Driving style determination method and device, equipment, vehicle, medium and program product

Abstract

The invention provides a driving style determination method and device, equipment, a vehicle, a medium and a program product, and can be applied to the technical field of intelligent driving. In the method, data in each kind of initial driving data is filtered according to a reference average value and a reference standard deviation corresponding to at least one kind of initial driving data, and then the driving style of a user is determined in combination with the reference average value and the reference standard deviation. According to the scheme, the driving style of the user is determined through the reference average value, the reference standard deviation and the initial driving data of the user, the user does not need to determine according to the driving style name, and the accuracy of the determined driving style is effectively improved.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to a method, device, equipment, vehicle, medium and program product for determining driving style. Background Technology

[0002] With the development of technology, vehicles are becoming increasingly intelligent, not only recommending driving modes based on the user's driving style, but also suggesting driving routes based on that style.

[0003] In existing technologies, the method for determining driving style is usually to preset several driving styles in the vehicle, and the user selects their own driving style according to the name of the driving style, so that the vehicle can recommend driving mode or driving route.

[0004] In summary, the existing method for determining driving style relies on the user's choice of driving style name, resulting in low accuracy in the determined driving style. Summary of the Invention

[0005] This application provides a driving style determination method, apparatus, device, vehicle, medium, and program product to solve the problem that existing driving style determination methods rely on users to determine the driving style based on its name, resulting in low accuracy of the driving style.

[0006] In a first aspect, embodiments of this application provide a method for determining driving style, including:

[0007] Acquire at least one type of initial driving data;

[0008] For each type of initial driving data, the data in the initial driving data is filtered according to the reference average and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data;

[0009] The user's driving style is determined based on the reference average, reference standard deviation, and target driving data corresponding to each initial driving data.

[0010] In one specific implementation, the step of filtering the data in the initial driving data based on the reference average and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data includes:

[0011] For each data point in the initial driving data, a standard score is calculated based on the data point and the reference mean and reference standard deviation corresponding to the initial driving data.

[0012] Data with a standard score greater than a preset filtering threshold in the initial driving data is deleted to obtain the target driving data corresponding to the initial driving data.

[0013] In one specific implementation, determining the user's driving style based on the reference average, reference standard deviation, and target driving data corresponding to each initial driving data includes:

[0014] Based on the reference mean and reference standard deviation corresponding to each type of initial driving data, determine at least one style distinction threshold corresponding to each type of initial driving data;

[0015] Calculate the average value of the target driving data corresponding to each type of initial driving data to obtain the target data value corresponding to each type of initial driving data;

[0016] The user's driving style is determined based on at least one style distinction threshold and a target data value corresponding to each type of initial driving data.

[0017] In one specific implementation, at least one style distinction threshold corresponding to each initial driving data includes at least one of a first threshold, a second threshold, a third threshold, and a fourth threshold;

[0018] The first threshold is greater than the second threshold, the second threshold is greater than the third threshold, and the third threshold is greater than the fourth threshold;

[0019] The types of initial driving data include accelerator pedal opening, brake pedal opening, longitudinal acceleration, straight-line speed, corner exit speed, corner entry speed, and steering angle;

[0020] The step of determining the user's driving style based on at least one style differentiation threshold and a target data value corresponding to each initial driving data includes:

[0021] Based on at least one style distinction threshold and target data value corresponding to each initial driving data, if at least one of the preset first condition, preset second condition and preset third condition is met, then the user's driving style is determined to be a straight-line driving style.

[0022] The preset first condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than the second threshold corresponding to the accelerator pedal opening, the target data value corresponding to the brake pedal opening is greater than the second threshold corresponding to the brake pedal opening, the target data value corresponding to the longitudinal acceleration is greater than the second threshold corresponding to the longitudinal acceleration, and the target data value corresponding to the linear speed is greater than the second threshold corresponding to the linear speed.

[0023] The preset second condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than or equal to the third threshold corresponding to the accelerator pedal opening and less than or equal to the first threshold corresponding to the accelerator pedal opening; the target data value corresponding to the brake pedal opening is greater than or equal to the third threshold corresponding to the brake pedal opening and less than or equal to the first threshold corresponding to the brake pedal opening; the target data value corresponding to the longitudinal acceleration is greater than or equal to the third threshold corresponding to the longitudinal acceleration and less than or equal to the first threshold corresponding to the longitudinal acceleration; the target data value corresponding to the straight speed is greater than or equal to the third threshold corresponding to the straight speed and less than or equal to the first threshold corresponding to the straight speed; the target data value corresponding to the exit speed is less than the third threshold corresponding to the exit speed; and the target data value corresponding to the entry speed is less than the third threshold corresponding to the entry speed.

[0024] The preset third condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than or equal to the third threshold corresponding to the accelerator pedal opening and less than or equal to the first threshold corresponding to the accelerator pedal opening; the target data value corresponding to the brake pedal opening is greater than or equal to the third threshold corresponding to the brake pedal opening and less than or equal to the first threshold corresponding to the brake pedal opening; the target data value corresponding to the longitudinal acceleration is greater than or equal to the third threshold corresponding to the longitudinal acceleration and less than or equal to the first threshold corresponding to the longitudinal acceleration; the target data value corresponding to the linear speed is greater than or equal to the third threshold corresponding to the linear speed and less than or equal to the first threshold corresponding to the linear speed; and the target data value corresponding to the steering angle is less than the third threshold corresponding to the steering angle.

[0025] In one specific embodiment, the initial driving data also includes lateral acceleration, and the method further includes:

[0026] Based on at least one style distinction threshold and target data value corresponding to each initial driving data, if at least one of the preset fourth condition, preset fifth condition and preset sixth condition is met, then the user's driving style is determined to be a curve driving style.

[0027] The preset fourth condition is as follows: the target data value corresponding to the lateral acceleration is greater than the second threshold corresponding to the lateral acceleration, the target data value corresponding to the cornering speed is greater than the second threshold corresponding to the cornering speed, the target data value corresponding to the cornering speed is greater than the second threshold corresponding to the cornering speed, and the target data value corresponding to the steering angle is greater than the second threshold corresponding to the steering angle.

[0028] The preset fifth condition is as follows: the target data value corresponding to the lateral acceleration is greater than or equal to the third threshold corresponding to the lateral acceleration and less than or equal to the first threshold corresponding to the lateral acceleration; the target data value corresponding to the cornering speed is greater than or equal to the third threshold corresponding to the cornering speed and less than or equal to the first threshold corresponding to the cornering speed; the target data value corresponding to the cornering speed is greater than or equal to the third threshold corresponding to the cornering speed and less than or equal to the first threshold corresponding to the cornering speed; the target data value corresponding to the steering angle is greater than or equal to the third threshold corresponding to the steering angle and less than or equal to the first threshold corresponding to the steering angle; the target data value corresponding to the straight speed is greater than or equal to the fourth threshold corresponding to the straight speed and less than or equal to the second threshold corresponding to the straight speed; and the target data value corresponding to the longitudinal acceleration is greater than or equal to the fourth threshold corresponding to the longitudinal acceleration and less than or equal to the second threshold corresponding to the longitudinal acceleration.

[0029] The preset sixth condition is as follows: the target data value corresponding to lateral acceleration is greater than or equal to the third threshold corresponding to lateral acceleration and less than or equal to the first threshold corresponding to lateral acceleration; the target data value corresponding to cornering speed is greater than or equal to the third threshold corresponding to cornering speed and less than or equal to the first threshold corresponding to cornering speed; the target data value corresponding to cornering speed is greater than or equal to the third threshold corresponding to cornering speed and less than or equal to the first threshold corresponding to cornering speed; the target data value corresponding to steering angle is greater than or equal to the third threshold corresponding to steering angle and less than or equal to the first threshold corresponding to steering angle; the target data value corresponding to accelerator pedal opening is greater than or equal to the fourth threshold corresponding to accelerator pedal opening and less than or equal to the second threshold corresponding to accelerator pedal opening; and the target data value corresponding to brake pedal opening is greater than or equal to the fourth threshold corresponding to brake pedal opening and less than or equal to the second threshold corresponding to brake pedal opening.

[0030] In one specific embodiment, the method further includes:

[0031] Based on at least one style distinction threshold and target data value corresponding to each initial driving data, if it is determined that none of the preset first condition, the preset second condition, the preset third condition, the preset fourth condition, the preset fifth condition, and the preset sixth condition are met, then the user's driving style is determined to be a balanced driving style.

[0032] In one specific implementation, the at least one initial driving data is configured by the user.

[0033] In one specific implementation, the at least one initial driving data is the user's historical driving data.

[0034] In one specific implementation, the reference average value corresponding to each initial driving data is the average value of the initial driving data of multiple drivers;

[0035] The reference standard deviation for each initial driving data is the standard deviation of the initial driving data of the multiple drivers.

[0036] In one specific implementation, the reference mean and reference standard deviation corresponding to each initial driving data are preset values.

[0037] Secondly, embodiments of this application provide a driving style determination device, comprising:

[0038] The acquisition module is used to acquire at least one type of initial driving data;

[0039] Processing module, used for:

[0040] For each type of initial driving data, the data in the initial driving data is filtered according to the reference average and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data;

[0041] The user's driving style is determined based on the reference average, reference standard deviation, and target driving data corresponding to each initial driving data.

[0042] Thirdly, embodiments of this application provide an electronic device, including:

[0043] Processor, memory, communication interface;

[0044] The memory is used to store the executable instructions of the processor;

[0045] The processor is configured to execute the driving style determination method according to any one of the first aspects by executing the executable instructions.

[0046] Fourthly, embodiments of this application provide a vehicle, including an in-vehicle terminal;

[0047] The vehicle-mounted terminal is used to execute the driving style determination method described in any of the first aspects above.

[0048] Fifthly, embodiments of this application provide a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the driving style determination method described in any of the first aspects.

[0049] Sixthly, embodiments of this application provide a computer program product, including a computer program, which, when executed by a processor, is used to implement the driving style determination method described in any of the first aspects.

[0050] The driving style determination method, apparatus, device, vehicle, medium, and program product provided in this application determine the user's driving style by filtering data from each type of initial driving data based on a reference average and reference standard deviation corresponding to at least one type of initial driving data, and then combining the reference average and reference standard deviation. This solution determines the user's driving style using the reference average and reference standard deviation, along with the initial driving data, eliminating the need for the user to determine the style based on a driving style name, thus effectively improving the accuracy of the determined driving style. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A flowchart illustrating an embodiment of the driving style determination method provided in this application;

[0053] Figure 2 A flowchart illustrating Embodiment 2 of the driving style determination method provided in this application;

[0054] Figure 3 A schematic diagram of the structure of an embodiment of the driving style determination device provided in this application;

[0055] Figure 4 This is a schematic diagram of the structure of an electronic device provided in this application. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments made by those skilled in the art under the guidance of these embodiments are within the scope of protection of this application.

[0057] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0058] With the development of technology, vehicles are becoming increasingly intelligent, not only recommending driving modes based on the user's driving style, but also suggesting driving routes based on that style.

[0059] In existing technologies, the determination of driving style typically involves several preset driving styles in the vehicle. The user selects their preferred driving style based on its name, and the vehicle then recommends driving modes or routes. However, because the driving style is determined by the user based on its name and personal experience, the accuracy of the determined driving style is relatively low.

[0060] To address the problems existing in the prior art, the inventors, during their research on driving style determination methods, discovered that to improve the accuracy of the determined driving style, it can be determined based on initial driving data, such as accelerator pedal opening, brake pedal opening, longitudinal acceleration, lateral acceleration, straight-line speed, corner exit speed, corner entry speed, and steering angle. The initial driving data can be the user's historical driving data or data configured by the user. After determining at least one style differentiation threshold and a target data value corresponding to each type of initial driving data, the user's driving style is determined based on the relationship between the target value and the style differentiation threshold. Based on the above inventive concept, the driving style determination scheme in this application was designed.

[0061] The driving style determination method in this application can be implemented by an in-vehicle terminal, or by a computer, server, vehicle, etc. This application does not limit it. The following explanation uses an in-vehicle terminal as an example.

[0062] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0063] The following provides examples illustrating the application scenarios of the driving style determination method provided in this application.

[0064] For example, in this application scenario, the server collects various initial driving data from multiple drivers and then sends it to the vehicle terminal.

[0065] The vehicle terminal calculates the average value of each type of initial driving data to obtain the reference average value corresponding to each type of initial driving data; it also calculates the standard deviation of each type of initial driving data to obtain the reference standard deviation corresponding to each type of initial driving data.

[0066] In order to recommend driving modes or routes to users based on their driving style, the in-vehicle terminal needs to first determine the driving style. The in-vehicle terminal first acquires at least one type of initial driving data, which can be the user's historical driving data.

[0067] The vehicle terminal filters the data in each initial driving data according to the reference average value and reference standard deviation corresponding to each initial driving data, and obtains the target driving data corresponding to each initial driving data.

[0068] Then, based on the reference average and reference standard deviation corresponding to each initial driving data, at least one style distinction threshold corresponding to each initial driving data is determined; the average value of the target driving data corresponding to each initial driving data is calculated to obtain the target data value corresponding to each initial driving data.

[0069] Then, based on at least one style distinction threshold and target data value corresponding to each initial driving data type, the user's driving style is determined. The in-vehicle terminal can then recommend driving modes or routes to the user based on their driving style, improving the user experience.

[0070] It should be noted that the above scenario is only an example of an application scenario provided by the embodiments of this application. The embodiments of this application do not limit the actual form of the various devices included in the scenario, nor do they limit the interaction method between devices. In the specific application of the solution, it can be set according to actual needs.

[0071] The technical solution of this application will now be described in detail through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0072] Figure 1 This is a flowchart illustrating an embodiment of the driving style determination method provided in this application. This embodiment describes how an onboard terminal determines a driving style based on initial driving data, a reference average value, and a reference standard deviation. The method in this embodiment can be implemented through software, hardware, or a combination of both. Figure 1 As shown, the method for determining driving style specifically includes the following steps:

[0073] S101: Acquire at least one initial driving data.

[0074] In this step, in order to determine the user's driving style, at least one type of initial driving data needs to be obtained.

[0075] In one implementation, the at least one initial driving data is configured by the user. The in-vehicle terminal may display an initial driving data configuration interface, where the user inputs the initial driving data. The in-vehicle terminal may also display an initial driving data calculation questionnaire, where the user selects options for questions in the questionnaire, and the in-vehicle terminal determines the corresponding initial driving data based on the user's selections.

[0076] In another implementation, the at least one initial driving data is the user's historical driving data.

[0077] It should be noted that the types of initial driving data include accelerator pedal opening, brake pedal opening, longitudinal acceleration, lateral acceleration, straight-line speed, exit speed, entry speed, steering angle, etc. This application embodiment does not limit the types of initial driving data, which can be determined according to the actual situation.

[0078] S102: For each type of initial driving data, the data in the initial driving data is filtered according to the reference average and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data.

[0079] In this step, after the vehicle terminal obtains various initial driving data from the user, since the user will inevitably pass through some abnormal road sections or encounter abnormal situations during the driving process, such as passing through natural disaster road sections or encountering traffic accidents, some abnormal data will be present in the initial driving data. Therefore, it is necessary to filter the data in the initial driving data to remove abnormal data, which can further improve the accuracy of driving style.

[0080] For each type of initial driving data, the data in the initial driving data is filtered according to the reference average and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data.

[0081] Specifically, for each data point in the initial driving data, a standard score (Z-score, also known as Z score) is calculated based on the data point and the reference mean and reference standard deviation corresponding to the initial driving data.

[0082] Formulas can be used Calculate the standard score, where Z represents the standard score, x represents the data in the initial driving data, μ represents the reference mean corresponding to the initial driving data, and σ represents the reference standard deviation corresponding to the initial driving data.

[0083] Data with a standard score greater than a preset filtering threshold in the initial driving data is deleted to obtain the target driving data corresponding to the initial driving data.

[0084] It should be noted that the preset filtering threshold can be 2.5, 2.7, 3, 3.2, etc. This application embodiment does not limit the preset filtering threshold, which can be determined according to the actual situation.

[0085] Since in a standard normal distribution, 68.27% of the data points fall within one standard deviation of the mean, 95.45% fall within two standard deviations, and 99.73% fall within three standard deviations, the preset filtering threshold can be set to 3. A standard score greater than 3 indicates that the data point differs significantly from the rest of the data, and is therefore considered outlier.

[0086] In one implementation, the reference average for each type of initial driving data is the average of the initial driving data from multiple drivers; the reference standard deviation for each type of initial driving data is the standard deviation of the initial driving data from multiple drivers. Before determining a user's driving style, the in-vehicle terminal needs to acquire multiple types of initial driving data from multiple drivers; then calculate the average of each type of initial driving data to obtain the reference average for each type of initial driving data; calculate the standard deviation of each type of initial driving data, obtain the reference standard deviation for each type of initial driving data, and store it so that it can be used as reference data to determine the driving style later, which can improve the accuracy of driving style determination. Furthermore, determining the reference average and reference standard deviation for each type of initial driving data before determining the driving style can improve the efficiency of subsequent driving style determination.

[0087] In another implementation, the reference mean and reference standard deviation for each type of initial driving data are preset values. These can be set by staff in the vehicle terminal, or the vehicle terminal can obtain the reference mean and reference standard deviation from a server and then set them.

[0088] S103: Determine the user's driving style based on the reference average, reference standard deviation, and target driving data corresponding to each initial driving data.

[0089] In this step, after the vehicle terminal determines the target driving data corresponding to each type of initial driving data, it combines the reference average value and reference standard deviation corresponding to each type of initial driving data to determine the user's driving style.

[0090] Driving styles can be categorized into straight-line driving style, curve driving style, and balanced driving style. Users of the straight-line driving style prefer driving on straight roads. Users of the curve driving style prefer driving through curves. Users of the balanced driving style prefer a smooth, comfortable driving experience with good fluidity.

[0091] Therefore, at least one style distinction threshold can be determined for each initial driving data based on the reference average and reference standard deviation; and the average value of the target driving data corresponding to each initial driving data can be calculated to obtain the target data value corresponding to each initial driving data.

[0092] The at least one style distinction threshold corresponding to each initial driving data includes at least one of a first threshold, a second threshold, a third threshold, and a fourth threshold, wherein the first threshold is greater than the second threshold, the second threshold is greater than the third threshold, and the third threshold is greater than the fourth threshold. The first threshold is μ+2kσ, the second threshold is μ+kσ, the third threshold is μ-kσ, and the fourth threshold is μ-2kσ, where μ is the reference average value corresponding to the initial driving data, σ is the reference standard deviation corresponding to the initial driving data, and k takes a value between 1 and 2, such as 1, 1.2, 1.5, 1.7, 2, etc. The embodiments of this application do not limit the size of k, and it can be determined according to the actual situation.

[0093] Then, based on at least one style distinction threshold and target data value corresponding to each initial driving data, the user's driving style is determined.

[0094] The driving style determination method provided in this embodiment determines the user's driving style by filtering the data in each initial driving data set based on a reference average and reference standard deviation corresponding to at least one type of initial driving data, and then combining the reference average and reference standard deviation. This solution determines the user's driving style using the reference average and reference standard deviation, along with the user's initial driving data, eliminating the need for the user to determine the style based on a driving style name, thus effectively improving the accuracy of the determined driving style.

[0095] Figure 2 This is a flowchart illustrating a second embodiment of the driving style determination method provided in this application. Based on the above embodiments, this application describes how to determine the driving style according to at least one style differentiation threshold and a target data value corresponding to each type of initial driving data. For example... Figure 2 As shown, the method for determining driving style specifically includes the following steps:

[0096] S201: Based on at least one style distinction threshold and target data value corresponding to each initial driving data, determine whether at least one of the preset first condition, preset second condition and preset third condition is true; if at least one of the preset first condition, preset second condition and preset third condition is true, then proceed to step S202; if none of the preset first condition, preset second condition and preset third condition is true, then proceed to step S203.

[0097] In this step, driving styles can be categorized into straight-line driving style, curved-course driving style, and balanced driving style. Different driving styles have different relationships with style distinction thresholds. First, it is determined whether at least one of the preset first condition, second condition, and third condition is met to ascertain whether the user's driving style is a straight-line driving style.

[0098] S202: Determines the user's driving style as straight-line driving style.

[0099] In this step, users with a straight-line driving style prefer to accelerate quickly by pressing the accelerator hard, generate large longitudinal acceleration during acceleration and deceleration, maintain high speed on straight sections, brake hard, and have small steering angles, as well as small entry and exit angles.

[0100] If at least one of the preset first condition, preset second condition, and preset third condition is found to be true, then the user's driving style is determined to be a straight-line driving style.

[0101] The first preset condition is: a0>a2, b0>b2, c0>c2, d0>d2.

[0102] The second condition is assumed to be: a3≤a0≤a1, b3≤b0≤b1, c3≤c0≤c1, d3≤d0≤d1, e0 <e3,f0<f3。

[0103] The third condition is assumed to be: a3≤a0≤a1, b3≤b0≤b1, c3≤c0≤c1, d3≤d0≤d1, g0 <g3。

[0104] a0 represents the target data value corresponding to the accelerator pedal opening, a1 represents the first threshold corresponding to the accelerator pedal opening, a2 represents the second threshold corresponding to the accelerator pedal opening, a3 represents the third threshold corresponding to the accelerator pedal opening, and a4 represents the fourth threshold corresponding to the accelerator pedal opening.

[0105] b0 represents the target data value corresponding to the brake pedal opening, b1 represents the first threshold corresponding to the brake pedal opening, b2 represents the second threshold corresponding to the brake pedal opening, b3 represents the third threshold corresponding to the brake pedal opening, and b4 represents the fourth threshold corresponding to the brake pedal opening.

[0106] c0 represents the target data value corresponding to longitudinal acceleration, c1 represents the first threshold corresponding to longitudinal acceleration, c2 represents the second threshold corresponding to longitudinal acceleration, c3 represents the third threshold corresponding to longitudinal acceleration, and c4 represents the fourth threshold corresponding to longitudinal acceleration.

[0107] d0 represents the target data value corresponding to the linear velocity, d1 represents the first threshold corresponding to the linear velocity, d2 represents the second threshold corresponding to the linear velocity, d3 represents the third threshold corresponding to the linear velocity, and d4 represents the fourth threshold corresponding to the linear velocity.

[0108] e0 represents the target data value corresponding to the exit speed, e1 represents the first threshold corresponding to the exit speed, e2 represents the second threshold corresponding to the exit speed, e3 represents the third threshold corresponding to the exit speed, and e4 represents the fourth threshold corresponding to the exit speed.

[0109] f0 represents the target data value corresponding to the cornering speed, f1 represents the first threshold corresponding to the cornering speed, f2 represents the second threshold corresponding to the cornering speed, f3 represents the third threshold corresponding to the cornering speed, and f4 represents the fourth threshold corresponding to the cornering speed.

[0110] g0 represents the target data value corresponding to the steering angle, g1 represents the first threshold corresponding to the steering angle, g2 represents the second threshold corresponding to the steering angle, g3 represents the third threshold corresponding to the steering angle, and g4 represents the fourth threshold corresponding to the steering angle.

[0111] S203: Based on at least one style distinction threshold and target data value corresponding to each initial driving data, determine whether at least one of the preset fourth condition, preset fifth condition and preset sixth condition is true; if at least one of the preset fourth condition, preset fifth condition and preset sixth condition is true, then proceed to step S204; if none of the preset fourth condition, preset fifth condition and preset sixth condition is true, then proceed to step S205.

[0112] In this step, if it is determined that the first, second, and third preset conditions are all invalid, it means that the user's driving style is not a straight-line driving style. It is necessary to further determine whether the driving style is a curve driving style or a balanced driving style. This requires determining whether at least one of the fourth, fifth, and sixth preset conditions is valid based on at least one style distinction threshold and target data value corresponding to each initial driving data.

[0113] S204: The user's driving style is determined to be the curve driving style.

[0114] In this step, users with a straight-line driving style prefer larger steering angles, larger cornering and exiting angles, larger lateral acceleration, smaller straight-line speed and longitudinal acceleration, and smaller opening of the accelerator and brake pedals.

[0115] If at least one of the preset fourth, fifth, and sixth conditions is found to be true, then the user's driving style is determined to be the curve driving style.

[0116] The fourth condition is preset as follows: h0>h2, f0>f2, e0>e2, g0>g2.

[0117] The fifth condition is preset as follows: h3≤h0≤h1, f3≤f0≤f1, e3≤e0≤e1, g3≤g0≤g1, d4≤d0≤d2, c4≤c0≤c2.

[0118] The sixth condition is set as follows: h3≤h0≤h1, f3≤f0≤f1, e3≤e0≤e1, g3≤g0≤g1, a4≤a0≤a2, b4≤b0≤b2.

[0119] h0 represents the target data value corresponding to lateral acceleration, h1 represents the first threshold corresponding to lateral acceleration, h2 represents the second threshold corresponding to lateral acceleration, h3 represents the third threshold corresponding to lateral acceleration, and h4 represents the fourth threshold corresponding to lateral acceleration.

[0120] S205: Determines the user's driving style as a balanced driving style.

[0121] In this step, users with balanced driving styles prefer moderate steering angles, cornering angles, cornering angles, lateral acceleration, straight-line speed, longitudinal acceleration, accelerator pedal opening, and brake pedal opening.

[0122] If it is determined that the preset fourth, fifth, and sixth conditions are all invalid, that is, the preset first to sixth conditions are all invalid, then the user's driving style is determined to be a balanced driving style.

[0123] The driving style determination method provided in this embodiment determines the user's driving style by using at least one style distinction threshold and target data value corresponding to each initial driving data, which effectively improves the accuracy of the determined driving style.

[0124] The following are embodiments of the apparatus of this application, which can be used to execute the embodiments of the method of this application. For details not disclosed in the embodiments of the apparatus of this application, please refer to the embodiments of the method of this application.

[0125] Figure 3 This is a schematic diagram of the structure of an embodiment of the driving style determination device provided in this application. Figure 3 As shown, the driving style determining device 30 includes:

[0126] Acquisition module 31 is used to acquire at least one type of initial driving data;

[0127] Processing module 32 is used for:

[0128] For each type of initial driving data, the data in the initial driving data is filtered according to the reference average and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data;

[0129] The user's driving style is determined based on the reference average, reference standard deviation, and target driving data corresponding to each initial driving data.

[0130] Furthermore, the processing module 32 is specifically used for:

[0131] For each data point in the initial driving data, a standard score is calculated based on the data point and the reference mean and reference standard deviation corresponding to the initial driving data.

[0132] Data with a standard score greater than a preset filtering threshold in the initial driving data is deleted to obtain the target driving data corresponding to the initial driving data.

[0133] Furthermore, the processing module 32 is specifically used for:

[0134] Based on the reference mean and reference standard deviation corresponding to each type of initial driving data, determine at least one style distinction threshold corresponding to each type of initial driving data;

[0135] Calculate the average value of the target driving data corresponding to each type of initial driving data to obtain the target data value corresponding to each type of initial driving data;

[0136] The user's driving style is determined based on at least one style distinction threshold and a target data value corresponding to each type of initial driving data.

[0137] Furthermore, at least one style distinction threshold corresponding to each initial driving data includes at least one of a first threshold, a second threshold, a third threshold, and a fourth threshold;

[0138] The first threshold is greater than the second threshold, the second threshold is greater than the third threshold, and the third threshold is greater than the fourth threshold;

[0139] The types of initial driving data include accelerator pedal opening, brake pedal opening, longitudinal acceleration, straight-line speed, corner exit speed, corner entry speed, and steering angle;

[0140] The processing module 32 is further configured to: determine that at least one of the preset first condition, preset second condition and preset third condition is met based on at least one style distinction threshold and target data value corresponding to each initial driving data, and then determine that the user's driving style is a straight-line driving style;

[0141] The preset first condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than the second threshold corresponding to the accelerator pedal opening, the target data value corresponding to the brake pedal opening is greater than the second threshold corresponding to the brake pedal opening, the target data value corresponding to the longitudinal acceleration is greater than the second threshold corresponding to the longitudinal acceleration, and the target data value corresponding to the linear speed is greater than the second threshold corresponding to the linear speed.

[0142] The preset second condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than or equal to the third threshold corresponding to the accelerator pedal opening and less than or equal to the first threshold corresponding to the accelerator pedal opening; the target data value corresponding to the brake pedal opening is greater than or equal to the third threshold corresponding to the brake pedal opening and less than or equal to the first threshold corresponding to the brake pedal opening; the target data value corresponding to the longitudinal acceleration is greater than or equal to the third threshold corresponding to the longitudinal acceleration and less than or equal to the first threshold corresponding to the longitudinal acceleration; the target data value corresponding to the straight speed is greater than or equal to the third threshold corresponding to the straight speed and less than or equal to the first threshold corresponding to the straight speed; the target data value corresponding to the exit speed is less than the third threshold corresponding to the exit speed; and the target data value corresponding to the entry speed is less than the third threshold corresponding to the entry speed.

[0143] The preset third condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than or equal to the third threshold corresponding to the accelerator pedal opening and less than or equal to the first threshold corresponding to the accelerator pedal opening; the target data value corresponding to the brake pedal opening is greater than or equal to the third threshold corresponding to the brake pedal opening and less than or equal to the first threshold corresponding to the brake pedal opening; the target data value corresponding to the longitudinal acceleration is greater than or equal to the third threshold corresponding to the longitudinal acceleration and less than or equal to the first threshold corresponding to the longitudinal acceleration; the target data value corresponding to the linear speed is greater than or equal to the third threshold corresponding to the linear speed and less than or equal to the first threshold corresponding to the linear speed; and the target data value corresponding to the steering angle is less than the third threshold corresponding to the steering angle.

[0144] Furthermore, the initial driving data also includes lateral acceleration, and the processing module 32 is further used for:

[0145] Based on at least one style distinction threshold and target data value corresponding to each initial driving data, if at least one of the preset fourth condition, preset fifth condition and preset sixth condition is met, then the user's driving style is determined to be a curve driving style.

[0146] The preset fourth condition is as follows: the target data value corresponding to the lateral acceleration is greater than the second threshold corresponding to the lateral acceleration, the target data value corresponding to the cornering speed is greater than the second threshold corresponding to the cornering speed, the target data value corresponding to the cornering speed is greater than the second threshold corresponding to the cornering speed, and the target data value corresponding to the steering angle is greater than the second threshold corresponding to the steering angle.

[0147] The preset fifth condition is as follows: the target data value corresponding to the lateral acceleration is greater than or equal to the third threshold corresponding to the lateral acceleration and less than or equal to the first threshold corresponding to the lateral acceleration; the target data value corresponding to the cornering speed is greater than or equal to the third threshold corresponding to the cornering speed and less than or equal to the first threshold corresponding to the cornering speed; the target data value corresponding to the cornering speed is greater than or equal to the third threshold corresponding to the cornering speed and less than or equal to the first threshold corresponding to the cornering speed; the target data value corresponding to the steering angle is greater than or equal to the third threshold corresponding to the steering angle and less than or equal to the first threshold corresponding to the steering angle; the target data value corresponding to the straight speed is greater than or equal to the fourth threshold corresponding to the straight speed and less than or equal to the second threshold corresponding to the straight speed; and the target data value corresponding to the longitudinal acceleration is greater than or equal to the fourth threshold corresponding to the longitudinal acceleration and less than or equal to the second threshold corresponding to the longitudinal acceleration.

[0148] The preset sixth condition is as follows: the target data value corresponding to lateral acceleration is greater than or equal to the third threshold corresponding to lateral acceleration and less than or equal to the first threshold corresponding to lateral acceleration; the target data value corresponding to cornering speed is greater than or equal to the third threshold corresponding to cornering speed and less than or equal to the first threshold corresponding to cornering speed; the target data value corresponding to cornering speed is greater than or equal to the third threshold corresponding to cornering speed and less than or equal to the first threshold corresponding to cornering speed; the target data value corresponding to steering angle is greater than or equal to the third threshold corresponding to steering angle and less than or equal to the first threshold corresponding to steering angle; the target data value corresponding to accelerator pedal opening is greater than or equal to the fourth threshold corresponding to accelerator pedal opening and less than or equal to the second threshold corresponding to accelerator pedal opening; and the target data value corresponding to brake pedal opening is greater than or equal to the fourth threshold corresponding to brake pedal opening and less than or equal to the second threshold corresponding to brake pedal opening.

[0149] Furthermore, the processing module 32 is also used for:

[0150] Based on at least one style distinction threshold and target data value corresponding to each initial driving data, if it is determined that none of the preset first condition, the preset second condition, the preset third condition, the preset fourth condition, the preset fifth condition, and the preset sixth condition are met, then the user's driving style is determined to be a balanced driving style.

[0151] Furthermore, the at least one initial driving data is configured by the user.

[0152] Furthermore, the at least one initial driving data is the user's historical driving data.

[0153] Furthermore, the reference average value corresponding to each initial driving data is the average value of the initial driving data of multiple drivers;

[0154] The reference standard deviation for each initial driving data is the standard deviation of the initial driving data of the multiple drivers.

[0155] Furthermore, the reference mean and reference standard deviation for each type of initial driving data are preset values.

[0156] The driving style determination device provided in this embodiment is used to execute the technical solution in any of the aforementioned method embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0157] Figure 4 This is a schematic diagram of the structure of an electronic device provided in this application. Figure 4 As shown, the electronic device 40 includes:

[0158] Processor 41, memory 42, and communication interface 43;

[0159] The memory 42 is used to store the executable instructions of the processor 41;

[0160] The processor 41 is configured to execute the technical solutions in any of the foregoing method embodiments by executing the executable instructions.

[0161] Optionally, the memory 42 can be either standalone or integrated with the processor 41.

[0162] Optionally, when the memory 42 is a device independent of the processor 41, the electronic device 40 may further include:

[0163] Bus 44, memory 42 and communication interface 43 are connected to processor 41 through bus 44 and complete communication with each other. Communication interface 43 is used to communicate with other devices.

[0164] Optionally, the communication interface 43 can be implemented using a transceiver. The communication interface is used to enable communication between the database access device and other devices (e.g., clients, read-write databases, and read-only databases). The memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk drive.

[0165] Bus 44 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0166] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0167] The electronic device is used to execute the technical solutions in any of the foregoing method embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0168] This application also provides a vehicle, which includes an on-board terminal.

[0169] The vehicle-mounted terminal is used to execute the technical solutions in any of the aforementioned method embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0170] This application also provides a readable storage medium storing a computer program thereon, which, when executed by a processor, implements the technical solutions provided in any of the foregoing method embodiments.

[0171] This application also provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the technical solutions provided in any of the foregoing method embodiments.

[0172] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for determining driving style, characterized in that, include: Acquire at least one type of initial driving data; For each type of initial driving data, the data in the initial driving data is filtered according to the reference average and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data; The user's driving style is determined based on the reference average, reference standard deviation, and target driving data corresponding to each initial driving data.

2. The method according to claim 1, characterized in that, The step of filtering the data in the initial driving data according to the reference average value and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data includes: For each data point in the initial driving data, a standard score is calculated based on the data point and the reference mean and reference standard deviation corresponding to the initial driving data. Data with a standard score greater than a preset filtering threshold in the initial driving data is deleted to obtain the target driving data corresponding to the initial driving data.

3. The method according to claim 1, characterized in that, The step of determining the user's driving style based on the reference average, reference standard deviation, and target driving data corresponding to each initial driving data includes: Based on the reference mean and reference standard deviation corresponding to each type of initial driving data, determine at least one style distinction threshold corresponding to each type of initial driving data; Calculate the average value of the target driving data corresponding to each type of initial driving data to obtain the target data value corresponding to each type of initial driving data; The user's driving style is determined based on at least one style distinction threshold and a target data value corresponding to each type of initial driving data.

4. The method according to claim 3, characterized in that, Each initial driving data type has at least one style distinction threshold, including at least one of a first threshold, a second threshold, a third threshold, and a fourth threshold; The first threshold is greater than the second threshold, the second threshold is greater than the third threshold, and the third threshold is greater than the fourth threshold; The types of initial driving data include accelerator pedal opening, brake pedal opening, longitudinal acceleration, straight-line speed, corner exit speed, corner entry speed, and steering angle; The step of determining the user's driving style based on at least one style differentiation threshold and a target data value corresponding to each initial driving data includes: Based on at least one style distinction threshold and target data value corresponding to each initial driving data, if at least one of the preset first condition, preset second condition and preset third condition is met, then the user's driving style is determined to be a straight-line driving style. The preset first condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than the second threshold corresponding to the accelerator pedal opening, the target data value corresponding to the brake pedal opening is greater than the second threshold corresponding to the brake pedal opening, the target data value corresponding to the longitudinal acceleration is greater than the second threshold corresponding to the longitudinal acceleration, and the target data value corresponding to the linear speed is greater than the second threshold corresponding to the linear speed. The preset second condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than or equal to the third threshold corresponding to the accelerator pedal opening and less than or equal to the first threshold corresponding to the accelerator pedal opening; the target data value corresponding to the brake pedal opening is greater than or equal to the third threshold corresponding to the brake pedal opening and less than or equal to the first threshold corresponding to the brake pedal opening; the target data value corresponding to the longitudinal acceleration is greater than or equal to the third threshold corresponding to the longitudinal acceleration and less than or equal to the first threshold corresponding to the longitudinal acceleration; the target data value corresponding to the straight speed is greater than or equal to the third threshold corresponding to the straight speed and less than or equal to the first threshold corresponding to the straight speed; the target data value corresponding to the exit speed is less than the third threshold corresponding to the exit speed; and the target data value corresponding to the entry speed is less than the third threshold corresponding to the entry speed. The preset third condition is as follows: the target data value corresponding to the accelerator pedal opening is greater than or equal to the third threshold corresponding to the accelerator pedal opening and less than or equal to the first threshold corresponding to the accelerator pedal opening; the target data value corresponding to the brake pedal opening is greater than or equal to the third threshold corresponding to the brake pedal opening and less than or equal to the first threshold corresponding to the brake pedal opening; the target data value corresponding to the longitudinal acceleration is greater than or equal to the third threshold corresponding to the longitudinal acceleration and less than or equal to the first threshold corresponding to the longitudinal acceleration; the target data value corresponding to the linear speed is greater than or equal to the third threshold corresponding to the linear speed and less than or equal to the first threshold corresponding to the linear speed; and the target data value corresponding to the steering angle is less than the third threshold corresponding to the steering angle.

5. The method according to claim 4, characterized in that, The types of initial driving data also include lateral acceleration, and the method further includes: Based on at least one style distinction threshold and target data value corresponding to each initial driving data, if at least one of the preset fourth condition, preset fifth condition and preset sixth condition is met, then the user's driving style is determined to be a curve driving style. The preset fourth condition is as follows: the target data value corresponding to the lateral acceleration is greater than the second threshold corresponding to the lateral acceleration, the target data value corresponding to the cornering speed is greater than the second threshold corresponding to the cornering speed, the target data value corresponding to the cornering speed is greater than the second threshold corresponding to the cornering speed, and the target data value corresponding to the steering angle is greater than the second threshold corresponding to the steering angle. The preset fifth condition is as follows: the target data value corresponding to the lateral acceleration is greater than or equal to the third threshold corresponding to the lateral acceleration and less than or equal to the first threshold corresponding to the lateral acceleration; the target data value corresponding to the cornering speed is greater than or equal to the third threshold corresponding to the cornering speed and less than or equal to the first threshold corresponding to the cornering speed; the target data value corresponding to the cornering speed is greater than or equal to the third threshold corresponding to the cornering speed and less than or equal to the first threshold corresponding to the cornering speed; the target data value corresponding to the steering angle is greater than or equal to the third threshold corresponding to the steering angle and less than or equal to the first threshold corresponding to the steering angle; the target data value corresponding to the straight speed is greater than or equal to the fourth threshold corresponding to the straight speed and less than or equal to the second threshold corresponding to the straight speed; and the target data value corresponding to the longitudinal acceleration is greater than or equal to the fourth threshold corresponding to the longitudinal acceleration and less than or equal to the second threshold corresponding to the longitudinal acceleration. The preset sixth condition is as follows: the target data value corresponding to lateral acceleration is greater than or equal to the third threshold corresponding to lateral acceleration and less than or equal to the first threshold corresponding to lateral acceleration; the target data value corresponding to cornering speed is greater than or equal to the third threshold corresponding to cornering speed and less than or equal to the first threshold corresponding to cornering speed; the target data value corresponding to cornering speed is greater than or equal to the third threshold corresponding to cornering speed and less than or equal to the first threshold corresponding to cornering speed; the target data value corresponding to steering angle is greater than or equal to the third threshold corresponding to steering angle and less than or equal to the first threshold corresponding to steering angle; the target data value corresponding to accelerator pedal opening is greater than or equal to the fourth threshold corresponding to accelerator pedal opening and less than or equal to the second threshold corresponding to accelerator pedal opening; and the target data value corresponding to brake pedal opening is greater than or equal to the fourth threshold corresponding to brake pedal opening and less than or equal to the second threshold corresponding to brake pedal opening.

6. The method according to claim 5, characterized in that, The method further includes: Based on at least one style distinction threshold and target data value corresponding to each initial driving data, if it is determined that none of the preset first condition, the preset second condition, the preset third condition, the preset fourth condition, the preset fifth condition, and the preset sixth condition are met, then the user's driving style is determined to be a balanced driving style.

7. The method according to any one of claims 1 to 6, characterized in that, The at least one type of initial driving data is configured by the user.

8. The method according to any one of claims 1 to 6, characterized in that, The at least one type of initial driving data is the user's historical driving data.

9. The method according to any one of claims 1 to 6, characterized in that, The reference average value for each initial driving data is the average value of the initial driving data of multiple drivers; The reference standard deviation for each initial driving data is the standard deviation of the initial driving data of the multiple drivers.

10. The method according to any one of claims 1 to 6, characterized in that, The reference mean and reference standard deviation for each initial driving data are preset values.

11. A driving style determining device, characterized in that, include: The acquisition module is used to acquire at least one type of initial driving data; Processing module, used for: For each type of initial driving data, the data in the initial driving data is filtered according to the reference average and reference standard deviation corresponding to the pre-acquired initial driving data to obtain the target driving data corresponding to the initial driving data; The user's driving style is determined based on the reference average, reference standard deviation, and target driving data corresponding to each initial driving data.

12. An electronic device, characterized in that, include: Processor, memory, communication interface; The memory is used to store the executable instructions of the processor; The processor is configured to execute the driving style determination method according to any one of claims 1 to 10 by executing the executable instructions.

13. A vehicle, characterized in that, Including vehicle-mounted terminals; The vehicle-mounted terminal is used to execute the driving style determination method according to any one of claims 1 to 10.

14. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the driving style determination method according to any one of claims 1 to 10.

15. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, is used to implement the driving style determination method according to any one of claims 1 to 10.

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