Vehicle driving mode control method and device, equipment and medium

Abstract

Embodiments of the present application disclose a vehicle driving mode control method and device, an electronic device and a computer readable medium, wherein the method comprises: determining a driving path mode of a vehicle according to a navigation mode of the vehicle and historical driving data of the vehicle; obtaining a plurality of weight coefficients corresponding to the driving path mode and parameter values of a plurality of current driving influence factors corresponding to the plurality of weight coefficients, the driving influence factors being used to represent factors influencing a driving state of the vehicle; updating a driving parameter threshold according to the plurality of weight coefficients and the parameter values of the plurality of current driving influence factors, the driving parameter threshold being used to represent a switching threshold of the vehicle driving mode; and controlling switching of the vehicle driving mode according to the driving parameter threshold. The accuracy of determining the vehicle driving mode can be improved by the method.

Description

Technical Field

[0001] This application relates to the field of vehicle driving technology, and more specifically, to a method for controlling a vehicle driving mode, a device for controlling a vehicle driving mode, an electronic device, and a computer-readable medium. Background Technology

[0002] The driving mode of a hybrid vehicle affects its energy consumption. Currently, the determination of the driving mode during the switching process of a hybrid vehicle is often relatively simple. It is usually determined by looking up the battery state of charge (SOC) and accelerator pedal opening table (map). The parameters in these maps are all calibrable parameters and are all fixed values. In complex driving environments, it is often impossible to make an accurate determination of the driving mode.

[0003] Therefore, improving the accuracy of determining the overall vehicle driving mode is an urgent problem to be solved. Summary of the Invention

[0004] The embodiments of this application provide a method and apparatus for controlling the driving mode of a vehicle, an electronic device, and a computer-readable medium, which can improve the accuracy of determining the driving mode of a vehicle.

[0005] In a first aspect, embodiments of this application provide a method for controlling a vehicle's driving mode, including:

[0006] The driving route pattern of the vehicle is determined based on the vehicle's navigation mode and historical driving data.

[0007] Obtain multiple weight coefficients corresponding to the driving path mode, and parameter values ​​of the current driving influence factors corresponding to the multiple weight coefficients respectively. The driving influence factors are used to characterize the factors affecting the driving state of the vehicle.

[0008] The driving parameter threshold is updated based on the multiple weighting coefficients and the parameter values ​​of the current multiple driving influencing factors. The driving parameter threshold is used to characterize the switching threshold of the vehicle driving mode.

[0009] The switching of the vehicle's overall driving mode is controlled based on the driving parameter thresholds.

[0010] In one embodiment of this application, based on the aforementioned scheme, the navigation mode includes a navigation mode, and the historical driving data includes multiple commonly used route data; if the navigation mode is the navigation mode, then route planning data is obtained; the route planning data is compared with the multiple commonly used route data to obtain a first comparison result; and the driving route mode is determined based on the first comparison result.

[0011] In one embodiment of this application, based on the aforementioned scheme, if the first comparison result indicates that the plurality of commonly used path data includes commonly used path data whose similarity value with the path planning data is greater than or equal to a first similarity threshold, then the driving path mode is determined to be a commonly used driving path mode; if the first comparison result indicates that the similarity value between the path planning data and each commonly used path data is less than the first similarity threshold, then the driving path mode is determined to be a non-common driving path mode with navigation.

[0012] In one embodiment of this application, based on the foregoing scheme, the navigation mode includes a no-navigation mode, and the historical driving data includes multiple commonly used route data; if the navigation mode is the no-navigation mode, the driven route data of the vehicle is obtained, which is generated by the vehicle's positioning system; the driven route data is compared with the multiple commonly used route data to obtain a second comparison result; and the driving route mode is determined based on the second comparison result.

[0013] In one embodiment of this application, based on the aforementioned scheme, the historical driving data further includes the driving time period corresponding to each frequently used route data, and the driven route data includes the time period of the driven route; if the second comparison result indicates that the frequently used route data includes frequently used route data whose driving time period overlaps with the time period of the driven route data, and whose similarity value between the route and the driven route is greater than a second preset threshold, then the driving route pattern is determined to be a frequently used driving route pattern; if the second comparison result indicates that the frequently used route data includes frequently used route data whose similarity value between the route and the driven route is greater than a third preset threshold, then the driving route pattern is determined to be a frequently used driving route pattern.

[0014] In one embodiment of this application, based on the aforementioned scheme, the parameter values ​​of the current driving influencing factors include parameter values ​​of road condition information, environmental information, vehicle status information, and driver style information; correction values ​​for road condition information, environmental information, vehicle status information, and driver style information are calculated based on the parameter values ​​of road condition information, environmental information, vehicle status information, and driver style information, and corresponding multiple weighting coefficients; the driving parameter thresholds are updated based on the correction values ​​of road condition information, environmental information, vehicle status information, and driver style information.

[0015] In one embodiment of this application, based on the aforementioned scheme, the driving parameter threshold includes a battery charge threshold and a throttle opening threshold; the plurality of weighting coefficients includes a first set of weighting coefficients and a second set of weighting coefficients, wherein the first set of weighting coefficients is different from the second set of weighting coefficients; a correction value for the first road condition information, a correction value for the first environment information, a correction value for the first vehicle state information, and a correction value for the first driver style information are calculated based on the first set of weighting coefficients and the parameter values ​​of the road condition information, the environmental information, the vehicle state information, and the driver style information, so as to update the battery charge threshold based on the correction values ​​of the first road condition information, the first environment information, the first vehicle state information, and the first driver style information; a correction value for the second road condition information, a correction value for the second environment information, a correction value for the second vehicle state information, and a correction value for the second driver style information are calculated based on the second set of weighting coefficients and the parameter values ​​of the road condition information, the environmental information, the vehicle state information, and the driver style information, so as to update the throttle opening threshold based on the correction values ​​of the second road condition information, the second environment information, the second vehicle state information, and the second driver style information.

[0016] In one embodiment of this application, based on the aforementioned scheme, actual driving parameter values ​​are obtained; according to the relationship between the driving parameter threshold and the actual driving parameters, the overall driving mode of the vehicle is determined, and the switching of the overall driving mode of the vehicle is controlled.

[0017] In one embodiment of this application, based on the aforementioned scheme, the driving parameter thresholds include a battery charge threshold and a throttle opening threshold; the actual driving parameter values ​​include a battery charge value and a throttle opening value; the vehicle driving mode includes an engine-on state and an engine-off state; if the battery charge value is greater than or equal to the battery charge threshold, and the throttle opening value is less than or equal to the throttle opening threshold, then the vehicle driving mode is determined to be the engine-off state; if the battery charge value is less than the battery charge threshold, and / or the throttle opening value is greater than the throttle opening threshold, then the vehicle driving mode is determined to be the engine-on state.

[0018] In one embodiment of this application, based on the aforementioned scheme, after determining the vehicle's overall driving mode according to the relationship between the driving parameter threshold and the actual driving parameters, driving data is acquired. The driving data is generated after the vehicle completes driving based on the route planning data and / or the already driven route data. The driving data and the historical driving data are then fused together according to the relationship between the driving data and the historical driving data.

[0019] In one embodiment of this application, based on the aforementioned scheme, the driving data includes the current vehicle's driving path data and driving association data corresponding to the driving path information; the historical driving data includes multiple frequently used path data and driving association data corresponding to each frequently used path data; the historical driving data also includes one or more rarely used driving path data and rarely used driving association data corresponding to each rarely used driving path data; if there is a first frequently used path data in the historical driving data whose path matches the driving path data, then the driving association data corresponding to the driving path information is added to the driving association data corresponding to the first frequently used path data; if there is no frequently used path data or rarely used path data in the historical driving data whose path matches the driving path data, then the driving data is added to the historical driving data as described above; if there is a first rarely used path data in the historical driving data whose path matches the driving path data, then the driving association data corresponding to the driving path information is added to the driving association data corresponding to the first rarely used path data.

[0020] Secondly, embodiments of this application provide a control device for a vehicle driving mode, including:

[0021] The processing unit is used to determine the driving path mode of the vehicle based on the vehicle's navigation mode and historical driving data.

[0022] The acquisition unit is used to acquire multiple weight coefficients corresponding to the driving path mode, and the parameter values ​​of the current driving influence factors corresponding to the multiple weight coefficients respectively. The driving influence factors are used to characterize the factors affecting the driving state of the vehicle.

[0023] The processing unit is further configured to update the driving parameter threshold based on the multiple weighting coefficients and the parameter values ​​of the current multiple driving influencing factors, wherein the driving parameter threshold is used to characterize the switching threshold of the vehicle driving mode;

[0024] The control unit is used to control the switching of the vehicle's overall driving mode based on the driving parameter thresholds.

[0025] Thirdly, embodiments of this application provide an electronic device, including one or more processors; and a memory for storing one or more programs, which, when executed by the one or more processors, enable the electronic device to implement the vehicle driving mode control method described above.

[0026] Fourthly, embodiments of this application provide a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the vehicle driving mode control method described above.

[0027] Fifthly, embodiments of this application provide a computer program product, including computer instructions, which, when executed by a processor, implement the vehicle driving mode control method described above.

[0028] In the technical solutions provided by the embodiments of this application:

[0029] The vehicle can determine a driving path mode based on the current navigation mode and historical driving data. Within this driving path mode, multiple weighted coefficients and their corresponding parameter values ​​for current driving influencing factors can be obtained. Furthermore, a driving parameter threshold can be updated based on these weighted coefficients and the parameter values ​​of the current driving influencing factors. This threshold characterizes the switching threshold for the vehicle's overall driving mode. Thus, the switching of the vehicle's overall driving mode can be controlled based on the calculated driving parameter threshold. The driving parameter threshold is calculated based on the parameter values ​​of the current driving influencing factors, which are constantly changing. Therefore, the driving parameter threshold also changes in real time. This means that the vehicle's control of the overall driving mode is based on real-time data, improving the accuracy of determining the overall driving mode.

[0030] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of an implementation environment in which embodiments of this application can be applied;

[0032] Figure 2 This is a flowchart illustrating a vehicle driving mode control method in an exemplary embodiment of this application;

[0033] Figure 3 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0034] Figure 4 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0035] Figure 5 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0036] Figure 6 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0037] Figure 7This is an exemplary embodiment of the present application illustrating a flowchart for determining the driving route pattern in a navigation-free mode;

[0038] Figure 8 This is a flowchart illustrating the determination of a driving path pattern, as shown in another exemplary embodiment of this application;

[0039] Figure 9 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0040] Figure 10 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0041] Figure 11 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0042] Figure 12 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0043] Figure 13 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0044] Figure 14 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0045] Figure 15 This is a flowchart illustrating a method for controlling the driving mode of a vehicle, as shown in another exemplary embodiment of this application;

[0046] Figure 16 This is a block diagram of a vehicle driving mode control device according to an embodiment of this application;

[0047] Figure 17 This is a schematic diagram of the structure of a computer system suitable for implementing the electronic devices of the present application embodiments. Detailed Implementation

[0048] 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.

[0049] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0050] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0051] It should also be noted that "multiple" as mentioned in this application refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0052] The vehicle driving mode control method, device, electronic equipment, and computer-readable medium proposed in this application relate to the field of vehicle driving technology. These embodiments will be described in detail below.

[0053] Please see Figure 1 , Figure 1 This is a schematic diagram of an implementation environment related to one of the claims in this application. For example... Figure 1 As shown, this implementation environment can be applied to a vehicle, specifically a hybrid vehicle equipped with an engine 130 and a battery 110. The engine 130 is a fuel-efficient engine. In other words, the vehicle can choose to be powered by both the fuel-efficient engine 130 and the battery 110. The vehicle also includes an accelerator pedal 120, which, when pressed by the driver, triggers an acceleration function, causing the vehicle to accelerate. When the driver presses the accelerator pedal 120, the vehicle can be powered by the engine 130, the battery 110, or both.

[0054] It should be noted that the throttle opening value in this embodiment refers to the depth to which the driver presses the accelerator pedal 120. For example, if the driver presses the accelerator pedal 120 to 1 / 2, the corresponding throttle opening value is 50%. In addition, the battery charge value refers to the battery state of charge (SOC) value, that is, the remaining capacity of the battery.

[0055] The vehicle also includes a sensor 140, which may be a lidar sensor, a gravity sensor, a liquid detection sensor, etc., capable of detecting current road conditions, road slope, rain, etc. This application embodiment does not limit the specific type of sensor 140. Furthermore, the vehicle may also include other components, such as a display screen, operating system, chip, memory, etc., which this application embodiment does not limit.

[0056] In this embodiment, the vehicle driving mode may include an engine-on state and an engine-off state. The vehicle can determine the vehicle driving mode to switch to based on the battery charge threshold and throttle opening threshold in order to control the vehicle.

[0057] Figure 2 This is a flowchart illustrating a control method for a vehicle driving mode according to an exemplary embodiment. Figure 2 As shown, in an exemplary embodiment, the method may include steps S210 to S240, and the executing entity in this embodiment may be a vehicle. Steps S210 to S240 are described in detail below:

[0058] Step S210: Determine the vehicle's driving route mode based on the vehicle's navigation mode and historical driving data.

[0059] The vehicle's navigation mode can include a navigation-enabled mode and a navigation-free mode. The navigation-enabled mode is when the vehicle is driving with navigation enabled, while the navigation-free mode is when the vehicle is driving without navigation enabled.

[0060] This historical driving data may include multiple frequently used route data points and the corresponding driving data for each frequently used route data point. The frequently used route data points refer to the routes the vehicle frequently travels, as recorded in the vehicle's history.

[0061] Optionally, in navigation mode, the vehicle can plan a route to the destination entered by the driver, obtain a planned route, and record the route after the vehicle travels along the planned route.

[0062] Optionally, the vehicle can travel partly according to the navigation plan to obtain the first part of the path. Further, it can travel in a navigation-free mode and record the positioning information in the navigation-free mode to calculate the second part of the path. Then, the first part of the path and the second part of the path are combined to obtain the driving path.

[0063] Optionally, when the vehicle is driving in a navigation-free mode, it can obtain location information and use this location information to determine the route the vehicle is traveling, thus obtaining the driving path.

[0064] Furthermore, for the driving routes obtained in the above three scenarios, if the vehicle has driven the driving route more than or equal to a preset number of times, the driving route can be marked as frequently used route data. The preset number of times can be 5 times, but this application embodiment does not limit it. Each time the vehicle records the driving route, it does not need to record whether the driving route was driven in navigation mode or not. That is, the frequently used route data ultimately recorded in the vehicle's historical driving data is unrelated to the navigation mode, but is related to the specific route of the driving path.

[0065] Furthermore, the vehicle can also record driving-related data corresponding to the frequently used route data. This driving data can include road condition information, environmental information, vehicle status information, and driver style information collected each time the vehicle travels according to the frequently used route data. It is understood that, assuming the preset number of times is 5, each frequently used route data included in the historical driving data corresponds to 5 or more driving-related data points, and each driving-related data point corresponds to the driving-related data recorded each time the vehicle travels according to the frequently used route data.

[0066] For example, Table 1 shows a common route data 1 and its corresponding driving association data, where the number of trips for the common route data 1 is 6.

[0067]

[0068] Table 1

[0069] In this embodiment of the application, for a driving route, if the number of times a vehicle travels the driving route is less than a preset number, the driving route and the driving-related data corresponding to the driving route can be temporarily stored in the historical driving data. If the vehicle does not travel along the driving route again for more than a preset time threshold after the last time it travels along the driving route, the driving route and the corresponding driving-related data can be deleted from the historical driving data.

[0070] In this embodiment, the driving route mode may include a frequently used driving route mode, a less frequently used driving route mode with navigation, and a frequently used driving route mode without navigation. The driving route mode can be determined based on the aforementioned navigation mode and historical driving data.

[0071] Step S220: Obtain multiple weight coefficients corresponding to the driving path mode, and the parameter values ​​of the current driving influence factors corresponding to the multiple weight coefficients. The driving influence factors are used to characterize the factors that affect the vehicle's driving status.

[0072] The multiple weighting coefficients include a first group of weighting coefficients and a second group of weighting coefficients.

[0073] Table 2 shows the mapping relationship between driving path mode and the first set of weight coefficients. The first set of weight coefficients includes a1, a2, a3, b1, b2, b3, b4, c1, c2, c3, c4, d1, and d2. This first set of weight coefficients is used to calculate the battery charge threshold in combination with the current driving influence factors.

[0074] Table 3 shows the mapping relationship between driving path mode and the second set of weight coefficients. The second set of weight coefficients includes A1, A2, A3, B1, B2, B3, B4, C1, C2, C3, C4, D1, and D2. This second set of weight coefficients is used to calculate the throttle opening threshold in combination with the current driving influence factors.

[0075]

[0076] Table 2

[0077]

[0078]

[0079] Table 3

[0080] Step S230: Update the driving parameter threshold based on multiple weighting coefficients and the parameter values ​​of multiple current driving influencing factors. The driving parameter threshold is used to characterize the critical value for switching the vehicle's driving mode.

[0081] The driving parameter thresholds include the battery charge threshold and the throttle opening threshold. The battery charge threshold can be calculated based on the first set of weighting coefficients and the current driving influence factors, and the throttle opening threshold can be calculated based on the second set of weighting coefficients and the current driving influence factors.

[0082] Step S240: Control the switching of the vehicle's overall driving mode based on driving parameter thresholds.

[0083] Specifically, the vehicle can acquire the actual battery charge value and throttle opening value, compare the battery charge value with the battery charge threshold, and compare the throttle opening value with the throttle opening threshold to determine which state the vehicle driving mode should be switched to, and generate the corresponding control command to control the switching of the vehicle driving mode.

[0084] Through the embodiments of this application, after obtaining the vehicle's driving path mode, the vehicle can update the driving parameter threshold by combining multiple weight coefficients corresponding to the driving path mode and the parameter values ​​of the obtained current driving influencing factors, so as to switch the vehicle's overall driving mode according to the parameter threshold. The driving parameter threshold can be calculated in real time, meaning that the vehicle's control of the overall driving mode is based on real-time data, which can improve the accuracy of determining the overall driving mode.

[0085] Please see Figure 3 , Figure 3 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 3 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S310 to S330 and steps S220 to S240.

[0086] Steps S310 to S330 will be described in detail below:

[0087] Step S310: If the navigation mode is the navigation mode, then obtain the path planning data.

[0088] The "Navigation Mode" refers to the navigation-enabled mode. In this mode, after the driver enters their destination, the vehicle can plan a route for the driver and obtain the route planning data.

[0089] In this embodiment, when the driver does not follow the route planning data, the vehicle will automatically update the route planning data based on the vehicle's location to obtain new route planning data. This new route planning data includes the route traveled by the driver according to the original route planning data, as well as the routes not traveled in the updated route planning data.

[0090] Step S320: Compare the path planning data with the multiple commonly used path data to obtain the first comparison result.

[0091] The vehicle can compare the route planning data with multiple commonly used route data in the historical driving data to determine whether there are commonly used route data that are the same as or similar to the route planning data, and obtain the first comparison result.

[0092] Step S330: Determine the driving path mode based on the first comparison result.

[0093] This method allows for the comparison of route planning data with multiple commonly used route data, which helps improve the efficiency of determining driving route patterns.

[0094] Please see Figure 4 , Figure 4 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 4 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S310 to S320, steps S410 to S420, and steps S220 to S240.

[0095] Steps S410 and S420 will be described in detail below:

[0096] Step S410: If the first comparison result indicates that among the multiple commonly used path data, there are commonly used path data whose similarity value with the path planning data is greater than or equal to the first similarity threshold, then the driving path mode is determined to be a commonly used driving path mode.

[0097] The similarity value can be a percentage, such as 95%. That is, when there are frequently used route data in the historical driving data that have a similarity value of 95% with the route planning data, the driving route pattern can be determined as a frequently used driving route pattern.

[0098] Step S420: If the similarity value between the first comparison result characterizing the path planning data and each commonly used path data is less than the first similarity threshold, then the driving path mode is determined to be a non-common driving path mode with navigation.

[0099] In other words, if the similarity value between all commonly used route data and route planning data in historical driving data is below 95%, then the driving route pattern is determined to be a non-common driving route pattern with navigation.

[0100] This method allows for the determination of the vehicle's driving path pattern under navigation mode based on the first comparison result, which helps improve the efficiency of determining the driving path pattern.

[0101] Please see Figure 5 , Figure 5 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 5 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S510 to S530 and steps S220 to S240.

[0102] Steps S510 to S530 will be described in detail below:

[0103] Step S510: If the navigation mode is no navigation mode, then obtain the vehicle's traveled route data, which is generated by the vehicle's positioning system.

[0104] The "no navigation mode" is the navigation off mode. In this mode, the vehicle can obtain its location information through the positioning system, thereby obtaining the path the vehicle has traveled, i.e., the path data.

[0105] Step S520: Compare the traveled route data with multiple commonly used route data to obtain the second comparison result.

[0106] The vehicle can compare the already driven route data with multiple frequently used route data in the historical driving data to determine whether there are frequently used route data that are the same as or similar to the already driven route data, and obtain the second comparison result.

[0107] Step S530: Determine the driving path pattern based on the second comparison result.

[0108] This method allows for the comparison of driven route data with multiple commonly used route data, which helps improve the efficiency of determining driving route patterns.

[0109] Please see Figure 6 , Figure 6 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 6 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S510 to S520, steps S610 to S630, and steps S220 to S240.

[0110] Among them, steps S210 to S220 have been described in detail below. Figure 2 The embodiments shown are described in detail and will not be repeated here. Steps S610 to S630 are described in detail below:

[0111] Step S610: If the second comparison result indicates that among the multiple commonly used path data, there are commonly used path data whose driving time period overlaps with the driving time period of the already driven path data, and whose similarity value between the path and the already driven path is greater than the second preset threshold, then the driving path mode is determined to be a commonly used driving path mode.

[0112] Each frequently used route data point can correspond to a different travel time period, and this travel time period is the time period statistically determined by the vehicle.

[0113] For example, for frequently used route data 1 that has been traveled 5 times, the recorded travel time periods are: 1. 7:30–8:00; 2. 7:28–8:01; 3. 7:32–7:57; 4. 7:35–8:05; and 5. It can be seen that the vehicle's travel time for this frequently used route data 1 is concentrated between 7:30 and 8:00. Therefore, the vehicle can be determined that the travel time for this frequently used route data 1 is between 7:30 and 8:00, allowing for a certain degree of error.

[0114] Furthermore, if the vehicle starts driving at 7:28, several frequently used route data with starting times around 7:28 can be filtered out. Further, after the vehicle has traveled s0km, assuming it reaches 7:35, the travel time of the s0km route data overlaps with the travel time of the several frequently used route data. The traveled route data is then compared with the starting portion of s0km in the several frequently used route data. For example, the traveled route data is compared with the portion from 0km to s0km of the frequently used route data 1. If there is a frequently used route data where the similarity value between the s0km route and the traveled route is greater than a second preset threshold, then the driving route mode is determined to be a frequently used driving route mode. The second preset threshold can be a ratio, for example, 98%, which is not limited in this embodiment.

[0115] Step S620: If the second comparison result indicates that among the multiple commonly used path data, there are commonly used path data whose similarity value with the already driven path is greater than the third preset threshold, then the driving path mode is determined to be a commonly used driving path mode.

[0116] Specifically, the vehicle starts moving from a standstill, and the historical driving data does not include frequently used route data where the starting time of the current journey is the same as the starting time of the current journey. After the vehicle has traveled s1km, the already traveled route data can be obtained. The vehicle can compare this s1km of already traveled route data with the starting portion of s1km in multiple frequently used route data sets. If there is a frequently used route data set where the similarity value between the s1km route and the already traveled route is greater than a third preset threshold, then the driving route mode is determined to be a frequently used driving route mode. If there is no frequently used route data set where the similarity value between the s1km route and the already traveled route is greater than the third preset threshold, then the driving route mode is determined to be a non-frequently used driving route mode without navigation. The weight, the third preset threshold, can be a ratio, for example, 98%.

[0117] Optionally, for step S610, if there is no common path data where the similarity value between the path at s0km and the already driven path in step S610 is greater than the second preset threshold, then it is necessary to wait until the vehicle continues to drive until s1km (s1>s0) before determining the vehicle's driving path mode according to the steps in step S620.

[0118] like Figure 7 As shown in the figure, this application embodiment also provides a flowchart for determining the driving route mode in a navigation-free mode. The flowchart may include steps S710 to S760, specifically:

[0119] Step S710: Obtain historical driving data and traveled route data.

[0120] Step S720: Determine whether there is frequently used route data in the historical driving data whose travel time period overlaps with the travel time period of the already traveled route data. If it exists, proceed to step S730; if it does not exist, proceed to step S740.

[0121] Step S730: Determine whether there is common route data with overlapping travel time periods where the similarity value between the starting part of s0km and the already traveled route data of s0km is greater than a second preset threshold. If so, proceed to step S750; otherwise, proceed to step S740.

[0122] Step S740: Determine whether there is any frequently used path data in the historical driving data where the similarity value between the starting part of s1km and the already driven path data of s1km is greater than a third preset threshold. If so, proceed to step S750; otherwise, proceed to step S760.

[0123] Step S750: Determine the driving route mode as the common driving route mode.

[0124] Step S760: Determine the driving route mode as an uncommon driving route mode without navigation.

[0125] In this embodiment of the application, when the driver switches the navigation route midway, the new remaining route planning data is matched with multiple commonly used route data in the historical driving data, and the driving route mode is switched according to the matching result.

[0126] In this embodiment, when the driver switches from navigation mode to no navigation mode midway through the journey, if the remaining path length in the route planning data is less than or equal to 5% of the total path length, the driving route mode before the navigation mode switch will be maintained. This 5% can be any other percentage; this embodiment uses 5% as an example and is not limited to any particular percentage.

[0127] In this embodiment of the application, when the driver switches from navigation mode to no navigation mode midway, if the remaining path length in the path planning data is greater than 5% of the total path length, the driving path mode is judged and updated in the no navigation state.

[0128] In this embodiment of the application, if the vehicle is still driving after completing the route planning based on the navigation mode, the driving route mode is re-evaluated and updated according to the no-navigation state.

[0129] This method allows the driving route mode to still be determined after the driver switches navigation modes, enabling the embodiments of this application to cope with different usage scenarios and improving the compatibility of the vehicle's driving modes.

[0130] like Figure 8As shown in the figure, this application embodiment also provides a flowchart for determining the driving route pattern. The flowchart may include steps S810 to S860, specifically:

[0131] Step S810: Obtain navigation mode.

[0132] Step S820: Determine whether the navigation mode is a navigation mode. If yes, proceed to step S830; otherwise, proceed to step S850.

[0133] Step S830: Obtain route planning data and determine whether the route planning data is frequently used route data. If yes, proceed to step S860; otherwise, proceed to step S870.

[0134] Step S840: Obtain the route data already traveled in the no-navigation mode.

[0135] Step S850: Determine whether the traveled route data is frequently used route data. If yes, proceed to step S860; otherwise, proceed to step S880.

[0136] Step S860: Determine the driving route mode as the common driving route mode.

[0137] Step S870: Determine the driving route mode as a non-standard driving route mode with navigation.

[0138] Step S880: Determine the driving route mode as an uncommon driving route mode without navigation.

[0139] This method can improve the accuracy of judging driving path patterns.

[0140] Please see Figure 9 , Figure 9 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 9 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S210 to S220, steps S910 to S920 and step S240.

[0141] Steps S910 to S920 will be described in detail below:

[0142] Step S910: Calculate the correction values ​​for road condition information, environment information, vehicle status information, and driver style information based on the parameter values ​​of road condition information, environment information, vehicle status information, and driver style information, and the corresponding multiple weighting coefficients.

[0143] The parameter values ​​of the current driving influencing factors include those of road condition information, environmental information, vehicle status information, and driver style information.

[0144] In this embodiment of the application, the correction value for road condition information can be SOC. r or Pedal r The correction value for environmental information can be SOC. e or Pedal e The correction value for vehicle status information can be SOC. v or Pedal v The correction value for driver style information can be SOC. d or Pedal d .

[0145] The parameter values ​​for this road condition information may include the current road slope parameter (X). slope ), parameters of traffic congestion on the current remaining route (X) traffic ) and the current remaining path distance parameter (X) distance The environmental information includes the current ambient temperature parameter (Y). temp ), Current vehicle driving environment weather parameters (Y) weather ), Current vehicle driving environment wind direction parameters (Y) wind ) and the current vehicle driving environment altitude parameters (Y altitud The vehicle status information includes the current vehicle speed parameter (M). speed ), Current vehicle remaining SOC parameters (M) SOC ), Current vehicle air conditioning status parameters (M) aircond The weighting coefficients (M) of the current vehicle's driving resistance parameter and the driving resistance parameter. resistance Driver style information includes the probability (N) that the driver will charge their phone after driving. charge ) and driver style parameters (N style ).

[0146] Step S920: Update the driving parameter thresholds based on the correction values ​​for road condition information, environmental information, vehicle status information, and driver style information.

[0147] In this embodiment of the application, in order to ensure smooth driving and energy-saving effect, and to prevent the vehicle driving mode from switching frequently due to the frequent switching of driving path mode, the driving parameter threshold can be updated at a certain frequency, such as once every 500ms. This can prevent the frequent switching of the vehicle driving mode.

[0148] This method allows for updating driving parameter thresholds based on multiple weighting coefficients and the parameter values ​​of multiple current driving influencing factors, resulting in more accurate driving parameter thresholds and more reliable determination of the vehicle's driving mode.

[0149] Please see Figure 10 , Figure 10 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 10 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in a vehicle and includes steps S210 to S220, steps S1010 to S1020, step S920 and step S240.

[0150] Steps S1010 to S1020 will be described in detail below:

[0151] Step S1010: Calculate the correction values ​​for the first road condition information, the first environment information, the first vehicle state information, and the first driver style information based on the first set of weighting coefficients and the parameter values ​​for road condition information, environment information, vehicle state information, and driver style information. Update the battery charge threshold based on the correction values ​​for the first road condition information, the first environment information, the first vehicle state information, and the first driver style information.

[0152] The correction value for the first traffic information is SOC. r The correction value for the first environmental information is SOC. e The correction value for the first vehicle status information is SOC. v The correction value for the first driver's style information is SOC. d .

[0153] Specifically, after updating the battery charge threshold, the State of Charge (SOC) can be obtained. new The SOC new This is the updated battery charge threshold. The specific formula is:

[0154] SOC new =SOC init +SOC r +SOC e +SOC v +SOC d

[0155] Among them, SOC r =a1*X slope +a2*X traffic +a3*X distance

[0156] SOCe =b1*Y temp +b2*Y weather +b3*Y wind +b4*Y altitude

[0157] SOC v =c1*M speed +c2*M soc +c3*M aircond +c4*M resistance

[0158] SOC d =d1*N charge +d2*N style

[0159] SOC new ∈[SOC minLimit SOC maxLimit ]

[0160] Among them, SOC init This represents the initial battery charge threshold, i.e., the SOC after the last update. new SOC minLimit and SOC maxLimit Represented as SOC new The upper and lower limits of the range, when SOC new If the upper or lower limit is exceeded, the nearest limit will be used.

[0161] The specific definitions of each parameter are as follows:

[0162] X slope Represented as the current road slope parameter, X slope =±G slope *hx, takes a + value in the SOC threshold (i.e., battery charge threshold) calculation; takes a - value in the accelerator pedal opening threshold calculation (the same applies below); G slope This represents the current percentage of the vehicle's gradient, especially when driving uphill. Downhill hx represents the percentage value of the corresponding accelerator pedal opening or SOC (State of Charge), which is usually calibrated (the same applies below). That is, when the vehicle is going uphill, the accelerator pedal opening threshold decreases and the SOC threshold increases, making it easier for the vehicle to start the engine; when the vehicle is going downhill, the accelerator pedal opening threshold increases and the SOC threshold decreases, making it easier for the vehicle to drive in pure electric mode.

[0163] X traffic X represents the parameter indicating traffic congestion on the remaining path. traffic =±G traffic *h, G trafficThis represents a percentage of road congestion. In other words, the more congested the traffic, the lower the throttle opening threshold, the higher the SOC threshold, and the easier it is to start the engine. When driving on unused routes without navigation, X... traffic Take 0.

[0164] X distance Represented as the remaining path distance parameter X distance =±G distance *hx, G distance X represents the percentage of remaining path distance; more remaining path means a lower throttle opening threshold, a higher SOC threshold, and easier engine start. When on unused driving routes without navigation, X... distance Take 0.

[0165] Y temp Y represents the current ambient temperature parameter for the vehicle's operation. temp =±G temp *hy, G temp A parameter indicating the temperature of the road currently in use. μ and σ represent the mean and standard deviation (which can be calibrated) of the normal distribution of temperature, and hy represents the percentage value of the corresponding accelerator pedal opening or SOC (State of Charge), which can usually be calibrated (the same applies below). That is, the higher or lower the ambient temperature, the lower the accelerator pedal opening threshold and the higher the SOC threshold, making it easier for the vehicle to start the engine.

[0166] Y weather Y represents the current weather parameters for the vehicle's driving environment. weather =±G weather *hy, G weather This indicates the current road weather parameters, categorized into five types: heavy rain, moderate rain, light rain, cloudy, and sunny, each corresponding to a different percentage. Specifically, in rainy weather, the throttle opening threshold decreases, the SOC threshold increases, and the vehicle starts the engine more easily.

[0167] Y wind Y represents the wind direction parameter in the current vehicle driving environment. wind =±G wind *hy, G wind This indicates the wind direction parameter for the current driving road. The weather is divided into five types: strong headwind, headwind, no wind, tailwind, and strong tailwind, each corresponding to a different percentage. Specifically, in a strong headwind, the throttle opening threshold decreases, the SOC threshold increases, and the vehicle is easier to start the engine.

[0168] Y altitude Y represents the altitude parameter of the current vehicle driving environment. altitude =±G altitude *hy, G altitude This indicates the current elevation parameters of the road being driven on, where In other words, the higher the altitude, the greater the throttle opening threshold and the smaller the SOC threshold, making it more difficult for the vehicle to start the engine.

[0169] M speed M represents the current vehicle speed parameter. speed =±G speed *hm, G speed This represents a percentage of the current vehicle speed, where hm represents the percentage value of the corresponding accelerator pedal opening or SOC (State of Charge), and the value is usually calibrated (the same applies below). That is, the higher the vehicle speed, the lower the accelerator pedal opening threshold and the higher the SOC threshold, making it easier to start the engine.

[0170] M SOC M represents the remaining SOC parameter of the vehicle at present. soc =±G soc *hm, G soc This represents a percentage of the current vehicle speed, where In other words, the lower the remaining SOC, the lower the throttle opening threshold and the higher the SOC threshold, making it easier for the vehicle to start the engine.

[0171] M aircond M represents the air conditioning status parameters for the current vehicle operation. aircond =±G aircond *hm, G aircond This represents a percentage of the air conditioning status parameters for the current vehicle operation, where... In other words, the higher the power of the air conditioner, the lower the throttle opening threshold and the higher the SOC threshold, making it easier for the vehicle to start the engine.

[0172] M resistance M represents the driving resistance parameter of the vehicle at present. resistance =±G resistance *hm, G resistance This represents a percentage of the vehicle's current drag parameters, primarily derived from vehicle weight and frontal area. In other words, higher drag results in a lower throttle opening threshold, a higher State of Charge (SOC) threshold, and makes it easier to start the engine.

[0173] N charge N represents the probability that the driver will charge the battery after driving. charge =±G charge *hn, G chargeThis indicates the probability that the vehicle will be charged after this trip, obtained from historical data statistics. hn represents the percentage value of the corresponding accelerator pedal opening or State of Charge (SOC), and the value is usually calibrated (the same applies below). That is, the lower the probability of charging after driving, the lower the accelerator pedal opening threshold and the higher the SOC threshold, making it easier to start the engine. When driving on an uncommon route, Ncharge is 0.

[0174] Nstyle is a driver style parameter, N style =±G style *hn, G style This indicates the current driver style, categorized into three types: aggressive, normal, and calm, each corresponding to a different percentage. Driver style data is categorized using historical and current driving data; before a classification is obtained, the parameters for the normal type are used. That is, a more aggressive driver style results in a lower throttle opening threshold, a higher State of Charge (SOC) threshold, and easier engine start.

[0175] Step S1020: Calculate the correction values ​​for the second road condition information, the second environment information, the second vehicle state information, and the second driver style information based on the second set of weighting coefficients and the parameter values ​​for road condition information, environment information, vehicle state information, and driver style information. Update the throttle opening threshold based on the correction values ​​for the second road condition information, the second environment information, the second vehicle state information, and the second driver style information.

[0176] The correction value for the second road condition information is Pedal. r The correction value for the second environmental information is Pedal. e The correction value for the second vehicle status information is Pedal. v The correction value for the second driver style information is Pedal. d .

[0177] Specifically, after the vehicle updates its battery charge threshold, Pedal can be obtained. new The Pedal new This is the updated battery charge threshold. The specific formula is:

[0178] Pedal new =Pedal init +Pedal r +Pedal e +Pedal v +Pedal d

[0179] Among them, Pedal r =A1*X slope+A2*X traffic +A3*X distance

[0180] Pedal e =B1*Y temp +B2*Y wearher +B3*Y wind +B4*Y altitude

[0181] Pedal v =C1*M speed +C2*M soc +C3*M aircond +C4*M resistance

[0182] Pedal d =D1*N charge +D2*N style

[0183] Pedal new ∈[Pedal minLimit Pedal maxLimit ]

[0184] Among them, Pedal init This represents the initial throttle opening threshold, i.e., the Pedal value after the last update. new Pedal minLimit and Pedal maxLimit Represented as Pedal new The upper and lower limits of the range, when Pedal new If the upper or lower limit is exceeded, the nearest limit will be used.

[0185] This method can calculate the real-time battery charge threshold and throttle opening threshold to determine the most suitable vehicle driving mode in real time, which helps to improve the accuracy of vehicle driving mode determination.

[0186] Please see Figure 11 , Figure 11 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 11 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S210 to S230 and steps S1110 to S1120.

[0187] Steps S1110 to S1120 will be described in detail below:

[0188] Step S1110: Obtain actual driving parameter values.

[0189] The actual driving parameters can include battery charge and throttle opening. Battery charge is the remaining charge of the vehicle's battery, and throttle opening is the depth to which the driver currently depresses the accelerator pedal.

[0190] Step S1120: Determine the vehicle's overall driving mode based on the relationship between driving parameter thresholds and actual driving parameters, and control the switching of the vehicle's overall driving mode.

[0191] In this embodiment of the application, in order to ensure smooth driving and energy-saving effect, and to prevent frequent switching of the vehicle driving mode, the time interval between switching of the vehicle driving mode should be greater than a certain interval, for example, judging whether the vehicle driving mode needs to be switched every 5 seconds.

[0192] This method allows the vehicle to acquire actual driving parameters and determine the overall driving mode based on the relationship between driving parameter thresholds and actual driving parameters. This enables real-time determination of the overall driving mode and improves the accuracy of overall driving mode determination.

[0193] Please see Figure 12 , Figure 12 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 12 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S210 to S230, step S1110 and steps S1210 to S1220.

[0194] Steps S1210 to S1220 will be described in detail below:

[0195] Step S1210: If the battery charge value is greater than or equal to the battery charge threshold and the throttle opening value is less than or equal to the throttle opening threshold, then the vehicle driving mode is determined to be the engine off state.

[0196] For example, if the battery charge threshold is 15% and the throttle opening threshold is 50%, and the actual battery charge is 30% and the throttle opening value is 40%, then the vehicle can determine that the overall driving mode is engine off.

[0197] Step S1220: If the battery charge value is less than the battery charge threshold and / or the throttle opening value is greater than the throttle opening threshold, then the vehicle driving mode is determined to be the engine-on state.

[0198] For example, if the actual battery charge is 10% and the throttle opening is 40%, then the vehicle driving mode is determined to be engine-on.

[0199] For example, if the actual battery charge is 10% and the throttle opening is 60%, then the vehicle driving mode is determined to be engine-on.

[0200] This method allows the vehicle to determine its overall driving mode based on the relationship between driving parameter thresholds and actual driving parameters. This enables real-time determination of the overall driving mode, improving its accuracy. Furthermore, the increased accuracy allows the vehicle to switch driving modes as needed, conserving power.

[0201] Please see Figure 13 , Figure 13 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 13 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S210 to S240 and steps S1310 to S1320.

[0202] Steps S1310 to S1320 will be described in detail below:

[0203] Step S1310: Obtain driving data, which is generated after the vehicle completes its journey based on the route planning data and / or the route already traveled.

[0204] The driving data may include the driving route data of this vehicle trip, as well as the corresponding related data, including driving time period, road condition information, environmental information, vehicle status information, and driver style information.

[0205] The driver style information includes whether the vehicle was charged after the driver started driving, as well as the charging time and charging type (fast or slow). Furthermore, the vehicle can generate driving style parameters based on the driving time period, road conditions, environmental information, vehicle status information, and driver style information.

[0206] Step S1320: Based on the relationship between driving data and historical driving data, merge the driving data and historical driving data.

[0207] In other words, driving data is saved to historical driving data.

[0208] This method allows us to obtain the vehicle's driving data for the current trip and add it to the historical driving data, which is helpful for judging the driving path pattern when the vehicle travels again.

[0209] Please see Figure 14 , Figure 14 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 14 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S210 to S240, step S1310, and steps S1410 to S1430.

[0210] Steps S1410 to S1430 will be described in detail below:

[0211] Step S1410: If there is a first frequently used path data in the historical driving data that matches the driving path data, then add the driving association data corresponding to the driving path information to the driving association data corresponding to the first frequently used path data.

[0212] If the first frequently used route data matches the driving route data, it means that the vehicle is driving according to the first frequently used route data again. Therefore, the driving association data obtained from this driving can be added to the driving association data corresponding to the first frequently used route data.

[0213] Step S1420: If there is no frequently used or infrequently used route data that matches the driving route data in the historical driving data, then add the driving data to the historical driving data.

[0214] If there is no frequently used or infrequently used route data that matches the driving route data in the historical data, a new driving route data can be created in the historical route data, and the number of times the driving route data is driven is one.

[0215] Step S1430: If there is a first unused path data in the historical driving data that matches the driving path data, then add the driving association data corresponding to the driving path data to the driving association data corresponding to the first unused path data.

[0216] The number of trips taken on the first uncommon route is less than a preset number, for example, less than 5 times.

[0217] In this embodiment of the application, after adding the driving association data corresponding to the driving route data to the driving association data corresponding to the first unused route data, if the number of times the first unused route data is driven is still less than 5, the first unused route data will still be stored as unused route data in the historical driving data.

[0218] In this embodiment of the application, after adding the driving association data corresponding to the driving route data to the driving association data corresponding to the first unused route data, if the number of driving times of the first unused route data is still greater than or equal to 5 times, the first unused route data can be marked as frequently used route data, and thereafter it will be saved in the historical driving data as frequently used route data.

[0219] In this embodiment, for the second unused route data in the historical driving data, if a preset time period has elapsed since its last use and it has not been used again, the second unused route data can be deleted from the historical driving data. The preset time period can be set by those skilled in the art and is not limited here. In this way, vehicle storage space can be saved by deleting infrequently used route data.

[0220] This method allows the vehicle to integrate current driving data with historical driving data, increasing the richness of historical driving data and making the judgment of the vehicle's driving mode more accurate in the next test.

[0221] Please see Figure 15 , Figure 15 A flowchart illustrating a method for controlling a vehicle's driving mode, as shown in another exemplary embodiment of this application. Figure 15 As shown, in an exemplary embodiment, the vehicle driving mode control method can be implemented in the vehicle and includes steps S1510 to S1580.

[0222] Steps S1510 to S1580 will be described in detail below:

[0223] Step S1510: Obtain historical driving data.

[0224] Step S1520: Determine the driving route mode based on the route planning data and / or the route already driven, road condition information, environmental information and historical driving data of the navigation mode.

[0225] Step S1530: Update driving route mode.

[0226] Step S1540: Calculate the driving parameter threshold based on the multiple weight coefficients corresponding to the driving path mode and the parameter values ​​of the current multiple driving influencing factors.

[0227] Step S1550: Update driving parameter thresholds.

[0228] Step S1560: Control the switching of the vehicle's overall driving mode based on driving parameter thresholds.

[0229] Step S1570: Obtain driving data.

[0230] Step S1580: Merge driving data with historical driving data.

[0231] This method allows the vehicle to control the switching of driving modes based on real-time data, improving the accuracy of determining the driving mode. Furthermore, driving data can be fused with historical driving data to enrich the historical driving data.

[0232] Figure 16 This is a schematic diagram illustrating the structure of a vehicle driving mode control device according to an exemplary embodiment. Figure 16 As shown, in an exemplary embodiment, the control device for the vehicle driving mode includes:

[0233] The processing unit 1610 is used to determine the driving route mode of the vehicle based on the vehicle's navigation mode and historical driving data.

[0234] The acquisition unit 1620 is used to acquire multiple weight coefficients corresponding to the driving path mode, and the parameter values ​​of the current driving influence factors corresponding to the multiple weight coefficients respectively. The driving influence factors are used to characterize the factors that affect the driving state of the vehicle.

[0235] The processing unit 1610 is also used to update the driving parameter threshold based on the parameter values ​​of multiple weighting coefficients and multiple current driving influencing factors. The driving parameter threshold is used to characterize the switching threshold of the vehicle driving mode.

[0236] The control unit 1630 is used to control the switching of the vehicle's overall driving mode based on driving parameter thresholds.

[0237] In one embodiment of this application, based on the aforementioned scheme, the navigation mode includes a navigation mode, and the historical driving data includes multiple commonly used route data; if the navigation mode is a navigation mode, the acquisition unit 1620 is further used to acquire route planning data; the comparison unit 1640 is used to compare the route planning data with multiple commonly used route data to obtain a first comparison result; the processing unit 1610 is further used to determine the driving route mode based on the first comparison result.

[0238] In one embodiment of this application, based on the aforementioned scheme, the processing unit 1610 is further configured to determine the driving path mode as a common driving path mode if the first comparison result indicates that the common path data among the multiple common path data includes common path data whose similarity value with the path planning data is greater than or equal to the first similarity threshold; and to determine the driving path mode as a non-common driving path mode with navigation if the first comparison result indicates that the similarity value between the path planning data and each common path data is less than the first similarity threshold.

[0239] In one embodiment of this application, based on the aforementioned scheme, the navigation mode includes a no-navigation mode, and the historical driving data includes multiple commonly used route data; if the navigation mode is a no-navigation mode, the acquisition unit 1620 is further used to acquire the vehicle's driven route data, which is generated by the vehicle's positioning system; the comparison unit 1640 is further used to compare the driven route data with multiple commonly used route data to obtain a second comparison result; the processing unit 1610 is further used to determine the driving route mode based on the second comparison result.

[0240] In one embodiment of this application, based on the aforementioned scheme, the historical driving data also includes the driving time period corresponding to each frequently used route data, and the driven route data includes the time period of the driven route; the processing unit 1610 is further configured to determine the driving route mode as a frequently used driving route mode if the second comparison result indicates that the driving time period of the multiple frequently used route data overlaps with the time period of the driven route data, and the similarity value between the route and the driven route is greater than a second preset threshold; and to determine the driving route mode as a frequently used driving route mode if the second comparison result indicates that the driving route data of the multiple frequently used route data includes the similarity value between the route and the driven route is greater than a third preset threshold.

[0241] In one embodiment of this application, based on the aforementioned scheme, the parameter values ​​of the current driving influencing factors include parameter values ​​of road condition information, environmental information, vehicle status information, and driver style information; the processing unit 1610 is further configured to calculate correction values ​​for road condition information, environmental information, vehicle status information, and driver style information respectively based on the parameter values ​​of road condition information, environmental information, vehicle status information, and driver style information and the corresponding multiple weight coefficients; and update the driving parameter thresholds based on the correction values ​​of road condition information, environmental information, vehicle status information, and driver style information.

[0242] In one embodiment of this application, based on the aforementioned scheme, the driving parameter thresholds include a battery charge threshold and a throttle opening threshold; multiple weighting coefficients include a first set of weighting coefficients and a second set of weighting coefficients, the first set of weighting coefficients being different from the second set of weighting coefficients; the processing unit 1610 is further configured to calculate correction values ​​for the first road condition information, the first environment information, the first vehicle state information, and the first driver style information based on the first set of weighting coefficients and the parameter values ​​of road condition information, environment information, vehicle state information, and driver style information, so as to update the battery charge threshold based on the correction values ​​of the first road condition information, the first environment information, the first vehicle state information, and the first driver style information; and to calculate correction values ​​for the second road condition information, the second environment information, the second vehicle state information, and the second driver style information based on the second set of weighting coefficients and the parameter values ​​of road condition information, environment information, vehicle state information, and driver style information, so as to update the throttle opening threshold based on the correction values ​​of the second road condition information, the second environment information, the second vehicle state information, and the second driver style information.

[0243] In one embodiment of this application, based on the aforementioned scheme, the acquisition unit 1620 is further configured to acquire actual driving parameter values; the processing unit 1610 is further configured to determine the vehicle's overall driving mode based on the relationship between the driving parameter threshold and the actual driving parameters, and to control the switching of the vehicle's overall driving mode.

[0244] In one embodiment of this application, based on the aforementioned scheme, the driving parameter thresholds include a battery charge threshold and a throttle opening threshold; the actual driving parameter values ​​include a battery charge value and a throttle opening value; the vehicle driving mode includes an engine-on state and an engine-off state; the processing unit 1610 is further configured to determine the vehicle driving mode as an engine-off state if the battery charge value is greater than or equal to the battery charge threshold and the throttle opening value is less than or equal to the throttle opening threshold; and to determine the vehicle driving mode as an engine-on state if the battery charge value is less than the battery charge threshold and / or the throttle opening value is greater than the throttle opening threshold.

[0245] In one embodiment of this application, based on the aforementioned scheme, after determining the vehicle's overall driving mode according to the relationship between driving parameter thresholds and actual driving parameters, the acquisition unit 1620 is further configured to acquire driving data, which is generated after the vehicle completes driving based on the path planning data and / or the already driven path data; the processing unit 1610 is further configured to perform fusion processing on the driving data and historical driving data according to the relationship between the driving data and historical driving data.

[0246] In one embodiment of this application, based on the aforementioned scheme, the driving data includes the current vehicle's driving path data and driving association data corresponding to the driving path information; the historical driving data includes multiple commonly used path data and driving association data corresponding to each commonly used path data; the historical driving data also includes one or more uncommon driving path data and uncommon driving association data corresponding to each uncommon driving path data; the processing unit 1610 is further configured to: if there is a first commonly used path data in the historical driving data whose path matches the driving path data, then add the driving association data corresponding to the driving path information to the driving association data corresponding to the first commonly used path data; if there is no commonly used path data or uncommon path data in the historical driving data whose path matches the driving path data, then add the driving data to the historical driving data; if there is a first uncommon path data in the historical driving data whose path matches the driving path data, then add the driving association data corresponding to the driving path information to the driving association data corresponding to the first uncommon path data.

[0247] It should be noted that the vehicle driving mode control device provided in the above embodiments and the vehicle driving mode control method provided in the above embodiments belong to the same concept. The specific way in which each module and unit performs operations has been described in detail in the method embodiments, and will not be repeated here.

[0248] Embodiments of this application also provide an electronic device, including: one or more processors; and a storage device for storing one or more programs, which, when executed by one or more processors, cause the electronic device to implement the vehicle driving mode control method provided in the above embodiments.

[0249] Figure 17 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0250] It should be noted that, Figure 17 The computer system 1700 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0251] like Figure 17As shown, the computer system 1700 includes a Central Processing Unit (CPU) 1701, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, based on programs stored in Read-Only Memory (ROM) 1702 or programs loaded from storage portion 1708 into Random Access Memory (RAM) 1703. The RAM 1703 also stores various programs and data required for system operation. The CPU 1701, ROM 1702, and RAM 1703 are interconnected via a bus 1704. An Input / Output (I / O) interface 1705 is also connected to the bus 1704.

[0252] The following components are connected to I / O interface 1705: an input section 1706 including a keyboard, mouse, etc.; an output section 1707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1708 including a hard disk, etc.; and a communication section 1709 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 1709 performs communication processing via a network such as the Internet. Drive 1710 is also connected to I / O interface 1705 as needed. Removable media 1711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1710 as needed so that computer programs read from them can be installed into storage section 1708 as needed.

[0253] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1709, and / or installed from removable medium 1711. When the computer program is executed by central processing unit (CPU) 1701, it performs various functions defined in the system of this application.

[0254] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. For example, a computer-readable medium can be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0255] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0256] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0257] Another aspect of this application provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the cross-domain data transfer method as described above. This computer-readable medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0258] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable medium. A processor of a computer device reads the computer instructions from the computer-readable medium and executes the computer instructions, causing the computer device to perform the cross-domain data transfer method provided in the various embodiments described above.

[0259] The above description is merely a preferred exemplary embodiment of this application and is not intended to limit the implementation of this application. Those skilled in the art can easily make corresponding modifications or alterations based on the main concept and spirit of this application. Therefore, the scope of protection of this application should be determined by the scope of protection claimed in the claims.

Claims

1. A method for controlling a vehicle's driving mode, characterized in that, include: The driving route mode of the vehicle is determined based on the vehicle's navigation mode and historical driving data. The navigation mode includes multiple navigation modes, and the historical driving data includes multiple commonly used route data. Obtain multiple weight coefficients corresponding to the driving path mode, and parameter values ​​of the current driving influence factors corresponding to the multiple weight coefficients respectively. The driving influence factors are used to characterize the factors affecting the driving state of the vehicle. The driving parameter threshold is updated based on the multiple weighting coefficients and the parameter values ​​of the current multiple driving influencing factors. The driving parameter threshold is used to characterize the switching threshold of the vehicle driving mode. The switching of the vehicle's overall driving mode is controlled based on the driving parameter thresholds. The step of determining the vehicle's driving route mode based on the vehicle's navigation mode and historical driving data includes: If the navigation mode is the specified navigation mode, then obtain the path planning data; The path planning data is compared with the multiple commonly used path data to obtain the first comparison result; The driving path pattern is determined based on the first comparison result.

2. The method according to claim 1, characterized in that, Determining the driving route pattern based on the first comparison result includes: If the first comparison result indicates that the multiple commonly used path data include commonly used path data with a similarity value greater than or equal to the path planning data, then the driving path pattern is determined to be a commonly used driving path pattern. If the first comparison result indicates that the similarity value between the path planning data and each commonly used path data is less than the first similarity threshold, then the driving path mode is determined to be a non-common driving path mode with navigation.

3. The method according to claim 1, characterized in that, The navigation mode includes a no-navigation mode, and the historical driving data includes multiple commonly used route data; determining the vehicle's driving route mode based on the vehicle's navigation mode and historical driving data includes: If the navigation mode is the no navigation mode, then the vehicle's traveled route data is obtained, which is generated by the vehicle's positioning system; The traveled route data is compared with the multiple commonly used route data to obtain a second comparison result; The driving path pattern is determined based on the second comparison result.

4. The method according to claim 3, characterized in that, The historical driving data also includes the driving time period corresponding to each frequently used route data, and the driven route data includes the time period of the driven route; Determining the driving route pattern based on the second comparison result includes: If the second comparison result indicates that the multiple commonly used path data include commonly used path data whose driving time period overlaps with the driving time period of the already driven path data, and whose path similarity value with the already driven path is greater than the second preset threshold, then the driving path mode is determined to be a commonly used driving path mode. If the second comparison result indicates that the multiple commonly used path data includes commonly used path data whose similarity value with the already driven path is greater than a third preset threshold, then the driving path mode is determined to be a commonly used driving path mode.

5. The method according to claim 1, characterized in that, The parameter values ​​of the current driving influencing factors include the parameter values ​​of road condition information, environmental information, vehicle status information, and driver style information. The step of updating the driving parameter threshold based on the multiple weighting coefficients and the parameter values ​​of the current multiple driving influencing factors includes: Based on the parameter values ​​of the road condition information, environmental information, vehicle status information, and driver style information, and the corresponding multiple weighting coefficients, the correction values ​​of the road condition information, environmental information, vehicle status information, and driver style information are calculated respectively. The driving parameter thresholds are updated based on the correction values ​​for road condition information, environmental information, vehicle status information, and driver style information.

6. The method according to claim 5, characterized in that, The driving parameter thresholds include battery charge thresholds and throttle opening thresholds; the multiple weighting coefficients include a first set of weighting coefficients and a second set of weighting coefficients, wherein the first set of weighting coefficients is different from the second set of weighting coefficients. The step of calculating the corrected values ​​for road condition information, environmental information, vehicle status information, and driver style information based on the parameter values ​​of the vehicle's road condition information, environmental information, vehicle status information, and driver style information, and corresponding weighting coefficients, includes: Based on the first set of weighting coefficients and the parameter values ​​of the road condition information, the environmental information, the vehicle status information, and the driver style information, calculate the correction values ​​of the first road condition information, the first environmental information, the first vehicle status information, and the first driver style information, and update the battery charge threshold based on the correction values ​​of the first road condition information, the first environmental information, the first vehicle status information, and the first driver style information. Based on the second set of weighting coefficients and the parameter values ​​of the road condition information, the environment information, the vehicle status information, and the driver style information, the correction values ​​of the second road condition information, the second environment information, the second vehicle status information, and the second driver style information are calculated, and the throttle opening threshold is updated based on the correction values ​​of the second road condition information, the second environment information, the second vehicle status information, and the second driver style information.

7. The method according to claim 1, characterized in that, The step of controlling the switching of the vehicle's overall driving mode based on the driving parameter threshold includes: Obtain actual driving parameters; Based on the relationship between the driving parameter threshold and the actual driving parameters, the overall driving mode of the vehicle is determined, and the switching of the overall driving mode of the vehicle is controlled.

8. The method according to claim 7, characterized in that, The driving parameter thresholds include battery charge thresholds and throttle opening thresholds; the actual driving parameters include battery charge value and throttle opening value; the vehicle driving modes include engine on state and engine off state. Determining the vehicle's overall driving mode based on the relationship between the driving parameter thresholds and the actual driving parameters includes: If the battery charge value is greater than or equal to the battery charge threshold, and the throttle opening value is less than or equal to the throttle opening threshold, then the vehicle driving mode is determined to be the engine off state. If the battery charge value is less than the battery charge threshold, and / or the throttle opening value is greater than the throttle opening threshold, then the vehicle driving mode is determined to be the engine-on state.

9. The method according to claim 8, characterized in that, After determining the vehicle's overall driving mode based on the relationship between the driving parameter thresholds and the actual driving parameters, the method further includes: Acquire driving data, which is generated after the vehicle completes its journey based on the route planning data and / or the route already traveled; Based on the relationship between the driving data and the historical driving data, the driving data and the historical driving data are fused together.

10. The method according to claim 9, characterized in that, The driving data includes the vehicle's current driving route data and the driving association data corresponding to the driving route information; the historical driving data includes multiple frequently used route data and the driving association data corresponding to each frequently used route data; the historical driving data also includes one or more rarely used driving route data and the rarely used driving association data corresponding to each rarely used driving route data. The step of fusing the driving data and the historical driving data based on the relationship between the driving data and the historical driving data includes: If there is a first frequently used path in the historical driving data that matches the driving path data, then the driving association data corresponding to the driving path information is added to the driving association data corresponding to the first frequently used path data. If there is no commonly used or uncommon route data in the historical driving data that matches the driving route data, then the driving data is added to the historical driving data. If there is a first unused path in the historical driving data that matches the driving path data, then the driving association data corresponding to the driving path information is added to the driving association data corresponding to the first unused path data.

11. A control device for a vehicle's driving mode, characterized in that, include: The processing unit is configured to determine the driving route mode of the vehicle based on the vehicle's navigation mode and historical driving data, wherein the navigation mode includes navigation patterns and the historical driving data includes multiple commonly used route data. The acquisition unit is used to acquire multiple weight coefficients corresponding to the driving path mode, and the parameter values ​​of the current driving influence factors corresponding to the multiple weight coefficients respectively. The driving influence factors are used to characterize the factors affecting the driving state of the vehicle. The processing unit is further configured to update the driving parameter threshold based on the multiple weighting coefficients and the parameter values ​​of the current multiple driving influencing factors, wherein the driving parameter threshold is used to characterize the switching threshold of the vehicle driving mode; The control unit is used to control the switching of the vehicle's overall driving mode according to the driving parameter thresholds; The step of determining the vehicle's driving route mode based on the vehicle's navigation mode and historical driving data includes: If the navigation mode is the specified navigation mode, then obtain the path planning data; The path planning data is compared with the multiple commonly used path data to obtain the first comparison result; The driving path pattern is determined based on the first comparison result.

12. An electronic device, characterized in that, include: One or more processors; A memory for storing one or more programs, which, when executed by the electronic device, cause the electronic device to implement the vehicle driving mode control method as described in any one of claims 1 to 10.

13. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the vehicle driving mode control method as described in any one of claims 1 to 10.

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