Vehicle driving mode switching method, device and equipment, vehicle and storage medium

Abstract

The embodiment of the invention provides a vehicle driving mode switching method and device, equipment, a vehicle and a storage medium. Relates to the technical field of vehicle control, and the method comprises the steps that when it is detected that a vehicle meets a constant speed cruise condition, a target driving mode is determined from multiple driving modes according to vehicle state data and front road data at the current moment, and the multiple driving modes are obtained by conducting clustering analysis on vehicle driving data; furthermore, the current driving mode of the vehicle can be switched to the target driving mode. The method is used for improving the driving experience of the user.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a method, device, equipment, vehicle and storage medium for switching vehicle driving modes. Background Art

[0002] With the continuous improvement of vehicle intelligence, cruise control has become a standard feature in modern vehicles. When the cruise control conditions are met, the vehicle automatically maintains the preset speed, effectively reducing frequent acceleration and deceleration operations and thus reducing the user's operational burden.

[0003] Conventional cruise control relies on a fixed driving mode. When the vehicle meets the cruising conditions, it switches to this fixed driving mode, adjusting engine output to maintain a constant speed. However, in actual driving, this cruise control method, which relies on a single fixed driving mode, can cause the vehicle to operate in an inappropriate driving mode when road conditions change, reducing the user's driving experience. Summary of the Invention

[0004] The embodiments of the present application provide a method, apparatus, device, vehicle, and storage medium for switching vehicle driving modes to address the shortcomings of traditional cruise control when facing dynamic road conditions and improve the user's driving experience.

[0005] In a first aspect, an embodiment of the present application provides a method for switching a vehicle driving mode, the method comprising:

[0006] When it is detected that the vehicle meets the cruise control conditions, a target driving mode is determined from a plurality of driving modes based on the current vehicle state data and the road ahead data, wherein the plurality of driving modes are obtained by clustering the vehicle driving data;

[0007] Switching the current driving mode of the vehicle to the target driving mode.

[0008] In one possible implementation, determining the target driving mode from a plurality of driving modes based on the current vehicle state data and the road ahead data includes:

[0009] determining a fitness score for each driving mode based on the vehicle state data and the road ahead data, the fitness score for each driving mode being used to indicate a degree of match between the driving mode and the vehicle state data and the road ahead data;

[0010] The driving mode with the highest fitness score is determined as the target driving mode.

[0011] In a possible implementation, determining the fitness score of each driving mode based on the vehicle state data and the front road data includes:

[0012] For any driving mode, matching the data of each dimension in the driving mode with the data of the corresponding dimension in the vehicle state data and the road ahead data to determine the fitness score of the driving mode in each dimension;

[0013] The sum of the fitness scores of the driving mode in each dimension is determined as the fitness score of the driving mode.

[0014] In a possible implementation, determining the fitness score of the driving mode in each dimension includes:

[0015] For any dimension, determining the weight and dimension data of the driving mode in the dimension;

[0016] The product of the weight and the dimension data is determined as the fitness score of the driving mode in the dimension.

[0017] In one possible implementation, before determining the target driving mode from the plurality of driving modes based on the current vehicle state data and the road ahead data, the method further includes:

[0018] Acquire multiple vehicle driving data;

[0019] Performing cluster analysis on the plurality of vehicle driving data to obtain a plurality of clusters;

[0020] Add the corresponding driving mode label to each cluster to obtain multiple driving modes.

[0021] In one possible implementation, the method further includes:

[0022] generating a target cruising speed control instruction and a target gear control instruction for the vehicle according to the target driving mode and the front road data;

[0023] controlling the vehicle to travel at the target cruising speed according to the target cruising speed control instruction;

[0024] According to the target gear control instruction, the transmission is controlled to switch to the target gear.

[0025] In one possible implementation, the method further includes:

[0026] generating a prompt message for the vehicle to enter cruise control;

[0027] The prompt information is sent to the visual interface of the vehicle for display.

[0028] In a possible implementation, the cruise control condition includes:

[0029] The cruise control state is turned on, the cruise control state is turned on for a preset time, the predictive cruise control state is turned on, and the forward road data is obtained.

[0030] In a second aspect, an embodiment of the present application provides a device for switching a vehicle driving mode, comprising:

[0031] a first processing module configured to, upon detecting that the vehicle meets cruise control conditions, determine a target driving mode from a plurality of driving modes based on current vehicle state data and forward road data, the plurality of driving modes being obtained by performing cluster analysis on the vehicle driving data;

[0032] The second processing module is configured to switch the current driving mode of the vehicle to the target driving mode.

[0033] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor;

[0034] The memory stores computer-executable instructions;

[0035] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0036] In a fourth aspect, an embodiment of the present application provides a vehicle comprising the electronic device as described in the third aspect.

[0037] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementation methods of the first aspect.

[0038] In a sixth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the first aspect and / or various possible implementation methods of the first aspect.

[0039] The vehicle driving mode switching method, apparatus, device, vehicle, and storage medium provided in embodiments of the present application include, upon detecting that a vehicle meets cruise control conditions, determining a target driving mode from multiple driving modes based on current vehicle status data and road ahead data, and switching the vehicle's current driving mode to the target driving mode. The multiple driving modes are obtained by clustering the vehicle's driving data. After obtaining multiple driving modes through cluster analysis, the target driving mode that best suits the road ahead can be determined and switched from the multiple driving modes based on the current vehicle status data and road ahead data, thereby improving the user's driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0041] Figure 1 A schematic diagram of an application scenario provided in an embodiment of the present application;

[0042] Figure 2 A flowchart of a first embodiment of a method for switching a vehicle driving mode provided in this application;

[0043] Figure 3 This is a flow chart of a second embodiment of a method for switching a vehicle driving mode provided by this application;

[0044] Figure 4 This is a flow chart of a third embodiment of a method for switching a vehicle driving mode provided in this application;

[0045] Figure 5 This is a flow chart of a fourth embodiment of a method for switching a vehicle driving mode provided in this application;

[0046] Figure 6 This is a flowchart of a fifth embodiment of a method for switching a vehicle driving mode provided in this application;

[0047] Figure 7 A flowchart illustrating an example of a method for switching a vehicle driving mode provided in an embodiment of the present application;

[0048] Figure 8 This is a structural diagram of a first embodiment of a vehicle driving mode switching device provided by the present application;

[0049] Figure 9 This is a structural diagram of a second embodiment of a vehicle driving mode switching device provided by this application;

[0050] Figure 10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0051] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0052] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0053] Figure 1 This is a schematic diagram of the application scenario provided by the embodiment of this application. Figure 1 When the vehicle control unit (VCU) detects that the vehicle meets the cruise control conditions, it can switch the vehicle's current driving mode according to the determined target driving mode, thereby optimizing the vehicle's driving performance and reducing the vehicle's energy consumption.

[0054] Conventional cruise control systems employ a pre-set, fixed driving mode. When cruising conditions are met, the system switches to this mode, adjusting engine output to maintain a constant speed. However, due to the dynamic nature of real-world road conditions, this single, fixed driving mode-based cruise control system is unable to adapt to changing road conditions, thereby degrading the user's driving experience.

[0055] To address the above issues, the inventors considered intelligently switching the vehicle's driving mode based on vehicle status data and road ahead data when the vehicle meets cruise control conditions. Based on this, after multiple experiments, the inventors discovered that cluster analysis of vehicle driving data could be performed to obtain multiple driving modes. Then, when the vehicle meets cruise control conditions, the inventors could determine a target driving mode from the multiple driving modes based on the current vehicle status data and road ahead data, and then switch the vehicle's current driving mode to the target driving mode to optimize the vehicle's driving performance. Based on this, the present application proposes a method for switching vehicle driving modes to further enhance the user's driving experience.

[0056] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0057] Figure 2 For a flow chart of the first embodiment of the method for switching the vehicle driving mode provided in this application, please refer to Figure 2 , the method comprising:

[0058] S201: When it is detected that the vehicle meets the cruise control condition, a target driving mode is determined from a plurality of driving modes according to the current vehicle state data and the road ahead data.

[0059] The execution subject of the embodiment of the present application can be an electronic device, or a vehicle driving mode switching device provided in the electronic device. The vehicle driving mode switching device can be implemented by software, or by a combination of software and hardware. The vehicle driving mode switching device can be a processor in the electronic device. For ease of understanding, the technical solution of the present application will be described below using the electronic device as a vehicle controller in a vehicle as an example.

[0060] In this step, when the vehicle controller determines that the vehicle meets the cruise control conditions, it can determine the target driving mode from multiple driving modes obtained by clustering analysis of the vehicle driving data based on the current vehicle status data and the road ahead data.

[0061] The cruise control conditions may refer to the entry conditions for the vehicle to enter the cruise control function, including the cruise control state being on, the cruise control state being on for a preset time, the predictive cruise control state being on, and obtaining the road ahead data.

[0062] Optionally, the cruise control state is in the on state, and the user may set the cruise control state to the on state by operating the cruise control button.

[0063] In an optional embodiment, the vehicle controller may set the cruise control state to the on state in response to a user's voice command. For example, the voice command may be "turn on cruise control."

[0064] The cruise control state is kept active for a preset time period to ensure that the cruise control system is stable. Optionally, the preset time period can be customized based on user needs. For example, the preset time period could be 10 seconds, meaning that after cruise control is activated, a 10-second wait is required to ensure that the cruise control system is stable.

[0065] For Predictive Cruise Control (PCC), this technology can use road data to predict road conditions ahead and adjust the vehicle's cruising speed and order-changing strategy accordingly to achieve better economy and driving experience.

[0066] Likewise, the predictive cruise control state may be set to the on state by the user operating a predictive cruise control button; or, in response to a user's voice command, such as “turn on predictive cruise control”.

[0067] Regarding obtaining the road ahead data, it can be to ensure that the vehicle controller can use the road ahead data to determine the optimal driving mode to cope with the changing road conditions ahead of the vehicle.

[0068] Optionally, the vehicle status data may include real-time speed, acceleration, etc., and the front road data may include road slope, road curvature, etc.; the vehicle driving data may include average speed, average acceleration, and fuel consumption rate.

[0069] For example, the vehicle's real-time speed is 80 km / h (kilometers per hour), the acceleration is 3 m / s² (meters per second squared), the road slope of the road ahead is +5%, the road curvature is 0.01 (that is, the curvature radius is 100 m), the vehicle's average speed for 100 km is 70 km / h, the average acceleration is 1.8 m / s², and the fuel consumption rate is 6.5 L / 100 km (liters per 100 kilometers).

[0070] Optionally, multiple driving modes can be obtained by clustering the vehicle driving data in the following manner:

[0071] Acquire multiple vehicle driving data, perform cluster analysis on the multiple vehicle driving data, and obtain multiple clusters; add a corresponding driving mode label to each cluster to obtain multiple driving modes.

[0072] For example, cluster analysis can be performed on 100 vehicle driving data to obtain three clusters, namely cluster 1, cluster 2, and cluster 3; the driving mode label added to cluster 1 is economic mode, the driving mode label added to cluster 2 is normal mode, and the driving mode label added to cluster 3 is sports mode.

[0073] Eco mode sacrifices some power and drivability for improved fuel economy. It optimizes throttle response, torque output, and coasting energy recovery for more efficient fuel efficiency. Normal mode combines power, drivability, and fuel economy, offering moderate throttle response, torque output, and energy recovery, making it suitable for everyday driving. Sport mode sacrifices some fuel economy for improved power and drivability. It provides quicker throttle response, stronger torque output, and reduced coasting energy recovery, delivering a more aggressive driving experience.

[0074] It should be understood that the driving modes in the examples (e.g., Economy, Sport, and Normal) are derived through cluster analysis of vehicle driving data and are designed to optimize vehicle performance and efficiency under different driving conditions. These modes are not fixed or unique, but can be adjusted and expanded based on different vehicle designs, user needs, and driving environments.

[0075] For example, when the vehicle controller detects that the vehicle's cruise control state is on, the cruise control state is on for 10 seconds, the predictive cruise control state is on, and the vehicle controller obtains the road ahead data, it can determine that the target driving mode is the sport mode from the economic mode, sport mode, and normal mode obtained by clustering analysis of the vehicle driving data based on the current vehicle state data and the road ahead data.

[0076] S202: Switch the current driving mode of the vehicle to the target driving mode.

[0077] In this step, after determining the target driving mode, the vehicle controller can switch the current driving mode of the vehicle to the target driving mode.

[0078] For example, if the current driving mode of the vehicle is the normal mode, the normal mode of the vehicle can be switched to the sports mode according to the determination of the sports mode.

[0079] Optionally, the current driving mode of the vehicle can be any one of the multiple driving modes in the clustering results, or other modes pre-set in the vehicle, such as energy-saving mode, off-road mode, snow mode, or comfort mode.

[0080] In an embodiment of the present application, upon detecting that the vehicle meets cruise control conditions, the vehicle controller can determine a target driving mode from multiple driving modes based on the current vehicle status data and road ahead data, and then switch the vehicle's current driving mode to the target driving mode. The multiple driving modes are derived from cluster analysis of vehicle driving data. In this process, by dynamically adjusting the driving mode based on real-time vehicle status data and road ahead data, the vehicle can better adapt to changes in the road environment, thereby improving the user's driving experience.

[0081] Figure 3 This is a flow chart of the second embodiment of the method for switching the vehicle driving mode provided by this application. Figure 2 Based on the examples shown, see Figure 3 , the method comprising:

[0082] S301: When it is detected that the vehicle meets the cruise control condition, determine the adaptability score of each driving mode according to the vehicle state data and the road ahead data.

[0083] In this step, when the vehicle controller detects that the vehicle meets the cruise control conditions, it can calculate the fitness score of each driving mode in the clustering results based on the vehicle status data and the road ahead data. The fitness score of each driving mode is used to indicate the degree of match between the driving mode and the vehicle status data and the road ahead data.

[0084] In an optional embodiment, for any driving mode, the data of each dimension in the driving mode can be matched with the data of the corresponding dimension in the vehicle status data and the road ahead data to determine the fitness score of the driving mode in each dimension; and the sum of the fitness scores of the driving mode in each dimension is determined as the fitness score of the driving mode.

[0085] For example, driving mode 1 is the economic mode. The data of each dimension in the economic mode can be matched with the data of the corresponding dimension in the vehicle status data and the road ahead data to determine the fitness score of the economic mode in the four dimensions of real-time speed, acceleration, road slope, and road curvature. The sum of the fitness scores of the economic mode in the four dimensions is determined as the fitness score of the economic mode.

[0086] For example, the clustering results include economic mode (driving mode 1), normal mode (driving mode 2), and sports mode (driving mode 3). The fitness scores corresponding to the three driving modes can be determined based on vehicle status data and road ahead data.

[0087] S302: Determine the driving mode with the highest fitness score as the target driving mode.

[0088] In this step, the vehicle controller can compare the fitness scores of multiple driving modes and determine the driving mode with the highest fitness score as the target driving mode.

[0089] For example, if the fitness score of the economic mode is 80 points, the fitness score of the conventional mode is 60 points, and the fitness score of the sports mode is 96 points, the sports mode can be determined as the target driving mode.

[0090] S303: Switch the current driving mode of the vehicle to the target driving mode.

[0091] For example, the vehicle's current driving mode may be switched to sport mode.

[0092] S304: Generate a target cruising speed control instruction and a target gear control instruction for the vehicle according to the target driving mode and the road ahead data.

[0093] In this step, after determining the target driving mode, the vehicle controller can determine the target cruising speed and target gear according to the road ahead data, and generate the target cruising speed control instruction and the target gear control instruction.

[0094] For example, when a vehicle travels through a 5km uphill section with a 5% gradient, a 3km downhill section with a -3% gradient, and a 12km straight section, the vehicle can maintain a constant cruising speed (e.g., 80km / h) in the absence of road data. However, when the vehicle controller detects that the road data includes a 5km uphill section with a 5% gradient, it can adjust the cruising speed to 70km / h. Alternatively, the target cruising speed can be calculated by the vehicle controller based on vehicle performance, road gradient, and economic efficiency. Furthermore, the vehicle controller can determine the most appropriate gear (e.g., 4th gear) based on the vehicle's 70km / h cruising speed and a 5% road gradient to reduce engine load and improve fuel efficiency.

[0095] When the vehicle controller detects that the road data ahead includes a 3km downhill section with a road slope of -3%, it can increase the cruising speed to 85km / h, while taking advantage of the natural acceleration of the downhill slope and reducing throttle input; in addition, the vehicle controller can also determine the most appropriate gear (such as 3rd gear) based on the vehicle's cruising speed of 85km / h and the road slope of -3%.

[0096] When the vehicle controller detects that the road data ahead includes a 12km straight section, the cruising speed can be restored to a constant cruising speed of 80km / h. In addition, the vehicle controller can also determine the most appropriate gear (such as 5th gear) based on the vehicle's cruising speed of 80km / h and the road slope of 0.

[0097] For example, based on the sports mode and the fact that the road ahead data includes a 5km uphill section with a road gradient of 5%, the vehicle's target cruise speed control instruction and target gear control instruction can be generated; wherein, the target cruise speed control instruction is used to adjust the vehicle's cruising speed to 70km / h on the 5km uphill section, and the target gear control instruction is used to adjust the gearbox's output gear to 4th gear on the 5km uphill section.

[0098] S305: Control the vehicle to travel at the target cruising speed according to the target cruising speed control instruction.

[0099] In this step, after the target cruising speed control instruction is generated, the vehicle controller can control the vehicle to travel at the target cruising speed according to the target cruising speed control instruction.

[0100] Optionally, the vehicle controller and other controllers of the vehicle, such as the engine controller, transmission controller, and brake controller, can exchange data in real time through the Controller Area Network (CAN), so that the various systems of the vehicle can work efficiently and in a coordinated manner.

[0101] For example, the vehicle controller can send a target cruising speed control instruction to the engine controller via the CAN bus to control the output torque of the engine so that the vehicle travels at a target cruising speed of 70 km / h.

[0102] S306 : Control the transmission to switch to the target gear according to the target gear control instruction.

[0103] For example, the vehicle controller can send the target gear control instruction to the transmission controller via the CAN bus to control the transmission to switch to the target gear 4.

[0104] In this embodiment of the present application, when the vehicle controller detects that the vehicle meets cruise control conditions, it can calculate the fitness score of each driving mode based on vehicle status data and road ahead data. It then determines the driving mode with the highest fitness score as the target driving mode and switches the vehicle's current driving mode to that target driving mode. In this process, the vehicle controller can select the optimal driving mode based on vehicle status data and road ahead data, thereby enhancing the user's driving experience.

[0105] Furthermore, the vehicle driving mode switching method provided in the embodiments of the present application, after determining the target driving mode, can adjust the vehicle's target cruising speed and target gear in real time based on the road ahead data. This dynamic adjustment not only adapts to changing road conditions but also optimizes the vehicle's power output, improves fuel efficiency, and ensures that the vehicle maintains optimal driving conditions in various driving environments.

[0106] Figure 4 This is a flow chart of the third embodiment of the method for switching the vehicle driving mode provided by this application. Figure 4 Based on the above-mentioned embodiment 2, in the specific implementation of the vehicle driving mode switching method, the step S301 of determining the fitness score of each driving mode based on the vehicle state data and the road ahead data further includes the following steps:

[0107] S401: For any driving mode, match the data of each dimension in the driving mode with the data of the corresponding dimension in the vehicle state data and the road ahead data to determine the fitness score of the driving mode in each dimension.

[0108] Optionally, the data of each dimension in the driving mode may refer to the weight of each dimension. For example, if the vehicle status data includes dimension data (real-time speed), the driving mode may include the weight corresponding to the dimension data (real-time speed).

[0109] For example, the economic mode may include weights in four dimensions: real-time speed, acceleration, road slope, and road curvature; the vehicle status data may include dimensional data in two dimensions: real-time speed and acceleration, and the road ahead data may include dimensional data in two dimensions: road slope and road curvature; for the economic mode, the weights of the four dimensions in the economic mode may be matched with the dimensional data in two dimensions in the vehicle status data and the dimensional data in two dimensions in the road ahead data to determine the fitness score of the economic mode in the four dimensions: real-time speed, acceleration, road slope, and road curvature.

[0110] In a specific implementation, for any dimension, the weight and dimension data of the driving mode in the dimension may be determined, and the product of the weight and the dimension data may be multiplied to determine the fitness score of the driving mode in the dimension.

[0111] S402: Determine the sum of the fitness scores of the driving mode in each dimension as the fitness score of the driving mode.

[0112] For example, the calculated total fitness scores of the three driving modes and the fitness scores of each dimension can be shown in Table 1, where the vehicle status data includes the real-time speed of 80 km / h and the acceleration of 0 m / s², and the road ahead data includes the road slope of 3% (0.03) and the road curvature of 0.01.

[0113] Table 1

[0114]

[0115] In an optional embodiment, the data (weight) of each dimension in each driving mode can be pre-set based on expert knowledge, data analysis, or historical experience.

[0116] It should be noted that if a dimension in the driving mode does not have a corresponding dimension in the vehicle status data and the road ahead data, it can be considered that the dimensional data corresponding to the dimension in the driving mode does not exist, and the value of the dimensional data corresponding to the dimension can be 0.

[0117] In an embodiment of the present application, for any driving mode, the data for each dimension of the driving mode can be matched with the data for the corresponding dimension in the vehicle status data and the road ahead data to determine the fitness score for the driving mode in each dimension. Furthermore, the sum of the fitness scores for the driving mode in each dimension can be used to determine the fitness score for the driving mode. This multi-dimensional comprehensive evaluation makes the fitness score more accurate, facilitating the selection of the optimal driving mode from the clustered multiple driving modes, thereby optimizing driving safety and reducing vehicle energy consumption, thereby enhancing the user's driving experience.

[0118] Figure 5 This is a flow chart of the fourth embodiment of the method for switching the vehicle driving mode provided by this application. Figure 5 Based on any of the above embodiments, before determining the target driving mode, the vehicle driving mode switching method further includes:

[0119] S501: Acquire multiple vehicle driving data.

[0120] In this step, the vehicle controller can obtain multiple vehicle driving data.

[0121] For example, the vehicle controller can obtain 100 vehicle driving data, and each driving data may include: average speed, average acceleration, and fuel consumption rate.

[0122] S502: Perform cluster analysis on multiple vehicle driving data to obtain multiple clusters.

[0123] In an optional implementation, a weighted K-means clustering algorithm may be used to perform cluster analysis on multiple vehicle driving data to obtain multiple clusters. The specific algorithm includes steps ①②③.

[0124] Step ①: First specify the number of clusters N and randomly select an initial cluster center for each cluster.

[0125] For example, the number of clusters N is 3, and 3 data points are randomly selected from 100 vehicle driving data as the initial cluster centers, and each vehicle driving data is a data point.

[0126] Step ②: Assign weights to each feature based on its importance.

[0127] For example, the weight of average speed is 1, the weight of average acceleration is 1, and the weight of fuel consumption rate is 2. Among them, the weight of fuel consumption rate is 2. It can be considered that fuel consumption rate is more important for distinguishing driving modes, so a higher weight of 2 can be given.

[0128] Step 3: Iterative calculation.

[0129] For each data point, calculate its weighted distance to each cluster center. In practice, you can use the weighted Euclidean distance formula to assign each data point to the cluster center closest to it.

[0130] Furthermore, the center of each cluster can be updated to the weighted average of all points in the cluster, and the above step ③ can be repeated until the cluster center no longer changes significantly or the preset number of iterations is reached. After clustering is completed, three clusters can be obtained, each cluster representing the vehicle driving characteristics of a driving mode.

[0131] S503: Add a corresponding driving mode label to each cluster to obtain multiple driving modes.

[0132] For example, an economy mode may be added to cluster 1, a normal mode may be added to cluster 2, and a sports mode may be added to cluster 3, thereby obtaining three driving modes.

[0133] In Economical Mode (ECO), the vehicle's throttle response is adjusted to be smoother to reduce unnecessary power output. This setting helps improve fuel economy. At the same time, the torque increase / decrease slope can be set to a gentler state to further reduce power mutations during acceleration and deceleration, enhancing driving smoothness. In addition, by increasing the coasting energy recovery torque, more energy can be recovered when the vehicle is coasting, thereby further reducing fuel consumption.

[0134] In Normal mode, the vehicle's throttle response is adjusted to moderate to ensure that users can obtain sufficient power output when needed without being too sensitive or slow, thereby improving driving comfort; at the same time, the torque increase / decrease slope can be set to a milder state to balance power and drivability; in addition, a moderate energy recovery torque can be set to ensure economy without affecting the driving experience.

[0135] In Sport mode, the vehicle's throttle response is adjusted to be more sensitive, making power output faster to meet the user's needs for speed and acceleration. This adjustment can enhance driving pleasure; at the same time, the increase / decrease torque slope can be set to a stronger state to provide a more direct acceleration and deceleration feeling; in addition, the coasting energy recovery torque can be reduced to reduce the restriction on power output, allowing the vehicle to exhibit stronger performance in Sport mode.

[0136] In an embodiment of the present application, the vehicle controller can acquire multiple vehicle driving data and, through cluster analysis, divide this data into multiple clusters. A corresponding driving mode label is then added to each cluster, generating multiple driving modes. In this process, multiple driving modes can be obtained through cluster analysis, providing a solid foundation for intelligent driving mode switching, enabling the vehicle to automatically adjust its driving mode in different driving scenarios, providing the user with an optimal driving experience.

[0137] Figure 6 This is a flow chart of the fifth embodiment of the method for switching the vehicle driving mode provided by this application. Figure 6 After the current driving mode of the vehicle is switched to the target driving mode, the method for switching the vehicle driving mode may further include:

[0138] S601: Generate prompt information for the vehicle to enter cruise control.

[0139] In this step, after the vehicle switches to the target driving mode, the vehicle controller may generate a prompt message to remind the user that the vehicle has entered the target driving mode.

[0140] For example, after the vehicle switches to the sports mode, the vehicle controller may generate a prompt message indicating that the vehicle has switched to the sports mode.

[0141] Optionally, the prompt information may also include at least one of the following information: target cruising speed, target gear, cruise control status is on, cruise control status is on time, predictive cruise control status is on, and vehicle controller receives road ahead data.

[0142] S602: Send the prompt information to the visual interface of the vehicle for display.

[0143] In this step, the vehicle controller can send prompt information to the vehicle's visual interface for display, reminding the user that the vehicle has entered the target driving mode.

[0144] The visual interface can be the vehicle's central control touchscreen or heads-up display. The central control touchscreen provides navigation, entertainment, and vehicle settings. Prompts can pop up on the central control screen, providing more detailed driving mode information and related setting options. With the heads-up display, the vehicle controller projects prompts onto the windshield, allowing users to access relevant driving mode information without looking down.

[0145] For example, the vehicle controller can send a prompt message indicating that the vehicle has switched to Sport mode to the vehicle's central control touch screen for display. The central control touch screen can display the prompt message that the vehicle has entered Sport mode in the form of a pop-up window or status bar notification.

[0146] In an optional embodiment, when the vehicle actively exits cruise control, or when the user takes control of the vehicle to exit cruise control, the vehicle controller may also indicate the reason for exiting cruise control, such as cruise control is off, predictive cruise control is off, or the vehicle controller is unable to receive road data ahead.

[0147] Among them, the cruise control status is turned off when the user turns off the cruise control by operating the cruise control button; the predictive cruise control status is turned off when the user turns off the predictive cruise control button by operating the predictive cruise control button; the vehicle control cannot receive the road ahead data because the vehicle's positioning signal is lost or the accuracy is insufficient, resulting in the vehicle controller being unable to determine the vehicle's exact position, or the road ahead data lacks information on the road slope, making it impossible for the vehicle controller to effectively adjust the speed.

[0148] In an embodiment of the present application, the vehicle controller can generate and send prompt information to promptly remind the user that the vehicle has entered the target driving mode after the driving mode is switched. This real-time information transmission can improve the user's understanding of the current status of the vehicle and enhance driving safety and convenience.

[0149] Furthermore, when the vehicle actively exits the cruise control state or the user manually takes over the vehicle, the vehicle controller can also provide a clear exit reason, helping the user quickly understand the reason for the change in cruise control state, further improving driving transparency and operating experience.

[0150] For ease of understanding, the following Figure 7 , the vehicle driving mode switching method provided in this application is further described in detail through specific examples.

[0151] Figure 7 This is a flow chart of an example of a method for switching a vehicle driving mode provided in an embodiment of the present application. Figure 7 , the method comprising:

[0152] S701: Collect vehicle driving data.

[0153] Optionally, multiple vehicle driving data may be collected, and each driving data may include average speed, average acceleration, and fuel consumption rate.

[0154] S702: Perform weighted K-means cluster analysis to obtain multiple driving modes.

[0155] For example, K-means cluster analysis can be performed on multiple vehicle driving data to obtain three driving modes, namely economic mode, normal mode, and sports mode.

[0156] S703: Acquire vehicle status data and forward road data.

[0157] For example, the vehicle status data that can be obtained includes real-time speed, acceleration, and current load, and the road ahead data may include road slope and road curvature.

[0158] S704: Calculate the adaptability score of each driving mode.

[0159] For example, based on the vehicle status data and the road ahead data, it can be calculated that the fitness score of the economic mode is 80 points, the fitness score of the conventional mode is 90 points, and the fitness score of the sports mode is 70 points.

[0160] S705: Select the optimal driving mode.

[0161] For example, the conventional mode may be selected as the optimal driving mode because the conventional mode has the highest fitness score, and the current driving mode of the vehicle may be switched.

[0162] S706: Determine a target cruising speed and a target gear position based on the optimal driving mode and the road ahead data.

[0163] For example, the target cruising speed may be determined to be V and the target gear position to be D according to the normal mode and the road gradient and road curvature included in the forward road data.

[0164] S707: Send control instructions to the vehicle control module.

[0165] For example, a target cruise speed control command can be sent to the engine controller to control the engine's output torque so that the vehicle travels at a target cruise speed V; a target gear control command can be sent to the transmission controller to control the transmission to shift to a target gear D. The target cruise speed control command and the target gear control command are generated based on the optimal driving mode and forward road data.

[0166] S708: Provide real-time feedback on cruise control status and exit reasons.

[0167] For example, when the cruise control function is operating normally, the vehicle's instrument panel or central control screen can display the current cruise speed and status, such as "Cruise control is activated, speed: 80km / h".

[0168] The embodiment of the present application provides an example of a method for switching vehicle driving modes. For the specific execution process, please refer to the technical solution shown in the above method embodiment. Its implementation principles and beneficial effects are similar and will not be repeated here.

[0169] Figure 8 This is a structural diagram of the first embodiment of the vehicle driving mode switching device provided by this application. Figure 8 , the vehicle driving mode switching device 10 includes:

[0170] A first processing module 11 is configured to, upon detecting that the vehicle meets cruise control conditions, determine a target driving mode from a plurality of driving modes based on current vehicle state data and forward road data, the plurality of driving modes being obtained by performing cluster analysis on the vehicle driving data;

[0171] The second processing module 12 is configured to switch the current driving mode of the vehicle to the target driving mode.

[0172] The vehicle driving mode switching device provided in the embodiment of the present application can implement the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar and will not be repeated here.

[0173] In a possible implementation manner, the first processing module 11 is specifically configured to:

[0174] determining a fitness score for each driving mode based on the vehicle state data and the road ahead data, the fitness score for each driving mode being used to indicate a degree of match between the driving mode and the vehicle state data and the road ahead data;

[0175] The driving mode with the highest fitness score is determined as the target driving mode.

[0176] In a possible implementation manner, the first processing module 11 is specifically configured to:

[0177] For any driving mode, matching the data of each dimension in the driving mode with the data of the corresponding dimension in the vehicle state data and the road ahead data to determine the fitness score of the driving mode in each dimension;

[0178] The sum of the fitness scores of the driving mode in each dimension is determined as the fitness score of the driving mode.

[0179] In a possible implementation manner, the first processing module 11 is specifically configured to:

[0180] For any dimension, determining the weight and dimension data of the driving mode in the dimension;

[0181] The product of the weight and the dimension data is determined as the fitness score of the driving mode in the dimension.

[0182] In a possible implementation, the first processing module 11 is further configured to:

[0183] Acquire multiple vehicle driving data;

[0184] Performing cluster analysis on the plurality of vehicle driving data to obtain a plurality of clusters;

[0185] Add the corresponding driving mode label to each cluster to obtain multiple driving modes.

[0186] In a possible implementation, the second processing module 12 is further configured to:

[0187] generating a target cruising speed control instruction and a target gear control instruction for the vehicle according to the target driving mode and the front road data;

[0188] controlling the vehicle to travel at the target cruising speed according to the target cruising speed control instruction;

[0189] According to the target gear control instruction, the transmission is controlled to switch to the target gear.

[0190] Figure 9 This is a structural diagram of the second embodiment of the vehicle driving mode switching device provided by this application. Figure 9 ,exist Figure 8 Based on the embodiment shown, the vehicle driving mode switching device 10 further includes a third processing module 13, wherein:

[0191] The third processing module 13 is configured to generate prompt information indicating that the vehicle has entered cruise control;

[0192] The third processing module 13 is further configured to send the prompt information to a visual interface of the vehicle for display.

[0193] In a possible implementation, the cruise control condition includes:

[0194] The cruise control state is turned on, the cruise control state is turned on for a preset time, the predictive cruise control state is turned on, and the forward road data is obtained.

[0195] The vehicle driving mode switching device provided in the embodiment of the present application can implement the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar and will not be repeated here.

[0196] Figure 10 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 10 The electronic device 20 may be a vehicle controller or another device with a driving mode switching function that can replace the vehicle controller. The electronic device 20 may include at least one processor 21 and a memory 22. Optionally, the electronic device 20 also includes a communication component 23. The processor 21, memory 22, and communication component 23 are connected via a bus 24.

[0197] During the specific implementation process, at least one processor 21 executes the computer-executable instructions stored in the memory 22, so that the at least one processor 21 performs the above method.

[0198] The specific implementation process of the processor 21 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0199] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0200] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage.

[0201] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0202] The embodiment of the present application also provides a vehicle, including Figure 10 The electronic device shown realizes intelligent automatic switching of driving modes through the coordinated work of its processor, memory and communication components.

[0203] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0204] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0205] The readable storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0206] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0207] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0208] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0209] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0210] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0211] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0212] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A method for switching a vehicle driving mode, characterized in that: The method comprises: When it is detected that the vehicle meets the cruise control conditions, a target driving mode is determined from a plurality of driving modes based on the current vehicle state data and the road ahead data, wherein the plurality of driving modes are obtained by clustering the vehicle driving data; Switching the current driving mode of the vehicle to the target driving mode.

2. The method according to claim 1, characterized in that The method of determining a target driving mode from a plurality of driving modes based on the current vehicle state data and the road ahead data includes: determining a fitness score for each driving mode based on the vehicle state data and the road ahead data, the fitness score for each driving mode being used to indicate a degree of match between the driving mode and the vehicle state data and the road ahead data; The driving mode with the highest fitness score is determined as the target driving mode.

3. The method according to claim 2, characterized in that The determining of the fitness score of each driving mode according to the vehicle state data and the front road data includes: For any driving mode, matching the data of each dimension in the driving mode with the data of the corresponding dimension in the vehicle state data and the road ahead data to determine the fitness score of the driving mode in each dimension; The sum of the fitness scores of the driving mode in each dimension is determined as the fitness score of the driving mode.

4. The method according to claim 3, characterized in that Determining the fitness score of the driving mode in each dimension includes: For any dimension, determining the weight and dimension data of the driving mode in the dimension; The product of the weight and the dimension data is determined as the fitness score of the driving mode in the dimension.

5. The method according to any one of claims 1 to 4, characterized in that Before determining the target driving mode from the plurality of driving modes based on the current vehicle state data and the forward road data, the method further includes: Acquire multiple vehicle driving data; Performing cluster analysis on the plurality of vehicle driving data to obtain a plurality of clusters; Add the corresponding driving mode label to each cluster to obtain multiple driving modes.

6. The method according to any one of claims 1 to 4, characterized in that The method further comprises: generating a target cruising speed control instruction and a target gear control instruction for the vehicle according to the target driving mode and the front road data; controlling the vehicle to travel at the target cruising speed according to the target cruising speed control instruction; According to the target gear control instruction, the transmission is controlled to switch to the target gear.

7. The method according to any one of claims 1 to 4, characterized in that The method further comprises: generating a prompt message for the vehicle to enter cruise control; The prompt information is sent to the visual interface of the vehicle for display.

8. The method according to any one of claims 1 to 4, characterized in that The cruise control conditions include: The cruise control state is turned on, the cruise control state is turned on for a preset time, the predictive cruise control state is turned on, and the forward road data is obtained.

9. A vehicle driving mode switching device, characterized in that: include: a first processing module configured to, upon detecting that the vehicle meets cruise control conditions, determine a target driving mode from a plurality of driving modes based on current vehicle state data and forward road data, the plurality of driving modes being obtained by performing cluster analysis on the vehicle driving data; The second processing module is configured to switch the current driving mode of the vehicle to the target driving mode.

10. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 8.

11. A vehicle, characterized in that: Comprising the electronic device as claimed in claim 10.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

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