Internet of vehicles data relay transmission method and system

Abstract

The invention relates to the technical field of vehicle-mounted data acquisition, and particularly discloses a vehicle networking data relay transmission method and system, and the method comprises the steps: obtaining vehicle operation data based on a vehicle-mounted terminal, and obtaining a data array at each moment; the method comprises the following steps: acquiring data arrays of all vehicles in the same road section in real time based on a fixed transfer terminal, and arranging the data arrays of each vehicle according to a time sequence to obtain an array sequence of each vehicle; when the vehicle abnormity degree of any vehicle reaches a preset abnormity degree threshold value, reading the array sequence, generating early warning information according to the array sequence, and feeding back the early warning information to the vehicle-mounted terminal; and when the vehicle anomaly of any vehicle is smaller than a preset anomaly threshold and the vehicle position is not included in the road section, packaging the array sequence, encrypting and forwarding the array sequence to the data center. According to the invention, the transfer ends are installed in different road sections, and the transfer ends acquire the vehicle driving data on the road sections, so that for vehicles, the data transmission distance is shortened, the transmission pressure is reduced, and the working pressure of the vehicle machine system is relieved.

Description

Technical Field

[0001] The present invention relates to the technical field of on-vehicle data acquisition, and specifically to a method and system for relaying and transmitting vehicle networking data. Background Art

[0002] During the driving process of a vehicle, data is very important. This data can be used for developing autonomous driving technologies and generating warning messages, thereby improving the traffic safety level. However, the data acquisition process in the prior art is very troublesome. For a vehicle, the in-vehicle system is only an auxiliary part with a small cost ratio. Although the in-vehicle systems in the prior art are becoming more and more advanced, they still do not have high performance in ordinary vehicles. If it is required to feedback operation data for a long time, the working pressure of the in-vehicle system is extremely high, which may affect the driving process. Therefore, how to provide a simpler vehicle driving data acquisition solution is the technical problem that the technical solution of the present invention wants to solve. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for relaying and transmitting vehicle networking data to solve the problems raised in the above background art.

[0004] To achieve the above purpose, the present invention provides the following technical solutions:

[0005] A method and system for relaying and transmitting vehicle networking data, the method comprising:

[0006] Statistical analysis of all vehicle data metrics to construct a metric array, and broadcasting the metric array to authorized in-vehicle terminals;

[0007] Based on the in-vehicle terminal, obtaining vehicle operation data to obtain a data array for each moment; the data array is generated based on the metric array;

[0008] Based on a fixed relay terminal, real-time acquisition of the data arrays of all vehicles in the same road section, arranging the data arrays of each vehicle according to the time sequence to obtain an array sequence for each vehicle;

[0009] Identifying the array sequence of each vehicle to determine the vehicle abnormality degree, querying the position of the vehicle, and obtaining the abnormality degree threshold at that position;

[0010] When the vehicle abnormality degree of any vehicle reaches the preset abnormality degree threshold, reading the array sequence, generating a warning message according to the array sequence, feeding it back to the in-vehicle terminal, and synchronously correcting the abnormality degree threshold within a preset area centered on the vehicle;

[0011] When the vehicle abnormality degree of any vehicle is less than the preset abnormality degree threshold and the vehicle position is not included in the road section, packing the array sequence, encrypting and forwarding it to the data center.

[0012] As a further solution of the present invention, the steps of statistically analyzing the data indicators of all vehicles, constructing an indicator array, and broadcasting the indicator array to the authorized vehicle-mounted terminals include:

[0013] Obtain the average sales volume and sensor type of each model of vehicle, and determine the data indicators according to the sensor type;

[0014] For each data indicator, calculate the sum of the average sales volumes of the vehicles corresponding to the data indicator, and determine the indicator popularity; the indicator popularity is directly proportional to the sum of the average sales volumes;

[0015] Determine the order of each data indicator according to the indicator popularity, and construct an indicator array;

[0016] Broadcast the indicator array to all vehicle-mounted terminals in the road section.

[0017] As a further solution of the present invention, the steps of identifying the array sequence of each vehicle, determining the vehicle abnormality degree, querying the position of the vehicle, and obtaining the abnormality degree threshold at the position include:

[0018] Read the array sequence of each vehicle, and calculate the difference sequence of the array sequence;

[0019] Input the array sequence and the difference sequence into the trained abnormality recognition model, and output the vehicle abnormality degree;

[0020] Query the position of the vehicle, obtain the corrected abnormality degree threshold of all other vehicles at the position at the current moment, and determine the abnormality degree threshold at the position;

[0021] Wherein, the number of difference sequences is at least one, the difference calculation step size of each difference sequence is a preset value, and when another data is missing at a certain position during the difference calculation process, the difference at the position is set to a preset default value.

[0022] As a further solution of the present invention, the steps of, when the vehicle abnormality degree of any vehicle reaches the preset abnormality degree threshold, reading the array sequence, generating a warning message according to the array sequence, feeding it back to the vehicle-mounted terminal, and synchronously correcting the abnormality degree threshold within a preset area centered on the vehicle include:

[0023] For any vehicle, read its vehicle abnormality degree and the abnormality degree threshold at its current position;

[0024] Compare the vehicle abnormality degree with the abnormality degree threshold. When the vehicle abnormality degree reaches the abnormality degree threshold, read the array sequence of the vehicle;

[0025] Input the array sequence into the trained warning message generation model, generate a warning message, and feed it back to the vehicle-mounted terminal;

[0026] Taking the current position of the vehicle as the center, determine the anomaly threshold for each position within the preset area based on the vehicle anomaly degree, and use it as the anomaly threshold for the vehicle at that position at that moment.

[0027] As a further solution of the present invention: the step of packing the array sequence and encrypting and forwarding it to the data center when the vehicle anomaly degree of any vehicle is less than the preset anomaly threshold and the vehicle position is not included in the road section includes:

[0028] For any vehicle, read the vehicle anomaly degree at each position in the road section;

[0029] When the vehicle anomaly degree at each position is less than the preset anomaly threshold, determine the entry time and exit time of the vehicle relative to the road section;

[0030] Read the array sequence of the entry time and exit time;

[0031] Encrypt the read array sequence and forward the encrypted array sequence to the data center.

[0032] As a further solution of the present invention: the method further includes:

[0033] Real-time statistics of the anomaly threshold at each position in the road section, constructing a threshold matrix for each moment; the row and column positions in the threshold matrix correspond to the positions in the road section, and the values at the row and column positions correspond to the statistically obtained anomaly thresholds;

[0034] Calculate the urgency at each position according to the threshold matrix at each moment; the urgency is inversely proportional to the anomaly threshold and directly proportional to the change rate of the anomaly threshold;

[0035] Partition the positions according to the urgency and generate control instructions for the mobile relay terminal.

[0036] The technical solution of the present invention also provides a vehicle networking data relay transmission system, and the system includes:

[0037] An index broadcast module, used to count the data indexes of all vehicles, construct an index array, and broadcast the index array to the authorized in-vehicle terminals;

[0038] A data acquisition module, used to obtain vehicle operation data based on the in-vehicle terminal to obtain a data array for each moment; the data array is generated based on the index array;

[0039] An array sequence generation module, used to obtain the data arrays of all vehicles in the same road section in real time based on the fixed relay terminal, arrange the data arrays of each vehicle according to the time sequence, and obtain the array sequence of each vehicle;

[0040] An array sequence recognition module, which is used to recognize the array sequence of each vehicle, determine the vehicle abnormality degree, query the position of the vehicle, and obtain the abnormality degree threshold at this position;

[0041] An early warning information generation module, which is used to read the array sequence when the vehicle abnormality degree of any vehicle reaches the preset abnormality degree threshold, generate early warning information according to the array sequence, feedback it to the in-vehicle terminal, and synchronously correct the abnormality degree threshold within the preset area centered on this vehicle;

[0042] A data forwarding module, which is used to pack the array sequence and encrypt and forward it to the data center when the vehicle abnormality degree of any vehicle is less than the preset abnormality degree threshold and the vehicle position is not included in the road section.

[0043] As a further solution of the present invention: the index broadcasting module includes:

[0044] An index query unit, which is used to obtain the average sales volume and sensor type of each model of vehicle, and determine the data index according to the sensor type;

[0045] A prevalence determination unit, which is used to calculate the sum of the average sales volumes of the vehicles corresponding to each data index for each data index, and determine the index prevalence; the index prevalence is proportional to the sum of the average sales volumes;

[0046] An order determination unit, which is used to determine the order of each data index according to the index prevalence and construct an index array;

[0047] An array sending unit, which is used to broadcast the index array to all in-vehicle terminals in the road section.

[0048] As a further solution of the present invention: the array sequence recognition module includes:

[0049] A preprocessing unit, which is used to read the array sequence of each vehicle and calculate the difference sequence of the array sequence;

[0050] An abnormality degree output unit, which is used to input the array sequence and the difference sequence into the trained abnormality recognition model and output the vehicle abnormality degree;

[0051] A threshold query unit, which is used to query the position of the vehicle, obtain the corrected abnormality degree threshold of all other vehicles at this position at the current moment, and determine the abnormality degree threshold at this position;

[0052] Among them, the number of difference sequences is at least one, the difference calculation step length of each difference sequence is a preset value, and when another data is missing at a certain position during the difference calculation process, the difference at this position is set to a preset default value.

[0053] As a further solution of the present invention: the early warning information generation module includes:

[0054] A threshold reading unit, configured to read, for any vehicle, the vehicle abnormality degree and the abnormality degree threshold of its current position;

[0055] A comparison unit, configured to compare the vehicle abnormality degree with the abnormality degree threshold, and when the vehicle abnormality degree reaches the abnormality degree threshold, read the array sequence of the vehicle;

[0056] A feedback unit, configured to input the array sequence into a trained early warning information generation model to generate early warning information and feedback it to the in-vehicle terminal;

[0057] A threshold updating unit, configured to determine, with the current position of the vehicle as the center, the abnormality degree thresholds of each position within a preset area based on the vehicle abnormality degree, and use them as the abnormality degree threshold of the vehicle at this position at this moment.

[0058] Compared with the prior art, the beneficial effects of the present invention are:

[0059] In the present invention, relay terminals are installed section by section, and the relay terminals obtain the vehicle driving data on the sections. For vehicles, the data transmission distance is shortened and the transmission pressure is reduced, thereby alleviating the working pressure of the vehicle-mounted system. At the same time, an identification module is built in the relay terminal to identify the vehicle driving data, and the feedback efficiency of the identification result is extremely high. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0061] Figure 1 Shows the overall flowchart of the vehicle networking data relay transmission method.

[0062] Figure 2 Shows the structure diagram of the vehicle networking data relay transmission system. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0063] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the following further describes the present invention in detail with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0064] Figure 1 Shows the overall flowchart of the vehicle networking data relay transmission method. In an embodiment of the present invention, a vehicle networking data relay transmission method includes:

[0065] Step S100: Statistically analyze the data indicators of all vehicles, construct an index array, and broadcast the index array to the authorized in-vehicle terminals;

[0066] The data of the Internet of Vehicles is the data generated during the operation of vehicles. There are many types of these data, and specifically which data needs to be obtained is determined in advance by the management party, such as tire pressure, vehicle speed, and distance to adjacent vehicles, etc. The data types of the obtained data are the data indicators in the above content. Statistically collect the data indicators that need to be obtained for all vehicles, construct an indicator array, and broadcast the indicator array to the authorized in-vehicle terminals.

[0067] It should be noted that the number and types of sensors installed on different vehicles are different. Therefore, it is necessary to consider the data indicators of all vehicles (regular vehicles that have been put into use). The total number of data indicators is limited. In actual applications, selections will also be made. Therefore, its quantity is not large, that is, the total number of elements in the indicator array is not large. In addition, the present invention is generally applied to each road section to obtain vehicle data on the road section. It is necessary to have the explicit authorization of the vehicle party to obtain its data, and the present invention is aimed at the data transfer process and by default already has the data acquisition permission.

[0068] Step S200: Based on the in-vehicle terminal, obtain the vehicle operation data to obtain a data array at each moment; the data array is generated based on the indicator array;

[0069] Based on the in-vehicle terminal, obtain the data generated during the vehicle operation process and fill it into the indicator array to obtain a data array at each moment. In fact, while obtaining the data array at each moment, the position of the vehicle can also be recorded. At this time, the data array represents the operation state of the vehicle at which moment and at which position.

[0070] Step S300: Based on the fixed transfer terminal, real-time obtain the data arrays of all vehicles in the same road section, and for the data array of each vehicle, arrange it according to the time sequence to obtain an array sequence for each vehicle;

[0071] Based on the fixed transfer terminal installed on the road section, real-time obtain the data arrays of all vehicles in the same road section, and arrange the data arrays of the same vehicle according to the time sequence to obtain an array sequence.

[0072] The fixed transfer terminal is an electronic device with data transceiver function and data processing function, which is used to serve a certain road section.

[0073] Step S400: Identify the array sequence of each vehicle, determine the vehicle abnormality degree, query the position of the vehicle, and obtain the abnormality degree threshold at this position;

[0074] The array sequence of each vehicle reflects the vehicle's state during this period. By identifying the array sequence, it can be determined whether the vehicle has any abnormalities, which is represented by the parameter of vehicle abnormality degree. At the same time, the current position of the vehicle is read, and the abnormality degree threshold at the current position is queried. The difference of the present invention is that the abnormality degree threshold is dynamic and jointly determined by the abnormal detection results of all vehicles. In practical applications, once a vehicle has a problem, it is possible that the surrounding vehicles also have problems. Therefore, a vehicle with a relatively high abnormality degree will cause the abnormality degree threshold of the surrounding positions to decrease, making the surrounding vehicles more likely to be determined as abnormal vehicles and thus receive warning messages.

[0075] Step S500: When the vehicle abnormality degree of any vehicle reaches the preset abnormality degree threshold, read the array sequence, generate a warning message according to the array sequence, feedback it to the in-vehicle terminal, and synchronously correct the abnormality degree threshold within the preset area centered on this vehicle;

[0076] When a certain vehicle is driving on this section of the road and the vehicle abnormality degree reaches the preset abnormality degree threshold, read the array sequence of this vehicle (the array within the existing time), generate a warning message according to the array sequence, feedback it to the in-vehicle terminal, and synchronously correct the abnormality degree threshold within the preset area centered on this vehicle.

[0077] Step S600: When the vehicle abnormality degree of any vehicle is less than the preset abnormality degree threshold and the vehicle position is not included in the road section, pack the array sequence, encrypt it and forward it to the data center;

[0078] When a certain vehicle is driving on this section of the road and the vehicle abnormality degree has been at a relatively small value and the vehicle position is not included in the road section, it means that the vehicle has left this section of the road. At this time, the array sequence represents all the data during the driving process, and these data have no abnormalities. Just forward them to the data center for retention; since the vehicle data is relatively important, it can be encrypted first and then forwarded when forwarding.

[0079] Regarding step S100, the steps of statistically analyzing the data indicators of all vehicles, constructing an indicator array, and broadcasting the indicator array to the authorized in-vehicle terminals include:

[0080] Obtain the average sales volume and sensor type of each model of vehicle, and determine the data indicators according to the sensor type;

[0081] For each data indicator, calculate the sum of the average sales volumes of the vehicles corresponding to this data indicator, and determine the indicator prevalence; the indicator prevalence is directly proportional to the sum of the average sales volumes;

[0082] Determine the order of each data indicator according to the indicator prevalence, and construct an indicator array;

[0083] Broadcast the index array to all vehicle-mounted devices in the road section.

[0084] The model of the vehicle is known and can be queried on public websites. Obtain the average sales volume and sensor type of each model of vehicle, determine the data index according to the sensor type. For each data index, calculate in which vehicles this data index appears, query the average sales volume of these vehicles, calculate the sum of the average sales volumes, and then determine the index prevalence. The larger the sum of the average sales volumes, the greater the index prevalence; determine the order of each data index according to the index prevalence, construct an index array. The greater the index prevalence, the smaller its order and the more forward it is in the index array. Broadcast the index array to all vehicle-mounted devices in the road section.

[0085] It should be noted that regarding the average sales volume, the average sales volume generally refers to the average sales volume of the previous year. There is actually a certain correlation between the average sales volume and the quantity. Although this relationship is not rigid, for a vehicle with an average sales volume of 1 million vehicles, its quantity is definitely more than that of a vehicle with an average sales volume of 10 vehicles. Of course, the average sales volume can also be limited to a certain city to represent the quantity of vehicle types that may appear on the road section, calculate the sum of the average sales volumes of the vehicles corresponding to this data index, and determine the index prevalence. The average sales volume

[0086] Regarding step S400, the steps of identifying the array sequence of each vehicle, determining the vehicle abnormality degree, querying the position of the vehicle, and obtaining the abnormality threshold at this position include:

[0087] Read the array sequence of each vehicle and calculate the difference sequence of the array sequence;

[0088] Input the array sequence and the difference sequence into the trained anomaly recognition model to output the vehicle abnormality degree;

[0089] Query the position of the vehicle, obtain the corrected abnormality threshold of all other vehicles at this position at the current moment, and determine the abnormality threshold at this position;

[0090] Among them, the number of difference sequences is at least one, and the difference calculation step size of each difference sequence is a preset value. When another data is missing at a certain position during the difference calculation process, set the difference at this position to a preset default value.

[0091] Read the array sequence of each vehicle, calculate the difference sequence of the array sequence. The simplest difference sequence is to subtract each array from the previous array. The subtraction is performed on the values of each element to obtain a difference array, and then arrange the difference array to get the difference sequence. The array sequence reflects the actual data of the vehicle, and the difference sequence reflects the change of the actual data of the vehicle. Train an anomaly recognition model with these two parameters, output the vehicle anomaly degree, query the position of the vehicle, obtain the corrected anomaly degree threshold of all other vehicles at this position at the current moment, and determine the anomaly degree threshold at this position.

[0092] It should be noted that regarding the difference sequence, when calculating the difference, the distance between arrays is the difference calculation step. For example, when subtracting an array from the previous array, the difference calculation step is one. When subtracting an array from the array at the previous two positions, the difference calculation step is two. During the calculation process, there may be no arrays before the first few arrays at the front, and the difference cannot be calculated. In this case, set it to the default value.

[0093] Regarding the anomaly recognition model, it can adopt existing recognition algorithms, or it can first count the array sequence and the difference sequence, and then the staff determines the recognition result and constructs a sample. The features of the sample are the array sequence and the difference sequence, and the label is the recognition result. Then train a neural network model, and when the error rate is small enough, it is used as the anomaly recognition model.

[0094] Regarding step S500, the step of reading the array sequence, generating a warning message according to the array sequence, feeding it back to the in-vehicle terminal, and synchronously correcting the anomaly degree threshold within a preset area centered on this vehicle when the vehicle anomaly degree of any vehicle reaches the preset anomaly degree threshold includes:

[0095] For any vehicle, read its vehicle anomaly degree and the anomaly degree threshold at its current position;

[0096] Compare the vehicle anomaly degree with the anomaly degree threshold. When the vehicle anomaly degree reaches the anomaly degree threshold, read the array sequence of the vehicle;

[0097] Input the array sequence into the trained warning message generation model to generate a warning message and feed it back to the in-vehicle terminal;

[0098] Based on the vehicle anomaly degree, determine the anomaly degree threshold of each position within the preset area centered on the current position of the vehicle as the anomaly degree threshold of this vehicle at this position at this moment.

[0099] For a certain vehicle, it has a position at each moment. Read the vehicle anomaly degree at its current moment in real time, and then read the anomaly degree threshold at its current position. When the vehicle anomaly degree reaches the anomaly degree threshold, read the array sequence of the vehicle, input the array sequence into the trained early warning information generation model to generate early warning information, and feedback it to the in-vehicle terminal; meanwhile, with the current position of the vehicle as the center, determine the anomaly degree thresholds of each position within the preset area based on the vehicle anomaly degree, and use them as the anomaly degree thresholds of the vehicle at this position at this moment.

[0100] Among them, the early warning information generation model is generally a data query model. First, construct a data table, and the early warning information can be matched in the table by the array sequence.

[0101] Regarding the process of determining the anomaly degree thresholds of each position within the preset area based on the vehicle anomaly degree and using them as the anomaly degree thresholds of the vehicle at this position at this moment, the anomaly degree thresholds of each position are inversely proportional to the vehicle anomaly degree and directly proportional to the distance between this position and the vehicle position. This means that the higher the vehicle anomaly degree, the greater the impact on the surrounding area, and the lower the anomaly degree thresholds of the surrounding area. However, the impact on farther places is smaller, and the anomaly degree thresholds of farther positions are higher. The lower the anomaly degree threshold, the easier it is to trigger early warning information.

[0102] In addition, actually each position is affected by multiple vehicles. Each vehicle has an anomaly degree threshold for a certain position at a certain moment. For a position, there are multiple anomaly degree thresholds, and the minimum value can be selected.

[0103] Regarding step S600, the step of packing the array sequence and encrypting and forwarding it to the data center when the vehicle anomaly degree of any vehicle is less than the preset anomaly degree threshold and the vehicle position is not included in the road section includes:

[0104] For any vehicle, read the vehicle anomaly degree at each position of the vehicle in the road section;

[0105] When the vehicle anomaly degrees at each position are all less than the preset anomaly degree threshold, determine the driving-in moment and driving-out moment of the vehicle relative to the road section;

[0106] Read the array sequences of the driving-in moment and driving-out moment;

[0107] Encrypt the read array sequences and forward the encrypted array sequences to the data center.

[0108] If, during the driving process of a vehicle on a road section, the abnormality degrees of all positions of the vehicle are small enough, it indicates that the vehicle is a safe vehicle. At this time, determine the entry time and exit time of the vehicle relative to the road section, and read the array sequence of the entry time and exit time (in fact, data recording starts when entering the road section and stops when leaving the road section, and the existing array sequence of the vehicle can be directly read). Encrypt the read array sequence and forward the encrypted array sequence to the data center.

[0109] As a preferred embodiment of the technical solution of the present invention, the method further includes:

[0110] Real-time statistics of the abnormality threshold of each position in the road section, and construction of a threshold matrix for each moment; the row and column positions in the threshold matrix correspond to the positions in the road section, and the values at the row and column positions correspond to the statistically obtained abnormality thresholds;

[0111] Calculate the urgency of each position according to the threshold matrix of each moment; the urgency is inversely proportional to the abnormality threshold and directly proportional to the change rate of the abnormality threshold;

[0112] Partition the positions according to the urgency and generate a control instruction pointing to the mobile relay terminal.

[0113] In an example of the technical solution of the present invention, real-time statistics of the abnormality threshold of each position in the road section, construction of a threshold matrix for each moment. The threshold matrix corresponds to the road section, indicating the abnormal conditions of each position in the road section. The abnormality threshold is dynamic, so there is a threshold matrix for each moment. Calculate the urgency of each position according to the threshold matrix of each moment, partition the positions according to the urgency, and generate a control instruction pointing to the mobile relay terminal.

[0114] Among them, the process of calculating the urgency of each position according to the threshold matrix of each moment is not complicated. An easier way is:

[0115] Calculate the change rate of the abnormality threshold of each position, and input the change rate and the abnormality threshold into a preset urgency calculation function; the urgency calculation function is a decreasing function of the abnormality threshold and an increasing function of the change rate; the decreasing function can use an inverse proportional function, and the increasing function can use a linear function. Combine the two to obtain the urgency calculation function.

[0116] After the urgency calculation is completed, calculate the difference in urgency between adjacent positions, and then partition all positions in the road section, calculate the average urgency of each area. When the average urgency reaches a preset average threshold, generate a control instruction pointing to the mobile relay terminal to control the mobile relay terminal to reach this area; the mobile relay terminal is a part of the fixed relay terminal, with the same function, only with an additional mobile function, used for closer data collection in dangerous areas.

[0117] Figure 2 The structure diagram of the vehicle networking data relay transmission system is shown. In a preferred embodiment of the technical solution of the present invention, a vehicle networking data relay transmission system is further provided. The system 10 includes:

[0118] An index broadcasting module 11, configured to count the data indexes of all vehicles, construct an index array, and broadcast the index array to the authorized in-vehicle terminals;

[0119] A data acquisition module 12, configured to obtain vehicle operation data based on the in-vehicle terminal to obtain a data array at each moment; the data array is generated based on the index array;

[0120] An array sequence generation module 13, configured to obtain the data arrays of all vehicles in the same road section in real time based on a fixed relay terminal, arrange the data arrays of each vehicle according to the time sequence to obtain an array sequence of each vehicle;

[0121] An array sequence recognition module 14, configured to recognize the array sequence of each vehicle, determine the vehicle abnormality degree, query the position of the vehicle, and obtain the abnormality degree threshold at that position;

[0122] An early warning information generation module 15, configured to, when the vehicle abnormality degree of any vehicle reaches a preset abnormality degree threshold, read the array sequence, generate early warning information according to the array sequence, feedback it to the in-vehicle terminal, and synchronously correct the abnormality degree threshold within a preset area centered on the vehicle;

[0123] A data forwarding module 16, configured to, when the vehicle abnormality degree of any vehicle is less than the preset abnormality degree threshold and the vehicle position is not included in the road section, package the array sequence and encrypt and forward it to the data center.

[0124] Furthermore, the index broadcasting module 11 includes:

[0125] An index query unit, configured to obtain the average sales volume and sensor type of each model of vehicle, and determine the data index according to the sensor type;

[0126] A prevalence determination unit, configured to calculate the sum of the average sales volumes of the vehicles corresponding to each data index for each data index, and determine the index prevalence; the index prevalence is proportional to the sum of the average sales volumes;

[0127] An order determination unit, configured to determine the order of each data index according to the index prevalence and construct an index array;

[0128] An array sending unit, configured to broadcast the index array to all in-vehicle terminals in the road section.

[0129] Specifically, the array sequence recognition module 14 includes:

[0130] A preprocessing unit for reading an array sequence of each vehicle and calculating a difference sequence of the array sequence;

[0131] An abnormality degree output unit for inputting the array sequence and the difference sequence into a trained abnormality recognition model and outputting a vehicle abnormality degree;

[0132] A threshold query unit for querying the position of a vehicle, obtaining a corrected abnormality degree threshold of all other vehicles at this position at the current moment, and determining the abnormality degree threshold at this position;

[0133] Wherein, the number of difference sequences is at least one, the difference calculation step size of each difference sequence is a preset value, and when another data is missing at a certain position during the difference calculation process, the difference at this position is set to a preset default value.

[0134] Furthermore, the warning information generation module 15 includes:

[0135] A threshold reading unit for, for any vehicle, reading its vehicle abnormality degree and the abnormality degree threshold at its current position;

[0136] A comparison unit for comparing the vehicle abnormality degree and the abnormality degree threshold, and when the vehicle abnormality degree reaches the abnormality degree threshold, reading the array sequence of the vehicle;

[0137] A feedback unit for inputting the array sequence into a trained warning information generation model, generating warning information, and feeding it back to the in-vehicle terminal;

[0138] A threshold updating unit for, with the current position of the vehicle as the center, determining the abnormality degree thresholds of each position within a preset area based on the vehicle abnormality degree as the abnormality degree threshold of the vehicle at this position at this moment.

[0139] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A method for relaying and transmitting vehicle networking data, characterized in that, The method includes: Counting the data metrics of all vehicles, constructing a metrics array, and broadcasting the metrics array to authorized in-vehicle terminals; Based on the in-vehicle terminals, obtaining the vehicle operation data to obtain a data array for each moment; the data array is generated based on the metrics array; Based on a fixed relay terminal, obtaining in real time the data arrays of all vehicles on the same road section, arranging the data arrays of each vehicle in chronological order to obtain an array sequence for each vehicle; Identifying the array sequence of each vehicle, determining the vehicle anomaly degree, querying the position of the vehicle, and obtaining the anomaly degree threshold at that position; When the vehicle anomaly degree of any vehicle reaches the preset anomaly degree threshold, reading the array sequence, generating a warning message according to the array sequence, feeding it back to the in-vehicle terminal, and synchronously correcting the anomaly degree threshold within a preset area centered on this vehicle; When the vehicle anomaly degree of any vehicle is less than the preset anomaly degree threshold and the vehicle position is not included in the road section, packing the array sequence and encrypting and forwarding it to the data center.

2. The vehicle networking data relay transmission method according to claim 1, wherein The steps of counting the data metrics of all vehicles, constructing a metrics array, and broadcasting the metrics array to authorized in-vehicle terminals include: Obtaining the average sales volume and sensor type of each model of vehicle, and determining the data metrics according to the sensor type; For each data metric, calculating the sum of the average sales volumes of the vehicles corresponding to this data metric to determine the metric prevalence; the metric prevalence is proportional to the sum of the average sales volumes; Determining the order of each data metric according to the metric prevalence, and constructing a metrics array; Broadcasting the metrics array to all in-vehicle terminals in the road section.

3. The vehicle networking data relay transmission method according to claim 1, wherein The steps of identifying the array sequence of each vehicle, determining the vehicle anomaly degree, querying the position of the vehicle, and obtaining the anomaly degree threshold at that position include: Reading the array sequence of each vehicle and calculating the difference sequence of the array sequence; Inputting the array sequence and the difference sequence into a trained anomaly recognition model to output the vehicle anomaly degree; Querying the position of the vehicle, obtaining the corrected anomaly degree threshold of all other vehicles at this position at the current moment, and determining the anomaly degree threshold at this position; Among them, the number of difference sequences is at least one, the difference calculation step size of each difference sequence is a preset value, and when another data is missing at a certain position during the difference calculation process, the difference at this position is set to a preset default value.

4. The vehicle networking data relay transmission method according to claim 1, characterized in that The steps of when the vehicle anomaly degree of any vehicle reaches the preset anomaly degree threshold, reading the array sequence, generating a warning message according to the array sequence, feeding it back to the in-vehicle terminal, and synchronously correcting the anomaly degree threshold within a preset area centered on this vehicle include: For any vehicle, reading its vehicle anomaly degree and the anomaly degree threshold at its current position; Comparing the vehicle anomaly degree with the anomaly degree threshold, and when the vehicle anomaly degree reaches the anomaly degree threshold, reading the array sequence of the vehicle; Inputting the array sequence into a trained warning message generation model to generate a warning message and feeding it back to the in-vehicle terminal; Centering on the current position of the vehicle, determining the anomaly degree thresholds of each position within the preset area based on the vehicle anomaly degree as the anomaly degree threshold of this vehicle at this position at this moment.

5. The vehicle networking data relay transmission method according to claim 1, wherein The step of packing the array sequence and encrypting and forwarding it to the data center when the vehicle abnormality degree of any vehicle is less than the preset abnormality degree threshold and the vehicle position is not included in the road section includes: For any vehicle, read the vehicle abnormality degree at each position of the vehicle in the road section; When the vehicle abnormality degrees at all positions are less than the preset abnormality degree threshold, determine the entry time and exit time of the vehicle relative to the road section; Read the array sequence at the entry time and exit time; Encrypt the read array sequence and forward the encrypted array sequence to the data center.

6. The method for relaying and transmitting vehicle networking data according to claim 1, wherein The method further includes: Real-time statistically calculate the abnormality degree threshold at each position in the road section and construct a threshold matrix for each moment; the row and column positions in the threshold matrix correspond to the positions in the road section, and the values at the row and column positions correspond to the statistically calculated abnormality degree thresholds; Calculate the urgency at each position according to the threshold matrix for each moment; the urgency is inversely proportional to the abnormality degree threshold and directly proportional to the change rate of the abnormality degree threshold; Partition the positions according to the urgency and generate a control instruction pointing to the mobile relay terminal.

7. A vehicle networking data relay and transmission system, characterized in that The system includes: An index broadcasting module for statistically calculating the data indexes of all vehicles, constructing an index array, and broadcasting the index array to the authorized in-vehicle terminals; A data acquisition module for obtaining vehicle operation data based on the in-vehicle terminals to obtain a data array for each moment; the data array is generated based on the index array; An array sequence generation module for real-time obtaining the data arrays of all vehicles in the same road section based on a fixed relay terminal, arranging the data arrays of each vehicle in chronological order to obtain an array sequence for each vehicle; An array sequence identification module for identifying the array sequence of each vehicle, determining the vehicle abnormality degree, querying the position of the vehicle, and obtaining the abnormality degree threshold at that position; An early warning information generation module for reading the array sequence when the vehicle abnormality degree of any vehicle reaches the preset abnormality degree threshold, generating early warning information according to the array sequence, feeding it back to the in-vehicle terminal, and synchronously correcting the abnormality degree threshold within a preset area centered on the vehicle; A data forwarding module for packing the array sequence, encrypting and forwarding it to the data center when the vehicle abnormality degree of any vehicle is less than the preset abnormality degree threshold and the vehicle position is not included in the road section.

8. The vehicle networking data relay and transmission system according to claim 7, wherein The index broadcasting module includes: An index query unit for obtaining the average sales volume and sensor type of each model of vehicle and determining the data index according to the sensor type; A prevalence determination unit for calculating the sum of the average sales volumes of the vehicles corresponding to each data index for each data index and determining the index prevalence; the index prevalence is directly proportional to the sum of the average sales volumes; An order determination unit for determining the order of each data index according to the index prevalence and constructing an index array; An array sending unit for broadcasting the index array to all in-vehicle terminals in the road section.

9. The vehicle networking data relay and transmission system according to claim 7, wherein The array sequence identification module includes: A preprocessing unit for reading the array sequence of each vehicle and calculating the difference sequence of the array sequence; An abnormality degree output unit for inputting the array sequence and the difference sequence into a trained abnormality identification model and outputting the vehicle abnormality degree; A threshold query unit, configured to query the position of a vehicle, obtain the corrected anomaly threshold of all other vehicles at this position at the current moment, and determine the anomaly threshold at this position; Wherein, the number of difference sequences is at least one, the difference calculation step size of each difference sequence is a preset value, and when another data is missing during the difference calculation at a certain position, the difference at this position is set to a preset default value.

10. The vehicle networking data relay and transmission system according to claim 7, characterized in that, The early warning information generation module includes: A threshold reading unit, configured to, for any vehicle, read its vehicle anomaly degree and the anomaly threshold of its current position; A comparison unit, configured to compare the vehicle anomaly degree with the anomaly threshold, and when the vehicle anomaly degree reaches the anomaly threshold, read the array sequence of the vehicle; A feedback unit, configured to input the array sequence into a trained early warning information generation model to generate early warning information and feedback it to the in-vehicle terminal; A threshold update unit, configured to, with the current position of the vehicle as the center, determine the anomaly thresholds of each position within a preset area based on the vehicle anomaly degree as the anomaly threshold of this vehicle at this position at this moment.

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