Method, device and equipment for intelligent adjustment of rearview mirror based on driving route and storage medium

Abstract

The application discloses a rearview mirror intelligent adjustment method and device based on a driving route, equipment and a storage medium, relates to the technical field of automobile driving control, and the rearview mirror intelligent adjustment method based on the driving route comprises the following steps: acquiring sensor data, wherein the sensor data comprises target pose data and driving planning data; obtaining a driving scene signal by a preset scene analysis model and the sensor data; obtaining a target adjustment angle of a rearview mirror according to a target rearview mirror angle adjustment model, the driving scene signal and the sensor data, so that the automobile can complete rearview mirror angle control according to the target adjustment angle. The application intelligently calculates the optimal rearview mirror adjustment angle by using the preset scene analysis model and the rearview mirror angle adjustment model through sensor information, so as to provide clear and comprehensive vision for the driver under various driving scenes, effectively reduce the vision blind area, and improve the driving safety.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobile driving control, and in particular to a rearview mirror intelligent adjustment method and device based on a driving route, equipment and a storage medium. BACKGROUND

[0002] With the development of automobile intelligence, the demand for driving assistance systems by drivers is increasing, especially in terms of driving safety. In a complex traffic environment, drivers need to keep abreast of the situation around the vehicle in real time. The rearview mirror, as an important tool for obtaining the side rear view, its intelligent adjustment has become a key requirement for improving driving safety.

[0003] Currently, the adjustment of most car rearview mirrors relies on manual operation by the driver, or only has basic automatic adjustment functions, such as automatic adjustment when reversing to provide a better view. These methods usually preset limited adjustment angles to adapt to normal driving and reversing in common scenarios, but lack the ability to adapt to complex driving environments.

[0004] However, in actual driving, various complex scenarios may be encountered, such as turning, merging into a main road, changing lanes, etc. At this time, the fixed angle of the rearview mirror may not meet the needs of the driver for the side rear view, resulting in a blind area and increasing the risk of driving. The limitation of the prior art is that it cannot intelligently adjust the rearview mirror angle in real time according to the driving route and specific circumstances, making it difficult for the driver to obtain the necessary side rear information in critical scenarios, thereby affecting the accurate judgment of the surrounding traffic conditions. Therefore, how to intelligently adjust the rearview mirror angle based on the driving route has become a problem to be solved. SUMMARY

[0005] The present application aims to provide a rearview mirror intelligent adjustment method and device based on a driving route, equipment and a storage medium, which aims to solve the technical problem of how to intelligently adjust the rearview mirror angle based on the driving route. To achieve the above-mentioned purpose, the present application proposes a rearview mirror intelligent adjustment method based on a driving route, which comprises:

[0006] Obtaining sensor data, the sensor data comprising target pose data and driving planning data;

[0007] Obtaining a driving scene signal by a preset scene analysis model and the sensor data;

[0008] Obtaining a target adjustment angle of the rearview mirror according to a target rearview mirror angle adjustment model, the driving scene signal and the sensor data, so that the automobile completes the rearview mirror angle control according to the target adjustment angle.

[0009] In an embodiment, obtaining a driving scene signal by a preset scene analysis model and the sensor data comprises:

[0010] obtaining a scene node set according to the driving planning data and a preset scene analysis model;

[0011] obtaining a target scene node by matching the scene node set with the target pose data;

[0012] obtaining a corresponding driving scene signal according to the target scene node.

[0013] In an embodiment, before obtaining the target scene node by matching the scene node set with the pose data, the method further comprises:

[0014] obtaining a preset distance threshold;

[0015] obtaining first position data according to the target pose data;

[0016] obtaining a reference scene node by matching the first position data with the scene node set;

[0017] obtaining a first target distance by matching the reference scene node with the first position data;

[0018] if the first target distance is greater than or equal to the preset distance threshold, exiting the rearview mirror angle control.

[0019] In an embodiment, before obtaining a target adjustment angle of the rearview mirror according to a target rearview mirror angle adjustment model, the driving scene signal and the sensor data, the method further comprises:

[0020] obtaining an initial rearview mirror angle adjustment model and initial data, wherein the initial data comprises reference environment data, reference pose data and reference user line-of-sight data;

[0021] obtaining training data and verification data based on the initial data, wherein the verification data is obtained by labeling the initial data;

[0022] obtaining a reference adjustment angle by matching the initial rearview mirror angle adjustment model with the training data;

[0023] obtaining a labeled adjustment angle based on the verification data;

[0024] determining a perspective loss value according to the reference adjustment angle and the labeled adjustment angle;

[0025] adjusting the initial rearview mirror angle adjustment model according to an angle adjustment parameter and the perspective loss value until the initial rearview mirror angle adjustment model converges to obtain a target rearview mirror angle adjustment model.

[0026] In an embodiment, the target adjustment angle of the rearview mirror is obtained according to a target rearview mirror angle adjustment model, the driving scene signal and the sensor data, so that the automobile completes the rearview mirror angle control according to the target adjustment angle, including:

[0027] A preset adjustment mode is determined according to the driving scene signal;

[0028] Target user line-of-sight data and target environment data are obtained through the sensor data;

[0029] The target adjustment angle of the rearview mirror is obtained according to the target pose data, the target user line-of-sight data, the target environment data and a target rearview mirror angle adjustment model;

[0030] The rearview mirror angle control is completed according to the target adjustment angle and the preset adjustment mode.

[0031] In an embodiment, after the target adjustment angle of the rearview mirror is obtained according to a target rearview mirror angle adjustment model, the driving scene signal and the sensor data, so that the automobile completes the rearview mirror angle control according to the target adjustment angle, the method further includes:

[0032] A target scene node, second position data and a preset safety distance threshold value and a preset angle are obtained;

[0033] Second target distance is obtained according to the second position data and the target scene node;

[0034] If the second target distance is greater than or equal to the preset safety distance threshold value, the rearview mirror is adjusted to the preset angle.

[0035] In an embodiment, after the second target distance is obtained according to the second position data and the target scene node, the method further includes:

[0036] A preset adjustment time threshold value is obtained;

[0037] The time when the target adjustment angle is obtained is recorded to obtain a target adjustment time;

[0038] If the target adjustment time is greater than or equal to the preset adjustment time threshold value, the rearview mirror is adjusted to the preset angle.

[0039] In addition, to achieve the above object, the application further provides a rearview mirror intelligent adjustment device based on a driving route, which comprises:

[0040] An acquisition module is configured to acquire sensor data, wherein the sensor data comprises target pose data and driving planning data;

[0041] obtaining a driving scene signal by a preset scene analysis model and the sensor data;

[0042] completing a target adjustment angle of the rearview mirror according to a target rearview mirror angle adjustment model, the driving scene signal and the sensor data, so as to complete the rearview mirror angle control according to the target adjustment angle.

[0043] In addition, to achieve the above object, the present application also provides a rearview mirror intelligent adjustment device based on a driving route, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the rearview mirror intelligent adjustment method based on a driving route as described above.

[0044] In addition, to achieve the above object, the present application also provides a storage medium, which is a computer readable storage medium, and a computer program is stored on the storage medium, and the computer program is executed by a processor to implement the steps of the rearview mirror intelligent adjustment method based on a driving route as described above.

[0045] In addition, to achieve the above object, the present application also provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the rearview mirror intelligent adjustment method based on a driving route as described above.

[0046] The one or more technical solutions provided by the present application have at least the following technical effects:

[0047] The present application first collects sensor data to master the position, posture and driving path to be executed of the vehicle in real time, to provide basic information for subsequent driving scene analysis and rearview mirror adjustment. Then, the sensor data and the preset scene analysis model are used to identify the current driving scene, such as the upcoming turn, merging into the main road, etc., thereby providing a scene basis for rearview mirror adjustment. Finally, the driving scene signal and the sensor data are combined to calculate the most suitable rearview mirror angle for the current driving scene, to ensure that the driver obtains the best side rear view. The present application can automatically adjust the rearview mirror angle according to the real-time driving environment, to adapt to various complex driving scenes, eliminate the visual blind area caused by improper rearview mirror angle in complex traffic environment, ensure clear rear view in various situations, reduce the risk of accidents caused by insufficient view, and improve the safety of driving. BRIEF DESCRIPTION OF DRAWINGS

[0048] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings can also provide the basis for obtaining other drawings for those skilled in the art without any creative effort.

[0050] Figure 1 The flowchart provided by the present application for the first embodiment of the intelligent adjustment method of the rearview mirror based on the driving route;

[0051] Figure 2 The flowchart provided by the present application for the second embodiment of the intelligent adjustment method of the rearview mirror based on the driving route;

[0052] Figure 3 The module structure diagram of the present application for the intelligent adjustment device of the rearview mirror based on the driving route;

[0053] Figure 4 The device structure diagram of the hardware running environment involved in the intelligent adjustment method of the rearview mirror based on the driving route in the embodiments of the present application.

[0054] The purpose of the present application, the functional characteristics and the advantages will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0055] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application, and are not used to limit the present application.

[0056] In order to better understand the technical solutions of the present application, the specific embodiments will be described in detail with reference to the accompanying drawings and the specific embodiments.

[0057] With the development of automobile intelligence, drivers have increasing demand for driving assistance systems, especially in terms of driving safety. In complex traffic environments, drivers need to have real-time awareness of the conditions around the vehicle. Rearview mirrors are important tools for obtaining side rear views, and the intelligent adjustment of rearview mirrors is a key requirement for improving driving safety. Currently, most rearview mirror adjustments in vehicles rely on manual operation by the driver or have only basic automatic adjustment functions, such as automatic adjustment during reversing to provide a better view. These methods usually have limited preset adjustment angles to accommodate normal driving and reversing, but lack the ability to adapt to complex driving environments. However, there are many complex scenarios in actual driving, such as turning, merging onto a main road, changing lanes, etc. In these situations, the fixed angle of the rearview mirror may not meet the driver's needs for side rear visibility, resulting in a blind area and increasing the risk of driving. The limitation of existing technology is the inability to intelligently adjust the rearview mirror angle in real time based on the driving route and specific conditions, making it difficult for the driver to obtain the necessary side rear information in critical situations, thereby affecting the accurate judgment of the surrounding traffic conditions.

[0058] The main solution of the embodiments of the present application is that the embodiments first collect sensor data to real-time master the position, posture and driving path to be executed of the vehicle, providing basic information for subsequent driving scene analysis and rearview mirror adjustment. Then, using sensor data and a preset scene analysis model, the current driving scene can be identified, such as about to turn, merge onto a main road, etc., thereby providing a scene basis for rearview mirror adjustment. Finally, combining the driving scene signal and sensor data, the most suitable rearview mirror angle for the current driving scene is calculated to ensure that the driver obtains the best side rear visibility. The embodiments can intelligently automatically adjust the rearview mirror angle according to the real-time driving environment to adapt to various complex driving scenarios, eliminating the blind area caused by improper rearview mirror angle in complex traffic environments, ensuring clear rear visibility in all situations, reducing the risk of accidents due to insufficient visibility, and thereby improving driving safety.

[0059] It should be noted that the execution subject of the embodiments of the present application can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device or an electronic control unit capable of realizing the above functions. The embodiments of the present application and the following embodiments will be described below with the electronic control unit as an example.

[0060] Based on this, the embodiments of the present application provide a rearview mirror intelligent adjustment method based on a driving route, which is described with reference to Figure 1 , Figure 1 The flowchart of the first embodiment of the rearview mirror intelligent adjustment method based on a driving route of the present application is shown in FIG. 1.

[0061] In this embodiment, the intelligent rearview mirror adjustment method based on driving route includes steps S10-S30:

[0062] Step S10, obtain sensor data, the sensor data including target pose data and driving planning data;

[0063] It should be noted that sensor data can be data collected and measured by sensing devices, which can be real-time state data representing the running state at a certain time, such as speed, power, etc.; or cumulative data representing the cumulative amount of data within a certain range, such as mileage, heat consumption, etc. In the field of automotive intelligence, sensor data is particularly important because they provide the car with information about its running state and environment, which is crucial for functions such as autonomous driving, safety monitoring, etc. Target pose data can be data describing the position and attitude of an object in space (including three dimensions of position and three dimensions of rotation, i.e. the so-called "six-dimensional pose"). In an autonomous vehicle, this may include the vehicle's Global Positioning System (GPS) coordinates, the vehicle's position relative to the surrounding environment, and the vehicle's direction and inclination angle, etc. Driving planning data involves the vehicle's driving path, speed, acceleration, etc. These data are usually generated by the vehicle's navigation system and driving assistance system to guide the vehicle to travel safely and efficiently according to the established route. Driving planning data can include path planning scheme, estimated arrival time, traffic condition information, etc., to help the vehicle make decisions in complex traffic environments. In summary, sensor data, target pose data and driving planning data together provide the car with comprehensive state and environmental perception capabilities, enabling the car to make precise control decisions based on real-time data to adapt to different driving scenarios and improve driving safety.

[0064] It can be understood that this step of obtaining sensor data involves collecting real-time information of the vehicle, which together provides the basis for decision-making for the intelligent adjustment of the rearview mirror system, enabling it to intelligently adjust the angle of the rearview mirror according to the actual driving conditions of the vehicle and the surrounding environment to optimize the driver's field of view.

[0065] Step S20, obtain driving scene signal by preset scene analysis model and sensor data;

[0066] It should be noted that the preset scene analysis model can be an analysis model established based on specific scene characteristics and rules, which can intelligently analyze and understand the driving environment of the vehicle. This model integrates deep learning algorithms, data mining techniques and various sensor data fusion technologies to identify and understand scene elements such as traffic signals, road signs, construction areas, etc. The driving scene signal can be a signal obtained by analyzing sensor data through the model, describing the specific driving environment and conditions of the vehicle, such as whether the vehicle is approaching an intersection, whether it is in a turning state, whether it needs to adjust the vehicle speed, etc. These signals are the key inputs for vehicle intelligent decision-making and control, such as automatic adjustment of rearview mirrors, vehicle speed control, etc., which enable the vehicle to more intelligently adapt to complex traffic environments, improving driving safety and efficiency.

[0067] It can be understood that by using a predefined analysis model, combined with real-time sensor data of the vehicle (such as position, speed, steering angle, etc.), the specific driving environment and state of the vehicle (such as straight driving, turning, approaching an intersection, etc.) are intelligently identified and judged, and these information is converted into driving scene signals, providing accurate basis for subsequent vehicle control decisions (such as rearview mirror adjustment, vehicle speed adjustment, etc.).

[0068] As an example, the driving scene signal is obtained through the preset scene analysis model and the sensor data, including: obtaining a scene node set according to the driving planning data and the preset scene analysis model; obtaining a target scene node by matching the scene node set with the target pose data; obtaining a corresponding driving scene signal according to the target scene node.

[0069] Among them, the scene node set can be a series of key points or condition sets defined in the preset scene analysis model, which represent various specific environments or events that may be encountered during driving, such as intersections, turning points, merging points, etc. These nodes are the basis for the model to identify and analyze driving scenes, used to divide complex driving environments into identifiable and operable units. The target scene node refers to the specific node matched from the scene node set, which is determined based on the comparison and analysis of the current target pose data of the vehicle (such as real-time position, speed, direction, etc.) and the scene node set. This node is directly related to the specific driving scene that the vehicle is about to enter or is experiencing, such as the intersection that the vehicle is about to reach or the bend that the vehicle is passing through. The driving scene signal can be a signal obtained according to the target scene node, which describes the specific driving scene of the vehicle in detail, providing necessary information for the intelligent system of the vehicle to make corresponding operations and decisions, such as adjusting the rearview mirror angle, changing the vehicle speed, issuing warnings, etc. This signal is the key for the vehicle intelligent control system to respond to external environmental changes, ensuring that the vehicle can safely and efficiently drive.

[0070] Specifically, first, a series of possible driving scene nodes, i.e., a scene node set, are determined according to the driving planning data of the vehicle and a preset scene analysis model built-in; then, the real-time target pose data of the vehicle is matched with the scene nodes to identify a specific scene node, i.e., a target scene node, into which the vehicle is about to enter or is currently in; finally, a corresponding driving scene signal is generated according to the target scene node, which describes in detail the specific driving environment and state of the vehicle, providing an accurate basis for subsequent driving decision and control.

[0071] As an example, before the target scene node is obtained by matching the scene node set with the pose data, the method further includes: obtaining a preset distance threshold; obtaining first position data according to the target pose data; obtaining a reference scene node by matching the first position data with the scene node set; obtaining a first target distance by matching the reference scene node with the first position data; and if the first target distance is greater than or equal to the preset distance threshold, exiting the control of the rearview mirror angle.

[0072] The preset distance threshold can be a distance parameter set in advance, which is used to determine the critical distance for determining whether the rearview mirror angle needs to be adjusted. When the distance between the vehicle and a specific scene node (such as a turning point or a merging point) reaches or exceeds this threshold, it will be determined whether the rearview mirror angle needs to be adjusted. The first position data can be position information calculated by the vehicle based on the target pose data, which usually includes the current position coordinates (such as latitude and longitude) of the vehicle, speed, heading, etc., for determining the specific position of the vehicle in space. The reference scene node can be a specific node selected from the scene node set that is related to the current position of the vehicle. By comparing the first position data with the scene node set, it can be determined which scene nodes are closest or most relevant to the current position of the vehicle, and these nodes are the reference scene nodes. The first target distance can be the distance between the current position of the vehicle (first position data) and the reference scene node. By calculating this distance, the proximity of the vehicle to the upcoming driving event (such as turning or merging) can be determined.

[0073] Specifically, a preset distance threshold is first set, and then the current position of the vehicle, i.e., the first position data, is determined according to the target pose data of the vehicle; then, this position data is matched with the scene node set to find the reference scene nodes most relevant to the position of the vehicle; then, the distances between the vehicle and these reference scene nodes, i.e., the first target distances, are calculated; finally, if the first target distance is greater than or equal to the preset distance threshold, it will be determined that the rearview mirror angle does not need to be adjusted, i.e., the rearview mirror angle control process is exited, to avoid unnecessary rearview mirror adjustment when the vehicle is too far from a key driving scene node.

[0074] As an example, before obtaining the target adjustment angle of the rearview mirror according to the target rearview mirror angle adjustment model, the driving scene signal, and the sensor data, the method further includes: obtaining an initial rearview mirror angle adjustment model and initial data, the initial data including reference environment data, reference pose data, and reference user line-of-sight data; obtaining training data and verification data based on the initial data, the verification data being obtained after the initial data is labeled; obtaining a reference adjustment angle through the initial rearview mirror angle adjustment model and the training data; obtaining a labeled adjustment angle based on the verification data; determining a perspective loss value according to the reference adjustment angle and the labeled adjustment angle; and adjusting the initial rearview mirror angle adjustment model according to an angle adjustment parameter and the perspective loss value until the initial rearview mirror angle adjustment model converges to obtain the target rearview mirror angle adjustment model.

[0075] The initial rearview mirror angle adjustment model is a machine learning-based system, which generally includes a data input layer, a feature extraction layer, a model core layer, and an output layer. In the data input layer, the model receives initial data, including reference environment data, reference pose data, and reference user line-of-sight data. These data are used to describe the vehicle's surrounding environment, the vehicle's position and attitude, and the driver's line-of-sight direction. The feature extraction layer is responsible for identifying and extracting key features from the input data, which are crucial for predicting the optimal adjustment angle of the rearview mirror. The model core layer usually contains multiple hidden layers, such as multi-layer perceptron or convolutional layers in deep learning models, to learn the complex mapping relationship between features and rearview mirror angle adjustment. Finally, the output layer generates the predicted reference adjustment angle, i.e., the rearview mirror angle predicted by the model based on the input features. The entire model is trained through training data, and during the training process, the model parameters are adjusted to minimize the angle loss value between the predicted angle and the labeled adjustment angle in the validation data until the model converges, which can accurately predict the rearview mirror angle under various conditions, forming the target rearview mirror angle adjustment model. The initial data can include three types of data for training and adjusting the initial model. The reference environment data can be used to describe the information of the vehicle's surrounding environment, such as road type, traffic conditions, etc. The reference pose data can describe the position and attitude information of the vehicle, such as the vehicle's latitude, longitude, heading, tilt angle, etc. The reference user line-of-sight data can be used to describe the driver's line-of-sight direction and focus point data to understand the driver's visual needs. The training data can be a dataset extracted from the initial data and used to train the initial rearview mirror angle adjustment model, helping the model learn how to predict the optimal rearview mirror angle. The validation data can be a dataset extracted from the initial data and used to verify the accuracy of the model's prediction, which is labeled, i.e., the correct rearview mirror angle is known. The reference adjustment angle can be the predicted angle calculated by the initial rearview mirror angle adjustment model and the training data, used to compare with the actual labeled angle. The labeled adjustment angle can be the correct rearview mirror angle known in the validation data, labeled by artificial labeling or obtained by other accurate measurement methods. The angle loss value can be the difference between the reference adjustment angle and the labeled adjustment angle, used to evaluate the accuracy of the model's prediction. The angle adjustment parameters can be parameters for adjusting the model to improve its prediction performance, which may include learning rate, weight decay, etc. The target rearview mirror angle adjustment model can be the final model obtained after multiple iterations and adjustments, which can accurately predict the optimal adjustment angle of the rearview mirror under different conditions.

[0076] Specifically, first, initial data is collected, including information such as environment, vehicle pose, and user line of sight. Then, a training set and a validation set are separated from the data, where the data of the validation set is accurate angle data manually labeled. Next, the initial rearview mirror angle adjustment model is trained using the training set data, and reference adjustment angles are generated. These angles are then compared with the labeled adjustment angles in the validation set to calculate the angle of view loss value, i.e., the difference between the model prediction value and the actual value. Finally, based on this loss value and some adjustment parameters, the model is iteratively optimized until the model can accurately predict the optimal angle of the rearview mirror, at which point the initial model converges to the target rearview mirror angle adjustment model, which can be used for actual automatic adjustment of the rearview mirror.

[0077] Step S30, according to the target rearview mirror angle adjustment model, the driving scene signal and the sensor data, the target adjustment angle of the rearview mirror is obtained, so that the automobile completes the rearview mirror angle control according to the target adjustment angle.

[0078] It should be noted that the target adjustment angle can be the optimal angle to which the rearview mirror should be adjusted, which is calculated based on the target rearview mirror angle adjustment model, the current driving scene signal, and real-time sensor data. This angle is based on a comprehensive analysis of the environment and driving state of the vehicle, and the purpose is to provide the best side rear view for the driver and ensure clear and comprehensive vision in various driving scenarios to improve driving safety.

[0079] It can be understood that the target rearview mirror angle adjustment model, which is an algorithm or mathematical model trained to accurately calculate the ideal rearview mirror position based on various input data, is used in combination with real-time driving scene signals and sensor data such as vehicle speed, steering angle, road conditions, etc. to dynamically calculate the target angle to which the rearview mirror should be adjusted. Subsequently, the automobile will automatically adjust the rearview mirror according to the calculated target adjustment angle to ensure that the driver can obtain the best side rear view in various driving scenarios, thereby improving driving safety and convenience.

[0080] As an example, after obtaining the target adjustment angle of the rearview mirror according to the target rearview mirror angle adjustment model, the driving scene signal and the sensor data, the method further comprises: obtaining a target scene node, second position data and a preset safety distance threshold and a preset angle; obtaining a second target distance according to the second position data and the target scene node; if the second target distance is greater than or equal to the preset safety distance threshold, adjusting the rearview mirror to the preset angle.

[0081] Among them, the second position data can be the current position information of the vehicle after passing the target scene node, which includes the GPS coordinates, speed, direction, etc. of the vehicle, which is used to determine the specific position of the vehicle in space. The preset safety distance threshold can be a pre-set distance value, which is used to determine the minimum safety distance that the vehicle should maintain from the target scene node after passing the target scene node. When the distance between the vehicle and the target scene node is greater than or equal to this threshold, it is considered that the vehicle is far enough away from the node and specific operations need to be performed. The preset angle can be a specific angle to which the rearview mirror should be adjusted. This angle is determined based on the user's normal driving on a straight road, and is used to provide the best field of view when the vehicle leaves the target scene node. The second target distance can be the actual distance between the vehicle's current position (second position data) and the target scene node. This distance is calculated to determine whether the vehicle has exited the preset safety distance threshold range.

[0082] Specifically, the system first obtains the location of the target scene node, the vehicle's current location (second location data), a preset safety distance threshold, and the preset angle to which the rearview mirror should be adjusted. Then, the actual distance between the vehicle and the target scene node (the second target distance) is calculated. If this distance reaches or exceeds the preset safety distance threshold, indicating that the vehicle has exited the critical driving scene, the rearview mirror will be automatically adjusted to the preset angle to ensure that the driver returns the rearview mirror in time after passing the critical driving scene, thereby improving driving safety.

[0083] As an example, after obtaining the second target distance based on the second position data and the target scene node, it also includes: obtaining a preset adjustment time threshold; obtaining the time when the target adjustment angle is obtained and recording it to obtain the target adjustment time; if the target adjustment time is greater than or equal to the preset adjustment time threshold, adjusting the rearview mirror to the preset angle.

[0084] The preset adjustment time threshold can be a pre-set time parameter used to determine the time limit for rearview mirror adjustment operations. It defines the maximum time range allowed when adjusting the rearview mirror angle. If the adjustment operation time exceeds this threshold, the adjustment may be deemed no longer valid or require reassessment. The target adjustment time can be the actual time taken from the start of adjustment to reaching the target adjustment angle when adjusting the rearview mirror angle. This time record is used to compare with the preset adjustment time threshold to determine whether the adjustment operation was completed within a reasonable time range. By comparing the target adjustment time with the preset adjustment time threshold, it can be decided whether to continue adjusting the rearview mirror to the preset angle to ensure the effectiveness and timeliness of the adjustment process.

[0085] Specifically, a preset adjustment time threshold is set, i.e., the maximum time allowed for the rearview mirror to adjust to the target angle. During the adjustment of the rearview mirror, the time taken from the start of the adjustment to the target angle is recorded, i.e., the target adjustment time. If the target adjustment time exceeds the preset threshold, i.e., the adjustment process takes too long, it may be due to hardware failure or other problems that cause the adjustment to be completed in time, and the rearview mirror will be automatically restored to the preset safe angle to ensure that the driver's line of sight is not disturbed in normal driving conditions and driving safety is ensured.

[0086] The embodiment provides a rearview mirror intelligent adjustment method based on a driving route. The embodiment first collects sensor data to real-time master the position, posture and driving path to be executed of the vehicle, to provide basic information for subsequent driving scene analysis and rearview mirror adjustment. Then, the sensor data and a preset scene analysis model are used to identify the current driving scene, such as a coming turn, merging into a trunk road, etc., thereby providing a scene basis for rearview mirror adjustment. Finally, the rearview mirror angle most suitable for the current driving scene is calculated in combination with the driving scene signal and the sensor data, to ensure that the driver obtains the best side rear view. The embodiment can intelligently automatically adjust the rearview mirror angle according to the real-time driving environment to adapt to various complex driving scenes, eliminates the visual blind area of the driver due to improper rearview mirror angle in a complex traffic environment, ensures that a clear rear view is obtained in various situations, reduces the accident risk caused by insufficient view, and thus improves the safety of driving.

[0087] Based on the first embodiment of the application, the same or similar contents as the above-mentioned first embodiment can be referred to the above description, and will not be described in detail hereinafter. On this basis, please refer to Figure 2 , Figure 2 The flowchart of the second embodiment of the rearview mirror intelligent adjustment method based on a driving route of the application is shown in FIG. 6. The steps S30 of the rearview mirror intelligent adjustment method based on a driving route include steps S31-S34.

[0088] Step S31, determining a preset adjustment mode according to the driving scene signal;

[0089] It should be noted that the preset adjustment mode can be a series of parameters and operations preset according to a specific driving scene signal. These parameters and operations are configured to be automatically executed when a specific scene is detected, to optimize the performance and safety of the vehicle.

[0090] It can be understood that by identifying the current driving scene signals and automatically selecting a pre-set adjustment mode according to these signals. This pre-set adjustment mode is a series of parameters configured for a specific driving scene (such as straight driving, turning, reversing, etc.), which can include the speed of the rearview mirror angle control and the opening of the anti-dazzling function to ensure optimal driving visibility and safety in different driving situations.

[0091] Step S32, obtaining target user gaze data and target environment data through the sensor data;

[0092] It should be noted that the target user gaze data involves gaze estimation technology, which analyzes the facial features of the driver, especially the position and direction of the eyes, to infer the point or direction that the driver is looking at. This data is crucial for applications such as in-car interaction systems and driver attention monitoring systems, helping the system better understand the driver's intentions and needs. At the same time, it can also obtain the gaze height of different users, providing data support for subsequent adjustment of the target angle. The target environment data can include various information about the vehicle's surroundings, such as the positions and speeds of other vehicles, pedestrians, and obstacles. These data are usually collected by vehicle-mounted sensors such as cameras, radars, and LiDARs. Environmental data can be used to support automatic adjustment of the rearview mirror.

[0093] It can be understood that the data collected by sensors installed on the vehicle, such as cameras, infrared sensors, and eye tracking devices, are used to analyze and determine the driver's gaze direction and height (target user gaze data) and the state of the vehicle's surroundings (target environment data), including information about other vehicles, pedestrians, road signs, and obstacles. These data help the vehicle's intelligent system understand the driver's visual focus and external environment conditions, so as to make corresponding adjustments and responses, such as adjusting the rearview mirror angle or taking obstacle avoidance measures, to improve driving safety and comfort.

[0094] Step S33, obtaining the target adjustment angle of the rearview mirror according to the target pose data, the target user gaze data, the target environment data, and a target rearview mirror angle adjustment model;

[0095] It can be understood that by comprehensively considering the target pose data of the vehicle (including the position, speed, and direction of the vehicle), the target user gaze data (the direction and focus of the driver's gaze), the target environment data (information about the vehicle's surroundings, such as the positions of other vehicles, pedestrians, and obstacles), and a target rearview mirror angle adjustment model. Through these inputs, the specific angle to which the rearview mirror should be adjusted can be calculated to ensure that the driver can obtain the best side rear view in various driving situations, thereby improving driving safety and driving experience.

[0096] Step S34, according to the target adjustment angle and the preset adjustment mode, the rearview mirror angle control is completed.

[0097] It can be understood that after the target adjustment angle is determined, the actual angle adjustment of the rearview mirror will be performed according to this angle and the preset adjustment mode. The preset adjustment mode can include a series of operation procedures or strategies designed to cope with specific driving scenarios. The rearview mirror will be automatically adjusted to the calculated target angle, or fine-tuned according to the parameters and rules in the preset mode, to ensure that the angle of the rearview mirror can meet the needs of the current driving scenario and meet the safety and comfort standards.

[0098] The embodiment first identifies the current driving environment (such as straight driving, turning, parking, etc.) by analyzing the driving scenario signal, and selects a preset adjustment mode that is most suitable for the environment. This mode contains the rearview mirror adjustment parameters optimized for the specific scenario, ensuring that the rearview mirror can quickly respond and adapt to different driving conditions. Then by obtaining target user line of sight data and target environment data, the target adjustment angle is calculated, and finally according to the calculated target adjustment angle and the preset adjustment mode, the rearview mirror is automatically adjusted to the best position. This step ensures that the angle of the rearview mirror can adapt to the changes in the driving environment in real time, providing the driver with the best side and rear view. This embodiment reduces the need for the driver to manually adjust the rearview mirror, allowing them to focus more on driving and improving driving safety. At the same time, it also improves comfort because the driver can always have the best view regardless of changes in driving conditions.

[0099] It should be noted that the above examples are only for understanding the present application and do not constitute a limitation on the present application based on the intelligent adjustment method of the rearview mirror based on the driving route. More forms of simple transformation based on this technical concept are within the scope of protection of the present application.

[0100] The present application also provides a rearview mirror intelligent adjustment device based on a driving route, please refer to Figure 3 , the rearview mirror intelligent adjustment device based on the driving route includes:

[0101] The acquisition module 10 is used to acquire sensor data, and the sensor data includes target pose data and driving planning data.

[0102] The obtaining module 20 is used to obtain the driving scenario signal through a preset scene analysis model and the sensor data.

[0103] The completion module 30 is used to obtain the target adjustment angle of the rearview mirror according to the target rearview mirror angle adjustment model, the driving scenario signal and the sensor data, so that the automobile completes the rearview mirror angle control according to the target adjustment angle.

[0104] The rearview mirror intelligent adjustment device based on a driving route provided in the present application adopts the rearview mirror intelligent adjustment method based on a driving route in the above embodiment, and can solve the technical problem of how to intelligently adjust the angle of a rearview mirror based on a driving route. Compared with the prior art, the rearview mirror intelligent adjustment device based on a driving route provided in the present application has the same beneficial effects as the rearview mirror intelligent adjustment method based on a driving route provided in the above embodiment, and other technical features in the rearview mirror intelligent adjustment device based on a driving route are the same as the features disclosed in the above embodiment method, which will not be described here.

[0105] The present application provides a rearview mirror intelligent adjustment device based on a driving route. The rearview mirror intelligent adjustment device based on a driving route comprises at least one processor and a memory in communication connection with the at least one processor. The memory stores instructions executable by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to execute the rearview mirror intelligent adjustment method based on a driving route in the above embodiment one.

[0106] Reference will now be made to the drawings, in which Figure 4 which shows a structural diagram of a rearview mirror intelligent adjustment device based on a driving route suitable for implementing the embodiments of the present application. The rearview mirror intelligent adjustment device based on a driving route in the embodiments of the present application can include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. Figure 4 The rearview mirror intelligent adjustment device based on a driving route shown is only an example, and should not bring any limitation to the functions and use range of the embodiments of the present application.

[0107] As Figure 4As shown, the route-based intelligent rearview mirror adjustment apparatus can include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to programs stored in a read only memory (ROM) 1002 or loaded from a storage device 1003 into a random access memory (RAM) 1004. In the RAM 1004, various programs and data required for the operation of the route-based intelligent rearview mirror adjustment apparatus are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; the storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the route-based intelligent rearview mirror adjustment apparatus to communicate wirelessly or wired with other devices to exchange data. Although the route-based intelligent rearview mirror adjustment apparatus having various systems is shown in the figure, it should be understood that all of the shown systems are not required to be implemented or possessed. More or less systems can be alternatively implemented or possessed.

[0108] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of embodiments of the present disclosure are performed.

[0109] The rearview mirror intelligent adjustment device based on a driving route provided in the application adopts the rearview mirror intelligent adjustment method based on a driving route in the above embodiment, and can solve the technical problem of how to intelligently adjust the angle of a rearview mirror based on a driving route. Compared with the prior art, the rearview mirror intelligent adjustment device based on a driving route provided in the application has the same beneficial effects as the rearview mirror intelligent adjustment method based on a driving route provided in the above embodiment, and other technical features in the rearview mirror intelligent adjustment device based on a driving route are the same as the features disclosed in the above embodiment method, which will not be described here.

[0110] It should be understood that various parts of the present application can be realized by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0111] The above describes only specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0112] The present application provides a computer-readable storage medium having stored thereon computer-readable program instructions (i.e., a computer program) for executing the rearview mirror intelligent adjustment method based on a driving route in the above embodiment.

[0113] The computer readable storage medium provided in the application may, for example, be a U disk, but is not limited to an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system, system, or device, or any combination thereof. More specific examples of the computer readable storage medium may include, but are not limited to, an electric connection with one or more conductive wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the embodiment, the computer readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer readable storage medium can be transmitted by any suitable medium, including but not limited to an electric wire, an optical cable, an RF (Radio Frequency), and the like, or any suitable combination thereof.

[0114] The computer readable storage medium described above may be contained in the intelligent adjustment device for the rearview mirror based on the driving route, or may exist separately without being assembled into the intelligent adjustment device for the rearview mirror based on the driving route.

[0115] The computer readable storage medium described above carries one or more programs, which, when executed by the intelligent adjustment device for the rearview mirror based on the driving route, cause the intelligent adjustment device for the rearview mirror based on the driving route to: obtain sensor data, the sensor data including target pose data and driving planning data; obtain driving scene signals by a preset scene analysis model and the sensor data; obtain a target adjustment angle of the rearview mirror according to a target rearview mirror angle adjustment model, the driving scene signals, and the sensor data, so that the automobile completes the rearview mirror angle control according to the target adjustment angle.

[0116] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0117] The flow diagrams and the block diagrams in the drawings are illustrations of architectures, functionalities, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of present application. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may

[0118] The modules involved in the embodiments of the present application can be implemented in the form of software or in the form of hardware. In some cases, the name of the module does not constitute a limitation on the module itself.

[0119] The readable storage medium provided by the present application is a computer readable storage medium, which stores computer readable program instructions (i.e. computer programs) for executing the rearview mirror intelligent adjustment method based on the driving route, and can solve the technical problem of how to intelligently adjust the rearview mirror angle based on the driving route. Compared with the prior art, the computer readable storage medium provided by the present application has the same beneficial effects as the rearview mirror intelligent adjustment method based on the driving route provided by the above-mentioned embodiments, and will not be described here.

[0120] The application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the intelligent rearview mirror adjustment method based on a driving route as described above.

[0121] The computer program product provided by the application can solve the technical problem of how to intelligently adjust the angle of the rearview mirror based on the driving route. Compared with the prior art, the beneficial effects of the computer program product provided by the application are the same as those of the intelligent rearview mirror adjustment method based on the driving route provided by the above-mentioned embodiments, and are not described here.

[0122] The above only describes some embodiments of the application, and does not limit the patent scope of the application. Any equivalent structural transformation, direct / indirect application in other related technical fields, or direct / indirect application in other related technical fields based on the technical concept of the application and the content of the specification and drawings are included in the patent protection scope of the application.

Claims

1. A method for intelligently adjusting a rearview mirror based on a driving route, characterized in that: The method comprises: Acquiring sensor data, wherein the sensor data includes target position data and driving planning data of the vehicle; Obtaining a driving scene signal through a preset scene analysis model and the sensor data; Obtaining a target rearview mirror adjustment angle according to a target rearview mirror angle adjustment model, the driving scene signal, and the sensor data, so that the vehicle completes mirror angle control according to the target adjustment angle; The method of obtaining a driving scene signal by using a preset scene analysis model and the sensor data includes: Obtaining a scene node set according to the driving planning data and a preset scene analysis model; Matching the scene node set by the target pose data to obtain a target scene node; According to the target scene node, a corresponding driving scene signal is obtained.

2. The method according to claim 1, wherein Before obtaining the target scene node by matching the scene node set with the pose data, the method further includes: Get the preset distance threshold; Obtaining first position data according to the target posture data; Combine the first position data and the scene node set to obtain a reference scene node; Obtaining a first target distance using the reference scene node and the first position data; If the first target distance is greater than or equal to the preset distance threshold, the rearview mirror angle control is exited.

3. The method according to claim 1, wherein Before obtaining the target adjustment angle of the rearview mirror according to the target rearview mirror angle adjustment model, the driving scene signal and the sensor data, the method further includes: Acquire an initial rearview mirror angle adjustment model and initial data, wherein the initial data includes reference environment data, reference posture data, and reference user sight data; Obtaining training data and verification data based on the initial data, wherein the verification data is obtained after the initial data is labeled; Obtaining a reference adjustment angle using the initial rearview mirror angle adjustment model and the training data; Obtaining a marked adjustment angle based on the verification data; determining a viewing angle loss value according to the reference adjustment angle and the marked adjustment angle; The initial rearview mirror angle adjustment model is adjusted according to the angle adjustment parameter and the viewing angle loss value until the initial rearview mirror angle adjustment model converges to obtain a target rearview mirror angle adjustment model.

4. The method according to claim 1, wherein The method of obtaining a target rearview mirror adjustment angle based on the target rearview mirror angle adjustment model, the driving scene signal, and the sensor data, so that the vehicle completes the rearview mirror angle control according to the target rearview mirror angle, includes: determining a preset adjustment mode according to the driving scene signal; Obtaining target user sight data and target environment data through the sensor data; Obtaining a target adjustment angle of the rearview mirror according to the target posture data, the target user sight data, the target environment data, and a target rearview mirror angle adjustment model; The rearview mirror angle control is completed according to the target adjustment angle and the preset adjustment mode.

5. The method according to claim 1, wherein After obtaining the target adjustment angle of the rearview mirror according to the target rearview mirror angle adjustment model, the driving scene signal and the sensor data so that the vehicle completes the mirror angle control according to the target adjustment angle, the method further includes: Obtaining the target scene node, the second position data, a preset safety distance threshold, and a preset angle; Obtaining a second target distance according to the second position data and the target scene node; If the second target distance is greater than or equal to the preset safety distance threshold, the rearview mirror is adjusted to the preset angle.

6. The method according to claim 5, wherein After obtaining the second target distance according to the second position data and the target scene node, the method further includes: Get the preset adjustment time threshold; Obtaining and recording the time when the target adjustment angle is obtained to obtain the target adjustment time; If the target adjustment time is greater than or equal to the preset adjustment time threshold, the rearview mirror is adjusted to the preset angle.

7. An intelligent rearview mirror adjustment device based on driving route, characterized in that: The device comprises: An acquisition module is used to acquire sensor data, wherein the sensor data includes target posture data and driving planning data of the vehicle; An obtaining module is used to obtain a driving scene signal through a preset scene analysis model and the sensor data, specifically including obtaining a scene node set according to the driving planning data and the preset scene analysis model; obtaining a target scene node by matching the scene node set with the target pose data; and obtaining a corresponding driving scene signal according to the target scene node; The completion module is used to obtain the target adjustment angle of the rearview mirror according to the target rearview mirror angle adjustment model, the driving scene signal and the sensor data, so that the car can complete the rearview mirror angle control according to the target adjustment angle.

8. An intelligent rearview mirror adjustment device based on driving route, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the method for intelligently adjusting a rearview mirror based on a driving route as claimed in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the rearview mirror intelligent adjustment method based on the driving route as described in any one of claims 1 to 6 are implemented.

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