Disclosure of Invention
The invention aims to provide a control system for adaptively adjusting the position of an external rearview mirror based on a DMS (digital subscriber management system) so as to solve the problems in the background art.
In order to achieve the aim, the invention provides the technical scheme that the control system for adaptively adjusting the position of the external rearview mirror based on the DMS comprises a static judging module, a dynamic judging module, a DMS main module, a seat adjusting module, a memory module, an information acquisition module, a data analyzing module, a rearview mirror adjusting module and a feedback optimizing module;
The dynamic judging module is used for judging whether the vehicle with the control system is in dynamic running of the vehicle or not in running of the vehicle;
The DMS main module is used for capturing physiological information of the driver and transmitting the physiological information of the driver to the seat adjusting module or the information acquisition module;
The seat adjusting module is used for receiving the physiological information of the driver of the DMS module, carrying out adaptive adjustment on the main driving seat of the cockpit according to the physiological information of the driver, and feeding back to the memory module after the adjustment is finished;
The memory module is used for recording current seat information for the subsequent driver to select;
The information acquisition module is used for acquiring road information and vehicle running information and feeding the road information and the vehicle running information back to the data analysis module;
The data analysis module is used for analyzing and calculating the current dynamic physiological information, road information and vehicle running information of the driver, judging the current driving intention of the driver, calculating the optimal visual field and feeding back to the rearview mirror adjustment module;
The rearview mirror adjusting module is used for receiving the data of the memory module and the data analysis module and adjusting the rearview mirror;
The feedback optimization module collects effect feedback after adjustment execution, analyzes the adjustment effect and the satisfaction of a driver, identifies potential problems and improvement space, and continuously optimizes the system.
According to still further technical scheme, the DMS main module comprises a static acquisition module and a dynamic acquisition module;
The static acquisition module is used for acquiring static physiological information of a driver when the vehicle stops running;
the dynamic acquisition module is used for acquiring dynamic physiological information of a driver when the vehicle is in dynamic running.
According to still further technical scheme, the static physiological information comprises the height, sitting posture and sight direction of the driver, and the dynamic physiological information comprises the identification of the change trend of the head position, the sight direction and the body posture of the driver.
The application further provides a technical scheme that the road information comprises road line shape, road gradient, road width, number of lanes, intersection type, number of main road lanes of an intersection, number of vehicles of an intersected road, traffic volume of the intersection and road surface condition, and the vehicle running information comprises current speed, average speed, highest speed, current position of a vehicle, braking distance, braking time, steering angle and current lamplight information of the vehicle.
According to still a further technical scheme, the control system further comprises a safety monitoring and early warning module, wherein the safety monitoring and early warning module is used for monitoring the sight line direction and the attention concentration degree of a driver in real time in the adjusting process, and sending an early warning signal if the sight line deviation or the lack of concentration of the driver is detected.
The application also provides a control method for adaptively adjusting the position of the external rearview mirror based on the DMS, which comprises the following steps:
s1, starting a static judging module to determine whether a driver drives the vehicle for the first time;
s2, if the driver drives for the first time, starting a static acquisition module of the DMS main module to acquire static physiological information of the driver;
s3, automatically adjusting the driver seat through the seat adjusting module by utilizing the static physiological information, and confirming an adjusting result by the driver;
S4, starting a dynamic judging module to monitor whether the vehicle is in a running state or not;
S5, starting a dynamic acquisition module of the DMS main module to acquire dynamic physiological information of a driver during running of the vehicle;
s6, collecting road and vehicle running information through an information acquisition module;
S7, the data analysis module processes the dynamic physiological information, the road information and the vehicle running information to judge the driving intention of the driver and calculate the optimal visual field;
s8, automatically adjusting the position of the rearview mirror by the rearview mirror adjusting module according to the calculation result of the data analyzing module;
And S9, the feedback optimization module collects and analyzes the adjustment effect, interacts with a driver to evaluate the satisfaction degree, and continuously optimizes the system.
According to a still further technical scheme, the step S7 further comprises the following steps:
S7.1, receiving dynamic physiological information of a driver from a dynamic acquisition module of the DMS main module, wherein the dynamic physiological information comprises the change trend of the head position, the sight direction and the body posture;
s7.2, receiving road information from an information acquisition module, wherein the road information comprises road line shape, road gradient, road width, number of lanes, intersection type, number of main road lanes of an intersection, number of vehicles of the intersected road, traffic volume of the intersection and road surface condition;
s7.3, receiving vehicle running information from an information acquisition module, wherein the vehicle running information comprises current speed, average speed, highest speed, current position of the vehicle, braking distance, braking time, steering angle and current lamplight information of the vehicle;
S7.4, formatting and standardizing the collected data, analyzing the dynamic physiological information of the driver by using a machine learning algorithm or a rule engine, and identifying the driving behavior mode and intention of the driver;
s7.5, combining the road information and the vehicle running information to further verify and refine the driving intention of the driver;
S7.6, calculating the optimal view angle and position of the rearview mirror according to the driving intention of a driver and the running state of the vehicle, and adjusting the view calculation result in consideration of road conditions and traffic conditions so as to ensure that the optimal view can be provided under various conditions;
s7.7, comparing the calculated view angle and position with the current rearview mirror setting to determine whether adjustment is needed;
s7.8, if adjustment is needed, generating an adjustment instruction, and executing the adjustment instruction through a rearview mirror adjustment module;
And S7.9, feeding back the results of the view calculation and adjustment to a feedback optimization module for subsequent system optimization and performance evaluation.
According to a still further technical scheme, the step S9 further comprises the following steps:
s9.1, automatically recording the visual field change after the rearview mirror is adjusted and physiological feedback data of a driver;
S9.2, inquiring satisfaction degree of the adjusting effect to a driver through a vehicle-mounted interface or a voice interaction system;
s9.3, evaluating system performance and user satisfaction by using a data analysis technology in combination with the collected data and driver feedback;
S9.4, according to the evaluation result, formulating and implementing system optimization measures including software upgrading and parameter adjustment;
And S9.5, putting the optimized system into operation again, and collecting new feedback data to form a continuously improved closed loop.
The application further provides a technical scheme that the step S7.4 further comprises the following steps:
s7.4.1 cleaning the collected dynamic physiological information, road information and vehicle running information, removing noise and abnormal values, ensuring data quality, converting the cleaned data into a uniform format so as to carry out subsequent analysis processing, and carrying out standardized processing on the data, so that the data with different sources and different dimensions have comparability, and the analysis accuracy is improved;
S7.4.2 extracting features which are helpful for identifying driving behavior patterns from the standardized data, wherein the features comprise the head position, the sight line direction and the change trend of the body posture of the driver;
S7.4.3, utilizing a machine learning algorithm or a rule engine to train a model according to the extracted characteristics, and identifying the driving behavior mode and intention of the driver;
S7.4.4 training and verification of the machine learning model may be performed by cross-validation or confusion matrix methods;
S7.4.5 analyzing the identification result, matching the driving intention and the behavior mode of the driver with the driving state of the vehicle, providing a basis for adjusting the rearview mirror, and adjusting the position of the rearview mirror according to the analysis result so as to provide the optimal driving visual field.
The application further provides a technical scheme that the step S7.6 also comprises the following steps:
S7.6.1, comprehensively analyzing by combining the driving intention of a driver, the running state of the vehicle and the real-time road and traffic conditions;
S7.6.2 calculating the optimal view angle and position of the rearview mirror by using the comprehensive analysis result and through geometrical optical calculation and a machine learning model;
S7.6.3, adjusting the rearview mirror according to the calculation result, and performing visual field optimization through driver feedback to ensure that the visual field setting meets the actual driving requirement and is continuously improved.
Compared with the prior art, the technical scheme provided by the invention has the following beneficial effects:
The control system for adaptively adjusting the position of the external rearview mirror based on the DMS provides a real-time adjusting function in the dynamic moving process of the vehicle, so that the driving safety and the comfort are remarkably improved, the system intelligently identifies whether a driver drives for the first time or whether the vehicle is in a driving state or not through the static and dynamic judging modules, so that a corresponding adjusting process is automatically started, and the static acquisition and dynamic acquisition module of the DMS main module can accurately capture physiological information of the driver, including the height, the sitting posture, the sight direction and the change trend of the head position and the body posture, and the information is used for the seat adjusting module and the rearview mirror adjusting module to realize personalized adjustment;
The control method provided by the invention ensures the accuracy and real-time performance of rearview mirror adjustment through a series of fine steps, firstly, the static judgment module and the dynamic judgment module are started to provide initial adjustment basis for the system, then, the DMS main module automatically adjusts the seat and the rearview mirror according to the static and dynamic physiological information of the driver so as to adapt to the personal requirements of the driver, the information acquisition module and the data analysis module work cooperatively, so that the system can calculate the optimal view angle and position according to real-time road and vehicle driving information, and finally, the feedback optimization module continuously optimizes the system performance through collecting adjustment effect and driver satisfaction, thereby forming a closed-loop continuous improvement process.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art without making any inventive effort, based on the embodiments of the present invention are within the scope of the present invention, and the present invention is further described below with reference to the embodiments.
Referring to fig. 1 and 2, in an embodiment of the present application, a control system for adaptively adjusting a position of an exterior rear view mirror based on a DMS includes a static determination module, a dynamic determination module, a DMS main module, a seat adjustment module, a memory module, an information acquisition module, a data analysis module, a rear view mirror adjustment module, and a feedback optimization module;
The dynamic judging module is used for judging whether the vehicle with the control system is in dynamic running of the vehicle or not in running of the vehicle;
The DMS main module is used for capturing physiological information of the driver and transmitting the physiological information of the driver to the seat adjusting module or the information acquisition module;
The seat adjusting module is used for receiving the physiological information of the driver of the DMS module, carrying out adaptive adjustment on the main driving seat of the cockpit according to the physiological information of the driver, and feeding back to the memory module after the adjustment is finished;
The memory module is used for recording current seat information for the subsequent driver to select;
The information acquisition module is used for acquiring road information and vehicle running information and feeding the road information and the vehicle running information back to the data analysis module;
The data analysis module is used for analyzing and calculating the current dynamic physiological information, road information and vehicle running information of the driver, judging the current driving intention of the driver, calculating the optimal visual field and feeding back to the rearview mirror adjustment module;
The rearview mirror adjusting module is used for receiving the data of the memory module and the data analysis module and adjusting the rearview mirror;
The feedback optimization module collects effect feedback after adjustment execution, analyzes the adjustment effect and the satisfaction of a driver, identifies potential problems and improvement space, and continuously optimizes the system.
Specifically, when the driver enters the vehicle and starts the engine, the static determination module of the system activates. The module judges whether a driver drives the vehicle for the first time through a vehicle identification system (such as a key card or a biological identification system), if the driver drives the vehicle for the first time, the static judgment module triggers the static acquisition module of the DMS main module to acquire static physiological information such as height, sitting posture and sight direction of the driver, and the seat adjustment module automatically adjusts the seat according to the information so as to ensure comfort and optimal visual field of the driver. After the adjustment is completed, the position information of the seat is recorded in the memory module.
Once the vehicle starts to run, the dynamic judging module confirms that the vehicle is in a dynamic running state and activates the dynamic collecting module of the DMS main module, the dynamic collecting module monitors the head position, the sight line direction and the body posture change of the driver in real time, the information is transmitted to the data analyzing module, the information collecting module collects road information (such as road line shape, gradient, width and the like) and vehicle running information (such as speed, position, steering angle and the like) at the same time, and the data analyzing module synthesizes the information, analyzes the driving intention of the driver and calculates the optimal visual field setting. For example, if the system detects that the driver frequently looks at the side, the rearview mirror may be automatically adjusted to reduce the blind area, and the rearview mirror adjustment module automatically adjusts the angle and position of the exterior rearview mirror to provide the best view based on the calculation result of the data analysis module.
The adjusted vision setting is fed back to the memory module for rapid adjustment in future driving sessions according to the preferences of the driver, the feedback optimization module collects the feedback of the driver after adjustment, satisfaction can be assessed by simple investigation of the vehicle interface or by monitoring the physiological response of the driver (such as heart rate, galvanic skin response, etc.), and the system learns itself according to the collected data and feedback, constantly optimizing the adjustment algorithm to improve future adjustment effect and driver satisfaction.
Further, the DMS main module comprises a static acquisition module and a dynamic acquisition module;
The static acquisition module is used for acquiring static physiological information of a driver when the vehicle stops running;
the dynamic acquisition module is used for acquiring dynamic physiological information of a driver when the vehicle is in dynamic running.
Further, the static physiological information includes the height, sitting posture and sight direction of the driver, and the dynamic physiological information includes the recognition of the change trend of the head position, sight direction and body posture of the driver.
Further, the road information comprises road line shape, road gradient, road width, number of lanes, intersection type, number of main road lanes at the intersection, number of vehicles at the intersected road, intersection traffic volume and road surface condition, and the vehicle running information comprises current speed, average speed, highest speed, current position of the vehicle, braking distance, braking time, steering angle and current lamplight information of the vehicle.
Furthermore, the control system also comprises a safety monitoring and early warning module which is used for monitoring the sight line direction and the concentration degree of the driver in real time in the adjusting process, and sending an early warning signal if the sight line deviation or the concentration lack of the driver is detected.
Specifically, in the present embodiment, real-time adjustment of the rearview mirror during dynamic driving of the vehicle is achieved through a series of highly integrated modules. The core of the system is its static and dynamic acquisition modules, which acquire physiological information of the driver in the stopped and driving states of the vehicle, respectively. The static acquisition module acquires the information such as the height, sitting posture and sight direction of the driver when the vehicle is not running, and the dynamic acquisition module captures the variation trend of the head position, the sight direction and the body posture of the driver when the vehicle is running.
In addition, the system also comprises a safety monitoring and early warning module which monitors the sight direction and the concentration degree of the driver in real time in the adjusting process. Once the driver is found to be out of sight or out of concentration, the system can immediately send out an early warning signal to prevent potential traffic accidents. The real-time monitoring and early warning function is combined with the dynamic adjustment of the position of the outer rearview mirror, so that the driving safety is remarkably improved.
The system also collects road information and vehicle travel information, such as road line shape, speed, and position, through an information collection module, which is used by a data analysis module to calculate an optimal field of view. The rearview mirror adjustment module automatically adjusts the position of the rearview mirror according to the data and the physiological information of the driver so as to provide the optimal visual field range. The whole adjusting process is dynamically carried out in the running process of the vehicle, so that the driver is ensured to always have the best rear view, and the driving safety and comfort are improved.
And finally, the feedback optimization module collects effect feedback after adjustment execution, analyzes the adjustment effect and the satisfaction of a driver, identifies potential problems and improvement space, and continuously optimizes the system. This closed loop feedback mechanism ensures that the system is continually learning and adapting to provide more personalized and accurate services. In this way, the system not only improves the efficiency and accuracy of adjustment, but also ensures that the system can continuously adapt to user demands and technical progress over time, thereby achieving long-term performance improvement.
The application provides a control method for adaptively adjusting the position of an external rearview mirror based on a DMS, which comprises the following steps:
s1, starting a static judging module to determine whether a driver drives the vehicle for the first time;
s2, if the driver drives for the first time, starting a static acquisition module of the DMS main module to acquire static physiological information of the driver;
s3, automatically adjusting the driver seat through the seat adjusting module by utilizing the static physiological information, and confirming an adjusting result by the driver;
S4, starting a dynamic judging module to monitor whether the vehicle is in a running state or not;
S5, starting a dynamic acquisition module of the DMS main module to acquire dynamic physiological information of a driver during running of the vehicle;
s6, collecting road and vehicle running information through an information acquisition module;
S7, the data analysis module processes the dynamic physiological information, the road information and the vehicle running information to judge the driving intention of the driver and calculate the optimal visual field;
s8, automatically adjusting the position of the rearview mirror by the rearview mirror adjusting module according to the calculation result of the data analyzing module;
And S9, the feedback optimization module collects and analyzes the adjustment effect, interacts with a driver to evaluate the satisfaction degree, and continuously optimizes the system.
Specifically, when a driver enters the vehicle and starts the engine, the system first determines, via the static determination module, whether the driver is driving the vehicle for the first time. This is accomplished by a vehicle identification system (e.g., key card, fingerprint or facial recognition) and if the system determines that the driver is driving for the first time, the static acquisition module of the DMS module is activated and begins to acquire the driver's static physiological information, including height, sitting position and gaze direction. This information is collected by sensors and cameras mounted in the cockpit;
Based on the collected static physiological information, the seat adjustment module automatically adjusts the driver's seat to ensure an optimal driving position and view. The driver can confirm the adjustment results to ensure that comfort and personalization requirements are met.
Once the vehicle starts to run, the dynamic judging module is activated and used for monitoring the running state of the vehicle, so that the system can respond to the change of the driving condition in time, and the dynamic physiological information of the driver, including the head position, the sight line direction and the change trend of the body posture, is acquired in real time by the dynamic acquisition module of the DMS main module in the running process of the vehicle. Such information is critical to understanding the immediate needs and intent of the driver, and the system collects road and vehicle travel information, such as road alignment, speed, location, etc., through the information acquisition module. These data provide an important basis for subsequent data analysis and rearview mirror adjustment.
The data analysis module processes the collected dynamic physiological information, road information and vehicle running information, judges the driving intention of the driver, and calculates the optimal view setting. The step ensures the accuracy and the real-time performance of the calculation result through an algorithm and a machine learning technology, and the rearview mirror adjusting module automatically adjusts the position of the outer rearview mirror according to the calculation result of the data analysis module so as to provide the optimal visual field range. This process is done automatically, without driver intervention.
The feedback optimization module collects feedback of a driver after adjustment and evaluates the adjustment effect and satisfaction. The system learns and optimizes itself based on these feedback to continuously increase the accuracy and individualization level of the adjustment.
Through the series of steps, the embodiment provides a high-efficiency and intelligent rearview mirror adjusting method, and the rearview mirror can be adjusted in real time in the dynamic running process of the vehicle so as to adapt to the physiological characteristics and driving environment of a driver, thereby obviously improving the driving safety and comfort.
Further, the step S7 further includes the following steps:
S7.1, receiving dynamic physiological information of a driver from a dynamic acquisition module of the DMS main module, wherein the dynamic physiological information comprises the change trend of the head position, the sight direction and the body posture;
s7.2, receiving road information from an information acquisition module, wherein the road information comprises road line shape, road gradient, road width, number of lanes, intersection type, number of main road lanes of an intersection, number of vehicles of the intersected road, traffic volume of the intersection and road surface condition;
s7.3, receiving vehicle running information from an information acquisition module, wherein the vehicle running information comprises current speed, average speed, highest speed, current position of the vehicle, braking distance, braking time, steering angle and current lamplight information of the vehicle;
S7.4, formatting and standardizing the collected data, analyzing the dynamic physiological information of the driver by using a machine learning algorithm or a rule engine, and identifying the driving behavior mode and intention of the driver;
s7.5, combining the road information and the vehicle running information to further verify and refine the driving intention of the driver;
S7.6, calculating the optimal view angle and position of the rearview mirror according to the driving intention of a driver and the running state of the vehicle, and adjusting the view calculation result in consideration of road conditions and traffic conditions so as to ensure that the optimal view can be provided under various conditions;
s7.7, comparing the calculated view angle and position with the current rearview mirror setting to determine whether adjustment is needed;
s7.8, if adjustment is needed, generating an adjustment instruction, and executing the adjustment instruction through a rearview mirror adjustment module;
And S7.9, feeding back the results of the view calculation and adjustment to a feedback optimization module for subsequent system optimization and performance evaluation.
Specifically, in this embodiment, the following is a specific implementation manner:
The method comprises the steps of capturing the head and body actions of a driver by using cameras and sensors installed in a cockpit, such as infrared cameras and motion sensors, acquiring road information by using a GPS system and a map database of a vehicle and sensors installed around the vehicle, such as radar and lidar, collecting vehicle driving data by using an on-board diagnostic system (OBD) of the vehicle and sensors, such as a speed sensor and a gyroscope, processing the data by using preset data cleaning rules and standardized flows, such as removing abnormal values and converting data formats, applying a machine learning algorithm, such as a decision tree or a neural network, training and identifying the behavior mode of the driver, comprehensively evaluating the driving intention by using a fuzzy logic or a Bayesian network and the like, calculating the optimal angle and position of the rearview mirror by using a geometrical optical principle and a machine learning model, and sending an adjustment command to a rearview mirror adjusting motor by using an Electronic Control Unit (ECU). Satisfaction score and physiological response data, such as heart rate and galvanic skin response, of the driver are collected by an on-board feedback system, and adjusted vision data are collected by sensors of the vehicle.
By monitoring the driver's dynamic physiological information in real time, the system is facilitated to understand the driver's immediate needs and intent, thereby providing more accurate rearview mirror adjustment, while collecting road information and vehicle travel information, enabling the system to adjust the rearview mirrors to provide an optimal view, particularly in complex road environments, based on road conditions and vehicle conditions.
The system can be used for accurately confirming the intention of the driver, reducing misjudgment, improving the accuracy of adjustment, calculating the optimal view according to the intention of the driver and the actual driving condition, ensuring the driver to obtain the optimal view under various conditions, reducing dead zones, automatically comparing the calculated view with the current setting, generating an adjustment instruction when necessary, realizing the automatic adjustment of the rearview mirror, improving driving safety, and adjusting feedback information for performance evaluation and continuous optimization of the system, so that the system can continuously adapt to new driving conditions and driver requirements.
Further, the step S7.4 further includes the following steps:
s7.4.1 cleaning the collected dynamic physiological information, road information and vehicle running information, removing noise and abnormal values, ensuring data quality, converting the cleaned data into a uniform format so as to carry out subsequent analysis processing, and carrying out standardized processing on the data, so that the data with different sources and different dimensions have comparability, and the analysis accuracy is improved;
S7.4.2 extracting features which are helpful for identifying driving behavior patterns from the standardized data, wherein the features comprise the head position, the sight line direction and the change trend of the body posture of the driver;
S7.4.3, utilizing a machine learning algorithm or a rule engine to train a model according to the extracted characteristics, and identifying the driving behavior mode and intention of the driver;
S7.4.4 training and verification of the machine learning model may be performed by cross-validation or confusion matrix methods;
S7.4.5 analyzing the identification result, matching the driving intention and the behavior mode of the driver with the driving state of the vehicle, providing a basis for adjusting the rearview mirror, and adjusting the position of the rearview mirror according to the analysis result so as to provide the optimal driving visual field.
Specifically, noise and outliers in the dynamic physiological information, the road information and the vehicle running information are removed by using a data cleaning technology such as filtering and clustering algorithms. The cleaned data is then converted to a unified format and normalized by a normalization process, such as Z-score normalization, to ensure that the data is comparable, and feature engineering methods, such as Principal Component Analysis (PCA) or automatic encoders, are applied to extract key features from the normalized data that can represent the driver's head position, gaze direction and body posture trend. A machine learning algorithm, such as a Support Vector Machine (SVM) or random forest, is used to train the model based on the extracted features to identify the driving behavior pattern and intent of the driver. And training and verifying the machine learning model through cross verification, such as k-fold cross verification, so as to evaluate the generalization capability of the model. And analyzing the recognition result of the model, matching the driving intention and the behavior mode of the driver with the driving state of the vehicle, and providing basis for rearview mirror adjustment. Based on the analysis, the system automatically adjusts the mirror position to provide an optimal driving field of view. In the adjusting process, the system can monitor the adjusting effect in real time and conduct fine adjustment according to the requirement.
The method has the advantages that through data cleaning and standardization processing, data quality is improved, analysis accuracy and model training effectiveness are ensured, feature extraction is helpful for identifying factors most influencing driving behavior identification from a large amount of data, model efficiency and accuracy are improved, a complex driving behavior mode can be automatically identified by training the model through a machine learning algorithm, dependence on manual rules is reduced, system adaptability and accuracy are improved, robustness and reliability of the model are ensured through cross verification and confusion matrix use, model prediction capability on unknown data is improved, and through matching driving intention with vehicle state, the system can intelligently adjust rearview mirrors to provide an optimal view, so that driving safety and comfort are improved. In addition, the real-time monitoring and fine tuning capabilities of the system ensure that the adjustment effect can meet the actual needs of the driver.
Further, the step S7.6 further includes the following steps:
S7.6.1, comprehensively analyzing by combining the driving intention of a driver, the running state of the vehicle and the real-time road and traffic conditions;
S7.6.2 calculating the optimal view angle and position of the rearview mirror by using the comprehensive analysis result and through geometrical optical calculation and a machine learning model;
S7.6.3, adjusting the rearview mirror according to the calculation result, and performing visual field optimization through driver feedback to ensure that the visual field setting meets the actual driving requirement and is continuously improved.
Specifically, during the running process of the system, the driving intention of the driver, the real-time running state data of the vehicle and the current road and traffic condition information are integrated first. This step involves fusing the data collected from the DMS module, information acquisition module and dynamic determination module for comprehensive analysis, and using the fused data, the system determines the ideal position of the mirror by geometric optical calculations to eliminate dead zones and provide an optimal view. Meanwhile, the machine learning model predicts the optimal view angle according to the historical data and the current situation, the models can learn the optimal view setting under different driving conditions, and the system automatically adjusts the rearview mirror to the optimal position according to the calculation result. After adjustment, the system collects feedback information by either directly querying the driver or by monitoring the driver's physiological response (e.g., eye movements, head posture, etc.). This feedback information is used to further optimize the field of view setting, ensure that it meets the actual driving needs, and enable the system to learn and improve continuously over time.
The comprehensive analysis provides comprehensive understanding of the intention of the driver and the current driving environment, so that the system can make more accurate adjustment decisions, the combination of geometric optical calculation and a machine learning model ensures the scientificity and rationality of the position of the rearview mirror, the system can adapt to different driving conditions and driver preferences, the adjustment flexibility and accuracy are improved, and the visual field optimization performed by the feedback of the driver ensures that the system can be continuously improved so as to adapt to the continuously-changed driving environment and meet the personalized requirements of the driver. This feedback mechanism enables the system to achieve closed loop control, continuously improving driving safety and comfort.
The control system for adaptively adjusting the position of the external rearview mirror based on the DMS provides a real-time adjusting function in the dynamic moving process of the vehicle, so that the driving safety and the comfort are remarkably improved, the system intelligently identifies whether a driver drives for the first time or whether the vehicle is in a driving state or not through the static and dynamic judging modules, so that a corresponding adjusting process is automatically started, and the static acquisition and dynamic acquisition module of the DMS main module can accurately capture physiological information of the driver, including the height, the sitting posture, the sight direction and the change trend of the head position and the body posture, and the information is used for the seat adjusting module and the rearview mirror adjusting module to realize personalized adjustment;
The control method provided by the invention ensures the accuracy and real-time performance of rearview mirror adjustment through a series of fine steps, firstly, the static judgment module and the dynamic judgment module are started to provide initial adjustment basis for the system, then, the DMS main module automatically adjusts the seat and the rearview mirror according to the static and dynamic physiological information of the driver so as to adapt to the personal requirements of the driver, the information acquisition module and the data analysis module work cooperatively, so that the system can calculate the optimal view angle and position according to real-time road and vehicle driving information, and finally, the feedback optimization module continuously optimizes the system performance through collecting adjustment effect and driver satisfaction, thereby forming a closed-loop continuous improvement process.
The invention and its embodiments have been described above by way of illustration and not limitation, and the invention is illustrated in the accompanying drawings and described in the drawings in which the actual structure is not limited thereto. Therefore, if one of ordinary skill in the art is informed by this disclosure, a structural manner and an embodiment similar to the technical scheme are not creatively devised without departing from the gist of the present invention, and all the structural manners and the embodiments belong to the protection scope of the present invention.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate technical solution, and this description is provided for clarity only, and those skilled in the art should consider the disclosure as a whole, and the technical solutions in the embodiments may be combined appropriately to form other embodiments that can be understood by those skilled in the art.