CN114312801A - Vehicle driving behavior processing method and device, storage medium and computer equipment - Google Patents
Vehicle driving behavior processing method and device, storage medium and computer equipment Download PDFInfo
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Abstract
The invention discloses a vehicle driving behavior processing method, a vehicle driving behavior processing device, a storage medium and computer equipment, wherein the processing method comprises the following steps: acquiring driving data of a vehicle, wherein the driving data comprises vehicle identification information and ID information of a current driver; the driving data is sent to the blockchain system, so that any node in the blockchain system can receive the driving data and broadcast the driving data; inputting driving data into a driving behavior analysis model established in advance so as to generate a driving behavior score of the current driver according to the ID information and the vehicle identification information of the current driver; and broadcasting the driving behavior score of the current driver in the blockchain system so that any node in the blockchain system generates an awarding result according to the driving behavior score of the current driver, and distributing the awarding result to the account of the current driver after broadcasting the awarding result. The method can effectively improve the credibility of the driving behavior scoring and the enthusiasm of the driver for participating in the driving behavior scoring.
Description
Technical Field
The present invention relates to the field of vehicle technologies, and in particular, to a vehicle driving behavior processing method, a vehicle driving behavior processing apparatus, a computer-readable storage medium, and a computer device.
Background
With the continuous development of economy, the automobile keeping quantity is increased year by year, but the driving level of drivers is uneven, bad driving habits are hard to return, and huge potential safety hazards are brought to traffic.
Therefore, in the related technology, a driving behavior analysis model is constructed by collecting data of a vehicle and a vehicle owner, such as data of GPS, speed, acceleration, deceleration, steering, whistling, driving state of a driver, road conditions and the like, and the driving behavior is scored to provide advice for the driver and correct bad driving behavior of the driver. However, this technique mainly has the following problems: the scoring dimension of the driving behaviors is single, and the scoring dimension is mainly focused on the safety dimension of a driver; the driver does not trust the driving score, resulting in poor acceptance. Therefore, the driving behavior score in the related art does not play a role in anticipating correction of the driver's bad driving behavior.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art. Therefore, the first purpose of the invention is to provide a vehicle driving behavior processing method, which scores the driving behavior of the driver through multiple dimensions and improves the credibility of the driving behavior scoring and the enthusiasm of the driver for participating in the driving behavior scoring through the reward rule of real-time scoring of the blockchain.
A second object of the invention is to propose a computer-readable storage medium.
A third object of the invention is to propose a computer device.
A fourth object of the present invention is to provide a vehicle driving behavior processing apparatus.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides a vehicle driving behavior processing method, including: acquiring driving data of a vehicle, wherein the driving data comprises vehicle identification information and ID information of a current driver; the driving data is sent to the blockchain system, so that any node in the blockchain system can receive the driving data and broadcast the driving data; inputting driving data into a driving behavior analysis model established in advance so as to generate a driving behavior score of the current driver according to the ID information and the vehicle identification information of the current driver; and broadcasting the driving behavior score of the current driver in the blockchain system so that any node in the blockchain system generates an awarding result according to the driving behavior score of the current driver, and distributing the awarding result to the account of the current driver after broadcasting the awarding result.
According to the vehicle driving behavior processing method provided by the embodiment of the invention, the driving data of the vehicle is analyzed through the driving behavior analysis model to obtain the driver behavior score, and the reward result is generated according to the driving behavior score of the current driver through the block chain system, so that the enthusiasm of the driver in participating in the driving behavior score is improved.
In order to achieve the above object, a second embodiment of the present invention provides a computer-readable storage medium, on which a vehicle driving behavior processing program is stored, which, when executed by a processor, implements the vehicle driving behavior processing method described above.
According to the computer-readable storage medium of the embodiment of the invention, when the vehicle driving behavior processing program stored on the computer-readable storage medium is executed by the processor, the driving data of the vehicle can be analyzed through the driving behavior analysis model to obtain the driver behavior score, and the reward result is generated according to the driving behavior score of the current driver through the block chain system, so that the enthusiasm of the driver for participating in the driving behavior score is improved.
In order to achieve the above object, a third embodiment of the present invention provides a computer device, which includes a memory, a processor, and a vehicle driving behavior processing program stored in the memory and operable on the processor, and when the processor executes the vehicle driving behavior processing program, the computer device implements the vehicle driving behavior processing method.
According to the computer device of the embodiment of the invention, when the vehicle driving behavior processing program which is stored on the memory and can run on the processor is executed by the processor, the driving data of the vehicle can be analyzed through the driving behavior analysis model to obtain the driving behavior score, and the reward result is generated according to the driving behavior score of the current driver through the block chain system, so that the enthusiasm of the driver for participating in the driving behavior score is improved.
In order to achieve the above object, a fourth aspect of the present invention provides a vehicle driving behavior processing apparatus, including an obtaining module, configured to obtain driving data of a vehicle, where the driving data includes vehicle identification information and ID information of a current driver; the system comprises a sending module, a receiving module and a processing module, wherein the sending module is used for sending driving data to a blockchain system so that any node in the blockchain system can receive the driving data and broadcast the driving data; and the scoring module is used for inputting the driving data into a pre-established driving behavior analysis model so as to generate a driving behavior score of the current driver according to the ID information and the vehicle identification information of the current driver, broadcasting the driving behavior score of the current driver in the blockchain system so as to generate an awarding result by any node in the blockchain system according to the driving behavior score of the current driver, and distributing the awarding result to an account of the current driver after broadcasting the awarding result.
According to the vehicle driving behavior processing device provided by the embodiment of the invention, the driving data of the vehicle is analyzed through the driving behavior analysis model to obtain the driver behavior score, and the reward result is generated according to the driving behavior score of the current driver through the block chain system, so that the enthusiasm of the driver in participating in the driving behavior score is improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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FIG. 1 is a flow chart of a vehicle driving behavior processing method according to one embodiment of the present invention;
fig. 2 is a block diagram showing the configuration of a vehicle driving behavior processing device according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
A vehicle driving behavior processing method, an apparatus, a storage medium, and a computer device according to embodiments of the present invention are described below with reference to the accompanying drawings.
Fig. 1 is a flowchart of a vehicle driving behavior processing method according to one embodiment of the present invention. As shown in fig. 1, the vehicle driving behavior processing method includes the steps of:
s101, driving data of the vehicle are obtained, wherein the driving data comprise vehicle identification information and ID information of a current driver.
The vehicle identification information may include information such as a license plate number and a frame number, and the driver ID information may include driver identity information such as an identification number and a name. The vehicle identification information and the current driver's ID information may be stored in the in-vehicle terminal or the cloud server when the driver controls the vehicle for the first time. In this embodiment, by acquiring the vehicle identification information and the ID information of the current driver, the acquired other driving data of the vehicle, such as specific driving behavior data, is bound with the vehicle identification information and the ID information of the driver, so as to send a driving behavior score and an incentive result generated according to the driving behavior score to the driver bound with the driving behavior data after the driving behavior analysis is performed.
In the present embodiment, the driving behavior data of the vehicle includes speed information, acceleration information, deceleration information, steering information, behavior information of the driver, and the like of the vehicle. The driving behavior data of the vehicle can be acquired by various sensors installed in the vehicle, such as a GPS (Global Positioning System) monitor, a camera, a steering sensor, and the like.
S102, the driving data is sent to the blockchain system, so that any node in the blockchain system can receive the driving data and broadcast the driving data.
Specifically, when the vehicle is running, the vehicle-mounted terminal or the cloud server and various sensors installed in the vehicle can respectively send vehicle identification information, current driver ID information and collected vehicle driving behavior data to the blockchain system, so that any node in multiple nodes in the blockchain system can receive and broadcast the driving data, and record and store the driving data through the blockchain system, and integrity and authenticity of the driving data are guaranteed.
In an embodiment of the present invention, after any node in the blockchain system receives and broadcasts the driving data, the node in the blockchain system, which stores the driving behavior analysis model, may receive the driving data, analyze the driving data based on the driving behavior analysis model to generate a driving behavior score of the current driver, generate an incentive result according to the driving behavior score of the current driver, and broadcast the incentive result.
And S103, inputting the driving data into a driving behavior analysis model established in advance so as to generate a driving behavior score of the current driver according to the ID information and the vehicle identification information of the current driver.
In one embodiment of the present invention, generating a driving behavior score for a current driver comprises: analyzing and processing the driving data to respectively generate a safety dimension score, a control dimension score, a civilization dimension score and an energy-saving dimension score of the current driver; and generating a driving behavior score of the current driver according to the safety dimension score, the control dimension score, the civilization dimension score, the energy-saving dimension score and the corresponding weight of the current driver.
Specifically, the safety dimension score, the control dimension score, the civilization dimension score, and the energy saving dimension score for generating the driving behavior score of the current driver may be obtained by evaluating according to the evaluation index scores specific to the respective dimensions. Wherein the safety dimension score can be obtained by evaluating a safety belt use index score, a fatigue driving index score, a late night driving index score and an attention index score; the control dimension score can be obtained by evaluating an urgent acceleration index score, an urgent deceleration index score, an urgent turning index score and a stable index score; the civilization dimension score can be obtained by evaluating the steering lamp use index score, the frequent lane change index score and the whistle index score; the energy-saving dimension score can be obtained by evaluating an air conditioner use index score, an idle speed duration index score and an energy consumption index score.
It should be noted that the weights corresponding to the safety dimension score, the control dimension score, the civilization dimension score and the energy-saving dimension score can be obtained by an analytic hierarchy process.
As an example, assuming that the driving behavior analysis model obtains a safety dimension score, a control dimension score, a civilization dimension score and an energy-saving dimension score of m1, m2, m3 and m4 respectively according to the driving data, weights corresponding to the safety dimension score, the control dimension score, the civilization dimension score and the energy-saving dimension score obtained according to the analytic hierarchy process are q1, q2, q3 and q4 respectively, wherein q1+ q2+ q3+ q4 is 100%. The driving behavior analysis model can obtain a driving behavior score m1 q1+ m2 q2+ m3 q3+ m4 q4 according to the scoring data. It should be noted that the driving behavior analysis model may also obtain the driving behavior score through other algorithms according to the above scoring data, and is not limited in detail here.
In one embodiment of the present invention, analyzing and processing the driving data to generate a safety dimension score, a control dimension score, a civilization dimension score and an energy-saving dimension score of the current driver respectively includes:
analyzing and processing the driving data to obtain a safety belt use index score, a fatigue driving index score, a late-night driving index score and an attention index score of the current driver, acquiring weights of the safety belt use index score, the fatigue driving index score, the late-night driving index score and the attention index score respectively occupying safety dimension scores by adopting a chromatographic analysis method, and calculating the safety dimension score of the current driver according to the weights of the safety belt use index score, the fatigue driving index score, the late-night driving index score and the attention index score respectively occupying safety dimension scores, and the weights of the safety belt use index score, the fatigue driving index score, the late-night driving index score and the attention index score of the current driver;
analyzing and processing the driving data to obtain a rapid acceleration index score, a rapid deceleration index score, a rapid turning index score and a stable index score of the current driver, acquiring weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score which respectively account for the control dimension score by adopting an analytic hierarchy process, and calculating the control dimension score of the current driver according to the weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score which respectively account for the control dimension score, and the weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score of the current driver;
analyzing and processing the driving data to obtain a steering lamp use index score, a frequent lane change index score and a whistle index score of the current driver, and obtaining the weights of the steering lamp use index score, the frequent lane change index score and the whistle index score which respectively account for the civilization dimension score by adopting an analytic hierarchy process, and calculating the civilization dimension score of the current driver according to the weights of the steering lamp use index score, the frequent lane change index score and the whistle index score which respectively account for the civilization dimension score, and the weights of the steering lamp use index score, the frequent lane change index score and the whistle index score of the current driver;
the driving data are analyzed and processed to obtain the air conditioner use index score, the idle speed duration index score and the energy consumption index score of the current driver, weights of the air conditioner use index score, the idle speed duration index score and the energy consumption index score which respectively account for the energy saving dimension score are obtained by adopting an analytic hierarchy process, and the energy saving dimension score of the current driver is calculated according to the weights of the air conditioner use index score, the idle speed duration index score and the energy consumption index score which respectively account for the energy saving dimension score, the air conditioner use index score of the current driver, the idle speed duration index score and the energy consumption index score.
Specifically, taking the safety dimension score as an example, the seat belt usage index, the fatigue driving index, the late night driving index, and the attention index used for the safety dimension score may be first divided among scoring zones, respectively. Taking the fatigue driving index as an example, the fatigue driving index score segments can be set to be 10 points at the highest and 0 point at the lowest. The fatigue index can be acquired by a camera arranged in the vehicle within preset time, such as yawning, of the driver, the ratio of the frequency of the action to the calibration frequency is acquired, and score division is performed according to the ratio.
As an example, assuming that the preset time is 1 as the calibrated value of the frequency of yawning within 10s, if the frequency of yawning of the driver collected by the camera inside the vehicle within 10s is greater than 6, the ratio is correspondingly greater than 6, the score of the fatigue driving index of the driver can be recorded as 0, if the frequency of yawning of the driver collected within 10s is greater than 3 and less than or equal to 6, the score of the fatigue driving index of the driver can be recorded as 5 according to the range of the ratio, if the frequency of yawning of the driver collected within 10s is greater than 1 and less than or equal to 3, the score of the fatigue driving index of the driver can be recorded as 8, and if the frequency of yawning of the driver collected within 10s is 0, the score of the fatigue driving index of the driver can be recorded as 10. Of course, the specific segment value and the segment interval of the fatigue driving index of the driver can be obtained according to other evaluation modes. The present invention is not particularly limited.
Taking the safety dimension score as an example, the analysis of the driving data may result in a seat belt usage index score, a fatigue driving index score, a late night driving index score, and an attention index score, such as a1, a2, A3, a4, respectively. The weight of the seat belt usage index score, the fatigue driving index score, the late night driving index score and the attention index score to the safety dimension score is then obtained by an analytic hierarchy process, such as B1, B2, B3, B4, wherein B1+ B2+ B3+ B4 is 100%. After the driving behavior analysis model obtains the scoring data, the safety dimension score of the current driver can be obtained as A1B 1+ A2B 2+ A3B 3+ A4B 4. Specifically, the safety dimension score corresponding to each index is calculated through each index, and then the safety dimension scores obtained through each index are summed to calculate the mean value of the safety dimension scores, so that the safety dimension score of the current driver is obtained. It should be noted that the driving behavior analysis model may also obtain the safety dimension score through other algorithms according to the score data, and is not limited in detail here.
S104, broadcasting the driving behavior score of the current driver in the blockchain system so that any node in the blockchain system can generate an awarding result according to the driving behavior score of the current driver, and distributing the awarding result to the account of the current driver after broadcasting.
Specifically, after the driving behavior analysis model generates the driving behavior score of the driver, the driving behavior score can be broadcasted through the corresponding node, so that other nodes in the block chain system generate an incentive result according to the dimensions, the weight corresponding to the index of the dimensions and the driving behavior score after receiving the driving behavior score. For example, a driving performance score threshold may be set, and a reward may be given when the driving performance score exceeds the driving performance score threshold.
As an example, when the safety dimension weight, the energy saving dimension weight, and the manipulation dimension weight are all high, but the civilization dimension weight is low, and the driving behavior score is very high (exceeding the driving behavior score threshold), the blockchain system may generate reward results of the safety dimension, the energy saving dimension, the manipulation dimension, and the civilization dimension, and when the driving behavior score is low (exceeding the driving behavior score threshold), the blockchain system may generate reward results of only the safety dimension, the energy saving dimension, and the manipulation dimension, and distribute the reward results to the account of the current driver after broadcasting.
According to the vehicle driving behavior processing method provided by the embodiment of the invention, the driving data of the vehicle is analyzed through the driving behavior analysis model to obtain the driver behavior score, and the reward result is generated according to the driving behavior score of the current driver through the block chain system, so that the enthusiasm of the driver in participating in the driving behavior score is improved.
Further, the present invention also proposes a computer-readable storage medium having a vehicle driving behavior processing program stored thereon, which when executed by a processor implements the vehicle driving behavior processing method described above.
According to the computer-readable storage medium of the embodiment of the invention, when the vehicle driving behavior processing program stored on the computer-readable storage medium is executed by the processor, the driving data of the vehicle can be analyzed through the driving behavior analysis model to obtain the driver behavior score, and the reward result is generated according to the driving behavior score of the current driver through the block chain system, so that the enthusiasm of the driver for participating in the driving behavior score is improved.
The invention further provides a computer device, which comprises a memory, a processor and a vehicle driving behavior processing program stored on the memory and capable of running on the processor, wherein when the processor executes the vehicle driving behavior processing program, the vehicle driving behavior processing method is realized.
According to the computer device of the embodiment of the invention, when the vehicle driving behavior processing program which is stored on the memory and can run on the processor is executed by the processor, the driving data of the vehicle can be analyzed through the driving behavior analysis model to obtain the driving behavior score, and the reward result is generated according to the driving behavior score of the current driver through the block chain system, so that the enthusiasm of the driver for participating in the driving behavior score is improved.
Fig. 2 is a block diagram showing the configuration of a vehicle driving behavior processing device according to an embodiment of the present invention. Referring to fig. 2, the vehicle driving behavior processing apparatus 100 includes an acquisition module 101, a transmission module 102, and a scoring module 103.
The acquiring module 101 is configured to acquire driving data of a vehicle, where the driving data includes vehicle identification information and ID information of a current driver.
The sending module 102 is configured to send the driving data to the blockchain system, so that any node in the blockchain system receives the driving data and broadcasts the driving data.
The scoring module 103 is configured to input driving data into a pre-established driving behavior analysis model, so as to generate a driving behavior score of a current driver according to ID information and vehicle identification information of the current driver, and broadcast the driving behavior score of the current driver in the blockchain system, so that any one node in the blockchain system generates an incentive result according to the driving behavior score of the current driver, and distributes the incentive result to an account of the current driver after broadcasting the incentive result.
In an embodiment of the present invention, after any one node in the blockchain system receives the driving data and broadcasts the driving data, the scoring module 103 is further configured to analyze the driving data based on the driving behavior analysis model by using the node in the blockchain system, where the driving behavior analysis model is stored, to generate a driving behavior score of the current driver, generate an incentive result according to the driving behavior score of the current driver, and broadcast the incentive result.
In an embodiment of the present invention, the scoring module 103 is further configured to analyze the driving data to generate a safety dimension score, a control dimension score, a civilization dimension score, and an energy saving dimension score of the current driver, respectively; and generating a driving behavior score of the current driver according to the safety dimension score, the control dimension score, the civilization dimension score, the energy-saving dimension score and the corresponding weight of the current driver.
In an embodiment of the present invention, the scoring module 103 is further configured to analyze the driving data to obtain a seat belt usage index score, a fatigue driving index score, a late night driving index score, and an attention index score of the current driver, and obtain weights of the seat belt usage index score, the fatigue driving index score, the late night driving index score, and the attention index score respectively occupying the safety dimension score by using a chromatography analysis method, and calculate the safety dimension score of the current driver according to the weights of the seat belt usage index score, the fatigue driving index score, the late night driving index score, and the attention index score of the current driver respectively occupying the safety dimension score, and the seat belt usage index score, the fatigue driving index score, the late night driving index score, and the attention index score of the current driver;
analyzing and processing the driving data to obtain a rapid acceleration index score, a rapid deceleration index score, a rapid turning index score and a stable index score of the current driver, acquiring weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score which respectively account for the control dimension score by adopting an analytic hierarchy process, and calculating the control dimension score of the current driver according to the weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score which respectively account for the control dimension score, and the weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score of the current driver;
analyzing and processing the driving data to obtain a steering lamp use index score, a frequent lane change index score and a whistle index score of the current driver, and obtaining the weights of the steering lamp use index score, the frequent lane change index score and the whistle index score which respectively account for the civilization dimension score by adopting an analytic hierarchy process, and calculating the civilization dimension score of the current driver according to the weights of the steering lamp use index score, the frequent lane change index score and the whistle index score which respectively account for the civilization dimension score, and the weights of the steering lamp use index score, the frequent lane change index score and the whistle index score of the current driver;
the driving data are analyzed and processed to obtain the air conditioner use index score, the idle speed duration index score and the energy consumption index score of the current driver, weights of the air conditioner use index score, the idle speed duration index score and the energy consumption index score which respectively account for the energy saving dimension score are obtained by adopting an analytic hierarchy process, and the energy saving dimension score of the current driver is calculated according to the weights of the air conditioner use index score, the idle speed duration index score and the energy consumption index score which respectively account for the energy saving dimension score, the air conditioner use index score of the current driver, the idle speed duration index score and the energy consumption index score.
According to the vehicle driving behavior processing device provided by the embodiment of the invention, the driving data of the vehicle is analyzed through the driving behavior analysis model to obtain the driver behavior score, and the reward result is generated according to the driving behavior score of the current driver through the block chain system, so that the enthusiasm of the driver in participating in the driving behavior score is improved.
It should be noted that the logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
In the description of the present invention, it is to be understood that the terms "central," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," "circumferential," and the like are used in the orientations and positional relationships indicated in the drawings for convenience in describing the invention and to simplify the description, and are not intended to indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and are therefore not to be considered limiting of the invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, the first feature "on" or "under" the second feature may be directly contacting the first and second features or indirectly contacting the first and second features through an intermediate. Also, a first feature "on," "over," and "above" a second feature may be directly or diagonally above the second feature, or may simply indicate that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature may be directly under or obliquely under the first feature, or may simply mean that the first feature is at a lesser elevation than the second feature.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A vehicle driving behavior processing method characterized by comprising the steps of:
acquiring driving data of a vehicle, wherein the driving data comprises vehicle identification information and ID information of a current driver;
the driving data are sent to a blockchain system, so that any node in the blockchain system can receive the driving data and broadcast the driving data;
inputting the driving data into a pre-established driving behavior analysis model so as to generate a driving behavior score of the current driver according to the ID information of the current driver and the vehicle identification information;
broadcasting the driving behavior score of the current driver in the blockchain system so that any node in the blockchain system can generate an incentive result according to the driving behavior score of the current driver, and distributing the incentive result to an account of the current driver after broadcasting the incentive result.
2. The vehicle driving behavior processing method according to claim 1, wherein after any one node in the blockchain system receives and broadcasts the driving data, the node in the blockchain system, in which the driving behavior analysis model is stored, analyzes the driving data based on the driving behavior analysis model to generate a driving behavior score of the current driver, generates the reward result according to the driving behavior score of the current driver, and broadcasts the reward result.
3. The vehicle driving behavior processing method according to claim 1 or 2, characterized in that generating the driving behavior score of the current driver includes:
analyzing and processing the driving data to respectively generate a safety dimension score, an operation dimension score, a civilization dimension score and an energy-saving dimension score of the current driver;
and generating the driving behavior score of the current driver according to the safety dimension score, the control dimension score, the civilization dimension score, the energy-saving dimension score and the corresponding weight of the current driver.
4. The vehicle driving behavior processing method according to claim 3, wherein the analyzing the driving data to generate a safety dimension score, a handling dimension score, a civilization dimension score, and an energy-saving dimension score of the current driver, respectively, comprises:
analyzing and processing the driving data to obtain a seat belt use index score, a fatigue driving index score, a late night driving index score and an attention index score of the current driver, and adopting a chromatographic analysis method to obtain weights of the seat belt use index score, the fatigue driving index score, the late night driving index score and the attention index score respectively occupying the safety dimension score, and calculating the safety dimension score of the current driver according to the weights of the seat belt use index score, the fatigue driving index score, the late night driving index score and the attention index score respectively occupying the safety dimension score, and the seat belt use index score, the fatigue driving index score, the late night driving index score and the attention index score of the current driver;
analyzing and processing the driving data to obtain a rapid acceleration index score, a rapid deceleration index score, a rapid turning index score and a stable index score of the current driver, acquiring weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score respectively occupying the control dimension score by adopting an analytic hierarchy process, and calculating the control dimension score of the current driver according to the weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score respectively occupying the control dimension score and the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score of the current driver;
analyzing and processing the driving data to obtain a steering lamp use index score, a frequent lane change index score and a whistle index score of the current driver, acquiring weights of the steering lamp use index score, the frequent lane change index score and the whistle index score respectively occupying the civilization dimension score by adopting an analytic hierarchy process, and calculating the civilization dimension score of the current driver according to the weights of the steering lamp use index score, the frequent lane change index score and the whistle index score respectively occupying the civilization dimension score and the steering lamp use index score, the frequent lane change index score and the whistle index score of the current driver;
analyzing and processing the driving data to obtain an air conditioner use index score, an idle speed duration index score and an energy consumption index score of the current driver, obtaining the weight of the air conditioner use index score, the idle speed duration index score and the energy consumption index score respectively occupying the energy-saving dimension score by adopting an analytic hierarchy process, and calculating the energy-saving dimension score of the current driver according to the weight of the air conditioner use index score, the idle speed duration index score and the energy consumption index score respectively occupying the energy-saving dimension score, and the air conditioner use index score, the idle speed duration index score and the energy consumption index score of the current driver.
5. A computer-readable storage medium, characterized in that a vehicle driving behavior processing program is stored thereon, which when executed by a processor implements the vehicle driving behavior processing method according to any one of claims 1 to 4.
6. A computer device comprising a memory, a processor, and a vehicle driving behavior processing program stored on the memory and executable on the processor, the processor implementing the vehicle driving behavior processing method according to any one of claims 1 to 4 when executing the vehicle driving behavior processing program.
7. A vehicle driving behavior processing apparatus characterized by comprising:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring driving data of a vehicle, and the driving data comprises vehicle identification information and ID information of a current driver;
the sending module is used for sending the driving data to a block chain system so that any node in the block chain system can receive the driving data and broadcast the driving data;
and the scoring module is used for inputting the driving data into a pre-established driving behavior analysis model so as to generate a driving behavior score of the current driver according to the ID information of the current driver and the vehicle identification information, and broadcasting the driving behavior score of the current driver in the blockchain system so that any node in the blockchain system generates an incentive result according to the driving behavior score of the current driver, and the incentive result is distributed to an account of the current driver after being broadcasted.
8. The vehicle driving behavior processing apparatus as claimed in claim 7, wherein after any node in the blockchain system receives and broadcasts the driving data, the scoring module is further configured to analyze the driving data based on the driving behavior analysis model by a node in the blockchain system in which the driving behavior analysis model is stored, so as to generate a driving behavior score of the current driver, generate the reward result according to the driving behavior score of the current driver, and broadcast the reward result.
9. The vehicle driving behavior processing apparatus according to claim 7 or 8, characterized in that the scoring module is further configured to,
analyzing and processing the driving data to respectively generate a safety dimension score, an operation dimension score, a civilization dimension score and an energy-saving dimension score of the current driver;
and generating the driving behavior score of the current driver according to the safety dimension score, the control dimension score, the civilization dimension score, the energy-saving dimension score and the corresponding weight of the current driver.
10. The vehicle driving behavior processing apparatus of claim 9, wherein the scoring module is further configured to,
analyzing and processing the driving data to obtain a seat belt use index score, a fatigue driving index score, a late night driving index score and an attention index score of the current driver, and adopting a chromatographic analysis method to obtain weights of the seat belt use index score, the fatigue driving index score, the late night driving index score and the attention index score respectively occupying the safety dimension score, and calculating the safety dimension score of the current driver according to the weights of the seat belt use index score, the fatigue driving index score, the late night driving index score and the attention index score respectively occupying the safety dimension score, and the seat belt use index score, the fatigue driving index score, the late night driving index score and the attention index score of the current driver;
analyzing and processing the driving data to obtain a rapid acceleration index score, a rapid deceleration index score, a rapid turning index score and a stable index score of the current driver, acquiring weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score respectively occupying the control dimension score by adopting an analytic hierarchy process, and calculating the control dimension score of the current driver according to the weights of the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score respectively occupying the control dimension score and the rapid acceleration index score, the rapid deceleration index score, the rapid turning index score and the stable index score of the current driver;
analyzing and processing the driving data to obtain a steering lamp use index score, a frequent lane change index score and a whistle index score of the current driver, acquiring weights of the steering lamp use index score, the frequent lane change index score and the whistle index score respectively occupying the civilization dimension score by adopting an analytic hierarchy process, and calculating the civilization dimension score of the current driver according to the weights of the steering lamp use index score, the frequent lane change index score and the whistle index score respectively occupying the civilization dimension score and the steering lamp use index score, the frequent lane change index score and the whistle index score of the current driver;
analyzing and processing the driving data to obtain an air conditioner use index score, an idle speed duration index score and an energy consumption index score of the current driver, obtaining the weight of the air conditioner use index score, the idle speed duration index score and the energy consumption index score respectively occupying the energy-saving dimension score by adopting an analytic hierarchy process, and calculating the energy-saving dimension score of the current driver according to the weight of the air conditioner use index score, the idle speed duration index score and the energy consumption index score respectively occupying the energy-saving dimension score, and the air conditioner use index score, the idle speed duration index score and the energy consumption index score of the current driver.
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