CN114205394A - Self-adaptive data identification and storage method and system for Internet of vehicles terminal - Google Patents
Self-adaptive data identification and storage method and system for Internet of vehicles terminal Download PDFInfo
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- CN114205394A CN114205394A CN202210144902.7A CN202210144902A CN114205394A CN 114205394 A CN114205394 A CN 114205394A CN 202210144902 A CN202210144902 A CN 202210144902A CN 114205394 A CN114205394 A CN 114205394A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/14—Session management
- H04L67/141—Setup of application sessions
Abstract
The invention is suitable for the field of computers, and provides a method and a system for recognizing and storing self-adaptive data of a vehicle networking terminal, wherein the method comprises the following steps: carrying out pre-recognition processing on the acquired road condition information and traffic jam data, and planning the driving information of the current vehicle in a subsequent road section according to the pre-recognition processing result, wherein the driving information at least comprises a driving route and a driving speed; judging whether the current vehicle is about to enter a dangerous road section within a preset distance according to the running information of the current vehicle, wherein the dangerous road section at least comprises a tunnel road section; if the current vehicle is about to enter the dangerous road section within the preset distance, the invention has the beneficial effects that: through the mode of pre-identification processing, carry out the information interaction between the adjacent vehicle when getting into dangerous highway section based on the car networking terminal, improve the security of traveling, make things convenient for the automatic classification storage of data, do benefit to follow-up study and judge and look over.
Description
Technical Field
The invention belongs to the technical field of computers, and particularly relates to a method and a system for recognizing and storing self-adaptive data of a vehicle networking terminal.
Background
As vehicles develop from simple transportation to intelligent entities with sensing and communication capabilities, a global network capable of being connected and communicating with each other is gradually formed between the vehicles, the network is called an internet of vehicles, and as the technology of the internet of vehicles develops, more and more terminals of the internet of vehicles are developed and applied.
The T-Box is taken as a current universal vehicle networking intelligent terminal, is a bridge for connecting vehicles and a network, is an important component of the vehicle networking, and is also called a telematics control unit which integrates functional modules such as a GPS (global positioning system), an external communication interface, an electronic processing unit, a microcontroller, a mobile communication unit, a memory and the like; the T-BOX is internally connected with a Vehicle CAN bus, and externally realizes Vehicle terminals, handheld equipment, roadside units and V2V (Vehicle-to-Vehicle) use through a cloud platform; V2P: (Vehicle to Pedestrian); V2R (information exchange between public networks for Vehicle to Road communication).
After the existing vehicle provided with the internet of vehicles terminal enters a dangerous road section, especially when the vehicle is shifted in loading goods, if the potential danger is not found in time by the owner of the vehicle and other adjacent vehicles, the safety accident is easy to happen.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a system for recognizing and storing self-adaptive data of a vehicle networking terminal, and aims to solve the problems in the background technology.
The embodiment of the invention is realized in such a way that, on one hand, a method for recognizing and storing self-adaptive data of a vehicle networking terminal comprises the following steps:
carrying out pre-recognition processing on the acquired road condition information and traffic jam data, and planning the driving information of the current vehicle in a subsequent road section according to the pre-recognition processing result, wherein the driving information at least comprises a driving route and a driving speed;
judging whether the current vehicle is about to enter a dangerous road section within a preset distance according to the running information of the current vehicle, wherein the dangerous road section at least comprises a tunnel road section;
if the current vehicle is about to enter the dangerous road section within the preset distance, before the current vehicle enters the dangerous road section, establishing a communication channel between the current vehicle and an internet-of-vehicles terminal where adjacent vehicles are located within a preset range;
judging whether dangerous transport behaviors exist in adjacent vehicles according to the acquired road condition information, wherein the dangerous transport behaviors at least comprise transport loading displacement behaviors, and reminding the current vehicle and the adjacent vehicles according to the dangerous transport behaviors and the running information of the current vehicle;
and storing the associated driving data of the current vehicle on the dangerous road section according to a preset classification sequence, wherein the associated driving data is associated with dangerous transportation behaviors.
As a further aspect of the present invention, before the pre-identifying the acquired traffic information and traffic congestion data, the method further includes:
acquiring road condition information of a current vehicle driving section in real time;
and acquiring traffic jam data in a preset road section.
As a still further aspect of the present invention, the pre-identifying the acquired road condition information and traffic congestion data, and planning the driving information of the current vehicle in the subsequent road segment according to the pre-identifying result, where the driving information at least includes a driving route and a driving speed specifically includes:
acquiring a primary planned route of a current vehicle and evaluating the acquired road condition information;
identifying a coverage area of the traffic jam data corresponding to the preliminarily planned route, marking an area with a jam value exceeding a preset jam value in the coverage area, calculating a real-time distance between the marked area and the current position of the vehicle, and judging the change rate of the jam value of the marked area along with time according to the traffic jam data;
calculating a first time length required for reaching a mark area nearest to the current vehicle according to the driving habit data, and judging a second time length required for reducing the congestion value of the mark area nearest to the current vehicle to a normal value according to the congestion value change rate of the mark area;
and comparing the first duration with the second duration, if the first duration is less than the second duration and the evaluation of the current road condition information is lower than the standard grade, defining the second duration as the running time reaching the nearest mark area so as to reduce the running speed, otherwise, sending a safe driving attention instruction.
As a still further aspect of the present invention, after determining whether the current vehicle is about to enter a dangerous segment within a preset distance according to the driving information of the current vehicle, where the dangerous segment includes at least a tunnel segment, the method further includes:
if the dangerous road section is on the driving route, calculating the size of a preset distance according to the driving speed of the driving habit data and the pre-acquired standard communication time;
a node is marked in the driving route, the distance from the dangerous road segment is equal to the preset distance.
As a further scheme of the present invention, if the current vehicle is about to enter the dangerous road section within the preset distance, before entering the dangerous road section, establishing a communication channel between the current vehicle and the internet-of-vehicles terminal where the adjacent vehicle within the preset range is located specifically includes:
if the current vehicle is detected to reach the mark node in the driving route, sending an instruction for requiring to establish a communication channel to at least one adjacent vehicle;
and responding to a communication channel establishment agreement instruction returned by at least one adjacent vehicle, and establishing a communication channel between the current vehicle and the corresponding vehicle.
As a further scheme of the present invention, the determining whether there is a dangerous transport behavior in the adjacent vehicle according to the acquired road condition information, where the dangerous transport behavior at least includes a transport loading displacement behavior, and the reminding of the current vehicle and the adjacent vehicle according to the dangerous transport behavior in combination with the driving information of the current vehicle specifically includes:
the method comprises the steps of performing frame processing on images of front vehicles in collected road condition information to obtain a plurality of image pictures of the front vehicles, screening rear end front-view image pictures with definition higher than a preset threshold value in the image pictures of the front vehicles, and marking the screened rear end front-view image pictures of the front vehicles according to a time axis;
acquiring maximum displacement change values of key parts in the marked rear-end orthophoto pictures, comparing the maximum displacement change values with preset reference displacement change values, and when any maximum displacement change value is larger than a first preset reference displacement change value, listing the rear-end orthophoto pictures of at least two front vehicles related to the maximum displacement change values as quasi-suspicious dangerous transport behavior pictures;
requesting to acquire a standard rear-end front-view image picture pre-stored by a front vehicle, comparing the suspected dangerous transport behavior picture with the standard rear-end front-view image picture, and judging that the suspected dangerous transport behavior picture is a suspected dangerous transport picture when any maximum displacement variation value of key parts of the suspected dangerous transport behavior picture and the standard rear-end front-view image picture is larger than a second preset reference displacement variation value;
sending the suspicious dangerous transportation picture to an adjacent vehicle and sending a possible dangerous early warning prompt;
whether a dangerous transport behavior confirmation instruction exists or not is sent to the front vehicle, and when the confirmation information of the front vehicle is not received or the dangerous transport behavior is confirmed to occur within a preset time period, a deceleration reminding is sent to the current vehicle and the adjacent vehicles.
As a further scheme of the invention, the key parts are a vehicle door part and a part for loading and transporting articles.
As a further aspect of the present invention, the storing of the associated driving data of the current vehicle on the dangerous road segment according to the preset classification order specifically includes:
defining road condition information and driving information acquired by a current vehicle from a time of coming into a dangerous road section to a time of leaving the dangerous road section as associated driving data of the current vehicle on the dangerous road section;
respectively extracting the running information of the current vehicle following the front vehicle in the associated running data;
extracting road condition information with dangerous transport behaviors in the associated driving data;
and classifying and storing the extracted driving information and road condition information.
As a further aspect of the present invention, in another aspect, a terminal adaptive data identification and storage system for internet of vehicles includes:
the preprocessing module is used for carrying out pre-recognition processing on the acquired road condition information and traffic jam data and planning the driving information of the current vehicle in a subsequent road section according to a pre-recognition processing result, wherein the driving information at least comprises a driving route and a driving speed;
the judging module is used for judging whether the current vehicle is about to enter a dangerous road section within a preset distance according to the running information of the current vehicle, wherein the dangerous road section at least comprises a tunnel road section;
the establishing module is used for establishing a communication channel between the current vehicle and an internet-of-vehicles terminal where adjacent vehicles in a preset range are located before the current vehicle enters the dangerous road section if the current vehicle is about to enter the dangerous road section within a preset distance;
the system comprises a danger judging and reminding module, a traffic information acquiring module and a traffic information acquiring module, wherein the danger judging and reminding module is used for judging whether dangerous transport behaviors exist in adjacent vehicles according to acquired road condition information, the dangerous transport behaviors at least comprise transport loading displacement behaviors, and the current vehicle and the adjacent vehicles are reminded according to the dangerous transport behaviors and the running information of the current vehicle;
and the classification module is used for storing the associated driving data of the current vehicle on the dangerous road section according to a preset classification sequence, wherein the associated driving data is associated with dangerous transportation behaviors.
According to the method and the system for recognizing and storing the self-adaptive data of the internet of vehicles terminal, the acquired road condition information and the acquired traffic jam data are pre-recognized before entering the dangerous road section, and the communication channel between the vehicles is established, when whether dangerous transport behaviors exist in the adjacent vehicles is judged according to the acquired road condition information, the current vehicle and the adjacent vehicles are reminded according to the dangerous transport behaviors and the running information of the current vehicle, so that the current vehicle and the adjacent vehicles can acquire the dangerous information, the acceleration is avoided, and the vehicles can run carefully; moreover, can carry out automatic classification storage relevant data, convenient follow-up reading and the relevant data of analysis at car networking terminal platform realize the information sharing under certain authority condition, conveniently reform transform dangerous highway section and carry out comprehensive study and judge when taking place danger.
Drawings
Fig. 1 is a main flow chart of a method for adaptively identifying and storing data of a terminal in the internet of vehicles.
Fig. 2 is a flowchart for planning the traveling information of the current vehicle in the subsequent road section according to the result of the pre-recognition processing.
Fig. 3 is a flow chart of reminding a current vehicle and neighboring vehicles according to dangerous transportation behavior in combination with driving information of the current vehicle.
Fig. 4 is a flowchart for storing the associated traveling data of the current vehicle on the dangerous road segment according to the preset classification order.
FIG. 5 is a main structural diagram of an adaptive data identification and storage system of a vehicle networking terminal.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Specific implementations of the present invention are described in detail below with reference to specific embodiments.
The invention provides a self-adaptive data identification and storage method and system for a vehicle networking terminal, which solve the technical problem in the background technology.
As shown in fig. 1, a main flow chart of an adaptive data identification and storage method for a vehicle networking terminal is provided for an embodiment of the present invention, where the adaptive data identification and storage method for a vehicle networking terminal includes:
step S10: carrying out pre-recognition processing on the acquired road condition information and traffic jam data, and planning the driving information of the current vehicle in a subsequent road section according to the pre-recognition processing result, wherein the driving information at least comprises a driving route and a driving speed;
step S11: judging whether the current vehicle is about to enter a dangerous road section within a preset distance according to the running information of the current vehicle, wherein the dangerous road section at least comprises a tunnel road section;
step S12: if the current vehicle is about to enter the dangerous road section within the preset distance, before the current vehicle enters the dangerous road section, establishing a communication channel between the current vehicle and an internet-of-vehicles terminal where adjacent vehicles are located within a preset range;
step S13: judging whether dangerous transport behaviors exist in adjacent vehicles according to the acquired road condition information, wherein the dangerous transport behaviors at least comprise transport loading displacement behaviors, and reminding the current vehicle and the adjacent vehicles according to the dangerous transport behaviors and the running information of the current vehicle; and
step S14: and storing the associated driving data of the current vehicle on the dangerous road section according to a preset classification sequence, wherein the associated driving data is associated with dangerous transportation behaviors.
When the method is applied, the acquired road condition information and traffic jam data are pre-identified before entering the dangerous road section, a communication channel between vehicles is established, and when whether dangerous transportation behaviors exist in adjacent vehicles is judged according to the acquired road condition information, the dangerous transportation behaviors at least comprise transportation loading displacement behaviors, especially when the dangerous transportation behaviors exist, the current vehicle and the adjacent vehicles are reminded according to the dangerous transportation behaviors and in combination with the running information of the current vehicle, so that the current vehicle and the adjacent vehicles (including the front vehicle) can acquire the dangerous information, acceleration is avoided, the front vehicle can be driven carefully, the front vehicle can be safely processed after running out of the dangerous road section or as soon as possible, and the associated running data are classified and extracted before being stored, namely the running information of the current vehicle following the front vehicle in the associated running data is respectively extracted, and the road with the dangerous transportation behaviors existing in the associated running data is extracted The condition information can be automatically classified and stored for relevant data, the relevant data can be conveniently read and analyzed subsequently on the Internet of vehicles terminal platform, information sharing under certain permission conditions is realized, and the dangerous road sections can be conveniently transformed and comprehensively researched and judged when danger occurs.
As a preferred embodiment of the present invention, before the pre-identifying the acquired traffic information and traffic congestion data, the method further includes:
step S20: acquiring road condition information of a current vehicle driving section in real time;
step S21: and acquiring traffic jam data in a preset road section.
It should be understood that the road condition information and the traffic jam data are respectively acquired in real time and acquired by changing the acquisition frequency according to the actual demand, and the acquisition of the traffic jam data can be directly accessed to the existing map for acquisition.
As shown in fig. 2, as a preferred embodiment of the present invention, the pre-identifying the acquired traffic information and traffic congestion data, and planning the driving information of the current vehicle in the subsequent road segment according to the result of the pre-identifying, where the driving information at least includes a driving route and a driving speed, specifically includes:
step S101: acquiring a primary planned route of a current vehicle and evaluating the acquired road condition information;
step S102: identifying a coverage area of the traffic jam data corresponding to the preliminarily planned route, marking an area with a jam value exceeding a preset jam value in the coverage area, calculating a real-time distance between the marked area and the current position of the vehicle, and judging the change rate of the jam value of the marked area along with time according to the traffic jam data;
step S103: calculating a first time length required for reaching a mark area nearest to the current vehicle according to the driving habit data, and judging a second time length required for reducing the congestion value of the mark area nearest to the current vehicle to a normal value according to the congestion value change rate of the mark area;
step S104: and comparing the first duration with the second duration, if the first duration is less than the second duration and the evaluation of the current road condition information is lower than the standard grade, defining the second duration as the running time reaching the nearest mark area so as to reduce the running speed, otherwise, sending a safe driving attention instruction.
When the embodiment is applied, if the first time length is less than the second time length and the evaluation of the current road condition information is lower than the standard level (representing the non-congestion level), the second time length is defined as the running time reaching the nearest marked area, so that the running speed is reduced, that is, the running speed can be reduced or a safe driving attention instruction can be sent out timely according to the change situation of the congestion value, so that the current vehicle cannot accelerate under the condition of poor road condition, the danger is avoided, and the waiting time after reaching the nearest marked area can also be reduced.
As a preferred embodiment of the present invention, after determining whether the current vehicle is about to enter a dangerous segment within a preset distance according to the driving information of the current vehicle, the dangerous segment including at least a tunnel segment, the method further includes:
step S31: if the dangerous road section is on the driving route, calculating the size of a preset distance according to the driving speed of the driving habit data and the pre-acquired standard communication time;
step S32: a node is marked in the driving route, the distance from the dangerous road segment is equal to the preset distance.
When the method is applied, the driving speed of the driving habit data can be an average speed of normal driving, the standard communication time can be the time for the current vehicle to establish communication with the farthest adjacent vehicle, so that the communication between the current vehicle and the adjacent vehicle can be established as soon as possible before the current vehicle enters the dangerous road section, and the preset distance value is the product of the driving speed of the driving habit data and the standard communication time acquired in advance.
As a preferred embodiment of the present invention, if the current vehicle is about to enter the dangerous road segment within the preset distance, before entering the dangerous road segment, establishing the communication channel between the current vehicle and the internet-of-vehicles terminal where the adjacent vehicle is located within the preset range specifically includes:
step S121: if the current vehicle is detected to reach the mark node in the driving route, sending an instruction for requiring to establish a communication channel to at least one adjacent vehicle;
step S122: and responding to a communication channel establishment agreement instruction returned by at least one adjacent vehicle, and establishing a communication channel between the current vehicle and the corresponding vehicle.
When the method is applied, a communication channel between the current vehicle and the vehicle networking terminal where the adjacent vehicle is located in the preset range is established, so that a basis can be provided for follow-up information confirmation and reminding.
As shown in fig. 3, as a preferred embodiment of the present invention, the determining whether there is a dangerous transportation behavior in the neighboring vehicle according to the acquired road condition information, where the dangerous transportation behavior at least includes a transportation loading displacement behavior, and the reminding of the current vehicle and the neighboring vehicle according to the dangerous transportation behavior in combination with the driving information of the current vehicle specifically includes:
step S131: the method comprises the steps of performing frame processing on images of front vehicles in collected road condition information to obtain a plurality of image pictures of the front vehicles, screening rear end front-view image pictures with definition higher than a preset threshold value in the image pictures of the front vehicles, and marking the screened rear end front-view image pictures of the front vehicles according to a time axis;
step S132: acquiring maximum displacement change values of key parts in the marked rear-end orthophoto pictures, comparing the maximum displacement change values with preset reference displacement change values, and when any maximum displacement change value is larger than a first preset reference displacement change value, listing the rear-end orthophoto pictures of at least two front vehicles related to the maximum displacement change values as quasi-suspicious dangerous transport behavior pictures;
step S133: requesting to acquire a standard rear-end front-view image picture pre-stored by a front vehicle, comparing the suspected dangerous transport behavior picture with the standard rear-end front-view image picture, and judging that the suspected dangerous transport behavior picture is a suspected dangerous transport picture when any maximum displacement variation value of key parts of the suspected dangerous transport behavior picture and the standard rear-end front-view image picture is larger than a second preset reference displacement variation value;
step S134: sending the suspicious dangerous transportation picture to an adjacent vehicle and sending a possible dangerous early warning prompt;
step S135: whether a dangerous transport behavior confirmation instruction exists or not is sent to the front vehicle, and when the confirmation information of the front vehicle is not received or the dangerous transport behavior is confirmed to occur within a preset time period, a deceleration reminding is sent to the current vehicle and the adjacent vehicles.
The key parts are the vehicle door part and the part for loading and transporting articles.
It can be understood that, when entering a dangerous road section, if the door of the front vehicle is opened or the part where the transported goods are loaded is displaced, under the condition, the current vehicle and the rear vehicle are greatly threatened, the rear vehicle is easy to be dangerous when overtaking, even if the rear vehicle does not overtake and the front vehicle is displaced when the transported goods are loaded, the rear vehicle is also greatly threatened, especially when the vehicle is extremely dangerous, such as when driving in a tunnel, the line of sight in the tunnel is blocked, the road is shunted, and danger is more easy to occur, therefore, by judging whether dangerous transport behaviors exist in the adjacent vehicle according to the acquired road condition information, the dangerous transport behaviors at least include the transport loading displacement behaviors, the current vehicle and the adjacent vehicle (including the front vehicle) are reminded according to the dangerous transport behaviors in combination with the driving information of the current vehicle, so that the current vehicle and the adjacent vehicle (including the front vehicle) can acquire the dangerous information, the vehicle safety management system avoids acceleration and is convenient for the front vehicle to safely process after driving out of a dangerous road section or as soon as possible.
As shown in fig. 4, as a preferred embodiment of the present invention, the storing the associated driving data of the current vehicle on the dangerous road segment according to a preset classification order specifically includes:
step S141: defining road condition information and driving information acquired by a current vehicle from a time of coming into a dangerous road section to a time of leaving the dangerous road section as associated driving data of the current vehicle on the dangerous road section;
step S142: respectively extracting the running information of the current vehicle following the front vehicle in the associated running data;
step S143: extracting road condition information with dangerous transport behaviors in the associated driving data;
step S144: and classifying and storing the extracted driving information and road condition information.
In the application of the embodiment, the associated driving data is extracted before being stored, namely, the driving information of the current vehicle following the front vehicle in the associated driving data and the road condition information of dangerous transportation behaviors existing in the associated driving data are respectively extracted, so that the subsequent reading and analysis of the relevant data on the internet of vehicles terminal platform are facilitated, the information sharing under a certain permission condition is realized, the dangerous road section is conveniently reconstructed and comprehensively judged when danger occurs, and it is understood that the current vehicle and the front vehicle in the associated driving data should include all the current vehicles and the front vehicles which enter the dangerous road section and meet the condition under the internet of vehicles terminal platform.
As shown in fig. 5, as another preferred embodiment of the present invention, in another aspect, a terminal-adaptive data identification and storage system for internet of vehicles includes:
the pre-processing module 100 is configured to perform pre-recognition processing on the acquired road condition information and traffic congestion data, and plan driving information of a current vehicle in a subsequent road section according to a pre-recognition processing result, where the driving information at least includes a driving route and a driving speed;
the judging module 200 is configured to judge whether the current vehicle is about to enter a dangerous road section within a preset distance according to the driving information of the current vehicle, where the dangerous road section at least includes a tunnel road section;
the establishing module 300 is configured to establish a communication channel between the current vehicle and an internet-of-vehicles terminal where an adjacent vehicle within a preset range is located before entering the dangerous road section if the current vehicle is about to enter the dangerous road section within a preset distance;
the danger judging and reminding module 400 is used for judging whether dangerous transport behaviors exist in the adjacent vehicles according to the acquired road condition information, wherein the dangerous transport behaviors at least comprise transport loading displacement behaviors, and reminding the current vehicle and the adjacent vehicles according to the dangerous transport behaviors and the running information of the current vehicle;
the classification module 500 is configured to store associated driving data of the current vehicle on the dangerous road segment according to a preset classification sequence, where the associated driving data is associated with dangerous transportation behaviors.
The embodiment of the invention provides a self-adaptive data identification and storage method of a terminal of an internet of vehicles, and provides a self-adaptive data identification and storage system of a terminal of an internet of vehicles based on the self-adaptive data identification and storage method of the terminal of the internet of vehicles, which comprises the steps of pre-identifying and processing acquired road condition information and traffic jam data before entering a dangerous road section, establishing a communication channel between vehicles, judging whether dangerous transport behaviors exist in adjacent vehicles according to the acquired road condition information, wherein the dangerous transport behaviors at least comprise transport loading displacement behaviors, and particularly reminding the current vehicle and the adjacent vehicles according to the dangerous transport behaviors and the running information of the current vehicle when the dangerous transport behaviors exist, so that the current vehicle and the adjacent vehicles (including the front vehicles) can acquire the dangerous information, avoid acceleration and carefully run, the front vehicle is safely processed after driving out of the dangerous road section or as soon as possible, and furthermore, the associated driving data is classified and extracted before being stored, namely, the driving information of the current vehicle following the front vehicle in the associated driving data is respectively extracted, and the road condition information of dangerous transportation behaviors in the associated driving data is extracted, so that the information of the processed data can be automatically classified and stored, the subsequent reading and analysis of the relevant data on a vehicle networking terminal platform are facilitated, the information sharing under a certain permission condition is realized, and the dangerous road section is conveniently reconstructed and comprehensively researched and judged when danger occurs.
In order to load the above method and system to operate successfully, the system may include more or less components than those described above, or combine some components, or different components, in addition to the various modules described above, for example, input/output devices, network access devices, buses, processors, memories, and the like.
The processor may be a Central Processing Unit (CPU), other general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is the control center for the system and that connects the various components using various interfaces and lines.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. A vehicle networking terminal self-adaptive data identification and storage method is characterized by comprising the following steps:
carrying out pre-recognition processing on the acquired road condition information and traffic jam data, and planning the driving information of the current vehicle in a subsequent road section according to the pre-recognition processing result, wherein the driving information at least comprises a driving route and a driving speed;
judging whether the current vehicle is about to enter a dangerous road section within a preset distance according to the running information of the current vehicle, wherein the dangerous road section at least comprises a tunnel road section;
if the current vehicle is about to enter the dangerous road section within the preset distance, before the current vehicle enters the dangerous road section, establishing a communication channel between the current vehicle and an internet-of-vehicles terminal where adjacent vehicles are located within a preset range;
judging whether dangerous transport behaviors exist in adjacent vehicles according to the acquired road condition information, wherein the dangerous transport behaviors at least comprise transport loading displacement behaviors, and reminding the current vehicle and the adjacent vehicles according to the dangerous transport behaviors and the running information of the current vehicle;
and storing the associated driving data of the current vehicle on the dangerous road section according to a preset classification sequence, wherein the associated driving data is associated with dangerous transportation behaviors.
2. The method for recognizing and storing the self-adaptive data of the internet of vehicles terminal according to claim 1, wherein before the pre-recognizing the acquired traffic information and traffic jam data, the method further comprises:
acquiring road condition information of a current vehicle driving section in real time;
and acquiring traffic jam data in a preset road section.
3. The method for recognizing and storing the self-adaptive data of the internet of vehicles terminal according to claim 1, wherein the pre-recognition processing is performed on the acquired road condition information and traffic congestion data, and the planning is performed on the driving information of the current vehicle in the subsequent road section according to the pre-recognition processing result, wherein the driving information at least comprises a driving route and a driving speed, and specifically comprises:
acquiring a primary planned route of a current vehicle and evaluating the acquired road condition information;
identifying a coverage area of the traffic jam data corresponding to the preliminarily planned route, marking an area with a jam value exceeding a preset jam value in the coverage area, calculating a real-time distance between the marked area and the current position of the vehicle, and judging the change rate of the jam value of the marked area along with time according to the traffic jam data;
calculating a first time length required for reaching a mark area nearest to the current vehicle according to the driving habit data, and judging a second time length required for reducing the congestion value of the mark area nearest to the current vehicle to a normal value according to the congestion value change rate of the mark area;
and comparing the first duration with the second duration, if the first duration is less than the second duration and the evaluation of the current road condition information is lower than the standard grade, defining the second duration as the running time reaching the nearest mark area so as to reduce the running speed, otherwise, sending a safe driving attention instruction.
4. The vehicle networking terminal adaptive data identification and storage method according to claim 1, wherein after judging whether the current vehicle is about to enter a dangerous section within a preset distance according to the driving information of the current vehicle, the dangerous section at least comprising a tunnel section, the method further comprises:
if the dangerous road section is on the driving route, calculating the size of a preset distance according to the driving speed of the driving habit data and the pre-acquired standard communication time;
a node is marked in the driving route, the distance from the dangerous road segment is equal to the preset distance.
5. The vehicle networking terminal self-adaptive data identification and storage method according to claim 4, wherein if the current vehicle is about to enter the dangerous section within a preset distance, before entering the dangerous section, establishing a communication channel between the current vehicle and the vehicle networking terminal where the adjacent vehicle within a preset range is located specifically comprises:
if the current vehicle is detected to reach the mark node in the driving route, sending an instruction for requiring to establish a communication channel to at least one adjacent vehicle;
and responding to a communication channel establishment agreement instruction returned by at least one adjacent vehicle, and establishing a communication channel between the current vehicle and the corresponding vehicle.
6. The internet of vehicles terminal adaptive data identification storage method according to claim 1, wherein the determining whether the adjacent vehicle has dangerous transport behavior according to the obtained road condition information, the dangerous transport behavior at least includes transport loading displacement behavior, and the reminding of the current vehicle and the adjacent vehicle according to the dangerous transport behavior in combination with the driving information of the current vehicle specifically includes:
the method comprises the steps of performing frame processing on images of front vehicles in collected road condition information to obtain a plurality of image pictures of the front vehicles, screening rear end front-view image pictures with definition higher than a preset threshold value in the image pictures of the front vehicles, and marking the screened rear end front-view image pictures of the front vehicles according to a time axis;
acquiring maximum displacement change values of key parts in the marked rear-end orthophoto pictures, comparing the maximum displacement change values with preset reference displacement change values, and when any maximum displacement change value is larger than a first preset reference displacement change value, listing the rear-end orthophoto pictures of at least two front vehicles related to the maximum displacement change values as quasi-suspicious dangerous transport behavior pictures;
requesting to acquire a standard rear-end front-view image picture pre-stored by a front vehicle, comparing the suspected dangerous transport behavior picture with the standard rear-end front-view image picture, and judging that the suspected dangerous transport behavior picture is a suspected dangerous transport picture when any maximum displacement variation value of key parts of the suspected dangerous transport behavior picture and the standard rear-end front-view image picture is larger than a second preset reference displacement variation value;
sending the suspicious dangerous transportation picture to an adjacent vehicle and sending a possible dangerous early warning prompt;
whether a dangerous transport behavior confirmation instruction exists or not is sent to the front vehicle, and when the confirmation information of the front vehicle is not received or the dangerous transport behavior is confirmed to occur within a preset time period, a deceleration reminding is sent to the current vehicle and the adjacent vehicles.
7. The self-adaptive data identification and storage method of the internet of vehicles terminal according to claim 6, wherein the key parts are the vehicle door part and the part for loading and transporting goods.
8. The vehicle networking terminal adaptive data identification and storage method according to claim 1, wherein the storing of the associated driving data of the current vehicle on the dangerous road section according to a preset classification sequence specifically comprises:
defining road condition information and driving information acquired by a current vehicle from a time of coming into a dangerous road section to a time of leaving the dangerous road section as associated driving data of the current vehicle on the dangerous road section;
respectively extracting the running information of the current vehicle following the front vehicle in the associated running data;
extracting road condition information with dangerous transport behaviors in the associated driving data;
and classifying and storing the extracted driving information and road condition information.
9. An Internet of vehicles terminal adaptive data identification storage system, the system comprising:
the preprocessing module is used for carrying out pre-recognition processing on the acquired road condition information and traffic jam data and planning the driving information of the current vehicle in a subsequent road section according to a pre-recognition processing result, wherein the driving information at least comprises a driving route and a driving speed;
the judging module is used for judging whether the current vehicle is about to enter a dangerous road section within a preset distance according to the running information of the current vehicle, wherein the dangerous road section at least comprises a tunnel road section;
the establishing module is used for establishing a communication channel between the current vehicle and an internet-of-vehicles terminal where adjacent vehicles in a preset range are located before the current vehicle enters the dangerous road section if the current vehicle is about to enter the dangerous road section within a preset distance;
the system comprises a danger judging and reminding module, a traffic information acquiring module and a traffic information acquiring module, wherein the danger judging and reminding module is used for judging whether dangerous transport behaviors exist in adjacent vehicles according to acquired road condition information, the dangerous transport behaviors at least comprise transport loading displacement behaviors, and the current vehicle and the adjacent vehicles are reminded according to the dangerous transport behaviors and the running information of the current vehicle;
and the classification module is used for storing the associated driving data of the current vehicle on the dangerous road section according to a preset classification sequence, wherein the associated driving data is associated with dangerous transportation behaviors.
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