Driving assistance method, device, vehicle, storage medium, and product

Abstract

A driving assistance method, a device, a vehicle, a storage medium, and a product. The driving assistance method comprises: acquiring the current operating condition of a vehicle; acquiring a desired operating state parameter on the basis of the current operating condition; generating a driving behavior suggestion on the basis of the difference between a current operating state parameter and the desired operating state parameter; and prompting a driver on the basis of the driving behavior suggestion.

Description

Driving assistance methods, devices, vehicles, storage media and products

[0001] Cross-reference to related applications

[0002] This disclosure claims priority to Chinese Patent Application No. 202410926429.7, filed on July 11, 2024, entitled “Driving Assistance Method, Device, Vehicle, Storage Medium and Product”, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to the field of new energy vehicle technology, specifically to a driving assistance method, device, vehicle, storage medium, and product. Background Technology

[0004] Driving style refers to a series of behavioral characteristics a driver exhibits while driving. It involves inputting information to the vehicle through driving behavior and responding based on the vehicle's operating status and energy consumption levels. Research shows a close correlation between driving style and energy consumption; aggressive driving styles tend to increase energy consumption and emissions more easily than conservative ones. Currently, some in-vehicle applications offer driving behavior scoring and related optimization suggestions, aiming to guide users in optimizing driving operations to reduce energy consumption and improve the user experience. However, users often don't perceive these features strongly, hindering their full potential. Summary of the Invention

[0005] The purpose of this disclosure is to provide a driving assistance method, device, vehicle, storage medium, and product. Based on the difference between the vehicle's current operating parameters and desired operating parameters, this method provides driving behavior guidance to the user, helping them to improve their driving behavior in a timely manner, reducing vehicle energy consumption, and enhancing driving safety, thus bringing a more intelligent driving experience to the user.

[0006] To achieve the above objectives, according to a first aspect of the present disclosure, a driving assistance method is provided, the method comprising:

[0007] Obtain the current operating status of the vehicle;

[0008] Based on the current operating conditions, obtain the desired operating state parameters;

[0009] Based on the difference between the current operating state parameters and the desired operating state parameters, driving behavior suggestions are generated;

[0010] The driver is prompted based on the driving behavior suggestions.

[0011] Optionally, before generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters, the method further includes:

[0012] Obtain the vehicle's current operating status parameters;

[0013] Based on the current operating status parameters, the driver's driving style is obtained, including a conservative driving style and a non-conservative driving style.

[0014] The step of generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters includes:

[0015] When the driver's driving style is the non-conservative driving style, driving behavior suggestions are generated based on the difference between the current operating state parameters and the expected operating state parameters.

[0016] Optionally, obtaining the driver's driving style based on the current operating state parameters includes:

[0017] The current operating status parameters are input into a pre-established driving style recognition model to obtain the driver's driving style.

[0018] Optionally, the method for establishing the driving style recognition model includes:

[0019] Obtain a sample of original driving state parameters, which includes historical operating state parameters and driving style labels;

[0020] The driving style recognition model is trained based on the original driving state parameter samples.

[0021] Optionally, obtaining the original driving state parameter sample includes:

[0022] Collect historical operational status parameters;

[0023] Clustering the historical operating state parameters yields multiple categories of historical operating state parameters;

[0024] Different driving style labels are added to different types of historical operating state parameters to obtain original driving state parameter samples.

[0025] Optionally, the current operating status parameters include at least one of the following parameters within a preset time period:

[0026] Average vehicle speed, standard deviation of vehicle speed, average acceleration, average deceleration, rate of change of acceleration, average accelerator pedal opening, and standard deviation of accelerator pedal opening.

[0027] Optionally, obtaining the current operating condition of the vehicle includes:

[0028] Obtain the current characteristic parameters of the vehicle, which include one or more of the following: average vehicle speed, maximum vehicle speed, and number of start-stop cycles within a set time period;

[0029] Obtain typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle. The typical characteristic parameters corresponding to each typical operating condition include one or more of the average vehicle speed, maximum vehicle speed and number of start-stop times of the vehicle within the set time under the typical operating condition.

[0030] Determine the similarity between the current feature parameter and the typical feature parameter corresponding to each typical operating condition;

[0031] The typical operating condition corresponding to the minimum value in the similarity is taken as the current operating condition of the vehicle.

[0032] Optionally, obtaining typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle includes:

[0033] Raw operating condition data is collected under offline conditions, including the raw operating data of the vehicle under different operating conditions.

[0034] The original operating condition data is cleaned to obtain cleaned operating condition data;

[0035] The cleaning operation data is sliced ​​to obtain an operation sample dataset.

[0036] The operating condition sample dataset is clustered to obtain multiple operating condition cluster centers. The multiple operating condition sample datasets corresponding to the multiple operating condition cluster centers are respectively used as the typical feature parameters corresponding to the multiple typical operating conditions.

[0037] Optionally, obtaining the desired operating state parameters based on the current operating conditions includes:

[0038] Based on the current operating conditions, the desired operating state parameters are obtained by looking up a table.

[0039] Optionally, the difference between the current operating status parameter and the desired operating status parameter includes multiple different difference levels, wherein different difference levels correspond to different display effects;

[0040] The step of providing prompts to the driver based on the driving behavior suggestions includes:

[0041] Determine the target difference level to which the difference between the current operating state parameters and the expected operating state parameters belongs;

[0042] Based on the display effect corresponding to the target difference level, the driving behavior suggestions are displayed.

[0043] Optionally, the vehicle includes a head-up display system, and the step of providing prompts to the driver based on the driving behavior suggestions includes:

[0044] The driving behavior suggestions are displayed through the head-up display system.

[0045] According to a second aspect of the present disclosure, a driving assistance device is provided, the device comprising:

[0046] The first acquisition device is used to acquire the current operating condition of the vehicle;

[0047] The second acquisition device is used to acquire the desired operating state parameters based on the current operating conditions.

[0048] The suggestion device is used to generate driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters;

[0049] Display devices are used to provide prompts to the driver based on the driving behavior suggestions.

[0050] According to a third aspect of the present disclosure, an electronic device is provided, comprising:

[0051] A memory on which computer programs are stored;

[0052] A processor for executing the computer program in the memory to implement the steps of the method of any one of the first aspects.

[0053] According to a fourth aspect of the present disclosure, a vehicle is provided, including: the electronic equipment described in the third aspect.

[0054] According to a fifth aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0055] According to a sixth aspect of the present disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0056] In summary, this disclosure provides a driving assistance method, which includes: acquiring the current operating condition of a vehicle; acquiring desired operating state parameters based on the current operating condition; generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters; and providing prompts to the driver based on the driving behavior suggestions. This disclosure can provide driving behavior guidance to users based on the difference between the current and desired operating state parameters, helping users to improve their driving behavior in a timely manner, reducing vehicle energy consumption, and improving driving safety, thus bringing users a more intelligent driving experience.

[0057] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0058] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings:

[0059] Figure 1 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0060] Figure 2 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0061] Figure 3 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0062] Figure 4 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0063] Figure 5 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0064] Figure 6 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0065] Figure 7 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0066] Figure 8 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0067] Figure 9 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0068] Figure 10 is a flowchart illustrating a driving assistance method according to an exemplary embodiment.

[0069] Figure 11 is a block diagram illustrating a driving assistance device according to an exemplary embodiment.

[0070] Figure 12 is a block diagram illustrating an electronic device according to an exemplary embodiment.

[0071] Figure 13 is a block diagram illustrating a vehicle according to an exemplary embodiment. Detailed Implementation

[0072] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0073] It should be understood that the term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the following description.

[0074] It should be noted that the concepts of "first," "second," etc., mentioned in this disclosure are used only to distinguish different devices, apparatuses, or units, and are not used to limit the order of functions performed by these devices, modules, or units or their interdependencies. The modifiers "a" and "a plurality of" mentioned in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless explicitly stated in the context, they should be understood as "one or more." In the description of this disclosure, unless otherwise stated, "a plurality of" means two or more, and other quantifiers are similar; "at least one," "one or more," or similar expressions refer to any combination of these items, including any combination of single or multiple items.

[0075] Although operations or steps are described in a specific order in the accompanying drawings in the embodiments of this disclosure, it should not be construed as requiring these operations or steps to be performed in the specific order or serial order shown, or requiring all of the shown operations or steps to be performed to obtain the desired result. In the embodiments of this disclosure, these operations or steps may be performed serially; they may be performed in parallel; or a portion of these operations or steps may be performed.

[0076] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of these messages or information. It is understood that before using the technical solutions disclosed in the embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained. The disclosure will now be described in conjunction with specific embodiments.

[0077] First, the application scenarios of this disclosure are explained. Existing technologies suffer from low usage rates, weak user perception, and insufficient effectiveness of driving behavior guidance functions. Because current technologies do not directly transmit driving behavior guidance information, most driving behavior evaluation information and related optimization suggestions can only be viewed after the trip is completed. Users cannot obtain relevant driving behavior suggestions and guidance information in real time while driving, resulting in low user willingness to use the function and failing to realize its value. To solve these problems, this disclosure provides a driving assistance method, device, vehicle, storage medium, and product. It utilizes big data technology to extract different typical operating conditions and expected operating state parameters under different typical operating conditions, combines this with the user's driving style to generate driving behavior suggestions, and provides real-time visual prompts of these suggestions through AR-HUD. This provides users with more intuitive information interaction and a more intelligent driving experience, helping users reduce vehicle energy consumption and improve driving safety through driving suggestion optimization.

[0078] Figure 1 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 1, this disclosure provides a driving assistance method, which may include the following steps:

[0079] In step S110, the current operating condition of the vehicle is obtained.

[0080] In this step, the current operating condition of the vehicle is obtained. For example, obtaining the current operating condition of the vehicle may include: first, obtaining the vehicle's current characteristic parameters, which include one or more of the following: average vehicle speed, maximum vehicle speed, and number of start-stop cycles within a set time period; then, obtaining typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle, where the typical characteristic parameters corresponding to each typical operating condition include one or more of the following: average vehicle speed, maximum vehicle speed, and number of start-stop cycles within the set time period under the typical operating condition; then, determining the similarity between the current characteristic parameters and the typical characteristic parameters corresponding to each typical operating condition, for example, the similarity can be Euclidean distance; finally, the typical operating condition corresponding to the minimum value of the similarity is taken as the current operating condition of the vehicle.

[0081] In step S120, the desired operating state parameters are obtained based on the current operating conditions.

[0082] In this step, the desired operating state parameters under the current operating conditions are obtained. For example, the desired operating state parameters under the current operating conditions can be obtained by looking up a table.

[0083] In step S130, driving behavior suggestions are generated based on the difference between the current operating state parameters and the desired operating state parameters.

[0084] In this step, driving behavior suggestions are generated based on the differences between the current and desired operating state parameters. When information such as desired operating state parameters is obtained, the specific parameter values ​​required for the vehicle to reach the desired operating state, such as pedal opening (accelerator / brake) and steering wheel angle, can be calculated by comparing the differences with the current parameter values. Driving behavior suggestions are then generated based on the differences between the desired and current operating state parameters. For example, suggestions may include acceleration, braking, or left / right steering input.

[0085] For example, if it is identified that the current vehicle is in a following state, the current vehicle speed is V1, and the following distance is D1, the expected acceleration A1 of the current state can be obtained by looking up a table and compared with the current acceleration A0. If the current acceleration A0 is greater than the expected acceleration A1, a driving behavior suggestion can be generated: reduce the throttle depth.

[0086] In step S140, the driver is prompted based on the driving behavior suggestions.

[0087] In this step, driving behavior suggestions are provided to the driver. For example, a target difference level can be determined based on the difference between the current operating state parameters and the desired operating state parameters, and then driving behavior suggestions can be displayed according to the display effect corresponding to the target difference level. For example, driving behavior suggestions can be displayed through a head-up display system.

[0088] In summary, this disclosure provides a driving assistance method, which includes: acquiring the current operating conditions of the vehicle, such as the operating conditions acquired in real time during vehicle operation; acquiring desired operating state parameters based on the current operating conditions; generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters; and providing prompts to the driver based on the driving behavior suggestions. This allows for real-time optimization suggestions for the driver's driving behavior during vehicle operation. Compared to related technologies where driving behavior evaluation information and related optimization suggestions can only be viewed after the trip is completed, the technical solution provided by this disclosure allows the driver to more intuitively perceive and pay attention to the driving behavior suggestions provided by the vehicle. Furthermore, compared to related technologies that provide broad driving behavior suggestions based on driving style, this disclosure provides more granular driving behavior guidance based on the difference between the vehicle's current operating state parameters and the desired operating state parameters. This guidance enables users to improve their driving behavior more promptly and accurately, reduce vehicle energy consumption, and improve driving safety, bringing a more intelligent driving experience to users.

[0089] Figure 2 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 2, before generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters, the method may include the following steps:

[0090] In step S210, the current operating status parameters of the vehicle are obtained.

[0091] In this step, the current operating status parameters of the vehicle are obtained. For example, the current operating status parameters may include at least one of the following parameters within a preset time period (e.g., 10 minutes): average vehicle speed, standard deviation of vehicle speed, average acceleration, average deceleration, rate of change of acceleration, average accelerator pedal opening, and standard deviation of accelerator pedal opening.

[0092] In step S220, the driver's driving style is obtained based on the current operating state parameters. The driving style includes a conservative driving style and a non-conservative driving style.

[0093] In this step, the driver's driving style is obtained based on the current operating status parameters. The driving style includes a conservative driving style and a non-conservative driving style. For example, the current operating status parameters can be input into a pre-established driving style recognition model to obtain the driver's driving style, which can be divided into a conservative style and a non-conservative style.

[0094] In step S230, if the driver's driving style is the non-conservative driving style, a driving behavior suggestion is generated based on the difference between the current operating state parameters and the desired operating state parameters.

[0095] In this step, when the driver's driving style is non-conservative, driving behavior suggestions are generated based on the difference between the current operating state parameters and the desired operating state parameters. For example, when the driver's driving style is non-conservative, generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters may include: obtaining the vehicle's current operating condition; then, based on the current operating condition, obtaining the desired operating state parameters under the current operating condition; then, when the driver's driving style is non-conservative, generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters; and finally, providing prompts to the driver based on the driving behavior suggestions.

[0096] In some embodiments, the current operating status parameter includes at least one of the following parameters within a preset time period:

[0097] Average vehicle speed, standard deviation of vehicle speed, average acceleration, average deceleration, rate of change of acceleration, average accelerator pedal opening, and standard deviation of accelerator pedal opening.

[0098] Figure 3 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 3, obtaining the driver's driving style based on the current operating state parameters may include the following steps:

[0099] In step S2201, the current operating status parameters are input into a pre-established driving style recognition model to obtain the driver's driving style.

[0100] In this step, the current operating state parameters are input into a pre-established driving style recognition model to obtain the driver's driving style. For example, the method for establishing the driving style recognition model may include: first obtaining raw driving state parameter samples, which include historical operating state parameters and driving style labels, and then training the driving style recognition model based on the raw driving state parameter samples.

[0101] Figure 4 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 4, the method for establishing the driving style recognition model may include the following steps:

[0102] In step S22011, an original driving state parameter sample is obtained, which includes historical operating state parameters and driving style labels.

[0103] In this step, a sample of original driving state parameters is obtained, which includes historical operating state parameters and driving style labels. For example, obtaining the original driving state parameter sample may include: first collecting historical operating state parameters, then clustering the historical operating state parameters to obtain multiple categories of historical operating state parameters, and then adding different driving style labels to the different categories of historical operating state parameters to obtain the original driving state parameter sample.

[0104] In step S22012, the driving style recognition model is trained based on the original driving state parameter samples.

[0105] In this step, the driving style recognition model is trained based on the original driving state parameter samples.

[0106] Figure 5 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 5, obtaining the original driving state parameter sample may include the following steps:

[0107] In step S220111, historical operating status parameters are collected.

[0108] In this step, historical operating status parameters are collected. For example, the historical operating status parameter sample may include at least one of the following parameters: average vehicle speed Vmean, vehicle speed standard deviation Vstd, average acceleration A1mean, average deceleration A2mean, acceleration change rate J, average accelerator pedal opening Accelerator_Pedalmean, and accelerator pedal opening standard deviation Accelerator_Pedalstd.

[0109] In step S220112, the historical operating status parameters are clustered to obtain multiple types of historical operating status parameters.

[0110] In this step, historical operating state parameters are clustered to obtain multiple classes of historical operating state parameters. For example, the clustering method can be k-means clustering.

[0111] In step S220113, different driving style labels are added to the historical operating state parameters of different types to obtain the original driving state parameter samples.

[0112] In this step, different driving style labels are added to the historical operating state parameters of different categories to obtain the original driving state parameter samples. For example, the driving style labels may include: conservative style label r1, standard style label r2, and aggressive style label r3.

[0113] Figure 6 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 6, obtaining the current operating condition of the vehicle may include the following steps:

[0114] In step S1101, the current characteristic parameters of the vehicle are obtained, including one or more of the following: average vehicle speed, maximum vehicle speed, and number of start-stop cycles within a set time period.

[0115] In this step, the vehicle's current characteristic parameters are obtained, which may include one or more of the following: average speed, maximum speed, and number of starts and stops over a set time period (e.g., 5 minutes).

[0116] In step S1102, typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle are obtained. The typical characteristic parameters corresponding to each typical operating condition include one or more of the average vehicle speed, maximum vehicle speed and number of start-stop times of the vehicle within the set time under the typical operating condition.

[0117] In this step, typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle are obtained. The typical characteristic parameters corresponding to each typical operating condition include one or more of the following: average vehicle speed, maximum vehicle speed, and number of start-stop times within a set time period (e.g., 5 minutes) under the typical operating condition.

[0118] In step S1103, the similarity between the current feature parameter and the typical feature parameter corresponding to each typical operating condition is determined.

[0119] In this step, the similarity between the current feature parameter and the typical feature parameter corresponding to each typical operating condition is determined. This similarity can be Euclidean distance. Euclidean distance refers to the true distance d between two points in m-dimensional space. xy The calculation formula can be:

[0120] In the formula, x i It is the value of the i-th variable in sample x; y i is the value of the i-th variable in sample y; m is the total number of variables in the sample.

[0121] In step S1104, the typical operating condition corresponding to the minimum value in the similarity is taken as the current operating condition of the vehicle.

[0122] In this step, the minimum value of the calculated similarity, such as the typical operating condition corresponding to the minimum Euclidean distance in the calculated Euclidean distance, is taken as the current operating condition of the vehicle.

[0123] Figure 7 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 7, obtaining typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle may include the following steps:

[0124] In step S11021, raw operating condition data is collected under offline conditions. The raw operating condition data includes the raw operating data of the vehicle under different operating conditions.

[0125] In this step, raw operating condition data is collected offline. This raw operating condition data includes the vehicle's original operating data under different operating conditions. For example, the operating condition data may include congested road operating condition data, urban ordinary road operating condition data, expressway operating condition data, highway operating condition data, and operating environment data, such as whether the vehicle is following another vehicle or whether it is deviating from its lane.

[0126] In step S11022, the original operating condition data is cleaned to obtain cleaned operating condition data.

[0127] In this step, the original operating condition data is cleaned to obtain cleaned operating condition data. For example, the original operating condition data is cleaned by removing missing values, outliers, etc., to obtain cleaned operating condition data.

[0128] In step S11023, the cleaning operation data is sliced ​​to obtain an operation sample dataset.

[0129] In this step, the cleaning operation data is sliced ​​to obtain an operation sample dataset. For example, the cleaning operation data is segmented into segments with a fixed time period (e.g., 120s). Average vehicle speed, maximum vehicle speed, and other information are calculated from the segmented operation data to generate multiple sample datasets D, i.e.: D={(y i ,i=1,….,e),e∈Z,

[0130] Where e is the number of operating condition sample datasets, y i =(y i1 ,y i2 ,…,y im ),m∈Z,y i Let be the data vector of the i-th operating condition sample, m be the number of parameters of each operating condition sample data vector, and z be the number of samples of parameters of the operating condition sample data vector.

[0131] In step S11024, the operating condition sample dataset is clustered to obtain multiple operating condition cluster centers, and the multiple operating condition sample datasets corresponding to the multiple operating condition cluster centers are respectively used as the typical feature parameters corresponding to the multiple typical operating conditions.

[0132] In this step, for example, k-means clustering is performed on the operating condition sample dataset D to obtain four operating condition cluster centers C = (s1, s2, s3, s4). The four operating condition sample datasets corresponding to the four operating condition cluster centers s1, s2, s3, and s4 are used as typical feature parameters corresponding to the four typical operating conditions.

[0133] Figure 8 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 8, obtaining the desired operating state parameters based on the current operating condition may include the following steps:

[0134] In step S1201, the desired operating state parameters are obtained by looking up a table based on the current operating conditions.

[0135] In this step, the desired operating state parameters under the current operating conditions can be obtained by looking up a table. For example, the desired acceleration A parameter table can be shown in Table 1:

[0136] Table 1

[0137] The expected operating state parameter table is created offline using big data analytics to analyze the expected speed, acceleration, following distance, and steering wheel angle of conservative drivers under various operating conditions, forming a typical parameter table for expected operating states. For example, by acquiring historical operating data from different vehicles, including vehicle speed, accelerator pedal opening, brake pedal opening, steering wheel angle, longitudinal acceleration, and energy consumption, as well as environmental data such as distance to the vehicle in front, speed of the vehicle in front, and lane departure, the system identifies the current road conditions and whether the driver is following another vehicle or staying in the center of the lane using information such as vehicle speed and distance to the vehicle in front. It also identifies the current driving style using information such as vehicle speed, acceleration, accelerator pedal opening, and brake pedal opening. For example, vehicle operating conditions can be categorized as congested road conditions, ordinary urban road conditions, expressway conditions, and highway conditions, including whether following another vehicle is being observed and whether the driver is deviating from the lane; driving style types are mainly categorized as conservative, normal, and aggressive. The conservative driving style operation samples under various working conditions are processed to form a feature dataset. Typical parameters such as vehicle speed level, acceleration level, following distance, steering wheel angle, and steering speed from the conservative samples are extracted to form a typical parameter table for the desired operating state. It is worth noting that this typical parameter table can be periodically updated according to different vehicle models and time periods, making the driving behavior guidance suggestions more aligned with user needs and improving user adoption.

[0138] Figure 9 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 9, the difference between the current operating state parameter and the desired operating state parameter includes multiple different difference levels, wherein different difference levels correspond to different display effects; the step of prompting the driver based on the driving behavior suggestion may include the following steps:

[0139] In step S1401a, the target difference level is determined based on the difference between the current operating state parameter and the desired operating state parameter.

[0140] In this step, the target difference level is determined based on the difference between the current operating state parameters and the desired operating state parameters. For example, the difference between the current operating state parameters and the desired operating state parameters may include: a. Whether there is a sudden acceleration behavior, determined by the average acceleration A during acceleration in the current operating state. acce Compared with the preset acceleration value A 加preCompare them, if A acce ≥A 加pre Then it is considered that there is a rapid acceleration behavior; b. Whether there is a sudden braking behavior, the judgment condition is the average deceleration A during deceleration in the current running state. brake Compared with the preset deceleration value A 减pre Compare them, if A brake ≤A 减pre Then it is considered that there is a sudden deceleration behavior; c. Whether the current vehicle is too close to the vehicle in front, the judgment condition is that the current driving state is identified as following mode, and the following distance L is detected. car-follow Following distance L pre For comparison, if L car-follow ≤L pre Then it is considered to be following too closely; d. Whether the current vehicle is in a continuous overtaking state, the judgment condition is: by identifying whether the steering wheel has been turned in one direction more than a preset angle value W in a recent period of time. pre Within a preset time period (e.g., 10 seconds), it rotates in another direction by more than a preset angle value W. pre If this behavior is detected more than 3 times consecutively and the time interval between these behaviors does not exceed a certain preset value (e.g., 10 seconds), then the current vehicle can be considered to be engaging in continuous overtaking behavior; e. Whether the current vehicle is engaging in sharp turning behavior is determined by: identifying the steering wheel angle S of the current vehicle. now When the steering wheel angle exceeds the preset angle value S pre When the system assumes the vehicle is turning, it acquires the current vehicle speed information V. now If the current vehicle speed V now Exceeding the preset speed value V pre If the behavior is detected as a sharp turn, it is considered that the vehicle is engaging in such behavior. These behaviors can be categorized into different levels based on whether they exceed different preset thresholds; examples can be classified as mild, moderate, and severe, and can be used to implement different levels of driving behavior suggestions and guidance.

[0141] In step S1402a, the driving behavior suggestions are displayed according to the display effect corresponding to the target difference level.

[0142] In this step, driving behavior suggestions are displayed based on the display effects corresponding to the target difference level. For example, suggestions can be displayed for acceleration, braking, or left / right steering, along with animation effects indicating the response level of each action. For instance, this response level can be divided into three levels: Level I (light response, low priority); Level II (medium response, medium priority, medium priority); and Level III (high priority, high priority). The driving behavior guidance system continuously identifies the vehicle's status. If the driver performs the suggested actions, the suggestion reminder will be turned off once the target operating state is reached.

[0143] Figure 10 is a flowchart illustrating a driving assistance method according to an exemplary embodiment. As shown in Figure 10, the vehicle includes a head-up display system, and the step of providing prompts to the driver based on the driving behavior suggestions may include the following steps:

[0144] In step S1401b, the driving behavior suggestions are displayed through the head-up display system.

[0145] In this step, driving behavior suggestions are displayed via a head-up display system. For example, the driving behavior guidance system provides suggestions on the AR-HUD based on the identified level of difference in driving behavior. An example of such a suggestion is that a slow (e.g., 1.2s frequency) green warning light flashes on the AR-HUD when a minor difference / response is detected; an orange warning light flashes at a moderate speed (e.g., 0.8s frequency) when a moderate difference / response is detected; and a red warning light flashes at a relatively fast speed (e.g., 0.4s frequency) when a severe difference / response is detected. Meanwhile, corresponding animation effects are presented for different driving behaviors. For example, when rapid acceleration is detected, the animation shows the accelerator pedal being slowly released to the desired value, accompanied by flashing lights to provide driving behavior guidance; when continuous overtaking is detected, the animation shows the steering wheel changing from swaying left and right to a stable state, accompanied by flashing lights to provide driving behavior guidance; when sharp turning is detected, the animation shows the turning road and draws the dynamic process of the current vehicle speed curve smoothly decreasing from high speed to the desired speed, accompanied by flashing lights to provide driving behavior guidance; when following too closely is detected, the animation can show the dynamic process of a car changing its distance from too close to the car in front (or a moving obstacle) to the desired distance, accompanied by flashing lights to provide driving behavior guidance.

[0146] In summary, this disclosure provides a driving assistance method, comprising: acquiring the current operating condition of a vehicle; acquiring desired operating state parameters based on the current operating condition; generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters; and providing prompts to the driver based on the driving behavior suggestions. This disclosure can provide driving behavior guidance to users through AR-HUD based on the user's driving style and the vehicle's current operating condition. The real-time interactive capabilities and intelligent information transmission experience provided by AR-HUD support the application value of the driving behavior guidance function, guiding users to improve their driving behavior in a timely manner, reducing vehicle energy consumption, and improving driving safety, thus bringing users a more intelligent driving experience.

[0147] Figure 11 is a block diagram illustrating a driving assistance device according to an exemplary embodiment. As shown in Figure 11, this disclosure provides a driving assistance device 1100, which may include the following components:

[0148] The first acquisition device 1110 is used to acquire the current operating condition of the vehicle.

[0149] The second acquisition device 1120 is used to acquire the desired operating state parameters based on the current operating conditions.

[0150] The suggested device 1130 is used to generate driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters.

[0151] Display device 1140 is used to provide prompts to the driver based on the driving behavior suggestions.

[0152] Optionally, the first acquiring device 1110 is further configured to:

[0153] Obtain the vehicle's current operating status parameters;

[0154] Based on the current operating status parameters, the driver's driving style is obtained, including a conservative driving style and a non-conservative driving style.

[0155] The proposed device 1130 is also used for:

[0156] When the driver's driving style is the non-conservative driving style, driving behavior suggestions are generated based on the difference between the current operating state parameters and the expected operating state parameters.

[0157] Optionally, the first acquiring device 1110 is further configured to:

[0158] The current operating status parameters are input into a pre-established driving style recognition model to obtain the driver's driving style.

[0159] Optionally, the first acquiring device 1110 is further configured to:

[0160] Obtain a sample of original driving state parameters, which includes historical operating state parameters and driving style labels;

[0161] The driving style recognition model is trained based on the original driving state parameter samples.

[0162] Optionally, the first acquiring device 1110 is further configured to:

[0163] Collect historical operational status parameters;

[0164] Clustering the historical operating state parameters yields multiple categories of historical operating state parameters;

[0165] Different driving style labels are added to different types of historical operating state parameters to obtain original driving state parameter samples.

[0166] Optionally, the current operating status parameters include at least one of the following parameters within a preset time period:

[0167] Average vehicle speed, standard deviation of vehicle speed, average acceleration, average deceleration, rate of change of acceleration, average accelerator pedal opening, and standard deviation of accelerator pedal opening.

[0168] Optionally, the first acquiring device 1110 is further configured to:

[0169] Obtain the current characteristic parameters of the vehicle, which include one or more of the following: average vehicle speed, maximum vehicle speed, and number of start-stop cycles within a set time period;

[0170] Obtain typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle. The typical characteristic parameters corresponding to each typical operating condition include one or more of the average vehicle speed, maximum vehicle speed and number of start-stop times of the vehicle within the set time under the typical operating condition.

[0171] Determine the similarity between the current feature parameter and the typical feature parameter corresponding to each typical operating condition;

[0172] The typical operating condition corresponding to the minimum value in the similarity is taken as the current operating condition of the vehicle.

[0173] Optionally, the first acquiring device 1110 is further configured to:

[0174] Raw operating condition data is collected under offline conditions, including the raw operating data of the vehicle under different operating conditions.

[0175] The original operating condition data is cleaned to obtain cleaned operating condition data;

[0176] The cleaning operation data is sliced ​​to obtain an operation sample dataset.

[0177] The operating condition sample dataset is clustered to obtain multiple operating condition cluster centers. The multiple operating condition sample datasets corresponding to the multiple operating condition cluster centers are respectively used as the typical feature parameters corresponding to the multiple typical operating conditions.

[0178] Optionally, the second acquiring device 1120 is further configured to:

[0179] Based on the current operating conditions, the desired operating state parameters are obtained by looking up a table.

[0180] Optionally, the difference between the current operating state parameter and the desired operating state parameter includes multiple different difference levels, wherein different difference levels correspond to different display effects; the display device 1140 is further used for:

[0181] Determine the target difference level to which the difference between the current operating state parameters and the expected operating state parameters belongs;

[0182] Based on the display effect corresponding to the target difference level, the driving behavior suggestions are displayed.

[0183] Optionally, the vehicle includes a head-up display system, and the display device 1140 is further used for:

[0184] The driving behavior suggestions are displayed through the head-up display system.

[0185] Regarding the apparatus in the above embodiments, the specific manner in which each device performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0186] In summary, this disclosure provides a driving assistance device, comprising: a first acquisition device for acquiring the current operating condition of a vehicle; a second acquisition device for acquiring desired operating state parameters based on the current operating condition; a suggestion device for generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters; and a display device for providing prompts to the driver based on the driving behavior suggestions. This disclosure can provide driving behavior guidance to users based on the difference between the current and desired operating state parameters, helping users improve their driving behavior in a timely manner, reducing vehicle energy consumption, and improving driving safety, thus bringing users a more intelligent driving experience.

[0187] Figure 12 is a block diagram illustrating an electronic device according to an exemplary embodiment. As shown in Figure 12, the electronic device 1200 may be a driver assistance controller, and the electronic device 1200 may include: a processor 1201, a memory 1202. The electronic device 1200 may also include one or more of a multimedia component 1203, an input / output (I / O) interface 1204, and a communication component 1205.

[0188] The processor 1201 controls the overall operation of the electronic device 1200 to complete all or part of the steps in the aforementioned driving assistance method. The memory 1202 stores various types of data to support the operation of the electronic device 1200. This data may include, for example, instructions for any application or method operating on the electronic device 1200, and application-related data such as contact data, sent and received messages, pictures, audio, video, etc. The memory 1202 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. Multimedia component 1203 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 1202 or transmitted via communication component 1205. The audio component also includes at least one speaker for outputting audio signals. I / O interface 1204 provides an interface between processor 1201 and other interface devices, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 1205 is used for wired or wireless communication between the electronic device 1200 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or combinations thereof, is not limited here. Therefore, the corresponding communication component 1205 may include: Wi-Fi devices, Bluetooth devices, NFC devices, etc.

[0189] In an exemplary embodiment, the electronic device 1200 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the driving assistance method described above.

[0190] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the driving assistance method described above. For example, the computer-readable storage medium may be the memory 1202 including program instructions, which may be executed by the processor 1201 of the electronic device 1200 to complete the driving assistance method described above.

[0191] In another exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program executable by a programmable device, the computer program having a code portion for performing the above-described driving assistance method when executed by the programmable device.

[0192] Figure 13 is a block diagram illustrating a vehicle according to an exemplary embodiment. As shown in Figure 13, this embodiment of the present disclosure provides a vehicle 1300, including the aforementioned electronic device 1200. Since the electronic device 1200 is capable of implementing the driving assistance method of this disclosure, the electronic device 1200 possesses the aforementioned advantages. Since the vehicle 1300 includes the electronic device 1200, the vehicle 1300 also possesses the aforementioned advantages.

[0193] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0194] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0195] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A driving assistance method, characterized in that, The method includes: Obtain the current operating status of the vehicle; Based on the current operating conditions, obtain the desired operating state parameters; Based on the difference between the current operating state parameters and the desired operating state parameters, driving behavior suggestions are generated; The driver is prompted based on the driving behavior suggestions.

2. The method according to claim 1, characterized in that, Before generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters, the method further includes: Obtain the vehicle's current operating status parameters; Based on the current operating status parameters, the driver's driving style is obtained, including a conservative driving style and a non-conservative driving style. The step of generating driving behavior suggestions based on the difference between the current operating state parameters and the desired operating state parameters includes: When the driver's driving style is the non-conservative driving style, driving behavior suggestions are generated based on the difference between the current operating state parameters and the expected operating state parameters.

3. The method according to claim 2, characterized in that, The step of obtaining the driver's driving style based on the current operating status parameters includes: The current operating status parameters are input into a pre-established driving style recognition model to obtain the driver's driving style.

4. The method according to claim 3, characterized in that, The method for establishing the driving style recognition model includes: Obtain a sample of original driving state parameters, which includes historical operating state parameters and driving style labels; The driving style recognition model is trained based on the original driving state parameter samples.

5. The method according to claim 4, characterized in that, The acquisition of the original driving state parameter sample includes: Collect historical operational status parameters; Clustering the historical operating state parameters yields multiple categories of historical operating state parameters; Different driving style labels are added to different types of historical operating state parameters to obtain original driving state parameter samples.

6. The method according to any one of claims 2-5, characterized in that, The current operating status parameters include at least one of the following parameters within a preset time period: Average vehicle speed, standard deviation of vehicle speed, average acceleration, average deceleration, rate of change of acceleration, average accelerator pedal opening, and standard deviation of accelerator pedal opening.

7. The method according to claim 1, characterized in that, The acquisition of the vehicle's current operating status includes: Obtain the current characteristic parameters of the vehicle, which include one or more of the following: average vehicle speed, maximum vehicle speed, and number of start-stop cycles within a set time period; Obtain typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle. The typical characteristic parameters corresponding to each typical operating condition include one or more of the average vehicle speed, maximum vehicle speed and number of start-stop times of the vehicle within the set time under the typical operating condition. Determine the similarity between the current feature parameter and the typical feature parameter corresponding to each typical operating condition; The typical operating condition corresponding to the minimum value in the similarity is taken as the current operating condition of the vehicle.

8. The method according to claim 7, characterized in that, The acquisition of typical characteristic parameters corresponding to multiple typical operating conditions of the vehicle includes: Raw operating condition data is collected under offline conditions, including the raw operating data of the vehicle under different operating conditions. The original operating condition data is cleaned to obtain cleaned operating condition data; The cleaning operation data is sliced ​​to obtain an operation sample dataset. The operating condition sample dataset is clustered to obtain multiple operating condition cluster centers. The multiple operating condition sample datasets corresponding to the multiple operating condition cluster centers are respectively used as the typical feature parameters corresponding to the multiple typical operating conditions.

9. The method according to claim 1, characterized in that, The step of obtaining the desired operating state parameters based on the current operating conditions includes: Based on the current operating conditions, the desired operating state parameters are obtained by looking up a table.

10. The method according to any one of claims 1-9, characterized in that, The difference between the current operating status parameters and the expected operating status parameters includes multiple different difference levels, where different difference levels correspond to different display effects; The step of providing prompts to the driver based on the driving behavior suggestions includes: Determine the target difference level to which the difference between the current operating state parameters and the expected operating state parameters belongs; Based on the display effect corresponding to the target difference level, the driving behavior suggestions are displayed.

11. The method according to any one of claims 1-9, characterized in that, The vehicle includes a head-up display system, and the step of providing prompts to the driver based on the driving behavior suggestions includes: The driving behavior suggestions are displayed through the head-up display system.

12. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1-11.

13. A vehicle, characterized in that, include: The electronic device according to claim 12.

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