CN114694368A - Vehicle management and control system - Google Patents
Vehicle management and control system Download PDFInfo
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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Abstract
The application discloses management and control system of vehicle includes: the vehicle-mounted terminal equipment is used for acquiring driving data of the vehicle; the road side terminal equipment is used for acquiring the driving data of the vehicle; and the edge computing platform is in communication connection with the vehicle and the roadside terminal equipment and is used for receiving and processing the driving data and the driving data so that the management and control system can be used for managing and controlling the vehicle according to the processing result. The management and control system calculates and processes the driving data and the driving data of the vehicle by introducing the edge calculation platform, reduces transmission delay in a vehicle communication network to a certain extent due to the fact that edge calculation has low delay and real-time performance, and effectively guarantees real-time performance of management and control of the vehicle. In addition, the processing result is generated into the control instruction to be sent to the vehicle, so that the driving behavior of the vehicle can be managed and controlled in real time without waiting for manual analysis and processing passively, and the vehicle is actively managed and controlled to a certain extent.
Description
Technical Field
The application relates to the technical field of vehicles, in particular to a management and control system of a vehicle.
Background
With the development of intelligent technology and communication technology, the big data is utilized to monitor the driver and the vehicle, and effective guarantee can be provided for road safety to a certain extent. In the related art, it is usually necessary to transmit the collected related data to a cloud server through a network, and the data is processed by the cloud server to perform related control on the vehicle. However, in the process of transmitting data from the vehicle-mounted terminal to the cloud, network transmission has a certain delay, and after the related data are transmitted to the cloud server, manual analysis processing is often required without calculation and analysis, which is time-consuming, labor-consuming and poor in effectiveness.
Disclosure of Invention
In view of this, the embodiment of the present application provides a management and control system of a vehicle.
The application provides a management and control system of vehicle includes:
the vehicle-mounted terminal equipment is used for acquiring the driving data of the vehicle;
the road side terminal equipment is used for acquiring the driving data of the vehicle;
and the edge computing platform is in communication connection with the vehicle and the roadside terminal equipment and is used for receiving and processing the driving data and the driving data so that the management and control system can be used for managing and controlling the vehicle according to a processing result.
In some implementation methods, the edge computing platform is further configured to generate a control instruction according to the processing result, send the control instruction to the vehicle, and send the driving data and the driving data to a third-party management platform to manage and control the vehicle.
In some implementation methods, the management and control system further includes a cloud control platform, where the cloud control platform is configured to receive the driving data, and the processing result sent by the edge computing platform, generate a control instruction according to the processing result, send the control instruction to the vehicle, and send the driving data and the driving data to a third-party management platform to manage and control the vehicle.
In some implementations, the driving data includes driving behavior data of a driver of the vehicle, and the edge computing platform is configured to process the driving behavior data to determine whether the driving behavior of the driver is abnormal.
In some implementations, the edge computing platform is configured to analyze the driving behavior data according to a pre-established driving behavior model to determine whether the driving behavior of the driver is abnormal.
In some implementations, the edge computing platform is to:
determining the driving smoothness, the driving speed and the driving duration of the vehicle according to the driving behavior data;
ranking the driving smoothness, the driving speed and the driving duration according to the driving behavior model;
and judging whether the driving behavior of the driver is abnormal or not according to the driving smoothness, the driving speed and the rating result of the driving time.
In some implementation methods, the driving data further includes driving behavior data of the vehicle, the driving data includes road condition data and violation data of the vehicle, and the edge computing platform is configured to process the driving behavior data, the road condition data, and the violation data to determine whether the driving behavior of the vehicle is abnormal.
In some implementation methods, the edge computing platform is configured to send abnormal driving data for confirming an abnormality and a violation to the third-party management platform, so that the third-party management platform can manage and control the vehicle according to the abnormal driving data and the violation.
In some implementation methods, the management and control system generates prompt information for the driver according to the processing result.
In some implementation methods, the management and control system generates speed limit control instructions for the vehicle according to the processing result.
In some implementation methods, the vehicle-mounted terminal device is further configured to collect health data of the driver, and send the health data and the positioning information of the vehicle to the third-party management platform.
The management and control system of the vehicle implementing the method comprises the following steps: the vehicle-mounted terminal equipment is used for acquiring driving data of the vehicle; the road side terminal equipment is used for acquiring the driving data of the vehicle; and the edge computing platform is in communication connection with the vehicle and the roadside terminal equipment and is used for receiving and processing the driving data and the driving data so that the management and control system can be used for managing and controlling the vehicle according to the processing result. According to the method and the device, the driving data and the driving data of the vehicle are calculated and processed by introducing the edge calculation platform, and the edge calculation has low time delay and real-time performance, so that the transmission time delay in a vehicle communication network is reduced to a certain extent, and the real-time performance of management and control of the vehicle is effectively guaranteed. In addition, the processing result is generated into the control instruction to be sent to the vehicle, so that the driving behavior of the vehicle can be managed and controlled in real time without waiting for manual analysis and processing passively, and the vehicle is actively managed and controlled to a certain extent.
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The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings.
FIG. 1 is a block diagram of a management system for a vehicle embodying certain methods of the present application;
FIG. 2 is a block diagram of a management and control system of a vehicle embodying certain methods of the present application.
Detailed description of the invention
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
Referring to fig. 1, the present embodiment provides a vehicle management and control system 100 for a third party to manage and control a vehicle, where the vehicle management and control system 100 includes a plurality of vehicle-mounted terminal devices 10, a plurality of road-side terminal devices 20, and a plurality of edge computing platforms 30. Further, the Vehicle-mounted terminal devices 10, the roadside terminal devices 20, and the Vehicle-mounted terminal devices 10 and the roadside terminal devices 20 may all be connected to a Vehicle wireless communication network, such as V2X (Vehicle to event) through a wireless communication manner. The plurality of edge computing platforms 30 may be connected via a wired or vehicular wireless communication network, such as V2X, and the plurality of vehicle-mounted terminal devices 10 and the plurality of roadside terminal devices 20 are connected to the plurality of edge computing platforms 30 via a vehicular wireless communication network, such as V2X.
Specifically, the in-vehicle terminal device 10 may be used to acquire traveling data of the vehicle. The vehicle-mounted terminal device 10 may implement active intelligent sensing, for example, includes a camera, a sound image sensor may collect driving behaviors of a driver, such as facial expressions and road front information, and an AI thermal imaging temperature measuring instrument may collect health data of the driver. The driving data includes driving behavior data of a driver of the vehicle, such as driving data of normal driving, speeding, rapid acceleration, rapid deceleration, distance to a preceding vehicle and other normal or illegal driving behaviors.
The vehicle-mounted terminal device 10 can acquire driving data of the vehicle in real time and send the driving data to the edge computing platform 30 for data processing, and can store part of illegal image or video data in a corresponding storage unit according to a control instruction of the server. Further, after the vehicle-mounted terminal device 10 receives the control instruction of the edge computing platform 30, the vehicle or the driver may execute a corresponding instruction operation according to the corresponding control instruction.
The roadside terminal device 20 may be used to acquire travel data of the vehicle. The roadside terminal device 20 includes an intelligent Roadside System (RSU), such as an intelligent camera, and communicates with a corresponding vehicle-mounted Unit of the vehicle, thereby performing operations such as vehicle identification and violation recording. Meanwhile, information such as road conditions and pedestrians can be shared to vehicles and drivers driving on the road surface through the RSU. The roadside terminal device 20 may acquire the driving data of the vehicle in real time and transmit the driving data to the edge computing platform 30 for data processing, or transmit information such as road conditions and pedestrians to the vehicle-mounted terminal device 10. The driving data of the vehicle includes road conditions such as traffic light information, and violation data of the vehicle.
The edge computing platform 30 is connected to the vehicle through a vehicle wireless communication network, receives vehicle driving data and driving data, and performs computing processing on the vehicle driving data and the driving data, so that the vehicle is correspondingly controlled according to a processing result. Among other things, edge computing can provide real-time, accurate, and reliable local computation and analysis of large amounts of data. Compared with cloud computing, the cloud computing system is closer to vehicles and local equipment, and an open platform integrating network, computing, storage and application core capabilities is adopted, so that the nearest-end service is provided nearby. By introducing the edge computing platform 30, the driving data and the driving data of the vehicle such as abnormal driving behaviors and dangerous driving behaviors needing immediate early warning are locally processed, and a processing result is rapidly generated and fed back. Therefore, for the car networking with high requirements on large data volume and instantaneity, compared with the traditional cloud computing, the edge computing can better solve the problems of overlong time delay, overlarge converged flow and the like, and better support is provided for instantaneity and bandwidth intensive services.
It can be understood that in the car networking communication process, the privacy safety of users and vehicles needs to be guaranteed, and in the existing communication such as a 5G network, the safety and the privacy can be guaranteed through various technologies. For example, with the SDN technology, multiple transmission paths are selected for a data flow according to the sensitivity level of the data flow, and at a receiving end, only a receiver can decrypt the data flow with a private key and reassemble the data flow from the multiple network transmission paths, thereby avoiding privacy disclosure at a wireless access point. Or the decoupling of software and hardware can be realized by utilizing a network virtualization technology, the virtual infrastructure platform can be managed uniformly, and dynamic resource reconfiguration can be carried out.
Therefore, the vehicle management and control system 100 of the embodiment of the present application introduces the edge computing platform 30 to perform computing processing on the driving data and the driving data of the vehicle, and because the edge computing has low latency and real-time performance, the transmission latency in the vehicle communication network is reduced to a certain extent, and the real-time performance of vehicle management and control is effectively ensured. In addition, the processing result is generated into the control instruction to be sent to the vehicle, so that the driving behavior of the vehicle can be managed and controlled in real time without waiting for manual analysis and processing passively, and the vehicle is actively managed and controlled to a certain extent.
In some embodiments, the edge computing platform 30 is further configured to generate a control command according to the processing result and send the control command to the vehicle, and after the vehicle receives the control command, the vehicle may perform corresponding operations according to a preset program, for example, when the vehicle receives a voice prompt control command, a vehicle voice system may be called to perform voice prompt.
Meanwhile, the edge computing platform 30 may further send the acquired driving data and driving data to a third-party management platform according to a preset state, and the third-party management platform may further analyze and judge according to the data, so as to achieve subsequent management and control of the vehicle.
Therefore, related data are sent to the third-party management platform for further management and control, the effectiveness of vehicle management and control can be guaranteed to a certain extent, and application experience is improved by increasing the management authority of third-party application.
Referring to fig. 2, in some embodiments, a cloud control platform 40 may be introduced into the management and control system, so that the management and control system 100 includes a plurality of vehicle-mounted terminal devices 10, a plurality of roadside terminal devices 20, a plurality of edge computing platforms 30, and a plurality of cloud control platforms 40. Further, a Vehicle wireless communication network, such as V2X (Vehicle to event), may be connected between the Vehicle-mounted terminal devices 10, between the roadside terminal devices 20, and between the Vehicle-mounted terminal devices 10 and the roadside terminal devices 20 through a wireless communication method. The plurality of edge computing platforms 30 may be connected to each other through a wired or vehicular wireless communication network such as V2X, and the plurality of vehicle-mounted terminal devices 10 or the plurality of roadside terminal devices 20 and the plurality of edge computing platforms 30 may be connected to each other through a vehicular wireless communication network such as V2X. The plurality of edge computing platforms 30 and the plurality of cloud control platforms 40 may be connected via a wired or vehicular wireless communication network, such as V2X. Cloud control platform 40 may communicate with edge computing platforms 30 via wired or vehicular wireless communication networks, such as V2X connections.
The cloud control platform 40 may be configured to receive the driving data, and the processing result sent by the edge computing platform 30, and generate a control instruction according to the processing result. For the driving data and the driving data of some vehicles, such as abnormal driving behaviors, dangerous driving behaviors requiring immediate early warning, etc., the edge computing platform 30 may process them and send the result to the cloud control platform 40. And after receiving the processing result, the cloud control platform 40 analyzes and calculates the processing result according to a corresponding control program or an artificial intelligence algorithm to generate a control instruction. Further, the cloud control platform 40 sends the control instruction to the vehicle-mounted terminal device 10, and sends the driving data and the driving data to the third-party management platform. When the third-party management platform receives the data, the data can be further processed in real time or periodically. And for the driving data and the driving data of the rest part of vehicles, such as violation behaviors, the human face recognition artificial intelligence model and the like, calculation processing can be carried out through the cloud control platform 40, and then a control instruction is generated, further, the cloud control platform 40 sends the control instruction to the vehicle-mounted terminal device 10, and sends the driving data and the driving data to a third-party management platform so as to control the vehicles.
It is understood that both the cloud control platform 40 and the edge computing platform 30 can perform corresponding calculations on the data and generate control instructions. In practical applications, part or all of the computing processing may be deployed on the edge computing platform 30 or the cloud control platform 40 according to the setting of the computation amount, the computation complexity, the real-time requirement, and the like. The following describes a communication flow of the management and control system 100 according to the present application by way of a specific example.
In some implementations, the driving data of the vehicle includes driving behavior data of the vehicle such as driver state data, vehicle instantaneous speed, average speed, turning data, brake pedal data, driving duration data, and the like. The data of the driver state can identify the facial expressions and actions of the driver through artificial intelligence to judge whether the driver is in different illegal driving states such as fatigue driving, smoking, drunk driving and the like. The vehicle-mounted terminal device 10 collects the driving behavior data of the vehicle in real time and sends the driving behavior data to the edge computing platform 30 for computing processing, and whether the current driving behavior of the vehicle is abnormal or whether the current driving behavior belongs to normal driving or illegal driving can be judged through a corresponding logic control program or a model algorithm.
Thus, the edge computing platform 30 may determine the normal or illegal driving behavior of the driver, and may issue the control command to the vehicle-mounted terminal device 10 by locally generating the control command at the edge computing platform 30, or by sending the computation processing result to the cloud control platform 40 for analysis and determination and issuing the control command to the vehicle-mounted terminal device 10. After receiving the corresponding control command, the vehicle-mounted terminal device 10 may perform a corresponding operation on the vehicle or the driver according to the command. Therefore, normal or illegal driving of the driver can be managed and controlled in real time.
In some embodiments, the edge computing platform 30 may pre-establish a driving behavior model to analyze the driving behavior data to determine whether the driving behavior of the driver is abnormal. It is understood that the driving behavior model can be used to calculate the driving behavior data, and the edge computing platform 30 analyzes the calculation result to determine whether the driving behavior of the driver is abnormal.
Specifically, the edge computing platform 30 may obtain driving behavior data of the vehicle such as driving smoothness, driving speed, and driving duration of the vehicle. And the driving behavior model can obtain the final driving score by calculating the respective scores of the driving smoothness, the driving speed and the driving duration. And grading the final driving score, and judging whether the driving behavior of the driver is abnormal or not according to a grading result.
Further, the driving stability can be calculated from the number of times of sudden acceleration, the number of times of sudden deceleration, the number of times of sudden turning, and the like of hundreds of kilometers. That is, the times of rapid acceleration, rapid deceleration and rapid turning are obtained every one hundred kilometers, and the smaller the total times, the higher the driving score.
The rapid acceleration and the rapid deceleration can be calculated by continuously collecting the running speed information twice within a short time interval, and the acceleration or the deceleration is identified by comparing with a reasonable threshold, for example, when the acceleration or the deceleration is greater than the threshold, the vehicle can be considered to be in a rapid acceleration or rapid deceleration state, and the behavior is counted as a rapid acceleration or rapid deceleration. And the travel value of the accelerator pedal and the travel value of the brake pedal can be continuously acquired twice in a short time and calculated. The change rate of the pedal stroke is obtained by dividing the difference value of the stroke values sampled twice by the time difference of the sampling, and when the change rate is larger than the threshold value, the vehicle is considered to be in a rapid acceleration or rapid deceleration state, and the behavior is counted as a rapid acceleration or rapid deceleration.
While a sharp turn may be computationally identified by vehicle speed and turn angle speed. Specifically, a speed of 30km/h may be set as a turning speed threshold, and a sharp turning angular speed threshold of 0.45 rad/s. And measuring the angular speed according to the angular speed sensor, and determining the sharp turning angular speed when the current angular speed value of the vehicle is more than 0.45 rad/s. And when the vehicle speed is greater than the turning speed threshold value and the turning angular speed is greater than the sharp turning angular speed threshold value, the vehicle can be judged to be in a sharp turning state at present.
In addition, the driving speed may be calculated from a normal speed driving period, an overspeed driving period, and the like. The higher the driving time or the percentage of the normal speed, the higher the score of the driving speed, and the higher the driving time or the percentage of the overspeed, the lower the score. The speed threshold value in the urban road can be set to be 60km/h, and when the instantaneous speed is greater than the set threshold value in a certain time, overspeed driving can be judged, and the duration is accumulated. The normal speed per hour, i.e., the speed durations below the vehicle speed threshold, are also accumulated. Thus, the driving speed can calculate the driving score from the normal speed driving time period, the overspeed driving time period and the like.
Second, the driving time period may be calculated from the normal driving time period and the illegal driving time period. The illegal driving time includes, but is not limited to, driving time such as overspeed driving time, fatigue driving time, smoking and telephone calling. The higher the normal driving time or the normal driving time is, the higher the score is, the higher the violation driving time or the violation driving time is, and the lower the score is.
Further, the bad driving behaviors of drivers who don't wear safety belts, drive fatigued, use mobile phones, smoke, and the like can be identified through artificial intelligence algorithm models, such as a convolutional neural network, a cyclic neural network, and the like. The camera or the image sensor of the vehicle-mounted terminal device can collect the current image or video data of the driver and send the current image or video data to the cloud control platform 40 or the edge computing platform 30, when the cloud control platform 40 or the edge computing platform 30 receives the driving behavior data, the driving behavior data are calculated and identified by an artificial intelligence algorithm, and if the identification result is that the driver is in a fatigue driving state at present.
For example, driver's bad driving behavior is identified by a neural network. Specifically, a real-time video of the driver is acquired by the in-vehicle terminal device 10. Firstly, screening the acquired videos according to the vehicle speed, namely, rejecting the videos below a set vehicle speed threshold. And secondly, taking frames from the obtained effective videos, namely taking a set number of 40 frame pictures at equal intervals from each video, and naming the frame pictures according to the time sequence. Then, extracting features by adopting a gradient direction histogram, sending the features into a support vector machine for carrying out object detection on a video picture by a two-classification method, thereby positioning a driver area, and simultaneously cutting, for example, removing pictures such as a backseat, outside a window and the like, and only keeping the picture of the driver area. Further, the driver picture can be identified by using the convolutional neural network, so that the abnormal type of the driver picture, such as normal driving, distracted driving, fatigue driving, smoking, or making a call, can be finally determined. And further processing according to the recognition result, and if the recognition result is that the driver is currently in the smoking state, generating a corresponding control command and sending the control command to the vehicle.
Thus, the edge computing platform 30 may obtain driving behavior data of the vehicle such as driving smoothness, driving speed, and driving duration of the vehicle. And then obtaining a final driving score through the driving behavior model, grading the final driving score, and judging whether the driving behavior of the driver is abnormal or not according to a grading result. Specifically, different score value ranges may be defined as different anomaly levels, and the edge computing platform 30 may then perform corresponding control according to the anomaly levels. For example, the driver performs rapid acceleration once in a hundred kilometers, the edge computing platform 30 calculates the score as 10 points through the driving behavior model, and can determine that the vehicle is a primary anomaly according to the corresponding grade determination standard, and the edge computing platform 30 can issue a corresponding control instruction of the primary anomaly in real time to the vehicle, such as performing voice prompt on the driver.
Thus, the edge computing platform 30 analyzes the driving behavior data according to the driving behavior model established in advance to determine whether the driving behavior of the driver is abnormal, establishes the driving behavior model according to the driving behavior data of various vehicles, such as driving stability, driving speed and driving duration, performs respective score computation on the acquired data, and finally forms a final driving score. The method can avoid triggering management and control by occasional abnormal driving behaviors, thereby ensuring the reliability and effectiveness of the management and control system to a certain extent.
In some implementation methods, the driving data acquired from the vehicle-mounted terminal device 10 further includes driving behavior data of the vehicle, and the driving data acquired from the roadside terminal device 20 includes road condition data and violation data of the vehicle. The driving behavior data includes the instantaneous speed of the vehicle, and relationship data with road vehicles and pedestrians, such as the distance to the front vehicle. The vehicle-mounted terminal device 10 can realize communication capability through an OBU integrated with a C-V2X module, and acquire driving behavior data of a currently driving vehicle by combining devices of a vehicle body, such as a front-mounted vehicle machine, a rear-mounted rearview mirror or a rear-mounted terminal box. The road condition data acquired from the roadside terminal device 20 includes road data, pedestrian data, current traffic conditions, and the like, and the violation data of the vehicle is data of violation of the current vehicle, including red light running, overspeed, retrograde motion, emergency lane occupation, and the like.
Specifically, when the current vehicle or the abnormal condition with the surrounding vehicles and pedestrians is monitored by the devices such as the camera and the vision sensor in the vehicle, the related data can be sent to the edge computing platform 30. For example, the vision sensor monitors that the current vehicle is too close to the vehicle ahead and exceeds a normal range threshold, and sends such driving behavior data to the edge computing platform 30, and the edge computing platform 30 may further make a comprehensive judgment by combining the acquired front vehicle data in the road data, and when the result after the calculation processing is that the distance to the front vehicle exceeds the normal range, it is judged that the vehicle is currently in an abnormal driving behavior, and generates a corresponding control instruction such as a primary abnormality and sends the corresponding control instruction to the vehicle.
For the violation behaviors of the vehicle, after the edge computing platform 30 receives the violation data of the roadside device 20, the vehicle information and the violation data can be extracted and sent to a third party management platform such as fleet management. Meanwhile, historical violation records of the vehicle can be obtained according to a preset program to further judge whether to carry out abnormal early warning and management and control. For example, when the current vehicle has a violation behavior of emergency lane occupation, the roadside terminal device 20 obtains the current violation information and sends the current violation information to the edge computing platform 30, the edge computing platform 30 further extracts historical violation information of the current vehicle after receiving the violation information to perform comprehensive computation and judgment, if an early warning such as voice prompt "the current emergency lane occupation and please leave the emergency lane immediately" can be performed, the edge computing platform 30 can further monitor whether the vehicle is executed from the vehicle or the roadside terminal device 20, if the vehicle is judged to be in a normal driving state through computation, the vehicle is stopped, otherwise, a speed limit control instruction can be further executed.
So, the management and control system of this application can carry out real time monitoring discernment and early warning to the dangerous driving of vehicle driving and the action of violating the regulations, avoids the emergence of accident through promoting the driver in advance, can reduce traffic accident incidence to a certain extent, improves the security of driving a vehicle. Further, for the violation behaviors of the vehicle, the edge computing platform 30 can correspondingly manage and control the violation vehicles in real time by acquiring the violation data of the roadside terminal device 20 in real time, so that the violation vehicles can be actively processed immediately, the violation behaviors are only subjected to passive processing such as deduction and the like, and more violation behaviors can be avoided to a certain extent.
In some embodiments, the edge computing platform 30 may send the abnormal driving data and the violation to the third party management platform, so that the third party management platform may further manage the vehicle according to the abnormal driving data and the violation.
In some embodiments, the edge computing platform 30 or the cloud control platform 40 processes the acquired data and generates corresponding control instructions. Wherein the control instruction comprises prompt information for the vehicle or the driver. Specifically, the prompt can be performed through vehicle-mounted voice prompt or vehicle-mounted large-screen information prompt, and when the vehicle and the driver have communication connection such as vehicle-mounted T-BOX (telematics BOX), the prompt information can also be sent to an intelligent terminal such as a mobile phone of the driver.
For example, the edge computing platform 30 obtains driving behavior data of the vehicle, and obtains the current fatigue driving of the driver through the driving behavior model computing processing, and the processing result is a first-level abnormality. Further, the edge computing platform 30 processes the results for the first-level anomaly as "tips 12", where the 12-digit numbers represent different types of tip information, here denoted as "fatigue driving". The edge computing platform 30 issues a control instruction of "prompt 12" to the vehicle-mounted terminal device 10, and after receiving the control instruction of "prompt 12", the vehicle-mounted terminal device 10 performs corresponding operations according to the preset, such as voice prompt "fatigue driving is currently in progress, please pay attention to rest", or sends a prompt message to the vehicle-mounted central control large screen "fatigue driving is currently in progress, please pay attention to rest".
For another example, the edge computing platform 30 obtains the driving behavior data of the vehicle, and calculates that the current vehicle is too close to the preceding vehicle, and the processing result is a first-level abnormality. Further, the edge computing platform 30 processes the result of the current-level exception as "prompt 21", where 21 is a number indicating different types of prompt information, here "too close to the leading vehicle". The edge computing platform 30 issues a control instruction of "prompt 21" to the vehicle-mounted terminal device 10, and after receiving the control instruction of "prompt 21", the vehicle-mounted terminal device 10 performs corresponding operations according to the preset instruction, such as voice prompt "the current distance is too close to the preceding vehicle, please note to keep the distance", or sends a prompt message to the vehicle-mounted central control large screen "please note to keep the distance to the preceding vehicle".
In this way, the management and control system 100 of the vehicle may be configured to prompt the vehicle or the driver for abnormal driving behavior of the vehicle or a corresponding grade ranked by the driving behavior model, such as a first-level abnormality to a second-level abnormality. The data are acquired in real time to calculate and generate results, and a driver can be reminded to take corresponding measures in time, so that the occurrence rate of traffic accidents is reduced to a certain extent, the driving habit of the driver is improved, and the driving safety is improved.
In some embodiments, the edge computing platform 30 or the cloud control platform 40 processes the acquired data and generates corresponding control instructions. Wherein the control instruction comprises a speed limit control instruction. When the vehicle-mounted terminal device 10 receives the speed limit control instruction, corresponding operations can be executed according to the current driving state.
Specifically, for example, the edge computing platform 30 may obtain driving behavior data of the vehicle, obtain that the current driver is driving at an overspeed and the duration is 30 minutes through the driving behavior model calculation processing, determine that the result is a three-level abnormality according to the score, and process the result of the three-level abnormality by the edge computing platform 30 as a "speed limit". Further, the edge computing platform 30 issues the speed limit related control command to the vehicle-mounted terminal device 10, and after the vehicle-mounted terminal device 10 receives the speed limit control command, according to a preset program, if a prompt is given firstly that "do not have to drive at an excessive speed, the speed is reduced to the normal speed within 1 minute, otherwise the vehicle can automatically decelerate", and a time threshold value of 1 minute is set, the vehicle speed is monitored in real time, if the vehicle is reduced to the normal speed within the time threshold value, the speed limit operation is abandoned, otherwise, the speed limit operation is executed after the time threshold value reaches 1 minute, and the vehicle speed is gradually reduced at a constant speed according to the preset program.
In this way, the management and control system 100 of the vehicle may be set to perform speed limit control on the vehicle or the driver for abnormal driving behaviors of the vehicle or corresponding levels after being ranked by the driving behavior model, such as primary to secondary abnormality. The data are acquired in real time to calculate and generate results, and the vehicle can be controlled in time to avoid long-time illegal driving, so that the incidence rate of traffic accidents is reduced to a certain extent, and the driving safety is improved.
In some implementation methods, the in-vehicle terminal device 10 may also be used to collect health data of the driver. In the special period of epidemic situation, if the health data needs to be collected for the driver of the vehicle, the body temperature of the driver can be monitored in real time through the AI thermal imaging thermodetector integrating the face recognition system in the vehicle. When the body temperature is abnormal, if the body temperature exceeds 37.3 ℃, the AI thermal imaging thermometer in the vehicle can send the body temperature information of the driver, the face image, the vehicle position and other information to the edge computing platform 30 or the cloud control platform 40. When the edge computing platform 30 or the cloud control platform 40 receives the information, the information is calculated and judged, and then the information is sent to a corresponding third-party management platform such as a medical epidemic prevention department.
In this way, the vehicle-mounted terminal device 10 collects the health data of the driver, and sends the health data to the edge computing platform 30 or the cloud control platform 40 for computing and processing, and sends the result to a third-party management platform such as a medical epidemic prevention department. Furthermore, after the medical epidemic prevention department receives the information, the information can be processed in real time according to the preset priority. Can provide real-time information and safety and health guarantee for public health safety in special epidemic situations to a certain extent.
The management and control system of the vehicle implementing the method comprises the following steps: the vehicle-mounted terminal device 10 is used for acquiring driving data of a vehicle; a roadside terminal device 20 for acquiring travel data of the vehicle; and the edge computing platform 30 is in communication connection with the vehicle and the roadside terminal equipment and is used for receiving and processing the driving data and the driving data so that the management and control system can be used for managing and controlling the vehicle according to the processing result. According to the method and the device, the edge computing platform 30 is introduced to compute and process the driving data and the driving data of the vehicle, and the edge computing has low time delay and real-time performance, so that the transmission time delay in a vehicle communication network is reduced to a certain extent, and the real-time performance of vehicle management and control is effectively guaranteed. In addition, the processing result is generated into the control instruction to be sent to the vehicle, so that the driving behavior of the vehicle can be managed and controlled in real time without waiting for manual analysis and processing passively, and the vehicle is actively managed and controlled to a certain extent. Further, the edge computing platform 30 sends the driving data and the driving data to the third party management platform, so that the third party can extract the driving data and the driving data of the vehicle, or perform real-time and periodic management and control, and the like, thereby improving the active management and control effect of the third party on the vehicle.
One skilled in the art can understand that all or part of the processes in the above embodiments can be implemented, and the above embodiments only express several implementation methods of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (11)
1. A management and control system of a vehicle, characterized by comprising:
the vehicle-mounted terminal equipment is used for acquiring the driving data of the vehicle;
the road side terminal equipment is used for acquiring the driving data of the vehicle;
and the edge computing platform is in communication connection with the vehicle and the roadside terminal equipment and is used for receiving and processing the driving data and the driving data so that the management and control system can be used for managing and controlling the vehicle according to a processing result.
2. The management and control system according to claim 1, wherein the edge computing platform is further configured to generate a control instruction according to the processing result, send the control instruction to the vehicle, and send the driving data and the driving data to a third-party management platform to manage and control the vehicle.
3. The management and control system according to claim 1, further comprising a cloud control platform, wherein the cloud control platform is configured to receive the driving data, and the processing result sent by the edge computing platform, generate a control instruction according to the processing result, send the control instruction to the vehicle, and send the driving data and the driving data to a third-party management platform to manage and control the vehicle.
4. The management and control system according to claim 1, wherein the driving data includes driving behavior data of a driver of the vehicle, and the edge computing platform is configured to process the driving behavior data to determine whether the driving behavior of the driver is abnormal.
5. The management and control system according to claim 4, wherein the edge computing platform is configured to analyze the driving behavior data according to a pre-established driving behavior model to determine whether the driving behavior of the driver is abnormal.
6. The management and control system of claim 5, wherein the edge computing platform is to:
determining the driving smoothness, the driving speed and the driving duration of the vehicle according to the driving behavior data;
ranking the driving smoothness, the driving speed and the driving duration according to the driving behavior model;
and judging whether the driving behavior of the driver is abnormal or not according to the driving smoothness, the driving speed and the rating result of the driving time.
7. The management and control system according to claim 1, wherein the driving data includes driving behavior data of the vehicle, the driving data includes road condition data and violation data of the vehicle, and the edge computing platform is configured to process the driving behavior data, the road condition data, and the violation data to determine whether the driving behavior of the vehicle is abnormal.
8. The management and control system according to claim 7, wherein the edge computing platform is configured to send abnormal driving data and violations for confirming the abnormality to the third party management platform, so that the third party management platform can manage and control the vehicle according to the abnormal driving data and the violations.
9. The management and control system according to claim 1, characterized in that the management and control system generates prompt information for a driver according to the processing result.
10. The management and control system according to claim 1, wherein the management and control system generates speed limit control instructions for the vehicle according to the processing result.
11. The management and control system according to claim 1, wherein the vehicle-mounted terminal device is further configured to collect health data of the driver, and send the health data and the positioning information of the vehicle to the third-party management platform.
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