CN117991750B - Vehicle-mounted network bus information transmission vehicle management system and method based on data acquisition and analysis - Google Patents
Vehicle-mounted network bus information transmission vehicle management system and method based on data acquisition and analysis Download PDFInfo
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Abstract
The invention discloses a vehicle-mounted network bus information transmission vehicle management system and method based on data acquisition and analysis, and belongs to the technical field of vehicle data acquisition. In order to solve the problems that the running state of the vehicle is difficult to accurately monitor and the detection of abnormal events and potential problems generally depends on manual work, the system can realize the real-time monitoring of the running state of the vehicle and the behavior of the driver by collecting the running state data and the behavior data of the driver in real time, discover the abnormal events and the potential problems in time, improve the accuracy and timeliness of the abnormal detection based on the abnormal detection of data collection and analysis, reduce the requirement of manual intervention, help to reduce the possibility of occurrence of faults of the vehicle, improve the reliability and the running efficiency of the vehicle, improve the efficiency of processing the abnormal events, and provide more accurate decision support for owners or administrators and optimize resource allocation and maintenance plans through data mining and analysis.
Description
Technical Field
The invention relates to the technical field of vehicle data acquisition, in particular to a vehicle network bus information transmission vehicle management system and method based on data acquisition and analysis.
Background
Along with the popularization of automobiles, more and more vehicles are on the road, the development of science and technology and the improvement of intelligent level are achieved, and meanwhile, the application of automobile management systems in the field of automobile management is also driven.
In existing car management systems, the application of data acquisition and analysis still has some drawbacks. First, the running state of the vehicle and the driver behavior are difficult to accurately monitor and manage due to the lack of real-time data acquisition and analysis. Second, detection of abnormal events and potential problems typically relies on manual intervention and periodic inspection, which makes the discovery and handling of anomalies somewhat lagging. In addition, the prior art has limited processing and mining capabilities for data, and potential value of the data cannot be fully mined, so that accuracy and efficiency of vehicle management decisions are affected.
Disclosure of Invention
The invention aims to provide a vehicle-mounted network bus information transmission vehicle management system and method based on data acquisition and analysis, so as to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: the vehicle-mounted network bus information transmission vehicle management system based on data acquisition and analysis comprises:
The data acquisition module is used for:
Acquiring vehicle state data, driver behavior data and environment data, wherein the vehicle state data comprises engine rotating speed, vehicle speed, oil quantity and water temperature, the driver behavior data comprises operation habits of braking, accelerator and steering, and the environment data comprises GPS position, external temperature and humidity;
a data processing module for:
Acquiring vehicle state data, driver behavior data and environment data acquired by a data acquisition module through a CAN bus, analyzing the vehicle running state and driving behavior, detecting abnormality, predicting possible faults based on vehicle history data, and reminding to maintain in advance;
the data transmission module is used for:
the data transmission between vehicles and between the vehicles and the cloud platform is realized, the data transmission module can receive data from other vehicles or the cloud platform and can send the data to other vehicles or the cloud platform, and the data transmission module supports various communication protocols including Wi-F i, bluetooth and LTE-V2X and selects a communication mode according to actual conditions;
the remote monitoring module is used for:
The car owner or company can check the state of the car and control the car remotely through a mobile phone or a computer;
a user interaction module for:
Providing a user interface, wherein a user views vehicle information and sets control parameters through the user interface;
a security privacy module for:
the security of data transmission and storage is ensured through encryption technology;
the statistics report module is used for:
And generating a statistical report and a data analysis report according to the needs of the user.
Further, the data acquisition module includes:
A sensor unit for:
Acquiring various state data from a vehicle, acquiring corresponding engine rotation speed, vehicle speed, oil quantity and water temperature through a rotation speed sensor, a vehicle speed sensor, an oil quantity sensor and a water temperature sensor, acquiring data by the sensors, and transmitting the data to a data processing module through a CAN bus;
the behavior data acquisition unit is used for:
recording the operation habit of a driver, and acquiring corresponding operation data of brake, accelerator and steering through installing a pedal sensor and a steering wheel torque sensor;
a GPS environment sensor unit for:
the method comprises the steps of acquiring environmental data such as GPS position, external temperature and humidity of a vehicle, acquiring position information of the vehicle through a GPS receiver, acquiring real-time environmental data through a temperature and humidity sensor, acquiring the data, and transmitting the data to a data processing module through a CAN bus.
Further, the data processing module includes:
a data preprocessing unit for:
data sent by a data acquisition module is received from a CAN bus, and the data is cleaned and preprocessed, wherein the preprocessing comprises data filtering, abnormal value detection and repair and data standardization;
A vehicle running state analysis unit configured to:
Analyzing the running state of the vehicle by processing the vehicle state data, and detecting the running mode and performance of the vehicle;
A driving behavior analysis unit for:
Processing and analyzing the behavior data of the driver, and evaluating the driving style and behavior mode of the driver and whether bad driving habit exists or not by analyzing the operation habits of brake, accelerator and steering;
an abnormality detection unit configured to:
abnormality detection is carried out on the running state and the driving behavior of the vehicle, and abnormal events or potential problems, such as overheating of an engine, abnormal oil consumption and the like, are detected by comparing current data with historical data and a preset normal range;
a failure prediction unit for:
based on the vehicle history data and the machine learning algorithm, possible faults are predicted, and by analyzing fault modes and trends in the history data, possible problems in the future can be predicted, and maintenance reminding can be sent out in advance.
Further, the abnormality detection unit compares the current data with the history data, and sets a normal range of the data based on a large amount of data and experience;
and detecting an abnormal event or a potential problem according to the set normal range and a comparison result with the historical data.
Based on the nature and severity of the anomaly, a determination is made as to what abnormal event or potential problem is.
Further, the fault prediction unit selects a feature related to the fault based on the processed data;
training a machine learning model using the selected features and the historical data;
Evaluating the model by using an independent verification data set, checking the prediction accuracy and performance of the model, and adjusting and optimizing the model according to the evaluation result;
and predicting future faults by using a trained model, and deducing the possible fault types and time according to the input characteristic data by the model.
Further, the remote monitoring module includes:
A data display unit for:
Checking various state data of the vehicle in real time through a mobile phone or a computer, wherein the state data comprise vehicle speed, mileage, oil quantity and engine state, and displaying the data in a digital display, chart or instrument panel mode;
a remote control unit for:
The vehicle is remotely controlled through a mobile phone or a computer, wherein the remote control comprises remote starting, closing an engine, locking or unlocking a vehicle door, and safety verification is required before a remote control unit is started, so that remote operation is ensured for authorized personnel;
a positioning tracking unit for:
The vehicle position and track are tracked in real time through GPS, and the vehicle owner or company can remotely check the real-time position, the historical track and the running speed information of the vehicle through the positioning tracking unit.
Further, the positioning and tracking unit includes:
the data transmission time information acquisition module is used for extracting each position data transmission time of the current vehicle;
the data receiving time information acquisition module is used for calling each position data receiving time of the current vehicle;
the transmission time length information acquisition module is used for acquiring the transmission time length of the position data of the current vehicle by utilizing the transmission time of each position data of the current vehicle and the receiving time of each position data of the current vehicle;
The data transmission quality parameter acquisition module is used for setting the data transmission quality parameter of the bit data of the current vehicle by utilizing the position data transmission time length of the current vehicle; the data transmission quality parameters of the position data are obtained through the following formula:
Wherein Q t represents a data transmission quality parameter; n represents the number of transmission times of the position data; t i denotes a time difference between a position data transmission time and a position data reception time when the position data transmission is performed the ith time; l represents the minimum distance (namely, the unit distance corresponding to the positioning precision) which can be identified by the current positioning change; v represents the average speed of the current vehicle;
the speed information acquisition module is used for acquiring the running speed information of the current vehicle in real time;
The vehicle running parameter acquisition module is used for acquiring the running parameters of the vehicle by using the running speed information of the current vehicle; wherein, the vehicle operation parameters are obtained by the following formula:
Wherein Q v represents a vehicle operating parameter; m represents the number of unit time which is experienced during the running of the current vehicle, and the unit time is 1s; v i denotes the speed of the current vehicle corresponding to the i-th unit time;
the compensation distance prediction module is used for predicting the compensation running distance of the current vehicle by utilizing the data transmission quality parameter and the vehicle running parameter, and performing forward compensation on the current vehicle position by utilizing the compensation running distance to obtain a prediction distance;
And the prediction information sending module is used for sending the position data corresponding to the prediction distance to the vehicle tracking platform as the position data of the current vehicle positioning.
Further, the compensation distance prediction module includes:
the first parameter extraction module is used for extracting the data transmission quality parameters;
The second parameter extraction module is used for extracting the vehicle operation parameters;
The compensation distance acquisition module is used for acquiring the compensation distance by utilizing the data transmission quality parameter and the vehicle operation parameter; the compensation distance is obtained through the following formula:
Wherein L c represents the compensation distance; v max represents the maximum travel speed of the current vehicle in the last 10 units of time of history; t x denotes a reference time; t represents the data transmission time corresponding to the position data of the current vehicle;
and the predicted distance acquisition module is used for taking the position of the current vehicle as a starting point, and migrating the position of the vehicle according to the compensation distance to obtain the predicted distance.
Further, the security privacy module includes:
A data encryption unit configured to:
encrypting all transmitted and stored data;
an identity verification unit for:
Providing an identity verification mechanism, wherein a user can access the data which the user is authorized to access by providing a correct user name and password;
a data desensitization unit for:
and (3) desensitizing the sensitive data, and covering or replacing sensitive fields, wherein the sensitive fields comprise personal information and bank card number information.
The invention provides a realization method of a vehicle-mounted network bus information transmission vehicle management system based on data acquisition and analysis, which comprises the following steps:
Step one: the system acquires vehicle state data, driver behavior data and environment data through a data acquisition module, wherein the data comprise engine rotating speed, vehicle speed, oil quantity and water temperature, operation habits of braking, accelerator and steering, GPS position, external temperature and humidity and the like;
step two: the data processing module is used for preprocessing and analyzing the acquired data, detecting the running state and performance of the vehicle, evaluating the driving style and behavior mode of the driver, and carrying out anomaly detection and fault prediction;
step three: comparing the current data with the historical data, and once an abnormal event or potential problem is detected, giving an alarm and reminding a user by the system, and simultaneously predicting future faults and giving a maintenance reminding in advance based on the historical data;
step four: the vehicle performs data interaction with other vehicles or cloud platforms, receives or transmits data, and a user remotely checks the state of the vehicle and controls the vehicle through a mobile phone or a computer;
step five: all the transmitted data are encrypted by the security privacy module, and security verification is carried out before the remote control unit carries out remote operation, so that the identity of authorized personnel is determined.
Compared with the prior art, the invention has the beneficial effects that:
1. The data acquisition module can acquire various state data of the vehicle in real time and send the data to the data processing module through the bus, a vehicle owner or an administrator can know the running state and the position of the vehicle in real time, when abnormal conditions occur, the system can give out early warning timely, the vehicle owner or the administrator can know the actual conditions of the vehicle more accurately, so that resource configuration is carried out better, the data acquisition module can record the operation habit of the driver and the information of the position, the environment data and the like of the vehicle, and decision support is provided for the vehicle owner or the administrator.
2. The abnormality detection unit can timely discover potential safety risks and problems by monitoring the abnormal conditions of the running state and the driving behavior of the vehicle in real time, and can take corresponding measures to carry out preventive maintenance by timely discovering abnormal events or potential problems, thereby being beneficial to reducing the possibility of occurrence of faults of the vehicle, improving the reliability and the running efficiency of the vehicle, improving the monitoring and management capability of a vehicle owner or an administrator on the vehicle, providing detailed abnormal event report and problem diagnosis by the system, and helping the vehicle owner or the administrator to solve the abnormal problems and the potential faults more quickly.
3. The fault prediction unit of the invention predicts possible faults, the system can carry out preventive maintenance before the faults occur, thereby avoiding potential vehicle faults and downtime, the preventive maintenance can reduce maintenance cost and downtime, improve reliability and operation efficiency of the vehicle, predict faults in advance and help a vehicle owner or manager to take measures in time, avoid potential safety risks, and the system can provide more accurate maintenance plan for the vehicle owner or manager through analysis of vehicle historical data and fault prediction, and is beneficial to reasonably arranging maintenance resources and time, improving maintenance efficiency and reducing maintenance cost.
Drawings
FIG. 1 is a schematic diagram of a system module according to the present invention.
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 based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the technical problems that the running state and the driver behavior of a vehicle are difficult to be accurately monitored and managed due to lack of real-time data acquisition and analysis, detection of abnormal events and potential problems is generally dependent on manual intervention and periodic inspection, so that abnormal discovery and processing have certain hysteresis, and the potential value of the data cannot be fully mined due to limited processing and mining capability of the data in the prior art, thereby affecting the accuracy and efficiency of vehicle management decision, referring to fig. 1, the invention provides the following technical scheme:
the vehicle-mounted network bus information transmission vehicle management system based on data acquisition and analysis comprises:
The data acquisition module is used for:
acquiring vehicle state data, driver behavior data and environment data, wherein the vehicle state data comprises engine speed, vehicle speed, oil quantity and water temperature, the driver behavior data comprises operation habits of braking, accelerator and steering, and the environment data comprises GPS (global positioning system) position, external temperature and humidity;
a data processing module for:
Acquiring vehicle state data, driver behavior data and environment data acquired by a data acquisition module through a CAN bus, analyzing the vehicle running state and driving behavior, detecting abnormality, predicting possible faults based on vehicle history data, and reminding to maintain in advance;
the data transmission module is used for:
The data transmission between vehicles and between the vehicles and the cloud platform is realized, the data transmission module can receive data from other vehicles or the cloud platform and can send the data to other vehicles or the cloud platform, the data transmission module supports various communication protocols including Wi-Fi, bluetooth and LTE-V2X, and a communication mode is selected according to actual conditions;
the remote monitoring module is used for:
The car owner or company can check the state of the car and control the car remotely through a mobile phone or a computer;
a user interaction module for:
Providing a user interface, wherein a user views vehicle information and sets control parameters through the user interface;
a security privacy module for:
the security of data transmission and storage is ensured through encryption technology;
the statistics report module is used for:
And generating a statistical report and a data analysis report according to the needs of the user.
Specifically, the system can integrate various types of data, including vehicle states, driver behaviors and environment information, and perform unified processing. This enables a comprehensive analysis of the vehicle conditions and driving behaviour. Through machine learning and data analysis, the system is able to predict potential vehicle faults. Such predictive functionality may alert drivers in advance to allow them time to take necessary maintenance measures to avoid potential vehicle failure and unexpected stops.
The data acquisition module comprises:
A sensor unit for:
Acquiring various state data from a vehicle, acquiring corresponding engine rotation speed, vehicle speed, oil quantity and water temperature through a rotation speed sensor, a vehicle speed sensor, an oil quantity sensor and a water temperature sensor, acquiring data by the sensors, and transmitting the data to a data processing module through a CAN bus;
the behavior data acquisition unit is used for:
recording the operation habit of a driver, and acquiring corresponding operation data of brake, accelerator and steering through installing a pedal sensor and a steering wheel torque sensor;
a GPS environment sensor unit for:
the method comprises the steps of acquiring environmental data such as GPS position, external temperature and humidity of a vehicle, acquiring position information of the vehicle through a GPS receiver, acquiring real-time environmental data through a temperature and humidity sensor, acquiring the data, and transmitting the data to a data processing module through a CAN bus.
Specifically, the data acquisition module can acquire various state data of the vehicle in real time, and send the data to the data processing module through the bus. The car owner or the administrator can know the running state and the position of the car in real time, and when abnormal conditions occur, the system can send out early warning timely. The vehicle owner or the administrator can know the actual condition of the vehicle more accurately, so that the resource allocation is better carried out. For example, the maintenance plan is arranged according to the actual running condition of the vehicle, so that the service life and the reliability of the vehicle are improved. The data acquisition module can record the operation habit of a driver, the position of a vehicle, environmental data and other information, and provides decision support for a vehicle owner or an administrator.
The data processing module comprises:
a data preprocessing unit for:
data sent by a data acquisition module is received from a CAN bus, and the data is cleaned and preprocessed, wherein the preprocessing comprises data filtering, abnormal value detection and repair and data standardization;
A vehicle running state analysis unit configured to:
Analyzing the running state of the vehicle by processing the vehicle state data, and detecting the running mode and performance of the vehicle;
A driving behavior analysis unit for:
Processing and analyzing the behavior data of the driver, and evaluating the driving style and behavior mode of the driver and whether bad driving habit exists or not by analyzing the operation habits of brake, accelerator and steering;
an abnormality detection unit configured to:
abnormality detection is carried out on the running state and the driving behavior of the vehicle, and abnormal events or potential problems, such as overheating of an engine, abnormal oil consumption and the like, are detected by comparing current data with historical data and a preset normal range;
the abnormality detection unit compares the current data with the history data;
Setting a normal range of data based on a large amount of data and experience;
Detecting an abnormal event or a potential problem according to the set normal range and a comparison result with the historical data; .
Based on the nature and severity of the anomaly, a determination is made as to what abnormal event or potential problem is.
Specifically, through the abnormal condition of real-time supervision vehicle running state and driving action, the latent security risk of discovery and problem in time can be in the unusual detection unit. For example, when overheat or abnormal oil consumption of the engine is detected, the system can immediately give an alarm to remind the vehicle owner or manager to take corresponding measures so as to avoid safety accidents. By finding out abnormal events or potential problems in time, the system can take corresponding measures for preventive maintenance. This helps to reduce the possibility of vehicle failure, improving the reliability and operating efficiency of the vehicle.
The abnormality detection unit can improve the monitoring and management ability of the vehicle owner or manager for the vehicle. The system can provide detailed abnormal event report and problem diagnosis, and help the vehicle owners or administrators to solve abnormal problems and potential faults more quickly. Through real-time monitoring of the running state and driving behavior of the vehicle, the system can analyze the occurrence frequency and trend of abnormal events or potential problems. This helps the vehicle owner or administrator to make a more reasonable maintenance plan, optimizing maintenance resources and costs.
A failure prediction unit for:
based on the vehicle history data and the machine learning algorithm, possible faults are predicted, and by analyzing fault modes and trends in the history data, possible problems in the future can be predicted, and maintenance reminding can be sent out in advance.
The fault prediction unit selects characteristics related to faults based on the processed data;
training a machine learning model using the selected features and the historical data;
Evaluating the model by using an independent verification data set, checking the prediction accuracy and performance of the model, and adjusting and optimizing the model according to the evaluation result;
and predicting future faults by using a trained model, and deducing the possible fault types and time according to the input characteristic data by the model.
In particular, by predicting a likely failure, the system may perform preventative maintenance prior to the occurrence of the failure, thereby avoiding potential vehicle failure and downtime. Such preventative maintenance may reduce maintenance costs and downtime, improving reliability and operating efficiency of the vehicle. Predicting faults in advance can help a vehicle owner or an administrator to take measures in time, and potential safety risks are avoided. For example, when it is predicted that the braking system may fail, maintenance or replacement of the brake pads may be performed in advance, ensuring safe operation of the vehicle.
By analyzing the vehicle history data and predicting faults, the system can provide a more accurate maintenance plan for a vehicle owner or manager. This helps to rationally arrange maintenance resources and time, improve maintenance efficiency, and reduce maintenance costs. And predicting and analyzing the vehicle faults, and providing decision support for vehicle owners or administrators. For example, upon predicting that a component may need replacement or repair, the system may provide relevant advice and solutions to assist the user in making more informed decisions.
The remote monitoring module comprises:
A data display unit for:
Various state data of the vehicle are checked in real time through a mobile phone or a computer, the state data comprise vehicle speed, mileage, oil quantity and engine state, the data are displayed in a digital display, chart or instrument panel mode, the data display unit provides real-time vehicle state data, and a vehicle owner or an administrator can know the running state and the position of the vehicle at any time. When an abnormal situation occurs, the system can send out early warning in time, so that a user is helped to respond quickly and solve the problem;
a remote control unit for:
The vehicle is remotely controlled through the mobile phone or the computer, the remote control comprises remote starting, closing the engine, locking or unlocking the vehicle door, safety verification is required before the remote control unit is started, remote operation is ensured for authorized personnel, and the remote control unit enables a user to remotely operate the vehicle through the mobile phone or the computer, such as starting, closing the engine, locking/unlocking the vehicle door and the like. The convenience is particularly suitable for common situations of forgetting to lock the vehicle, forgetting to close the engine and the like, and better use experience is provided for users;
a positioning tracking unit for:
the vehicle owner or company can remotely check the real-time position, the historical track and the running speed information of the vehicle through the GPS and track the position and track of the vehicle in real time, and the positioning and tracking unit can provide remote vehicle positioning and historical track inquiring functions for a user through the GPS and track the position and track of the vehicle in real time. This helps find application scenarios such as lost vehicles, supervising vehicle travel routes, and scheduling.
In particular, for business or fleet managers, the remote monitoring module can help them manage vehicles more efficiently. Through real-time data display and remote control functions, a manager can know the state of a vehicle in real time and conduct remote scheduling, unnecessary site inspection and labor cost are reduced, and potential safety hazards can be found in time and corresponding measures can be taken through real-time monitoring of the state and the position of the vehicle. Through the remote monitoring module, enterprises or vehicle owners can know the actual condition of the vehicle more accurately, so that resource allocation is performed better. For example, the maintenance plan is arranged according to the actual running condition of the vehicle, so that the service life and the reliability of the vehicle are improved.
Further, the positioning and tracking unit includes:
the data transmission time information acquisition module is used for extracting each position data transmission time of the current vehicle;
the data receiving time information acquisition module is used for calling each position data receiving time of the current vehicle;
the transmission time length information acquisition module is used for acquiring the transmission time length of the position data of the current vehicle by utilizing the transmission time of each position data of the current vehicle and the receiving time of each position data of the current vehicle;
The data transmission quality parameter acquisition module is used for setting the data transmission quality parameter of the bit data of the current vehicle by utilizing the position data transmission time length of the current vehicle; the data transmission quality parameters of the position data are obtained through the following formula:
Wherein Q t represents a data transmission quality parameter; n represents the number of transmission times of the position data; t i denotes a time difference between a position data transmission time and a position data reception time when the position data transmission is performed the ith time; l represents the minimum distance (namely, the unit distance corresponding to the positioning precision) which can be identified by the current positioning change; v represents the average speed of the current vehicle;
the speed information acquisition module is used for acquiring the running speed information of the current vehicle in real time;
The vehicle running parameter acquisition module is used for acquiring the running parameters of the vehicle by using the running speed information of the current vehicle; wherein, the vehicle operation parameters are obtained by the following formula:
Wherein Q v represents a vehicle operating parameter; m represents the number of unit time which is experienced during the running of the current vehicle, and the unit time is 1s; v i denotes the speed of the current vehicle corresponding to the i-th unit time;
the compensation distance prediction module is used for predicting the compensation running distance of the current vehicle by utilizing the data transmission quality parameter and the vehicle running parameter, and performing forward compensation on the current vehicle position by utilizing the compensation running distance to obtain a prediction distance;
And the prediction information sending module is used for sending the position data corresponding to the prediction distance to the vehicle tracking platform as the position data of the current vehicle positioning.
The technical effects of the technical scheme are as follows: the system can accurately extract and record the position data sending and receiving moments of the vehicle through the data sending moment information acquisition module and the data receiving moment information acquisition module. The method ensures the accuracy and real-time performance of the data and provides a basis for subsequent data processing and positioning tracking. The transmission time length information acquisition module can calculate the transmission time length of each position data by utilizing the data sending and receiving time. The method is helpful for knowing the delay and packet loss conditions in the data transmission process, and further improves the accuracy of positioning tracking.
The data transmission quality parameter is related to a plurality of factors such as the transmission times, the transmission time length, the positioning accuracy, the vehicle speed and the like of the position data. By setting the parameter, the system can comprehensively consider the influence of various factors on the data transmission quality, and provide basis for subsequent positioning compensation. The speed information acquisition module monitors the running speed of the vehicle in real time and provides real-time data for acquiring the running parameters of the vehicle. This ensures the real-time and accuracy of the vehicle running parameters, contributing to more accurate prediction of the running track of the vehicle.
Through the vehicle operation parameter acquisition module, the system can calculate the operation parameters of the vehicle according to the acquired speed information. The parameters can reflect the running state and track of the vehicle, and provide important basis for prediction compensation. The compensation distance prediction module predicts the compensation running distance of the current vehicle by using the data transmission quality parameter and the vehicle running parameter. The prediction distance is obtained through forward compensation, so that the accuracy of positioning tracking is improved, and meanwhile, the influence of overlong transmission time of position information on positioning deviation is reduced. The prediction information sending module sends the position data corresponding to the prediction distance to the vehicle tracking platform as the position data of the current vehicle positioning. The vehicle tracking platform can grasp the accurate position of the vehicle in real time, and provides a basis for further dispatching and control.
In summary, the technical scheme realizes accurate positioning and tracking of the vehicle by acquiring and calculating relevant parameters such as the position, the speed, the transmission quality and the like of the vehicle in real time. This helps to improve the efficiency of vehicle scheduling and management, enhancing the capability of handling incidents. Meanwhile, the technical scheme has better flexibility and expandability, and can be customized and optimized according to actual requirements.
Specifically, the compensation distance prediction module includes:
the first parameter extraction module is used for extracting the data transmission quality parameters;
The second parameter extraction module is used for extracting the vehicle operation parameters;
The compensation distance acquisition module is used for acquiring the compensation distance by utilizing the data transmission quality parameter and the vehicle operation parameter; the compensation distance is obtained through the following formula:
Wherein L c represents the compensation distance; v max represents the maximum travel speed of the current vehicle in the last 10 units of time of history; t x denotes a reference time; t represents the data transmission time corresponding to the position data of the current vehicle;
and the predicted distance acquisition module is used for taking the position of the current vehicle as a starting point, and migrating the position of the vehicle according to the compensation distance to obtain the predicted distance.
The technical effects of the technical scheme are as follows: the system extracts data transmission quality parameters from the data by a first parameter extraction module. This parameter reflects the quality condition during data transmission and has important significance for predicting the compensation distance. The second parameter extraction module is responsible for extracting vehicle operation parameters, including dynamic information such as speed, acceleration and the like of the vehicle. These parameters are critical for predicting future travel trajectories and compensation distances of the vehicle.
The compensation distance acquisition module calculates the compensation distance through a specific algorithm or formula by utilizing the data transmission quality parameter and the vehicle operation parameter. This compensation distance takes into account factors such as data transmission delays and vehicle dynamics, and aims to correct errors in positioning data. In calculating the compensation distance, a reference time needs to be set. The selection of the reference time can be determined according to actual requirements, and meanwhile, the influence of external interference on a prediction result can be reduced to the greatest extent by the reference time obtained through the mode.
The predicted distance acquisition module takes the current position of the vehicle as a starting point, and migrates the position of the vehicle according to the compensation distance. Therefore, the predicted distance which is closer to the actual running track can be obtained, and the accuracy of positioning and tracking is improved. And finally, sending the position data corresponding to the predicted distance to a vehicle tracking platform as the positioning information of the current vehicle. The tracking platform can grasp the compensated vehicle position information in real time, and provides more accurate data support for subsequent dispatching and control.
In summary, the compensation distance prediction module of the technical scheme realizes accurate prediction of the compensation running distance of the vehicle by comprehensively considering the data transmission quality and the vehicle running parameters. This helps to improve the accuracy of vehicle location tracking, enhancing the ability to manage and control vehicle location information. Meanwhile, the technical scheme has strong flexibility and expandability, and can be customized and optimized according to actual requirements.
The security privacy module includes:
A data encryption unit configured to:
all the transmitted and stored data are encrypted, and the data encryption unit can encrypt all the transmitted and stored data, so that the safety of the data in the transmission and storage processes is ensured, and the data is prevented from being illegally acquired and tampered;
an identity verification unit for:
The authentication mechanism is provided, the user can access the data which the user is authorized to access by providing the correct user name and password, and the authentication unit provides a multi-level authentication mechanism, so that only the authorized user can access the corresponding data, and unauthorized access and data leakage are prevented;
a data desensitization unit for:
The sensitive data is desensitized, sensitive fields are covered or replaced, the sensitive fields comprise personal information and bank card number information, and the data desensitizing unit is used for desensitizing the sensitive data, so that the risk of sensitive data leakage can be reduced, and the personal privacy and information safety of a user are protected.
Specifically, the overall design and the processing flow of the security privacy module can improve the reliability and the stability of the system, ensure that the system can resist various security threats and attacks, ensure that the system meets the requirements of relevant laws and regulations and industry standards, avoid legal risks caused by non-compliance problems, improve the trust degree of users on the system, enable the users to use the system more confidently, and strengthen the loyalty and satisfaction of the users.
The embodiment now provides a method for realizing a vehicle-mounted network bus information transmission vehicle management system based on data acquisition and analysis, which comprises the following steps:
Step one: the system acquires vehicle state data, driver behavior data and environment data through a data acquisition module, wherein the data comprise engine rotating speed, vehicle speed, oil quantity and water temperature, operation habits of braking, accelerator and steering, GPS position, external temperature and humidity and the like;
step two: the data processing module is used for preprocessing and analyzing the acquired data, detecting the running state and performance of the vehicle, evaluating the driving style and behavior mode of the driver, and carrying out anomaly detection and fault prediction;
step three: comparing the current data with the historical data, and once an abnormal event or potential problem is detected, giving an alarm and reminding a user by the system, and simultaneously predicting future faults and giving a maintenance reminding in advance based on the historical data;
step four: the vehicle performs data interaction with other vehicles or cloud platforms, receives or transmits data, and a user remotely checks the state of the vehicle and controls the vehicle through a mobile phone or a computer;
step five: all the transmitted data are encrypted by the security privacy module, and security verification is carried out before the remote control unit carries out remote operation, so that the identity of authorized personnel is determined.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should be covered by the protection scope of the present invention by making equivalents and modifications to the technical solution and the inventive concept thereof.
Claims (8)
1. The vehicle-mounted network bus information transmission vehicle management system based on data acquisition and analysis is characterized by comprising:
The data acquisition module is used for:
Acquiring vehicle state data, driver behavior data and environment data, wherein the vehicle state data comprises engine rotating speed, vehicle speed, oil quantity and water temperature, the driver behavior data comprises operation habits of braking, accelerator and steering, and the environment data comprises GPS position, external temperature and humidity;
a data processing module for:
Acquiring vehicle state data, driver behavior data and environment data acquired by a data acquisition module through a CAN bus, analyzing the vehicle running state and driving behavior, detecting abnormality, predicting possible faults based on vehicle history data, and reminding to maintain in advance;
the data transmission module is used for:
The data transmission between vehicles and between the vehicles and the cloud platform is realized, the data transmission module can receive data from other vehicles or the cloud platform and can send the data to other vehicles or the cloud platform, the data transmission module supports various communication protocols including Wi-Fi, bluetooth and LTE-V2X, and a communication mode is selected according to actual conditions;
the remote monitoring module is used for:
The car owner or company remotely checks the state of the car and controls the car through a mobile phone or a computer;
a user interaction module for:
Providing a user interface, wherein a user views vehicle information and sets control parameters through the user interface;
a security privacy module for:
the security of data transmission and storage is ensured through encryption technology;
the statistics report module is used for:
Generating a statistical report and a data analysis report according to the needs of the user;
the remote monitoring module comprises:
A data display unit for:
Checking various state data of the vehicle in real time through a mobile phone or a computer, wherein the state data comprise vehicle speed, mileage, oil quantity and engine state, and displaying the data in a digital display, chart or instrument panel mode;
a remote control unit for:
The vehicle is remotely controlled through a mobile phone or a computer, wherein the remote control comprises remote starting, closing an engine, locking or unlocking a vehicle door, and safety verification is performed before a remote control unit is started, so that remote operation is ensured for authorized personnel;
a positioning tracking unit for:
Tracking the position and track of the vehicle in real time through a GPS, and remotely checking the real-time position, the historical track and the running speed information of the vehicle by a vehicle owner or company through a positioning tracking unit;
A location tracking unit comprising:
the data transmission time information acquisition module is used for extracting each position data transmission time of the current vehicle;
the data receiving time information acquisition module is used for calling each position data receiving time of the current vehicle;
the transmission time length information acquisition module is used for acquiring the transmission time length of the position data of the current vehicle by utilizing the transmission time of each position data of the current vehicle and the receiving time of each position data of the current vehicle;
the data transmission quality parameter acquisition module is used for setting the data transmission quality parameter of the position data of the current vehicle by utilizing the position data transmission time length of the current vehicle; the data transmission quality parameters of the position data are obtained through the following formula:
Wherein Q t represents a data transmission quality parameter; n represents the number of transmission times of the position data; t i denotes a time difference between a position data transmission time and a position data reception time when the position data transmission is performed the ith time; l represents the minimum distance that the current positioning change can recognize; v represents the average speed of the current vehicle;
the speed information acquisition module is used for acquiring the running speed information of the current vehicle in real time;
The vehicle running parameter acquisition module is used for acquiring the running parameters of the vehicle by using the running speed information of the current vehicle; wherein, the vehicle operation parameters are obtained by the following formula:
Wherein Q v represents a vehicle operating parameter; m represents the number of unit time which is experienced during the running of the current vehicle, and the unit time is 1s; v i denotes the speed of the current vehicle corresponding to the i-th unit time;
the compensation distance prediction module is used for predicting the compensation running distance of the current vehicle by utilizing the data transmission quality parameter and the vehicle running parameter, and performing forward compensation on the current vehicle position by utilizing the compensation running distance to obtain a prediction distance;
And the prediction information sending module is used for sending the position data corresponding to the prediction distance to the vehicle tracking platform as the position data of the current vehicle positioning.
2. The vehicle network bus information transmission vehicle management system based on data acquisition and analysis as claimed in claim 1, wherein: the data acquisition module comprises:
A sensor unit for:
Acquiring various state data from a vehicle, acquiring corresponding engine rotation speed, vehicle speed, oil quantity and water temperature through a rotation speed sensor, a vehicle speed sensor, an oil quantity sensor and a water temperature sensor, acquiring data by the sensors, and transmitting the data to a data processing module through a CAN bus;
the behavior data acquisition unit is used for:
recording the operation habit of a driver, and acquiring corresponding operation data of brake, accelerator and steering through installing a pedal sensor and a steering wheel torque sensor;
a GPS environment sensor unit for:
the method comprises the steps of acquiring GPS position, external temperature and humidity of a vehicle, acquiring position information of the vehicle through a GPS receiver, acquiring real-time environmental data through a temperature and humidity sensor, acquiring the data, and transmitting the data to a data processing module through a CAN bus.
3. The vehicle network bus information transmission vehicle management system based on data acquisition and analysis as claimed in claim 1, wherein: the data processing module comprises:
a data preprocessing unit for:
data sent by a data acquisition module is received from a CAN bus, and the data is cleaned and preprocessed, wherein the preprocessing comprises data filtering, abnormal value detection and repair and data standardization;
A vehicle running state analysis unit configured to:
Analyzing the running state of the vehicle by processing the vehicle state data, and detecting the running mode and performance of the vehicle;
A driving behavior analysis unit for:
Processing and analyzing the behavior data of the driver, and evaluating the driving style and behavior mode of the driver and whether bad driving habit exists or not by analyzing the operation habits of brake, accelerator and steering;
an abnormality detection unit configured to:
Detecting abnormality of the running state and the driving behavior of the vehicle, and detecting an abnormal event or potential problem by comparing the current data with the historical data and a preset normal range;
a failure prediction unit for:
Based on vehicle history data and a machine learning algorithm, possible faults are predicted, possible problems in the future are predicted by analyzing fault modes and trends in the history data, and maintenance reminding is sent out in advance.
4. A vehicle network bus information transfer vehicle management system based on data acquisition analysis as claimed in claim 3, wherein: the abnormality detection unit compares the current data with the historical data and sets the normal range of the data;
Detecting an abnormal event or a potential problem according to the set normal range and a comparison result with the historical data;
based on the nature and severity of the anomaly, a determination is made as to what abnormal event or potential problem is.
5. A vehicle network bus information transfer vehicle management system based on data acquisition analysis as claimed in claim 3, wherein: the fault prediction unit selects features related to faults based on the processed data;
training a machine learning model using the selected features and the historical data;
Evaluating the model by using an independent verification data set, checking the prediction accuracy and performance of the model, and adjusting and optimizing the model according to the evaluation result;
and predicting future faults by using a trained model, and deducing the possible fault types and time according to the input characteristic data by the model.
6. The vehicle network bus information transmission vehicle management system based on data acquisition and analysis as claimed in claim 1, wherein: a compensation distance prediction module comprising:
the first parameter extraction module is used for extracting the data transmission quality parameters;
The second parameter extraction module is used for extracting the vehicle operation parameters;
The compensation distance acquisition module is used for acquiring the compensation distance by utilizing the data transmission quality parameter and the vehicle operation parameter; the compensation distance is obtained through the following formula:
Wherein L c represents the compensation distance; v max represents the maximum travel speed of the current vehicle in the last 10 units of time of history; t x denotes a reference time; t represents the data transmission time corresponding to the position data of the current vehicle;
and the predicted distance acquisition module is used for taking the position of the current vehicle as a starting point, and migrating the position of the vehicle according to the compensation distance to obtain the predicted distance.
7. The vehicle network bus information transmission vehicle management system based on data acquisition and analysis as claimed in claim 1, wherein: the security privacy module includes:
A data encryption unit configured to:
encrypting all transmitted and stored data;
an identity verification unit for:
Providing an identity verification mechanism, wherein a user can access the data which the user is authorized to access by providing a correct user name and password;
a data desensitization unit for:
and (3) desensitizing the sensitive data, and covering or replacing sensitive fields, wherein the sensitive fields comprise personal information and bank card number information.
8. A method for implementing a vehicle network bus information transmission vehicle management system based on data acquisition and analysis according to any one of claims 1-7, characterized in that: the method comprises the following steps:
Step one: the system acquires vehicle state data, driver behavior data and environment data through a data acquisition module;
step two: the data processing module is used for preprocessing and analyzing the acquired data, detecting the running state and performance of the vehicle, evaluating the driving style and behavior mode of the driver, and carrying out anomaly detection and fault prediction;
step three: comparing the current data with the historical data, and once an abnormal event or potential problem is detected, giving an alarm and reminding a user by the system, and simultaneously predicting future faults and giving a maintenance reminding in advance based on the historical data;
step four: the vehicle performs data interaction with other vehicles or cloud platforms, receives or transmits data, and a user remotely checks the state of the vehicle and controls the vehicle through a mobile phone or a computer;
step five: all the transmitted data are encrypted by the security privacy module, and security verification is carried out before the remote control unit carries out remote operation, so that the identity of authorized personnel is determined.
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