A vehicle monitoring system based on a VIN vehicle terminal

Abstract

The application discloses a kind of vehicle monitoring systems based on VIN vehicle terminal, it is related to automobile monitoring technical field, including vehicle controller, signal monitoring module, management center and vehicle evaluation module;Vehicle controller is used to integrate the driving time series data and video information received, obtains driving monitoring data;Signal monitoring module is used to monitor the communication condition of driving area, communication deviation index XZ is calculated to determine whether driving monitoring data is uploaded;If XZ is greater than or equal to preset deviation threshold, it indicates that the current network condition is very poor, and vehicle controller saves driving monitoring data in local database, and no longer carries out data upload, to reduce the occupation of driving monitoring data to network bandwidth;Vehicle evaluation module is used to obtain the driving time series data of vehicle and carries out driving loss coefficient CS evaluation, if CS is greater than preset loss threshold, administrator is reminded to maintain vehicle, to realize the dynamic health management problem of vehicle.

Description

Technical Field

[0001] This invention relates to the field of automotive monitoring technology, specifically a vehicle monitoring system based on a VIN (Vehicle Information Network) terminal. Background Technology

[0002] With the evolution of existing in-vehicle products such as dashcams, GPS vehicle terminals, and in-vehicle entertainment systems, people are no longer satisfied with just functions such as vehicle driving information collection, location data collection, and image capture. They also need to record video images in real time and be able to remotely acquire video footage inside and outside the vehicle in real time, so as to facilitate visual monitoring of the vehicle's status while driving or after parking.

[0003] Existing vehicle monitoring systems lack the function of resuming video image file transmissions. If the connection is interrupted before a video image file is fully transmitted, the file will be retransmitted, increasing network overhead. Due to network signal issues, data distortion or loss may also occur. Furthermore, vehicle driving information is only collected without further analysis, making it difficult to achieve dynamic health management of vehicles. Based on these shortcomings, this invention proposes a vehicle monitoring system based on a VIN vehicle terminal. Summary of the Invention

[0004] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes a vehicle monitoring system based on a VIN (Vehicle Information Network) terminal.

[0005] To achieve the above objectives, an embodiment of the first aspect of the present invention provides a vehicle monitoring system based on a VIN vehicle terminal, including a driving monitoring module, a video monitoring module, a signal monitoring module, a management center, and a vehicle evaluation module;

[0006] The driving monitoring module includes vehicle-mounted sensors distributed around the vehicle to collect driving time-series data in real time and upload the collected driving time-series data to the vehicle controller; the driving time-series data includes the real-time current value flowing through the vehicle drive motor, the rotational speed of the vehicle drive wheels, the real-time vehicle speed, and the acceleration at the same time.

[0007] The video monitoring module includes cameras distributed inside and outside the vehicle, used to collect video information inside and outside the vehicle, and upload the collected video information to the vehicle controller; the vehicle controller is used to integrate the received driving time data and video information to obtain driving monitoring data;

[0008] The signal monitoring module is connected to the vehicle controller and is used to monitor the communication status of the driving area and calculate the communication deviation index XZ to determine whether to upload driving monitoring data.

[0009] If the communication deviation index XZ deviates from the preset deviation threshold, it indicates that the current network condition is very poor, and the vehicle controller saves the driving monitoring data in the local database without uploading the data;

[0010] If the communication deviation index XZ is less than the preset deviation threshold, it indicates that the current network condition is good, and the vehicle controller uploads the driving monitoring data to the management center through the data transmission module;

[0011] The vehicle evaluation module is connected with the management center, and is used for obtaining driving time sequence data of the vehicle to evaluate the driving loss coefficient CS. The specific evaluation steps are as follows:

[0012] S1: intercepting a time interval from the collected driving time sequence data;

[0013] S2: judging whether the vehicle has stopped in the time interval;

[0014] S3: judging whether the stop is due to emergency braking of the vehicle;

[0015] S4: obtaining the driving time period of the vehicle according to the driving time sequence data; and calculating the driving loss coefficient CS of the vehicle in combination with the space-time variation of the emergency braking of the vehicle;

[0016] If the driving loss coefficient CS is greater than the preset loss threshold, a loss signal is generated to the management center to remind the administrator to maintain the vehicle.

[0017] Further, the specific monitoring steps of the signal monitoring module are as follows:

[0018] The vehicle controller is connected with the base station group to periodically send a measurement configuration message to the base station group at a preset interval, wherein the measurement configuration message includes a first signal quality threshold; the base station group is composed of a plurality of base stations;

[0019] In response to receiving the measurement configuration message, each base station immediately sends a second synchronization signal to the vehicle controller; after the vehicle controller receives the second synchronization signal, the signal quality of the second synchronization signal is determined and compared with the first signal quality threshold to obtain a first quality difference CA;

[0020] The first quality difference CA is compared with a set value; if the first quality difference CA is greater than the set value, it indicates that the signal attenuation is serious, and an unqualified signal is generated;

[0021] When the unqualified signal is monitored, automatic countdown is performed, and the countdown is D1, which is a preset value; wherein each time the measurement configuration message is sent, the countdown is reduced by one;

[0022] The unqualified signal is continuously monitored in the countdown stage, if a new unqualified signal is monitored, the countdown is automatically returned to the original value, and the countdown is restarted according to D1; otherwise, the countdown is continued;

[0023] The number of occurrences of the unqualified signal in the countdown stage is P1, and the length of the countdown stage is L1; the communication deviation index XZ of the driving area is calculated by using the formula XZ=u×(P1×a1) / (L1×a2), wherein a1 and a2 are preset coefficient factors, and u is a preset compensation coefficient.

[0024] Further, the time interval in step S1 includes data of multiple time points, and the data of each time point includes data of multiple fields; the fields include current, driving wheel speed, vehicle speed, and acceleration.

[0025] Further, in step S2, it is judged whether the vehicle has stopped in the time interval, specifically, it is judged whether the value of the vehicle speed field appears 0 in the time interval; if it appears, the first time point with the value of 0 of the vehicle speed field is determined as the stopping time point.

[0026] Further, step S3 judges whether this stop is due to emergency braking of the vehicle, specifically including:

[0027] S31: a new time interval including data of the stopping time point and multiple time points adjacent to the stopping time point is re-intercepted from the time sequence data;

[0028] S32: the real-time current value flowing through the in-wheel motor of the vehicle is obtained based on the value of the current field of each time point in the new time interval; a curve graph of the real-time current value changing with time is established;

[0029] According to the change of the real-time current value, the real-time current value changing with time curve is divided into an ascending stage and a descending stage; the real-time current change derivative values of the curve equations in the ascending stage and the descending stage are calculated respectively;

[0030] S33: when the real-time current value is in the ascending stage, if the real-time current change derivative values of the vehicle are all greater than the preset threshold value within the first preset time T1, it is indicated that a suspected emergency braking is triggered, and step S34 is entered;

[0031] S34: when the real-time current value rises to the maximum value, if the real-time current value drops to 0 and the real-time current change derivative values are all greater than the preset threshold value within the second preset time T2, it is confirmed that the emergency braking occurs.

[0032] Further, the specific calculation method of the driving loss coefficient CS in step S4 is:

[0033] In the driving time period, the number of vehicle emergency braking is Z1, the driving time of the vehicle is Tz, the maximum real-time current value of the driving motor is marked as Lt, the maximum driving wheel speed is marked as Nt, the maximum vehicle speed is marked as Vt, and the maximum acceleration is marked as Gt.

[0034] The driving loss coefficient CS of the vehicle is calculated by the formula CS=f*Z1*Tz*(Lt*b3+Nt*b4+Vt*b5+Gt*b6), wherein b3, b4, b5 and b6 are preset coefficient factors, and f is a preset compensation coefficient.

[0035] Compared with the prior art, the present application has the following advantages:

[0036] 1. In the present application, the signal monitoring module is connected with the vehicle-mounted controller, and is used for monitoring the communication condition of the driving area to determine whether to upload the driving monitoring data; if the communication deviation index XZ is greater than or equal to the preset deviation threshold, it indicates that the current network condition is very poor, and the vehicle-mounted controller saves the driving monitoring data in the local database without data uploading; thereby reducing the occupation of the network bandwidth by the driving monitoring data; if the communication deviation index XZ is less than the preset deviation threshold, it indicates that the current network condition is good, and the vehicle-mounted controller uploads the driving monitoring data to the management center through the data transmission module, so that the management personnel can remotely obtain the video pictures inside and outside the vehicle in real time, and the vehicle state during driving and after parking can be visually supervised.

[0037] 2. In the present application, the vehicle evaluation module is connected with the management center, and is used for obtaining the driving time sequence data of the vehicle to evaluate the driving loss coefficient CS; first, the time interval is intercepted from the collected driving time sequence data to determine whether the vehicle has stopped in the time interval; then, whether the stop is due to the emergency braking of the vehicle is determined based on the curve graph of the real-time current value changing with time; the driving loss coefficient CS of the vehicle is calculated in combination with the number of emergency braking of the vehicle, the driving time and each driving time sequence parameter; if the driving loss coefficient CS is greater than the preset loss threshold, the administrator is reminded to maintain the vehicle, and the dynamic health management of the vehicle is realized. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0039] Figure 1 The system block diagram of the vehicle monitoring system based on the VIN vehicle-mounted terminal of the present application. Detailed Implementation

[0040] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] like Figure 1 As shown, a vehicle monitoring system based on a VIN vehicle terminal includes a driving monitoring module, a vehicle controller, a video monitoring module, a signal monitoring module, a local database, a data transmission module, a management center, and a vehicle evaluation module.

[0042] The driving monitoring module includes distributed on-board sensors around the vehicle to collect driving time-series data in real time and upload the collected driving time-series data to the on-board controller. The driving time-series data includes the real-time current value flowing through the vehicle's drive motor, the rotational speed of the vehicle's drive wheels, the real-time vehicle speed, and acceleration at the same time.

[0043] The video surveillance module includes cameras distributed inside and outside the vehicle to collect video information from inside and outside the vehicle and upload the collected video information to the vehicle controller; the vehicle controller is used to integrate the received driving time data and video information to obtain driving monitoring data;

[0044] In one embodiment of the present invention, the signal monitoring module is connected to the vehicle controller and is used to monitor the communication status of the driving area to determine whether to upload driving monitoring data; the specific monitoring steps are as follows:

[0045] The vehicle controller establishes a communication connection with the base station group and periodically sends measurement configuration messages to the base station group at preset intervals. The measurement configuration messages include a first signal quality threshold. The base station group consists of several base stations.

[0046] In response to receiving the measurement configuration message, each base station immediately sends a second synchronization signal to the vehicle controller; after receiving the second synchronization signal, the vehicle controller determines the signal quality of the second synchronization signal and compares it with the first signal quality threshold to obtain the first quality difference CA;

[0047] Those skilled in the art should understand that any metric known in the art can be used to characterize signal quality, such as RSRQ, RSRP, RSSI, etc.; the quality difference here can reflect the attenuation of the signal during transmission.

[0048] The first mass difference CA is compared with a set value; if the first mass difference CA is greater than the set value, it indicates that the signal attenuation is serious, and an unqualified signal is generated;

[0049] When an unqualified signal is monitored, automatic countdown is performed, and the countdown is D1, which is a preset value; wherein the countdown is reduced by one each time a measurement configuration message is sent;

[0050] The unqualified signal is continuously monitored during the countdown stage, and if a new unqualified signal is monitored, the countdown is automatically reset to the original value, and the countdown is restarted according to D1; otherwise, the countdown is continued;

[0051] The number of occurrences of unqualified signals in the countdown stage is counted as P1, and the length of the countdown stage is counted as L1; the communication deviation index XZ of the driving area is calculated using the formula XZ = u × (P1 × a1) / (L1 × a2), wherein a1 and a2 are both preset coefficient factors, and u is a preset compensation coefficient;

[0052] The communication deviation index XZ is compared with a preset deviation threshold; if the communication deviation index XZ is greater than or equal to the preset deviation threshold, it indicates that the current network condition is very poor, and the vehicle controller saves the driving monitoring data in the local database without uploading the data; thereby reducing the occupation of the driving monitoring data on the network bandwidth; wherein the local database is an SD card of the vehicle controller;

[0053] If the communication deviation index XZ is less than the preset deviation threshold, it indicates that the current network condition is good, and the vehicle controller uploads the driving monitoring data to the management center through the data transmission module, so that the management personnel can remotely obtain the video pictures inside and outside the vehicle in real time, and the vehicle state during driving and parking can be visually supervised;

[0054] The vehicle evaluation module is connected to the management center, and is used to obtain the driving time series data of the vehicle to evaluate the driving loss coefficient CS, and the specific evaluation steps are as follows:

[0055] S1: The time interval is intercepted from the collected driving time series data, and the time interval includes data at multiple times, and each time data includes data of multiple fields; the fields include current, driving wheel speed, vehicle speed and acceleration;

[0056] S2: Determine whether the vehicle has stopped in the time interval, that is, determine whether the value of the vehicle speed field appears 0 in the time interval; if it appears, the first time when the value of the vehicle speed field is 0 is determined as the parking time;

[0057] S3: Determine whether this parking is due to emergency braking of the vehicle, and the specific process is as follows:

[0058] S31: re-intercepting a new time interval including the parking time and data of a plurality of time points adjacent to the parking time from the time sequence data;

[0059] S32: obtaining a real-time current value flowing through the vehicle driving motor based on the value of the current field of each time point in the new time interval; and establishing a curve of the real-time current value changing with time;

[0060] According to the change of the real-time current value, the real-time current value changing with time curve is divided into an ascending stage and a descending stage; and the real-time current change derivative values of the curve equation in the ascending stage and the descending stage are calculated respectively;

[0061] S33: when the real-time current value is in the ascending stage, if the real-time current change derivative values of the vehicle are all greater than a preset threshold value within a first preset time T1, it is indicated that a suspected emergency braking is triggered, and step S34 is entered;

[0062] S34: after the real-time current value rises to a maximum value, if the real-time current value drops to 0 and the real-time current change derivative values are all greater than the preset threshold value within a second preset time T2, it is confirmed that an emergency braking occurs;

[0063] S4: obtaining a driving time period of the vehicle according to the driving time sequence data; and in the driving time period, the number of emergency brakings of the vehicle is counted as Z1, and the driving time length of the vehicle is counted as Tz;

[0064] The maximum value of the real-time current value of the driving motor is marked as Lt, the maximum value of the driving wheel rotating speed is marked as Nt, the maximum value of the vehicle speed is marked as Vt, and the maximum value of the acceleration is marked as Gt;

[0065] The driving loss coefficient CS of the vehicle is calculated by using the formula CS=f×Z1×Tz×(Lt×b3+Nt×b4+Vt×b5+Gt×b6), wherein b3, b4, b5 and b6 are preset coefficient factors, and f is a preset compensation coefficient;

[0066] The driving loss coefficient CS is compared with a preset loss threshold value; if the driving loss coefficient CS is greater than the preset loss threshold value, a loss signal is generated to a management center; and the administrator is reminded to perform maintenance work on the vehicle, so as to realize the dynamic health management problem of the vehicle.

[0067] The above formulas are all dimensionless values, the formula is obtained by collecting a large amount of data and simulating software to obtain a formula closest to the real situation, and the preset parameters and the preset threshold value in the formula are set by the person skilled in the art according to the actual situation or obtained by a large amount of data simulation.

[0068] The working principle of the application is as follows:

[0069] A vehicle monitoring system based on a VIN vehicle terminal, in operation, a driving monitoring module includes vehicle sensors distributed around the vehicle for real-time acquisition of driving time series data; a video monitoring module includes cameras distributed inside and outside the vehicle for acquiring video information inside and outside the vehicle; a vehicle controller is used to integrate the received driving time series data and video information to obtain driving monitoring data; a signal monitoring module is connected with the vehicle controller for monitoring the communication condition of the driving area to determine whether to upload the driving monitoring data; if the communication deviation index XZ is greater than or equal to a preset deviation threshold, it indicates that the current network condition is very poor, and the vehicle controller saves the driving monitoring data in the local database without data uploading; thereby reducing the occupation of network bandwidth by the driving monitoring data; if the communication deviation index XZ is less than the preset deviation threshold, it indicates that the current network condition is good, and the vehicle controller uploads the driving monitoring data to the management center through a data transmission module, so that the management personnel can remotely obtain the video pictures inside and outside the vehicle in real time, and the vehicle state during driving and after parking can be visually supervised;

[0070] A vehicle evaluation module is connected with the management center for acquiring the driving time series data of the vehicle to evaluate the driving loss coefficient CS; first, the time interval is intercepted from the acquired driving time series data to determine whether the vehicle has stopped in the time interval; then, whether the stop is due to emergency braking of the vehicle is determined based on the curve of the real-time current value changing with time; the driving loss coefficient CS of the vehicle is calculated in combination with the number of emergency braking of the vehicle, the driving time and each driving time series parameter; if the driving loss coefficient CS is greater than a preset loss threshold, a loss signal is generated to the management center to remind the administrator to maintain the vehicle, and the dynamic health management of the vehicle is realized.

[0071] In the description of the present specification, the description of the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are contained in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0072] The preferred embodiments of the application disclosed above are only to facilitate the elucidation of the application. The preferred embodiments do not describe all the details of the application and limit the application to the specific embodiments. Obviously, many modifications and variations can be made in light of the teachings above. The description is chosen and described in order to provide the best illustration of the application and its practical application to those skilled in the art and to enable those skilled in the art to best utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. A vehicle monitoring system based on a VIN on-board terminal, characterized in that, The driving monitoring module, the video monitoring module, the signal monitoring module, the management center and the vehicle evaluation module are included. The driving monitoring module includes distributed vehicle-mounted sensors arranged around the vehicle, which are used to collect driving time series data in real time and upload the collected driving time series data to the vehicle-mounted controller. The video monitoring module includes cameras distributed inside and outside the vehicle, which are used to collect video information inside and outside the vehicle and upload the collected video information to the vehicle-mounted controller. The signal monitoring module is connected with the vehicle-mounted controller, which is used to monitor the communication condition of the driving area and calculate the communication deviation index XZ to determine whether to upload the driving monitoring data. The vehicle-mounted controller establishes a communication connection with the base station group and periodically sends a measurement configuration message to the base station group at a preset interval, wherein the measurement configuration message includes a first signal quality threshold. In response to receiving the measurement configuration message, each base station immediately sends a second synchronization signal to the vehicle-mounted controller. After receiving the second synchronization signal, the vehicle-mounted controller determines the signal quality of the second synchronization signal and compares it with the first signal quality threshold to obtain the first quality difference CA. Compare the first quality difference CA with the set value; if the first quality difference CA is greater than the set value, it indicates that the signal attenuation is serious, and an unqualified signal is generated. When an unqualified signal is monitored, automatic countdown is performed, and the countdown is D1, which is a preset value; wherein each time the measurement configuration message is sent, the countdown is reduced by one. Continue to monitor the unqualified signal in the countdown stage, if a new unqualified signal is monitored, the countdown is automatically reset to the original value, and the countdown is restarted according to D1; otherwise, continue to count down. The number of occurrences of unqualified signals in the countdown stage is P1, and the length of the countdown stage is L1. The communication deviation index XZ of the driving area is calculated by the formula XZ = u × (P1 × a1) / (L1 × a2), wherein a1 and a2 are preset coefficient factors, and u is a preset compensation coefficient. If the communication deviation index XZ is greater than or equal to the preset deviation threshold, it indicates that the current network condition is very poor, and the vehicle-mounted controller saves the driving monitoring data in the local database without uploading the data. If the communication deviation index XZ is less than the preset deviation threshold, it indicates that the current network condition is good, and the vehicle-mounted controller uploads the driving monitoring data to the management center through the data transmission module. The vehicle evaluation module is connected with the management center, which is used to obtain the driving time series data of the vehicle to evaluate the driving loss coefficient CS, and the specific evaluation steps are as follows: S1: Extract the time interval from the collected driving time series data; S2: Determine whether the vehicle has stopped in the time interval; S3: Determine whether this stop is due to emergency braking of the vehicle; specifically including: S31: Re-intercepting a new time interval including the parking time and data of a plurality of time points adjacent to the parking time from the time sequence data; S32: Obtaining real-time current values flowing through the vehicle driving motor based on the values of the current field of each time point in the new time interval; and establishing a curve of the real-time current values changing with time; According to the change of the real-time current values, the curve of the real-time current values changing with time is divided into an ascending stage and a descending stage; and the real-time current change derivative values of the curve equation in the ascending stage and the descending stage are calculated respectively; S33: When the real-time current values are in the ascending stage, if the real-time current change derivative values of the vehicle are all greater than a preset threshold value within a first preset time T1, it is indicated that a suspected emergency braking is triggered, and step S34 is entered; S34: When the real-time current values rise to a maximum value, if the real-time current values drop to 0 and the real-time current change derivative values are all greater than the preset threshold value within a second preset time T2, it is confirmed that an emergency braking occurs; S4: The driving time period of the vehicle is obtained by analyzing the driving time sequence data; and the driving loss coefficient CS of the vehicle is calculated in combination with the spatio-temporal variation of the emergency braking of the vehicle; and the specific calculation method is: In the driving time period, the number of emergency braking of the vehicle is counted as Z1, and the driving time of the vehicle is counted as Tz; the maximum value of the real-time current value of the driving motor is marked as Lt, the maximum value of the driving wheel speed is marked as Nt, the maximum value of the vehicle speed is marked as Vt, and the maximum value of the acceleration is marked as Gt; The driving loss coefficient CS of the vehicle is calculated by using the formula CS=ƒ×Z1×Tz×(Lt×b3+Nt×b4+Vt×b5+Gt×b6), wherein b3, b4, b5, and b6 are preset coefficient factors, and ƒ is a preset compensation coefficient; If the driving loss coefficient CS is greater than a preset loss threshold value, a loss signal is generated to the management center to remind the administrator to perform maintenance work on the vehicle.

2. The vehicle monitoring system based on the VIN vehicle terminal according to claim 1, characterized in that, In step S1, the data in the time interval includes a plurality of time points, and the data of each time point includes data of a plurality of fields; the fields include current, driving wheel speed, vehicle speed, and acceleration.

3. The vehicle monitoring system based on the VIN vehicle terminal according to claim 2, characterized in that, In step S2, it is determined whether the vehicle has stopped in the time interval, specifically: It is determined whether the value of the vehicle speed field appears 0 in the time interval; if it appears, the first time point with the value of 0 of the vehicle speed field is determined as the parking time.

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