CN113762755A - Method and device for pushing driver analysis report, computer equipment and storage medium - Google Patents

Method and device for pushing driver analysis report, computer equipment and storage medium Download PDF

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CN113762755A
CN113762755A CN202111006422.6A CN202111006422A CN113762755A CN 113762755 A CN113762755 A CN 113762755A CN 202111006422 A CN202111006422 A CN 202111006422A CN 113762755 A CN113762755 A CN 113762755A
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driver
label
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赵超
王柏淇
刘传
邵亚辉
李木子
陈浩
张跃华
郑岩
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FAW Jiefang Automotive Co Ltd
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Abstract

The application relates to a method and a device for pushing a driver analysis report, computer equipment and a storage medium. The method comprises the following steps: acquiring a label for representing the driving habit of a driver based on historical driving data, wherein the historical driving data comprises bad driving behavior data of the driver; and determining an analysis report of the driver according to the label, and pushing the analysis report to the first user terminal. By adopting the method, the management of the vehicle can be implemented to the driver, so that the driver can clearly know the driving habit of the driver according to the analysis report, thereby improving or perfecting the driving technology and further improving the safety of vehicle operation.

Description

Method and device for pushing driver analysis report, computer equipment and storage medium
Technical Field
The application relates to the technical field of vehicle networking, in particular to a method and a device for pushing a driver analysis report, computer equipment and a storage medium.
Background
Mobile internet technology is changing the life, business model, and global economy. With the penetration of the car networking technology to the aspects of research, production, sale, service and the like of commercial cars, the data value of the car networking of commercial cars is in urgent need of development and utilization. At present, each whole vehicle factory pays attention to the value of vehicle data, starts to collect the vehicle data, stores the vehicle data in the own vehicle networking system, and does not disconnect the data sending application mode.
At present, for safety management of road transportation of vehicles and drivers, a mode of random spot check and post evidence collection through a vehicle-mounted terminal is adopted, and on the premise of large input of manpower and material resources, the safety level of road transportation of an enterprise is still difficult to improve. Therefore, it is highly desirable to provide a method for pushing an analysis report corresponding to the driving habits of a driver, so that the management of the vehicle is implemented on the driver, and the driver can clearly recognize the driving habits according to the analysis report, thereby improving or perfecting the driving technology and further improving the safety of vehicle operation.
Disclosure of Invention
In view of the above, it is necessary to provide a driver analysis report pushing method, device, computer device and storage medium capable of improving vehicle operation safety.
A driver analysis report pushing method, the method comprising:
acquiring a label for representing the driving habit of a driver based on historical driving data, wherein the historical driving data comprises bad driving behavior data of the driver;
and determining an analysis report of the driver according to the label, and pushing the analysis report to the first user terminal.
In one embodiment, the obtaining of the label for representing the driving habits of the driver based on the historical driving data of the driver comprises:
determining the total times of the occurrence of the poor driving behaviors in the historical time period according to the historical driving data of the driver at each historical moment in the historical time period;
acquiring a label for representing the driving habit of the driver based on a value range in which the total times of the bad driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type.
In one embodiment, the historical driving data includes acceleration; accordingly, the undesirable driving behavior is any one of a plurality of behaviors including rapid acceleration and rapid deceleration; alternatively, the first and second electrodes may be,
the historical driving data comprises centripetal acceleration; accordingly, the bad driving behavior is a sharp turn; alternatively, the first and second electrodes may be,
the historical driving data includes vehicle speed; accordingly, the bad driving behavior is overspeed; alternatively, the first and second electrodes may be,
the historical driving data comprises the vehicle speed and the engine speed, and correspondingly, the poor driving behavior is the stopping and accelerator bombing.
In one embodiment, the historical driving data includes risky driving behavior data of the driver; accordingly, the label for representing the driving habits of the driver is obtained based on the historical driving data of the driver, and the label comprises the following components:
identifying the in-vehicle behaviors of a driver in a historical time period, and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls;
acquiring a label for representing the driving habit of the driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively dangerous type, early warning type and safe type.
In one embodiment, the historical driving data includes the accumulated oil consumption and the total vehicle weight; accordingly, the label for representing the driving habits of the driver is obtained based on the historical driving data of the driver, and the label comprises the following components:
calculating the ratio of the accumulated oil consumption to the weight of the whole vehicle;
acquiring a label for representing the driving habit of the driver based on the value range in which the ratio falls; wherein the label is any one of the following three types of labels, and the following three types of labels are oil consumption type, general oil consumption type and oil saving type respectively.
In one embodiment, the historical driving data includes vehicle positioning data; accordingly, the label for representing the driving habits of the driver is obtained based on the historical driving data of the driver, and the label comprises the following components:
determining the number of places passed by the driver in the historical time period based on the vehicle positioning data;
acquiring a label for representing the driving habit of the driver based on the number of the places; the label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
In one embodiment, the labels comprise a driving stability degree label, a driving risk degree label, a driving oil consumption degree label and a driving record label; historical driving data still includes driver's risk driving behavior data, accumulative total oil consumption, whole car weight and vehicle positioning data, correspondingly, based on driver's historical driving data, acquires the label that is used for the representation driver driving habit, include:
determining the total times of the sudden acceleration and the sudden deceleration in the historical time period according to the acceleration of the driver at each historical moment in the historical time period;
determining the total number of times of the sudden turning in the historical time period according to the centripetal acceleration of the driver at each historical moment in the historical time period;
determining the total number of overspeed occurrences in the historical time period according to the speed of the driver at each historical moment in the historical time period;
determining the total times of over-stopping accelerator bombing in the historical time period according to the speed of the driver at each historical moment in the historical time period and the rotating speed of the engine;
summing the total times of over-sharp acceleration and over-sharp deceleration, the total times of sharp turns, the total times of overspeed and the total times of stopping and accelerator bombing in a historical time period, and acquiring a driving stability degree label for representing the driving habit of a driver based on a value range in which a summation result falls; the driving stability and gravity degree label is any one of the following three types of labels, wherein the following three types of labels are an aggressive type label, a stable type label and a stable type label;
identifying the in-vehicle behaviors of a driver in a historical time period, and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls;
acquiring a driving risk degree label for representing driving habits of a driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the driving risk degree label is any one of the following three types of labels, namely a dangerous type label, an early warning type label and a safe type label;
calculating the ratio of the accumulated oil consumption to the weight of the vehicle;
acquiring a driving fuel consumption degree label for representing the driving habit of the driver based on the value of the ratio; wherein, the driving oil consumption degree label is any one of the following three types of labels, and the following three types of labels are respectively oil consumption type, general oil consumption type and oil saving type;
determining the number of places passed by the driver in the historical time period based on the vehicle positioning data;
acquiring a driving history label for representing the driving habits of the driver based on the number of the places; the driving history label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
A driver analysis report pushing device, the device comprising:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring a label for representing the driving habit of a driver based on historical driving data, and the historical driving data comprises bad driving behavior data of the driver;
and the determining module is used for determining the analysis report of the driver according to the label and pushing the analysis report to the first user terminal.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring a label for representing the driving habit of a driver based on historical driving data, wherein the historical driving data comprises bad driving behavior data of the driver;
and determining an analysis report of the driver according to the label, and pushing the analysis report to the first user terminal.
A computer-readable storage medium storing a computer program which, when executed by a processor, performs the steps of:
acquiring a label for representing the driving habit of a driver based on historical driving data, wherein the historical driving data comprises bad driving behavior data of the driver;
and determining an analysis report of the driver according to the label, and pushing the analysis report to the first user terminal.
According to the method and the device for pushing the driver analysis report, the computer equipment and the storage medium, the label used for representing the driving habit of the driver is obtained based on the historical driving data; according to the label, an analysis report of the driver is determined, the analysis report is pushed to the first user terminal, and management of the vehicle is implemented on the driver, so that the driver can clearly know own driving habits according to the analysis report, driving technologies are improved or perfected, and safety of vehicle operation is improved.
Drawings
FIG. 1 is a flow diagram illustrating a method for pushing driver analysis reports in one embodiment;
FIG. 2 is a schematic illustration of an analysis report in one embodiment;
FIG. 3 is a block diagram of a driver analysis report pushing system in one embodiment;
FIG. 4 is a block diagram showing the construction of a driver analysis report pushing apparatus according to another embodiment;
FIG. 5 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application 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 present application and are not intended to limit the present application.
Mobile internet technology is changing the life, business model, and global economy. With the penetration of the car networking technology to the aspects of research, production, sale, service and the like of commercial cars, the data value of the car networking of commercial cars is in urgent need of development and utilization. At present, each whole vehicle factory pays attention to the value of vehicle data, starts to collect the vehicle data, stores the vehicle data in the own vehicle networking system, and does not disconnect the data sending application mode.
At present, for safety management of road transportation of vehicles and drivers, a mode of random spot check and post evidence collection through a vehicle-mounted terminal is adopted, and on the premise of large input of manpower and material resources, the safety level of road transportation of an enterprise is still difficult to improve. Therefore, it is highly desirable to provide a method for pushing an analysis report corresponding to the driving habits of a driver, so that the management of the vehicle is implemented on the driver, and the driver can clearly recognize the driving habits according to the analysis report, thereby improving or perfecting the driving technology and further improving the safety of vehicle operation.
Before describing the specific implementation of the embodiment of the present invention, a description will be given of a main application scenario of the embodiment of the present invention. The method for pushing the analysis report of the driver in the embodiment of the invention is mainly applied to an application scene of managing a fleet by a commercial vehicle whole-vehicle factory, wherein the commercial vehicle is an automobile for transporting personnel and goods in design and technical characteristics, and if the driving habit of the driver of the commercial vehicle is not good, the possibility of traffic accidents of the commercial vehicle is increased, so that the great economic loss of the commercial vehicle whole-vehicle factory is caused. Therefore, it is important for the entire commercial vehicle plant to provide a method for pushing an analysis report of driving habits of the driver of the commercial vehicle. The method for pushing the analysis report of the driver mainly comprises the steps of obtaining a label used for representing the driving habits of the driver based on historical driving data, determining the analysis report of the driver according to the label, and pushing the analysis report to the driver, so that the driver of the commercial vehicle can clearly know the driving habits of the driver according to the analysis report, the driving technology is improved or perfected, and the safety of the commercial vehicle operation of the whole vehicle plant of the commercial vehicle is improved.
In view of the above problems in the related art, embodiments of the present invention provide a method for pushing a driver analysis report, where the method may be applied to a server, and the server may be implemented by an independent server or a server cluster formed by multiple servers. It should be noted that, the numbers of "a plurality" and the like mentioned in the embodiments of the present application each refer to a number of "at least two", for example, "a plurality" refers to "at least two".
In combination with the content of the foregoing embodiments, in an embodiment, as shown in fig. 1, a method for pushing a driver analysis report is provided, which is applied to a server, and an execution subject is described as an example of the server, where the method includes the following steps:
101. acquiring a label for representing the driving habit of a driver based on historical driving data, wherein the historical driving data comprises bad driving behavior data of the driver;
102. and determining an analysis report of the driver according to the label, and pushing the analysis report to the first user terminal.
In step 101, the historical driving data may mainly be the driving data of the driver in the corresponding time period from the time of purchasing the vehicle to the present time, or may also be the driving data of the driver in any sub-time period from the time of purchasing the vehicle to the present time, which is not specifically limited in the embodiment of the present invention. Specifically, in practical applications, after the analysis report is obtained, the driver can clearly recognize the driving habits of the driver according to the analysis report, so as to improve or perfect the driving technology, and therefore, in order to ensure that the analysis report of the driver is closer to the actual driving habits of the driver, the historical driving data used in determining the analysis report may be the driving data obtained by the driver from the last time the analysis report was obtained until the current corresponding time period.
In addition, the embodiment of the present invention does not specifically limit the manner of obtaining the label for representing the driving habits of the driver based on the historical driving data, and includes but is not limited to: acquiring vehicle operation data at each historical moment according to historical driving data of a driver at each historical moment in a historical time period; determining the total times of the occurrence of the poor driving behaviors in the historical time period according to the vehicle operation data at each historical moment; acquiring a label for representing the driving habit of the driver based on a value range in which the total times of the bad driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type.
For example, the historical driving data includes a vehicle speed, correspondingly, acceleration at each historical time is obtained according to the vehicle speed of the driver at each historical time in the historical time period, the total number of times of occurrence of poor driving behaviors in the historical time period is determined according to the acceleration at each historical time, the poor driving behaviors are any one of the following behaviors, the following behaviors include rapid acceleration and rapid deceleration, and a label used for representing the driving habits of the driver is obtained based on a value range in which the total number of times of the poor driving behaviors of the driver in the historical time period falls; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type. For example, the historical driving data includes a direction angle, accordingly, according to the direction angle of the driver at each historical time in the historical time period, the centripetal acceleration at each historical time is obtained, the total number of times of the bad driving behaviors occurring in the historical time period is determined according to the centripetal acceleration at each historical time, the bad driving behaviors are sharp turns, and a label used for representing the driving habits of the driver is obtained based on a value range in which the total number of times of the bad driving behaviors, namely the sharp turns of the driver in the historical time period, falls; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type. It should be noted that, a label used for representing the driving habit of the driver may also be obtained based on the value range in which the total number of times of sudden acceleration, sudden deceleration and sudden turning in the historical time period falls; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type.
In addition, the historical driving data includes driver personal information data, the driver personal information data may include the driving age of the driver, and accordingly, the tags for characterizing the driving habits of the driver are acquired based on the historical driving data of the driver, including: acquiring a label for representing the driving habit of the driver based on the driving age of the driver; wherein the label is the driving age of the driver. In addition, the historical driving data comprises the total mileage, and accordingly, the label used for representing the driving habits of the driver is acquired based on the historical driving data of the driver, and the method comprises the following steps: acquiring a label for representing the driving habits of the driver based on the total mileage; wherein the label is the total mileage.
In addition, in the step 101, the tag may be a plurality of tags in the following types, which are respectively: the driving stability degree label, the driving risk degree label, the driving fuel consumption degree label, the driving history label, and the like, which are not specifically limited in the embodiment of the present invention. It should be noted that the more types included in the tag, the closer the analysis report of the driver finally determined according to the tag is to the real driving habit of the driver, that is, the more accurate the obtained analysis report is. It should be noted that the driving age and the total mileage both belong to the driving history label. For example, the tags include a driving history tag, the historical driving data includes vehicle positioning data, driving age and total mileage, and accordingly, the tags for representing the driving habits of the driver are obtained based on the historical driving data of the driver, including: determining the number of places passed by the driver in the historical time period based on the vehicle positioning data; acquiring a label for representing the driving habits of the driver based on the number of places, the driving age and the total mileage; the label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
In step 102, the presentation form of the analysis report may be a portrait, a table, a text, etc., but the embodiment of the present invention is not limited thereto. In addition, in step 102, the first user terminal may be a mobile phone or a vehicle-mounted terminal, which is not limited in this embodiment of the present invention.
According to the method provided by the embodiment of the invention, the label used for representing the driving habit of the driver is obtained based on the historical driving data; according to the label, an analysis report of the driver is determined, the analysis report is pushed to the first user terminal, and management of the vehicle is implemented on the driver, so that the driver can clearly know own driving habits according to the analysis report, driving technologies are improved or perfected, and safety of vehicle operation is improved.
With reference to the foregoing embodiments, in one embodiment, obtaining a label for characterizing driving habits of a driver based on historical driving data of the driver includes:
determining the total times of the occurrence of the poor driving behaviors in the historical time period according to the historical driving data of the driver at each historical moment in the historical time period;
acquiring a label for representing the driving habit of the driver based on a value range in which the total times of the bad driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type.
For example, the historical driving data includes the engine speed, and accordingly, the poor driving behavior is fatigue driving. The determination condition of the fatigue driving may be that the engine speed is not less than 0 for 4 hours continuously, i.e., the fatigue driving is determined.
In combination with the above embodiments, in one embodiment, the historical driving data includes acceleration; accordingly, the undesirable driving behavior is any one of a plurality of behaviors including rapid acceleration and rapid deceleration; alternatively, the first and second electrodes may be,
the historical driving data comprises centripetal acceleration; accordingly, the bad driving behavior is a sharp turn; alternatively, the first and second electrodes may be,
the historical driving data includes vehicle speed; accordingly, the bad driving behavior is overspeed; alternatively, the first and second electrodes may be,
the historical driving data comprises the vehicle speed and the engine speed, and correspondingly, the poor driving behavior is the stopping and accelerator bombing.
Wherein the poor driving behavior corresponding to the acceleration can be determined based on the following process: and determining the bad driving behaviors corresponding to the acceleration at each historical moment according to the preset interval in which the value of the acceleration at each historical moment falls, wherein the acceleration is divided into a plurality of preset intervals in advance and corresponds to the following behaviors one by one. For example, the following actions include rapid acceleration and rapid deceleration, and accordingly, the predetermined interval may be determined as follows: the acceleration frequency ratio of the vehicle of the same type as the vehicle driven by the driver is counted by adopting a normal distribution method, namely the counted acceleration is sequenced according to the value, the 15% of the counted acceleration is determined as rapid deceleration, the 15% of the counted acceleration is determined as rapid acceleration, and correspondingly, a preset interval is determined.
Wherein, the bad driving behavior corresponding to the centripetal acceleration can be determined based on the following processes: and determining the bad driving behavior corresponding to the acceleration at each historical moment according to the preset interval in which the value of the centripetal acceleration at each historical moment falls. It should be noted that, the process of determining the preset interval may be as follows: the method comprises the steps of counting the frequency ratio of centripetal acceleration of the same type of vehicle as a driver drives by a normal distribution method, namely sequencing the counted centripetal acceleration according to the value, determining that the first 15% is a sharp turn, and correspondingly determining a preset interval.
The overspeed is determined when the vehicle speed is continuously greater than 100km/h for 30 s.
The condition for judging whether the vehicle is parked or not may be that the vehicle speed is 0 and the vehicle is parked or not when the engine speed is greater than 600 rpm.
In combination with the above embodiments, in one embodiment, the historical driving data includes risky driving behavior data of the driver; accordingly, the label for representing the driving habits of the driver is obtained based on the historical driving data of the driver, and the label comprises the following components:
identifying the in-vehicle behaviors of a driver in a historical time period, and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls;
acquiring a label for representing the driving habit of the driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively dangerous type, early warning type and safe type.
According to the method provided by the embodiment of the invention, the total times of the dangerous driving behaviors in the historical time period are determined by identifying the behaviors of the driver in the vehicle in the historical time period, and the label used for representing the driving habits of the driver is obtained based on the value range in which the total times of the dangerous driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively dangerous type, early warning type and safe type. The driver can clearly recognize the risk driving behavior of the driver, so that the risk driving behavior is avoided, and the safety of vehicle operation is improved.
With reference to the foregoing embodiments, in one embodiment, the historical driving data includes an accumulated oil consumption and a vehicle weight; accordingly, the label for representing the driving habits of the driver is obtained based on the historical driving data of the driver, and the label comprises the following components:
calculating the ratio of the accumulated oil consumption to the weight of the whole vehicle;
acquiring a label for representing the driving habit of the driver based on the value range in which the ratio falls; wherein the label is any one of the following three types of labels, and the following three types of labels are oil consumption type, general oil consumption type and oil saving type respectively.
According to the method provided by the embodiment of the invention, the label used for representing the driving habit of the driver is obtained by calculating the ratio between the accumulated oil consumption and the weight of the whole vehicle and based on the value interval in which the ratio falls; wherein the label is any one of the following three types of labels, and the following three types of labels are oil consumption type, general oil consumption type and oil saving type respectively. The fuel consumption of the driver can reflect the driving habits of the driver to a certain extent, and the driver with more fuel consumption is more aggressive to drive relatively. The driver improves the driving habit of the driver through the label, namely, the fuel consumption is reduced, so that on one hand, the resource is saved, and the environment is protected; on the other hand, the changed driving style is realized, so that the vehicle is changed from a radical type to a steady type, and the safety of vehicle operation is further improved.
In combination with the above embodiments, in one embodiment, the historical driving data includes vehicle positioning data; accordingly, the label for representing the driving habits of the driver is obtained based on the historical driving data of the driver, and the label comprises the following components:
determining the number of places passed by the driver in the historical time period based on the vehicle positioning data;
acquiring a label for representing the driving habit of the driver based on the number of the places; the label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
According to the method provided by the embodiment of the invention, the number of places passed by a driver in a historical time period is determined based on vehicle positioning data; acquiring a label for representing the driving habit of the driver based on the number of the places; the label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type. The driver has clear cognition to the driving history of the driver through the label, the new hand type and the advanced type are converted to the rich type in an effort, the driving technology of the driver is improved through improving the experience, and the safety of vehicle operation is improved.
With reference to the foregoing embodiments, in one embodiment, the tags include a driving stability degree tag, a driving risk degree tag, a driving fuel consumption degree tag, and a driving history tag; historical driving data still includes driver's risk driving behavior data, accumulative total oil consumption, whole car weight and vehicle positioning data, correspondingly, based on driver's historical driving data, acquires the label that is used for the representation driver driving habit, include:
determining the total times of the sudden acceleration and the sudden deceleration in the historical time period according to the acceleration of the driver at each historical moment in the historical time period;
determining the total number of times of the sudden turning in the historical time period according to the centripetal acceleration of the driver at each historical moment in the historical time period;
determining the total number of overspeed occurrences in the historical time period according to the speed of the driver at each historical moment in the historical time period;
determining the total times of over-stopping accelerator bombing in the historical time period according to the speed of the driver at each historical moment in the historical time period and the rotating speed of the engine;
summing the total times of over-sharp acceleration and over-sharp deceleration, the total times of sharp turns, the total times of overspeed and the total times of stopping and accelerator bombing in a historical time period, and acquiring a driving stability degree label for representing the driving habit of a driver based on a value range in which a summation result falls; the driving stability and gravity degree label is any one of the following three types of labels, wherein the following three types of labels are an aggressive type label, a stable type label and a stable type label;
identifying the in-vehicle behaviors of a driver in a historical time period, and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls;
acquiring a driving risk degree label for representing driving habits of a driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the driving risk degree label is any one of the following three types of labels, namely a dangerous type label, an early warning type label and a safe type label;
calculating the ratio of the accumulated oil consumption to the weight of the vehicle;
acquiring a driving fuel consumption degree label for representing the driving habit of the driver based on the value interval in which the ratio falls; wherein, the driving oil consumption degree label is any one of the following three types of labels, and the following three types of labels are respectively oil consumption type, general oil consumption type and oil saving type;
determining the number of places passed by the driver in the historical time period based on the vehicle positioning data;
acquiring a driving history label for representing the driving habits of the driver based on the number of the places; the driving history label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
The method provided by the embodiment of the invention determines the analysis report of the driver based on the driving stability degree label, the driving risk degree label, the driving oil consumption degree label and the driving history label. Through determining the analysis report of the driver from multiple aspects, the analysis report of the determined driver is closer to the real driving behavior of the driver, and based on the analysis report, the driver can comprehensively know the driving habit of the driver through the analysis report, the driving technology of the driver is improved, and the safety of vehicle operation is improved.
In connection with the above-mentioned embodiments, in one embodiment, as shown in fig. 3, there is provided a driver analysis report push system, including:
the user terminal is used for collecting static data and transmitting the static data to the big data analysis platform, wherein the static data can include: the sex, age, driving age, resident area, vehicle identification code, vehicle license plate number and the like of the driver;
the vehicle-mounted terminal is used for acquiring dynamic data, and the dynamic data can comprise: the method comprises the following steps that vehicle positioning data, a direction angle, accumulated mileage, accumulated oil consumption, a vehicle speed, an engine rotating speed, vehicle weight, a vehicle identification code and the like are obtained, bad driving behavior data such as rapid acceleration, rapid deceleration, overspeed, rapid turning, fatigue driving and accelerator stopping are obtained according to dynamic data, and the dynamic data and the bad driving behavior data are transmitted to a big data analysis platform;
the big data analysis platform is used for receiving the static data, the dynamic data and the bad driving behavior data and cleaning the static data, the dynamic data and the bad driving behavior data;
and the Internet of vehicles platform is used for acquiring a label for representing the driving habit of the driver according to the static data, the dynamic data and the bad driving behavior data, determining an analysis report of the driver according to the label and pushing the analysis report to the user terminal.
Specifically, the first user terminal may be a mobile phone, and the APP on the mobile phone is used to collect static data. It should be noted that the premise of collecting the static data is that the user registers the APP, that is, the static data needs to be collected under the condition that the user agrees.
Specifically, the vehicle-mounted terminal collects dynamic data of the vehicle through the CAN bus, so that the data collection speed is increased, and the data anti-interference capability is improved. The minimum frequency of the vehicle-mounted terminal for acquiring signals is 1HZ, so that the resource waste caused by too high acquisition frequency is avoided, and the driving habit of a driver cannot be analyzed due to too low frequency.
Specifically, the steps performed by the big data analysis platform may also be performed by the vehicle network platform, but in order to reduce the workload of the vehicle network platform, a part of the steps are assigned to the big data platform for execution.
Specifically, the specific step of the vehicle network platform acquiring the label for representing the driving habit of the driver according to the static data, the dynamic data and the bad driving behavior data, and the step of determining the driver analysis report are the same as the step of acquiring the label and the step of determining the analysis report in the driver analysis report pushing method, so that the description is omitted here.
According to the system provided by the embodiment of the invention, the analysis report of the driver is determined through the vehicle network platform according to the label, and the analysis report is pushed to the user terminal. The management of the vehicle is implemented to the driver, so that the driver can clearly know own driving habits according to the analysis report, the driving technology is improved or perfected, and the safety of vehicle operation is improved.
It should be understood that, although the various steps in the flowchart of fig. 1 are shown in order as indicated by the arrows, the steps are not necessarily performed in order 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 fig. 1 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
In connection with the above-mentioned embodiments, in one embodiment, as shown in fig. 4, there is provided a driver analysis report push apparatus including:
the obtaining module 401 is configured to obtain a tag used for representing a driving habit of a driver based on historical driving data, where the historical driving data includes adverse driving behavior data of the driver;
a determining module 402, configured to determine an analysis report of the driver according to the tag, and push the analysis report to the first user terminal.
In one embodiment, the obtaining module 401 includes:
the determining unit is used for determining the total times of the occurrence of the poor driving behaviors in the historical time period according to the historical driving data of the driver at each historical moment in the historical time period;
the acquiring unit is used for acquiring a label used for representing the driving habit of the driver based on a value range in which the total times of the bad driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type.
In one embodiment, the historical driving data includes acceleration; accordingly, the undesirable driving behavior is any one of a plurality of behaviors including rapid acceleration and rapid deceleration; alternatively, the first and second electrodes may be,
the historical driving data comprises centripetal acceleration; accordingly, the bad driving behavior is a sharp turn; alternatively, the first and second electrodes may be,
the historical driving data includes vehicle speed; accordingly, the bad driving behavior is overspeed; alternatively, the first and second electrodes may be,
the historical driving data comprises the vehicle speed and the engine speed, and correspondingly, the poor driving behavior is the stopping and accelerator bombing.
In one embodiment, the historical driving data includes risky driving behavior data of the driver; accordingly, the obtaining module 401 includes:
the system comprises a determining unit, a judging unit and a judging unit, wherein the determining unit is used for identifying the in-vehicle behaviors of a driver in a historical time period and determining the total times of the dangerous driving behaviors in the historical time period, and the dangerous driving behaviors are any one of the following behaviors which comprise smoking and making a call;
the acquiring unit is used for acquiring a label used for representing the driving habit of the driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively dangerous type, early warning type and safe type.
In one embodiment, the historical driving data includes the accumulated fuel consumption and the total vehicle weight; accordingly, the obtaining module 401 includes:
the calculating unit is used for calculating the ratio of the accumulated oil consumption to the weight of the whole vehicle;
the acquisition unit is used for acquiring a label used for representing the driving habit of the driver based on the value range in which the ratio falls; wherein the label is any one of the following three types of labels, and the following three types of labels are oil consumption type, general oil consumption type and oil saving type respectively.
In one embodiment, the historical driving data includes vehicle positioning data; accordingly, the obtaining module 401 includes:
a determination unit configured to determine the number of places passed by the driver in a history time period based on the vehicle positioning data;
the acquisition unit is used for acquiring a label for representing the driving habit of the driver based on the number of the places; the label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
In one embodiment, the tags include a driving stability degree tag, a driving risk degree tag, a driving fuel consumption degree tag, and a driving history tag; historical driving data still includes driver's risk driving behavior data, accumulative total oil consumption, whole car weight and vehicle positioning data, correspondingly, acquires module 401, includes:
the first determining unit is used for determining the total times of the sudden acceleration and the sudden deceleration in the historical time period according to the acceleration of the driver at each historical moment in the historical time period; determining the total number of times of the sudden turning in the historical time period according to the centripetal acceleration of the driver at each historical moment in the historical time period; determining the total number of overspeed occurrences in the historical time period according to the speed of the driver at each historical moment in the historical time period; determining the total times of over-stopping accelerator bombing in the historical time period according to the speed of the driver at each historical moment in the historical time period and the rotating speed of the engine;
the first acquisition unit is used for summing the total times of over-sharp acceleration and over-sharp deceleration, the total times of sharp turning, the total times of over-speeding and the total times of accelerator bombing during the historical time period, and acquiring a driving stability degree label for representing the driving habit of a driver based on a value range in which a summation result falls; the driving stability and gravity degree label is any one of the following three types of labels, wherein the following three types of labels are an aggressive type label, a stable type label and a stable type label;
the second determining unit is used for identifying the in-vehicle behaviors of the driver in the historical time period and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls;
the second acquisition unit is used for acquiring a driving risk degree label used for representing the driving habit of the driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the driving risk degree label is any one of the following three types of labels, namely a dangerous type label, an early warning type label and a safe type label;
the calculating unit is used for calculating the ratio of the accumulated oil consumption to the weight of the vehicle;
the third acquisition unit is used for acquiring a driving fuel consumption degree label used for representing the driving habit of the driver based on the value of the ratio; wherein, the driving oil consumption degree label is any one of the following three types of labels, and the following three types of labels are respectively oil consumption type, general oil consumption type and oil saving type;
a third determination unit configured to determine the number of places passed by the driver in the history period of time based on the vehicle positioning data;
a fourth acquisition unit, configured to acquire a driving history tag used for representing driving habits of a driver based on the number of locations; the driving history label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
The device provided by the embodiment of the invention is used for acquiring a label for representing the driving habit of a driver based on historical driving data through the acquisition module 401; the determining module 402 is configured to determine an analysis report of the driver according to the tag, push the analysis report to the first user terminal, and implement management of the vehicle on the driver, so that the driver can clearly recognize driving habits of the driver according to the analysis report, thereby improving or perfecting driving technologies and further improving safety of vehicle operation.
For specific limitations of the driver analysis report pushing device, reference may be made to the above limitations of the driver analysis report pushing method, which are not described herein again. The above-mentioned various modules in the driver analysis report pushing apparatus may be implemented wholly or partially by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing historical driving data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a driver analysis report pushing method.
It will be appreciated by those skilled in the art that the configuration shown in fig. 5 is a block diagram of only a portion of the configuration relevant to the present solution and does not constitute a limitation on the computer apparatus to which the present solution is applied, and in particular the computer apparatus may include more or less components than those shown in the drawings, or combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring a label for representing the driving habit of a driver based on historical driving data, wherein the historical driving data comprises bad driving behavior data of the driver;
and determining an analysis report of the driver according to the label, and pushing the analysis report to the first user terminal.
In one embodiment, the processor, when executing the computer program, further performs the steps of: determining the total times of the occurrence of the poor driving behaviors in the historical time period according to the historical driving data of the driver at each historical moment in the historical time period; acquiring a label for representing the driving habit of the driver based on a value range in which the total times of the bad driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type.
In one embodiment, the processor, when executing the computer program, the historical driving data comprises acceleration; accordingly, the undesirable driving behavior is any one of a plurality of behaviors including rapid acceleration and rapid deceleration; or, the historical driving data comprises centripetal acceleration; accordingly, the bad driving behavior is a sharp turn; or, the historical driving data comprises vehicle speed; accordingly, the bad driving behavior is overspeed; or, the historical driving data comprises the vehicle speed and the engine speed, and accordingly, the poor driving behavior is the stopping and accelerator rolling.
In one embodiment, the historical driving data comprises risky driving behavior data of the driver, and the processor, when executing the computer program, further performs the steps of: identifying the in-vehicle behaviors of a driver in a historical time period, and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls; acquiring a label for representing the driving habit of the driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively dangerous type, early warning type and safe type.
In one embodiment, the historical driving data includes an accumulated oil consumption and a total vehicle weight, and accordingly, the processor executes the computer program to further implement the following steps: calculating the ratio of the accumulated oil consumption to the weight of the whole vehicle; acquiring a label for representing the driving habit of the driver based on the value range in which the ratio falls; wherein the label is any one of the following three types of labels, and the following three types of labels are oil consumption type, general oil consumption type and oil saving type respectively.
In one embodiment, the historical driving data comprises vehicle positioning data, and accordingly the processor when executing the computer program further performs the steps of: determining the number of places passed by the driver in the historical time period based on the vehicle positioning data; acquiring a label for representing the driving habit of the driver based on the number of the places; the label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
In one embodiment, the tags include a driving stability degree tag, a driving risk degree tag, a driving fuel consumption degree tag, and a driving history tag; the historical driving data further comprises risk driving behavior data of a driver, accumulated oil consumption, the whole vehicle weight and vehicle positioning data, and correspondingly, the following steps are further realized when the processor executes the computer program:
determining the total times of the sudden acceleration and the sudden deceleration in the historical time period according to the acceleration of the driver at each historical moment in the historical time period; determining the total number of times of the sudden turning in the historical time period according to the centripetal acceleration of the driver at each historical moment in the historical time period; determining the total number of overspeed occurrences in the historical time period according to the speed of the driver at each historical moment in the historical time period; determining the total times of over-stopping accelerator bombing in the historical time period according to the speed of the driver at each historical moment in the historical time period and the rotating speed of the engine; summing the total times of over-sharp acceleration and over-sharp deceleration, the total times of sharp turns, the total times of overspeed and the total times of stopping and accelerator bombing in a historical time period, and acquiring a driving stability degree label for representing the driving habit of a driver based on a value range in which a summation result falls; the driving stability and gravity degree label is any one of the following three types of labels, wherein the following three types of labels are an aggressive type label, a stable type label and a stable type label;
identifying the in-vehicle behaviors of a driver in a historical time period, and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls; acquiring a driving risk degree label for representing driving habits of a driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the driving risk degree label is any one of the following three types of labels, namely a dangerous type label, an early warning type label and a safe type label;
calculating the ratio of the accumulated oil consumption to the weight of the vehicle; acquiring a driving fuel consumption degree label for representing the driving habit of the driver based on the value of the ratio; wherein, the driving oil consumption degree label is any one of the following three types of labels, and the following three types of labels are respectively oil consumption type, general oil consumption type and oil saving type;
determining the number of places passed by the driver in the historical time period based on the vehicle positioning data; acquiring a driving history label for representing the driving habits of the driver based on the number of the places; the driving history label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring a label for representing the driving habit of a driver based on historical driving data, wherein the historical driving data comprises bad driving behavior data of the driver;
and determining an analysis report of the driver according to the label, and pushing the analysis report to the first user terminal.
In one embodiment, the computer program when executed by the processor further performs the steps of: determining the total times of the occurrence of the poor driving behaviors in the historical time period according to the historical driving data of the driver at each historical moment in the historical time period; acquiring a label for representing the driving habit of the driver based on a value range in which the total times of the bad driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type.
In one embodiment, the computer program, when executed by the processor, includes historical driving data including acceleration; accordingly, the undesirable driving behavior is any one of a plurality of behaviors including rapid acceleration and rapid deceleration; or, the historical driving data comprises centripetal acceleration; accordingly, the bad driving behavior is a sharp turn; or, the historical driving data comprises vehicle speed; accordingly, the bad driving behavior is overspeed; or, the historical driving data comprises the vehicle speed and the engine speed, and accordingly, the poor driving behavior is the stopping and accelerator rolling.
In one embodiment, the historical driving data comprises risky driving behavior data of the driver, and accordingly, the computer program when executed by the processor further performs the steps of: identifying the in-vehicle behaviors of a driver in a historical time period, and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls; acquiring a label for representing the driving habit of the driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively dangerous type, early warning type and safe type.
In one embodiment, the historical driving data includes an accumulated fuel consumption and a total vehicle weight, and accordingly, when executed by the processor, the computer program further performs the steps of: calculating the ratio of the accumulated oil consumption to the weight of the whole vehicle; acquiring a label for representing the driving habit of the driver based on the value range in which the ratio falls; wherein the label is any one of the following three types of labels, and the following three types of labels are oil consumption type, general oil consumption type and oil saving type respectively.
In one embodiment, the historical driving data comprises vehicle positioning data, and accordingly, the computer program when executed by the processor further performs the steps of: determining the number of places passed by the driver in the historical time period based on the vehicle positioning data; acquiring a label for representing the driving habit of the driver based on the number of the places; the label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
In one embodiment, the tags include a driving stability degree tag, a driving risk degree tag, a driving fuel consumption degree tag, and a driving history tag; the historical driving data further comprises risk driving behavior data of a driver, accumulated oil consumption, the whole vehicle weight and vehicle positioning data, and accordingly, when the computer program is executed by the processor, the following steps are further realized:
determining the total times of the sudden acceleration and the sudden deceleration in the historical time period according to the acceleration of the driver at each historical moment in the historical time period; determining the total number of times of the sudden turning in the historical time period according to the centripetal acceleration of the driver at each historical moment in the historical time period; determining the total number of overspeed occurrences in the historical time period according to the speed of the driver at each historical moment in the historical time period; determining the total times of over-stopping accelerator bombing in the historical time period according to the speed of the driver at each historical moment in the historical time period and the rotating speed of the engine; summing the total times of over-sharp acceleration and over-sharp deceleration, the total times of sharp turns, the total times of overspeed and the total times of stopping and accelerator bombing in a historical time period, and acquiring a driving stability degree label for representing the driving habit of a driver based on a value range in which a summation result falls; the driving stability and gravity degree label is any one of the following three types of labels, wherein the following three types of labels are an aggressive type label, a stable type label and a stable type label;
identifying the in-vehicle behaviors of a driver in a historical time period, and determining the total times of the dangerous driving behaviors in the historical time period, wherein the dangerous driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls; acquiring a driving risk degree label for representing driving habits of a driver based on a value range in which the total times of dangerous driving behaviors of the driver in a historical time period fall; the driving risk degree label is any one of the following three types of labels, namely a dangerous type label, an early warning type label and a safe type label;
calculating the ratio of the accumulated oil consumption to the weight of the vehicle; acquiring a driving fuel consumption degree label for representing the driving habit of the driver based on the value of the ratio; wherein, the driving oil consumption degree label is any one of the following three types of labels, and the following three types of labels are respectively oil consumption type, general oil consumption type and oil saving type;
determining the number of places passed by the driver in the historical time period based on the vehicle positioning data; acquiring a driving history label for representing the driving habits of the driver based on the number of the places; the driving history label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as 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 application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A driver analysis report pushing method, characterized in that the method comprises:
acquiring a label for representing the driving habit of a driver based on historical driving data, wherein the historical driving data comprises bad driving behavior data of the driver;
and determining an analysis report of the driver according to the label, and pushing the analysis report to a first user terminal.
2. The method according to claim 1, wherein the obtaining of the label for characterizing the driving habits of the driver based on the driver's historical driving data comprises:
determining the total times of the occurrence of the poor driving behaviors in the historical time period according to the historical driving data of the driver at each historical moment in the historical time period;
acquiring a label for representing the driving habits of the driver based on a value interval in which the total times of the bad driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively an aggressive type, a stable type and a stable type.
3. The method of claim 2, wherein the historical driving data comprises acceleration; accordingly, the poor driving behavior is any one of a plurality of behaviors including rapid acceleration and rapid deceleration; alternatively, the first and second electrodes may be,
the historical driving data comprises centripetal acceleration; accordingly, the bad driving behavior is a sharp turn; alternatively, the first and second electrodes may be,
the historical driving data comprises vehicle speed; accordingly, the bad driving behavior is overspeed; alternatively, the first and second electrodes may be,
the historical driving data comprises the speed of the vehicle and the rotating speed of the engine, and correspondingly, the bad driving behavior is the stopping and accelerator bombing.
4. The method of claim 1, wherein the historical driving data comprises risky driving behavior data of the driver; accordingly, the obtaining of the label for representing the driving habits of the driver based on the historical driving data of the driver comprises:
identifying the in-vehicle behaviors of the driver in the historical time period, and determining the total times of the risky driving behaviors in the historical time period, wherein the risky driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls;
acquiring a label for representing the driving habit of the driver based on a value range in which the total times of the dangerous driving behaviors of the driver in the historical time period fall; the label is any one of the following three types of labels, wherein the following three types of labels are respectively dangerous type, early warning type and safe type.
5. The method of claim 1, wherein the historical driving data includes accumulated fuel consumption and vehicle weight; accordingly, the obtaining of the label for representing the driving habits of the driver based on the historical driving data of the driver comprises:
calculating the ratio of the accumulated oil consumption to the whole vehicle weight;
acquiring a label for representing the driving habit of the driver based on the value range in which the ratio falls; wherein the label is any one of the following three types of labels, wherein the following three types of labels are oil consumption type, general oil consumption type and oil saving type respectively.
6. The method of claim 1, wherein the historical driving data comprises vehicle positioning data; accordingly, the obtaining of the label for representing the driving habits of the driver based on the historical driving data of the driver comprises:
determining, based on the vehicle positioning data, a number of locations traversed by the driver over the historical time period;
acquiring a label for representing the driving habits of the driver based on the number of the places; the label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
7. The method of claim 1, wherein the tags include a driving stability degree tag, a driving risk degree tag, a driving fuel consumption degree tag, and a driving history tag; historical driving data still includes driver's risk driving behavior data, accumulative total oil consumption, whole car weight and vehicle positioning data, correspondingly, based on driver's historical driving data, acquire and be used for the characterization driver driving habit's label includes:
determining the total times of the sudden acceleration and the sudden deceleration in the historical time period according to the acceleration of the driver at each historical moment in the historical time period;
determining the total number of times of sudden turning in the historical time period according to the centripetal acceleration of the driver at each historical moment in the historical time period;
determining the total number of overspeed occurrences in the historical time period according to the speed of the driver at each historical time in the historical time period;
determining the total times of the over-parking accelerator bombing in the historical time period according to the speed and the engine speed of the driver at each historical moment in the historical time period;
summing the total times of over-sharp acceleration and over-sharp deceleration, the total times of sharp turning, the total times of over-speeding and the total times of stopping and accelerator bombing in the historical time period, and acquiring a driving stability degree label for representing the driving habit of the driver based on a value range in which a summation result falls; the driving stability and gravity degree mark is any one of the following three types of labels, wherein the following three types of labels are an aggressive type label, a stable type label and a stable type label;
identifying the in-vehicle behaviors of the driver in the historical time period, and determining the total times of the risky driving behaviors in the historical time period, wherein the risky driving behaviors are any one of the following behaviors, and the following behaviors comprise smoking and making and receiving calls;
acquiring a driving risk degree label used for representing the driving habit of the driver based on a value interval in which the total times of the dangerous driving behaviors of the driver in the historical time period fall; the driving risk degree label is any one of the following three types of labels, wherein the following three types of labels are respectively a dangerous type label, an early warning type label and a safe type label;
calculating a ratio between the accumulated fuel consumption and the vehicle weight;
acquiring a driving fuel consumption degree label used for representing the driving habit of the driver based on the value of the ratio; wherein the driving fuel consumption label is any one of the following three types of labels, namely fuel consumption type, general fuel consumption type and fuel-saving type;
determining, based on the vehicle positioning data, a number of locations traversed by the driver over the historical time period;
acquiring a driving history label for representing the driving habits of the driver based on the number of the places; the driving history label is any one of the following three types of labels, wherein the following three types of labels are respectively rich type, advanced type and new hand type.
8. A driver analytics report pushing apparatus, the apparatus comprising:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring a label for representing the driving habit of a driver based on historical driving data, and the historical driving data comprises bad driving behavior data of the driver;
and the determining module is used for determining the analysis report of the driver according to the label and pushing the analysis report to the first user terminal.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
CN202111006422.6A 2021-08-30 2021-08-30 Method and device for pushing driver analysis report, computer equipment and storage medium Pending CN113762755A (en)

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