users find it difficult to intuitively determine the reachable range corresponding to the battery level.

[0153] This method uses augmented reality technology to transform abstract battery status into intuitive spatial visualization information. It uses color coding (e.g., green > yellow > red) to hierarchically classify accessibility and dynamically updates it to reflect real-time traffic changes (e.g., the green area shrinks when congestion increases energy consumption). Compared to existing navigation systems that only display single numbers like "remaining range 50 km" or "50 km driving range," this method reduces the user's cognitive load regarding reachability and minimizes route planning errors caused by misjudgments (e.g., manually navigating to an inaccessible charging station).

[0154] In addition, the energy channel can be combined with dynamic rendering mechanisms, such as dynamically adjusting the coverage area of ​​reachable and inaccessible areas based on terrain data, which can further improve the real-time performance and accuracy of information, enabling users to make decisions more efficiently in complex driving scenarios.

[0155] In one possible implementation, after rendering the energy channel in the map, the method further includes: updating the features of the energy channel according to a preset energy consumption model and terrain data to obtain updated features; adjusting the coverage area of ​​the reachable area and the inaccessible area according to the updated features, and updating the rendered energy channel.

[0156] For example, a preset energy consumption model can be understood as a rule for calculating energy consumption per unit distance for vehicles under different road conditions (such as flat roads, slopes, and congestion). Terrain data can be understood as data representing geographical information such as road slope, elevation, and congestion status. For example, a road segment has a slope of 5% and a congestion level of 3 (moderate congestion).

[0157] For example, the energy consumption on a flat road is 0.18 kWh / km, uphill energy consumption is 0.23 kWh / km, and downhill energy consumption is 0.13 kWh / km. A preset energy consumption model can be constructed from the energy consumption corresponding to these three road terrains. It should be understood that the preset energy consumption model may include dimensions such as congestion and altitude in addition to road terrain. This application embodiment does not limit this.

[0158] Terrain data can be real-time data acquired during the vehicle's current driving. Combined with a preset energy consumption model, energy consumption parameters can be determined, such as 0.18 kWh / km or 0.23 kWh / km. In this way, based on the remaining power and the determined energy consumption parameters, the reachable distance value and the coordinates of the farthest reachable location in the energy channel can be dynamically updated to obtain the updated elements.

[0159] Furthermore, after obtaining the updated features, the coverage areas of reachable and inaccessible areas can be adjusted based on the updated features. For example, the rendering energy channel can be adjusted by changing the color of the coverage areas of reachable and inaccessible areas in the map.

[0160] For example, energy channels can be calculated and updated in real time based on current SOC and terrain data. Green areas represent reachable ranges at normal energy consumption (0.18 kWh / km); yellow areas represent reachable ranges at energy-efficient energy consumption (0.14 kWh / km); red areas: all other areas can be rendered in red, representing inaccessible areas. These ranges can be overlaid with semi-transparent colors on the map.

[0161] By combining a pre-set energy consumption model with real-time terrain data, the color distribution of the energy channel can be dynamically adjusted. For example, if the current road segment is uphill or congested, and the vehicle's remaining battery power is known, the energy consumption model can automatically adjust the energy consumption per unit distance. This results in a reduction in the green area (accessible area without energy consumption), a reduction in the yellow area (accessible area with energy consumption), and a corresponding expansion of the red area (inaccessible area). This dynamic adjustment process can be completed through collaborative computing between the cloud and the vehicle, ensuring that the rendering results of the energy channel reflect real-time changes in actual road conditions.

[0162] In this embodiment, by combining a preset energy consumption model and terrain data, the rendered energy channel is dynamically updated, achieving an accurate representation of the achievable range of power consumption under complex road conditions and improving the real-time performance of energy channel adjustments. Compared to a static energy consumption model, this solution can more realistically reflect actual driving conditions, such as increased energy consumption on uphill sections, reducing the likelihood of users misjudging the reachable area due to a lack of consideration for terrain factors, thereby improving the reliability of route planning.

[0163] For example, existing navigation systems fail to automatically adjust the complexity of the display interface based on user behavior. If a large amount of information is still displayed on the interface in low-battery scenarios, it will cause users to worry about rapid battery drain and exacerbate their anxiety. To address this, the method provided in this application can automatically switch between graded display modes based on an anxiety index (battery stress level × 60% + behavioral anxiety level × 40%). Different levels of display modes can reduce information overload on the display interface, thereby alleviating the exacerbation of user anxiety.

[0164] In one possible implementation, after obtaining the vehicle's battery level and location information, the method further includes: obtaining user behavior data, which is used to characterize user actions related to vehicle battery level triggered during driving; determining an anxiety index based on the user behavior data and battery level information, which is used to characterize the user's level of anxiety about the vehicle's battery level; and switching the map display mode based on the anxiety index.

[0165] For example, user behavior data can be understood as data representing a user's operational behaviors related to the vehicle's battery level while driving, such as the number and frequency with which the user checks the battery level, or the number of times the user changes routes. For instance, if a user checks the remaining battery level 5 times within 1 minute, then 5 times / minute constitutes one user behavior data point.

[0166] When acquiring user behavior data, it can be obtained by counting the number of times a user clicks to check the remaining battery value within a period, or by counting the number of times a user asks the vehicle's intelligent agent about the remaining battery value, or by other means. This application embodiment does not limit this.

[0167] Anxiety index can be understood as a quantitative indicator representing the level of user anxiety. For example, it can be calculated by weighting vehicle battery information and user behavior data. For instance, Anxiety Index = Battery Tension × 60% + Behavioral Anxiety × 40%. Here, 60% and 40% are just examples of preset weights for weighting battery tension and behavioral anxiety. In actual application of this method, the weight values ​​can be preset to any value according to the needs of the scenario.

[0168] Battery anxiety can be understood as an indicator that quantifies the level of anxiety related to vehicle battery level. By using preset formulas or mapping relationships, a relationship can be established between battery information and battery anxiety, allowing the calculation of battery anxiety level. For example, battery anxiety level is inversely proportional to State of Charge (SOC); the lower the SOC, the higher the battery anxiety level. For instance, when SOC = 10%, the battery anxiety level could be 90.

[0169] For example, the preset formula for calculating battery stress is: Battery Stress = XT SOC Where X represents the maximum value of the power shortage, for example, 100; T SOC This represents the SOC value without the percentage sign. For example, if X is 100 and SOC is 20%, then T... SOC The value is 20, so the battery stress level can be calculated as 100 - 20 = 80. The preset mapping relationship can be, for example, a mapping table. For instance, SOC = 20% maps to a battery stress level of 80; SOC = 30% maps to a battery stress level of 70, and so on.

[0170] Behavioral anxiety can be understood as an indicator that quantifies the degree of anxiety in user behavior. By using preset formulas or mapping relationships, a relationship can be established between user behavior data and behavioral anxiety, allowing the calculation of the behavioral anxiety score. For example, the more frequently a user checks their vehicle's battery level, the higher their behavioral anxiety score. For instance, checking the remaining battery level 5 times per minute would result in a behavioral anxiety score of 80. By weighted summing battery level anxiety and behavioral anxiety, an anxiety index can be obtained. For example, the calculated anxiety index value would fall within the range of [0, 100].

[0171] A preset formula for calculating behavioral anxiety level is, for example: Behavioral Anxiety Level = k × Q, where k represents the calculation ratio of behavioral anxiety level and can be any positive value; Q represents the number of times the vehicle battery level is checked. For example, if k = 15 and Q = 4, the behavioral anxiety level = 15 × 4 = 60. The preset mapping relationship can be, for example, a mapping table. For instance, checking the vehicle battery level 4 times maps to a behavioral anxiety level of 20; checking the vehicle battery level 5 times maps to a behavioral anxiety level of 25, and so on.

[0172] Display mode can be understood as the mode in which different content items are displayed. For example, you can switch between display modes such as normal mode, alert mode, and emergency mode.

[0173] For example, normal mode can be understood as a display mode that does not restrict any displayed content. For instance, in normal mode, a standard map can be displayed; a semi-transparent green halo can be displayed at the edge of the reachable area; and regular icons can be displayed for charging stations.

[0174] Warning mode can be understood as a display mode that restricts the displayed content to a lower degree. For example, in warning mode, you can switch to an interface that displays the energy channels. The green area represents areas reachable by normal driving; the yellow area represents areas that require energy-saving mode (air conditioning off, speed limited) to reach; and the red area represents areas that are inaccessible due to insufficient energy. Virtual warning lines can be displayed around the edges of these areas. Warning mode can also display icons for several nearby charging stations (e.g., three), enlarged and highlighted. Other non-essential information (such as restaurant and attraction icons) can be hidden or displayed semi-transparently.

[0175] Emergency mode can be understood as a display mode that severely restricts the information displayed. For example, in emergency mode, all non-critical information is hidden, only the remaining mileage, charging station direction, and current speed are displayed, and the font size can be enlarged several times (e.g., 2 times) for easier identification. For example, in emergency mode, the screen displays an orange breathing light effect (slowly flashing, simulating deep breathing); a voice prompt automatically announces information such as "Nearest charging station planned, 3 minutes away, please relax" to alleviate anxiety; the nearest charging station is marked with a tall, three-dimensional (3D) pulsed light pillar, visible even through buildings. This 3D pulsed light pillar provides a strong visual impact to guide the user towards the charging station, allowing them to quickly identify important navigational targets in complex environments.

[0176] When switching map display modes based on the anxiety index, you can set the switching criteria based solely on the anxiety index, or you can combine the anxiety index with other dimensions such as battery information to set the switching criteria.

[0177] Normal mode can be understood as a Level 1 display mode. For example, it can be triggered when SOC > 30% or anxiety index < 40, and displays complete information. Alert mode can be understood as a Level 2 display mode. For example, it can be triggered when SOC is between 15% and 30% or anxiety index is between 40 and 70, and simplifies the interface while highlighting key information, such as the nearest charging station. Emergency mode can be understood as a Level 3 display mode. For example, it can be triggered when SOC < 15% or anxiety index > 70, and displays extremely simplified content, such as only remaining mileage, charging station directions, and vehicle speed, while using breathing light effects and voice reassurance to reduce user stress.

[0178] By dynamically linking user behavior (such as the frequency of battery level checks) with vehicle status (such as SOC), an adaptive interface switching logic is constructed, solving the information overload problem caused by the "one-size-fits-all" interface design of traditional navigation systems. The method in this application embodiment quantifies the user's anxiety state into an anxiety index, and dynamically adjusts the interface complexity based on the anxiety index (such as hiding non-critical information and amplifying key prompts) to alleviate the user's anxiety about the vehicle's battery level.

[0179] For example, in emergency mode, the system simulates deep breathing with a breathing light effect (such as slowly flashing orange light), combined with reassuring voice prompts, thus proactively intervening in the user's emotions at both the visual and auditory levels. Parameters for the breathing light effect can include color, frequency, and brightness. Compared to interfaces with fixed complexity, this solution reduces battery anxiety caused by information overload in low-battery scenarios and guides users to focus on key operations (such as selecting the direction of a charging station) by simplifying the interface, thereby reducing the probability of dangerous driving behaviors such as sudden braking and frequent checks of the dashboard.

[0180] In this embodiment, by dynamically linking user behavior data with anxiety index, adaptive adjustment of interface complexity is achieved, reducing user anxiety about battery life caused by information overload and providing reassurance. Simplifying the interface guides users to focus on key operations, reducing the probability of dangerous driving behaviors.

[0181] For example, in low-battery scenarios, users may be prone to accidental touches or failed operations due to anxiety. To address this, combining voice commands and / or gesture commands can reduce accidental touches and failed operations, improving operational accuracy.

[0182] In one possible implementation, the display mode includes an emergency mode, and the map display mode is switched according to the anxiety index, including: receiving voice commands and / or gesture commands when the map is switched to emergency mode according to the anxiety index; and performing operation control on the map based on the voice commands and / or gesture commands.

[0183] For example, a voice command can be understood as an operation command input by the user through voice. For instance, if the voice command is "Go to the nearest charging station", after receiving this voice command, the system can search for a path to the nearest charging station, or it can automatically navigate to the nearest charging station.

[0184] Gesture commands can be understood as operation instructions initiated by users through hand movements. Gesture commands can occur on the display screen or touchscreen, or in space outside the display screen or other preset locations. For example, gesture commands include finger swiping, waving, and tapping the screen. For instance, a user might use a swipe gesture to select a charging option in emergency mode.

[0185] In some scenarios, both voice and gesture commands can be received. By introducing multimodal interaction methods using voice and gesture commands in emergency mode, the complexity of user operation can be reduced. For example, users can quickly locate a target charging station using voice commands, and the touchscreen only needs to confirm the plan, reducing the risk of accidental touches.

[0186] By integrating voice and gesture commands into a multimodal interaction design, the risk of accidental touches caused by relying solely on a single touch operation in emergency mode is resolved.

[0187] For example, when the battery level is below 10%, users can trigger navigation directly via voice command "Go to the nearest charging station" without having to manually click through multiple options, thus reducing operational errors caused by stress or distraction. Compared to other single-modal interactions, this solution improves operational efficiency and reliability in emergency scenarios.

[0188] In this embodiment, multimodal interaction enhances the operational efficiency of emergency mode, reduces user operational errors caused by tension, improves operational efficiency and reliability, and enables users to quickly complete critical path selection.

[0189] For example, existing charging solution comparisons only provide static parameters (such as distance and price), requiring users to weigh and compare them mentally or manually, making it difficult to intuitively measure multi-dimensional factors such as time, cost, and risk of running out of power. Therefore, the method in this application employs split-screen animation simulation technology to display multiple charging solutions in parallel, synchronously playing timeline animations to dynamically present changes in the energy curve, accumulated costs, and estimated time consumption. It can also use a triangular comparison chart (representing time-saving, cost-saving, and power safety dimensions) to highlight the comprehensive advantages and disadvantages of different solutions.

[0190] In one possible implementation, after rendering the energy channels on the map, the method further includes: generating multiple charging schemes based on the acquired charging point information; performing timeline animation simulations on the multiple charging schemes; and displaying the timeline animations of the multiple schemes on the map in a split-screen format.

[0191] For example, a charging point can be any location where a vehicle can be charged, such as a charging station or a home charging station. Charging point information can include the location of the charging point, charging parameters (voltage, power, etc.), and charging costs. Charging point information can be obtained through data communication or by accessing a database.

[0192] A charging plan can be understood as a possible route planning scheme for the vehicle to reach a charging station, including fast charging, slow charging, and energy-saving direct charging. For example, Plan A is the nearest fast charging station (5km, 80% charge in 20 minutes). A timeline animation can be understood as a dynamic graphical representation of the energy consumption change process and estimated time taken for the charging plan. For example, the animation shows the SOC dropping from 20% to 5%, and then rising to 80% via fast charging. Multiple charging plans can be two or more, not limited to three.

[0193] After the energy channel rendering is complete, multiple charging schemes can be generated, such as fast charging, slow charging, and energy-saving direct charging. The energy consumption change process of each scheme can be animated over time (e.g., SOC decrease → charging increase). Through a split-screen display on the map, users can intuitively compare the differences between different schemes in terms of time, cost, and risk of running out of power. For example, the left screen displays the energy consumption curve of the fast charging scheme, the middle screen displays the cost growth trend of the slow charging scheme, and the right screen displays the animation of the energy-saving option operation for the energy-saving direct charging scheme and the remaining power after energy saving is achieved.

[0194] For example, when multiple charging options are animated over time, a "Compare Options" button is displayed when more than two charging stations are available. Clicking this button automatically generates three options: Option A: Nearest fast charging station (5km away, 20 minutes to 80% charging, cost 45 yuan); Option B: Slightly farther slow charging station (8km away, 60 minutes to 100% charging, cost 25 yuan); Option C: Energy-saving direct route to destination (no charging, air conditioning off + speed limit, 15% risk of battery depletion).

[0195] Split-screen parallel display could be achieved by dividing the screen into three columns, each displaying one option; synchronized timeline animations showing energy curve changes (decreasing → increasing or continuously decreasing); cumulative costs (scrolling numbers); and estimated total time consumption. Additionally, a triangular comparison chart can be generated. For example, the three vertices could represent: time saving, cost saving, and battery safety, with different colors used to indicate different options. After the user selects an option, the navigation automatically switches to the route corresponding to that option.

[0196] When performing simultaneous simulations of the charging schemes, a timeline (0-90 minutes) can be established for each charging scheme. During the journey to the charging station, the vehicle's State of Charge (SOC) decreases by 0.15% per minute; during the charging phase, fast charging increases the charge by 4% per minute for the first 80% and by 1% per minute for the last 20%; slow charging increases the charge by 1.67% per minute. Animations of the three charging schemes can be played simultaneously.

[0197] By transforming abstract decision parameters (time, cost, and risk of running out of power) into dynamic and visual information, the problem of subjective judgment for users comparing multiple options is solved. Its core principle lies in using timeline animation to synchronously display the energy consumption change process of different options (such as the rapid increase of SOC during fast charging and the slow increase of SOC during slow charging), and combining it with a triangular comparison chart to intuitively present the comprehensive advantages and disadvantages of each option.

[0198] For example, when faced with the decision of "choosing the nearest fast charging station (shorter charging time but higher cost)" or "choosing a slightly farther slow charging station (lower cost but longer charging time)," users can directly observe the energy consumption curves and cost growth trends of the two options through split-screen animation, thereby more efficiently selecting the optimal path. Compared to a static parameter list, the method in this application embodiment enhances the user's perception of multi-dimensional decision-making factors and reduces decision hesitation or misjudgment caused by information asymmetry.

[0199] In this embodiment of the application, the charging solution is simulated through split-screen animation, which enables an intuitive comparison of multi-dimensional decision-making factors, improves the user's perception of comprehensive factors such as time, cost, and risk, and reduces the probability of misjudgment.

[0200] In one possible implementation, after generating multiple charging options, the method further includes: determining a recommended priority for the multiple charging options based on an anxiety index; and / or updating the route planning of the multiple charging options based on terrain data.

[0201] For example, recommendation priority can be understood as the order in which multiple charging options are recommended based on the anxiety index. For instance, fast charging options are recommended first when the anxiety index is high.

[0202] Updating route planning can be understood as optimizing the route selection of one or more charging options among multiple charging options based on terrain data. For example, when optimizing route selection, steep slopes or congested sections can be avoided to save battery power.

[0203] By combining anxiety index with the recommended priority of charging options, fast charging is prioritized when the anxiety index is high (the degree of anxiety can be determined by a threshold), and slow charging is prioritized when the anxiety index is low. Furthermore, by incorporating terrain data, the planned routes can be updated and optimized in real time to avoid steep slopes or congestion, thereby reducing energy consumption. In this way, the generated charging options can both meet the user's anxiety level and reflect actual driving conditions.

[0204] In this embodiment, by combining anxiety index and / or terrain data to optimize charging solutions, personalized and precise decision-making is achieved. Compared to charging solution generation and recommendation with fixed priority, the solution in this embodiment is more aligned with the user's actual needs and environmental conditions, thereby improving decision-making quality.

[0205] In one possible implementation, after displaying the timeline animation of multiple charging options in a split-screen manner on the map, the method further includes: updating the navigation path on the map based on the target charging option determined by the user among the multiple charging options; detecting the vehicle's battery information in real time and periodically updating and rendering the energy channel on the map.

[0206] For example, navigation route updates can be understood as adjusting the previous navigation route based on the user's selected target charging plan. For instance, after the user selects a slow charging option, the navigation system automatically plans the route to the corresponding charging station. Periodic updates to the rendered energy channel can be understood as monitoring the vehicle's battery level in real time and updating the elements of the energy channel based on this information, thereby updating the rendered energy channel. For example, as the battery level decreases, the green area of ​​the energy channel gradually shrinks. These periodic updates can be performed at any preset time interval, such as once per second or once every 5 seconds, and the duration of the period can be determined based on the specific application scenario.

[0207] The method in this application embodiment allows the electronic device to continue updating the energy channel after the user selects a target charging solution, ensuring that the energy channel consistently and accurately displays to the user "where it can go and where it cannot go." For example, when the user selects a fast charging solution, the electronic device automatically adjusts the navigation path to the nearest fast charging station and monitors changes in battery level in real time, updating the color distribution of the energy channel to always reflect the current battery level and the specific situation of the reachable and inaccessible areas.

[0208] In this embodiment, the navigation path is updated promptly based on the user-determined target charging method, enabling rapid response to user needs and improving navigation real-time performance. By dynamically updating the navigation path and the rendering energy channel, real-time response to user operations and environmental changes is achieved. Compared to static navigation schemes, the method in this embodiment improves the real-time performance and adaptability of the navigation system, ensuring users consistently receive a superior navigation experience.

[0209] Figure 3 This is a flowchart illustrating the navigation method provided in the embodiments of this application. The following is a summary of the process. Figure 3 The navigation method provided in the embodiments of this application will be further described.

[0210] The electronic device executing the navigation method of this application embodiment may include a hardware configuration of vehicle-side hardware and optional hardware. For example, the vehicle-side hardware includes a CAN bus interface for reading SOC, vehicle speed, and GPS location. The vehicle-side hardware also includes an in-vehicle display screen, for example, the in-vehicle display screen has a resolution greater than or equal to 1920×1080 pixels and supports touch control.

[0211] In addition, the vehicle-side hardware may include a 4G / 5G module for real-time communication, capable of downloading road gradient data and charging station information from maps. Optional hardware could include a Bluetooth module for connecting to a smartwatch to read heart rate, enhancing anxiety detection accuracy.

[0212] For example, a cloud server interacting with electronic devices can be used to store terrain data, such as road slope and altitude. The cloud server can also be used to store charging station information, such as location, price, and number of available charging stations. The electronic devices and the cloud server can be distributed electronic devices within a navigation system, through which any of the navigation methods provided in the embodiments of this application can be implemented.

[0213] like Figure 3 As shown, after the vehicle starts, the electronic devices can read information such as SOC and GPS. Based on this information, an anxiety index is calculated, comprehensively assessing the user's battery anxiety through a combination of battery level and user behavior. The subsequent execution path is determined based on preset judgment conditions. If SOC ≥ 30% or anxiety indicator ≤ 40, the interface is displayed in normal mode, such as with a green halo. If SOC < 30% or anxiety indicator > 40, the interface is displayed in alert / emergency mode, such as with an energy channel displayed on the screen, simplifying the interface content.

[0214] Furthermore, when multiple selectable charging stations are detected, several charging plans are generated, and a "Plan Comparison" button is displayed on the interface. If the user clicks the "Plan Comparison" button, a split-screen timeline animation of multiple charging plans can be displayed, allowing for a comparison of the advantages and disadvantages of each plan in terms of time, cost, and risk of running out of power. Based on the user's selected target charging plan, terrain-aware navigation is performed using road slope data, and the system provides path navigation corresponding to the target charging plan for the user.

[0215] Based on the navigation method provided in this application, the adaptive interface and reassuring design can reduce user anxiety and help reduce the probability of dangerous driving in extremely low battery scenarios. The energy channel improves the user's understanding of the reachable area and enhances spatial awareness, reducing route planning error rates, such as preventing users from navigating to inaccessible charging stations. Through multi-scheme analysis, the accuracy of users selecting the optimal charging solution is improved, shortening decision time and optimizing decision quality. Terrain perception reduces energy consumption prediction errors, improves prediction accuracy, and reduces situations where the navigation system predicts the destination but the user cannot actually reach it. Furthermore, the method in this application is primarily a software solution, requiring no additional hardware, is low-cost and easy to implement, and can be adapted to existing in-vehicle navigation systems or mobile apps, exhibiting high applicability across various scenarios.

[0216] The navigation method or navigation system provided in this application can be applied to scenarios such as in-vehicle navigation for new energy vehicles and navigation via mobile applications, and has significant application value, especially in long-distance driving, adverse road conditions, or emergency low battery situations.

[0217] Figure 4 This is a schematic diagram of the structure of the navigation device provided in the embodiments of this application, such as... Figure 4 As shown, this application embodiment provides a navigation device, the device comprising:

[0218] The acquisition module 401 is used to acquire the vehicle's battery level and location information;

[0219] The generation module 402 is used to generate elements of the energy channel based on the power information and location information. The energy channel is used to visually display the accessible and inaccessible areas of the vehicle.

[0220] Rendering module 403 is used to render energy channels in the map based on the elements of the energy channels;

[0221] The generation module 402 is specifically used to: correct the energy consumption parameters based on the acquired road slope data and / or congestion status data of the current road to obtain the corrected energy consumption parameters; and generate the elements of the energy channel based on the corrected energy consumption parameters, power information and location information.

[0222] In one possible implementation, the rendering module 403 is specifically used for:

[0223] The reachable and unreachable areas in the energy channel are rendered using different colors.

[0224] In one possible implementation, the reachable area range includes an energy-saving reachable area range and an energy-free reachable area range. The energy-saving reachable area range includes the area range corresponding to the vehicle after energy-saving control is implemented, and the energy-free reachable area range includes the area range corresponding to the vehicle without energy-saving settings.

[0225] In one possible implementation, the apparatus further includes an update module, which is used to:

[0226] Based on the preset energy consumption model and terrain data, the elements of the energy channel are updated to obtain the updated elements;

[0227] Based on the updated features, adjust the coverage areas of reachable and inaccessible areas, and update the rendering energy channels;

[0228] and or,

[0229] The acquisition module 401 is also used for:

[0230] Acquire user behavior data, which is used to characterize user actions related to vehicle battery level during driving;

[0231] Anxiety index is determined based on user behavior data and battery information. The anxiety index is used to characterize the user's level of anxiety about the vehicle's battery level.

[0232] Switch map display modes based on anxiety level.

[0233] In one possible implementation, the display mode includes an emergency mode, and the acquisition module 401 is specifically used for:

[0234] When switching the map to emergency mode based on the anxiety index, receive voice commands and / or gesture commands;

[0235] Map operation and control are performed based on voice commands and / or gesture commands.

[0236] In one possible implementation, the device further includes a display module, which is used for:

[0237] Based on the acquired charging point information, multiple charging plans are generated;

[0238] Perform timeline animation simulations of multiple charging schemes;

[0239] Display timeline animations of multiple options on a split-screen display on the map.

[0240] In one possible implementation, the display module is also used for:

[0241] Based on the anxiety index, the recommended priority of multiple charging options is determined;

[0242] And / or, update the route planning for multiple charging options based on terrain data.

[0243] In one possible implementation, the display module is also used for:

[0244] Update the navigation path on the map based on the user's chosen charging option among multiple charging options;

[0245] The system monitors vehicle battery levels in real time and periodically updates and renders the energy channels on the map.

[0246] The navigation device provided in this application can be used to execute the technical solution of the navigation method in any of the above embodiments of this application. Its implementation principle and technical effect are similar, and will not be described again here.

[0247] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 5 As shown, the electronic device of this embodiment may include: at least one processor 501; and a memory 502 communicatively connected to the at least one processor; wherein the memory 502 stores instructions executable by the at least one processor 501, the instructions being executed by the at least one processor 501 to cause the electronic device to perform the method as described in any of the above embodiments.

[0248] Optionally, the memory 502 can be either standalone or integrated with the processor 501.

[0249] The implementation principle and technical effects of the electronic device provided in this embodiment can be found in the foregoing embodiments, and will not be repeated here.

[0250] This application also provides a vehicle that includes the electronic equipment provided in this application.

[0251] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the method of any of the foregoing embodiments.

[0252] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method of any of the foregoing embodiments.

[0253] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed.

[0254] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0255] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU) or other general-purpose processors. The processor can also be a Digital Signal Processor (DSP) or an Application Specific Integrated Circuit (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0256] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device, and may also be various media that can store program code, such as USB flash drives, portable hard drives, read-only memory (ROM), disks or optical discs.

[0257] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Examples of storage media include Static Random-Access Memory (SRAM) or Electrically Erasable Programmable Read Only Memory (EEPROM).

[0258] Storage media can be, for example, erasable programmable read-only memory (EPROM) or programmable read-only memory (PROM). Storage media can also be read-only memory (ROM), magnetic storage, flash memory, magnetic disks, or optical disks. Storage media can be any available medium accessible to general-purpose or special-purpose computers.

[0259] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside within an application-specific integrated circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components within an electronic device or host device.

[0260] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0261] The sequence numbers of the embodiments in this application are merely for description and do not represent the superiority or inferiority of the embodiments. Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0262] Based on this understanding, the technical solution of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0263] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

[0264] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0265] It should be further noted that although the steps in the flowchart are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise explicitly stated in this document, there is no strict order requirement for the execution of these steps, and they can be executed in other orders.

[0266] Furthermore, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0267] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0268] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0269] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A navigation method, characterized in that, The method includes: Obtain vehicle battery level and location information; The elements of the energy channel are generated based on the power information and the location information. The energy channel is used to visually display the accessible and inaccessible areas of the vehicle. Render the energy channel in the map based on the elements of the energy channel; The elements for generating the energy channel based on the power information and the location information include: Based on the obtained current road slope data and / or congestion status data, the energy consumption parameters are corrected to obtain the corrected energy consumption parameters; The elements of the energy channel are generated based on the corrected energy consumption parameters, the power information, and the location information.

2. The method according to claim 1, characterized in that, Rendering the energy channel in the map includes: The reachable and unreachable regions in the energy channel are rendered using different colors.

3. The method according to claim 1, characterized in that, The reachable area range includes an energy-saving reachable area range and an energy-free reachable area range. The energy-saving reachable area range includes the area range corresponding to the vehicle after energy-saving control is implemented, and the energy-free reachable area range includes the area range corresponding to the vehicle without energy-saving settings.

4. The method according to any one of claims 1-3, characterized in that, After rendering the energy channel in the map, the method further includes: Based on the preset energy consumption model and terrain data, the elements of the energy channel are updated to obtain the updated elements; Based on the updated elements, adjust the coverage areas of the reachable and inaccessible areas, and update the rendering of the energy channels; And / or, After obtaining the vehicle's battery level and location information, the method further includes: Acquire user behavior data, which is used to characterize user actions related to vehicle battery level triggered during driving; An anxiety index is determined based on the user behavior data and the battery information, and the anxiety index is used to characterize the user's anxiety level about the vehicle's battery level. The map display mode is switched based on the anxiety index.

5. The method according to claim 4, characterized in that, The display mode includes an emergency mode, and the step of switching the map display mode according to the anxiety index includes: When switching the map to the emergency mode based on the anxiety index, receive voice commands and / or gesture commands; The map is operated and controlled based on the voice commands and / or the gesture commands.

6. The method according to claim 4, characterized in that, After rendering the energy channel in the map, the method further includes: Based on the acquired charging point information, multiple charging plans are generated; Perform timeline animation simulation of the multiple charging schemes; The timeline animations of the multiple schemes are displayed in a split-screen format on the map.

7. The method according to claim 6, characterized in that, After generating multiple charging schemes, the method further includes: Based on the anxiety index, the recommended priority of the multiple charging solutions is determined; And / or, update the route planning of the multiple charging schemes based on terrain data.

8. The method according to claim 6, characterized in that, After displaying the timeline animations of the multiple schemes in a split-screen format on the map, the method further includes: The navigation path on the map is updated based on the target charging scheme determined by the user among the multiple charging schemes. The vehicle's battery level is monitored in real time, and the energy channel is periodically updated and rendered on the map.

9. An electronic device, characterized in that, include: Memory and processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-8.

10. A vehicle, characterized in that, The vehicle includes the electronic equipment as described in claim 9.

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