CN115630777A - Vehicle driving behavior scoring system based on data collected by vehicle-mounted terminal - Google Patents
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Abstract
The invention provides a vehicle driving behavior scoring system based on data collected by a vehicle-mounted terminal, belonging to the field of big data and Internet of vehicles, comprising: the data storage module is used for storing state data acquired by the vehicle-mounted terminal in the vehicle running process; the multi-source data preprocessing module is used for analyzing, filtering and converting the state data to obtain standardized format data; the multi-source data fusion module is used for fusing format data of different sources to acquire multi-dimensional data of the vehicles at the same moment; the driving behavior calculation module is used for analyzing and extracting driving behavior characteristics from the multi-dimensional data and calculating vehicle driving behavior data through the driving behavior characteristics; and the driving behavior analysis module is used for giving different weights to different vehicle driving behavior data and carrying out comprehensive evaluation on the vehicle driving behavior according to the assignment result. The invention can comprehensively evaluate and analyze the driving behavior of the vehicle according to the state data acquired by the vehicle-mounted terminal in real time, and help a driver to standardize the driving behavior.
Description
Technical Field
The invention belongs to the technical field of big data and Internet of vehicles, and particularly relates to a vehicle driving behavior scoring system based on data collected by a vehicle-mounted terminal.
Background
Research shows that most traffic accidents are caused by illegal operations, and the driving attitude is the decisive factor of traffic safety.
If the historical driving behaviors of the vehicle can be analyzed through technical means, the driving behaviors of a driver can be standardized, and traffic accidents are avoided. Meanwhile, a small number of car owners frequently have traffic accidents, and the payment is high, so that most of the car owners who safely drive bear high premium, and the driving behavior is calculated through the vehicle data acquired by the vehicle-mounted terminal, so that the car insurance pricing scheme can be optimized.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a vehicle driving behavior scoring system based on data collected by a vehicle-mounted terminal, and the existing mode of monitoring and evaluating the driving behavior of a driver by adopting a camera is improved through a vehicle networking big data technology.
In order to achieve the above purpose, the invention provides the following technical scheme:
a vehicle driving behavior scoring system based on data collected by a vehicle-mounted terminal comprises:
the data storage module is used for storing state data acquired by the vehicle-mounted terminal in the vehicle running process;
the multi-source data preprocessing module is used for analyzing, filtering and converting the state data to obtain standardized format data;
the multi-source data fusion module is used for fusing different sources of standardized format data according to a time window to obtain multi-dimensional data of the vehicles at the same moment;
the driving behavior calculation module is used for analyzing and extracting driving behavior characteristics from the multi-dimensional data and calculating vehicle driving behavior data through the driving behavior characteristics;
and the driving behavior analysis module is used for giving different weights to different vehicle driving behavior data and carrying out comprehensive evaluation on the vehicle driving behavior according to the assignment result.
Preferably, the data storage module stores state data, collected by the vehicle-mounted terminal, of the vehicle in the running process by using an Hbase database, wherein the state data comprises switching value data, pulse data, CAN data and GPS data.
Preferably, the standardized format of the switching value data acquisition is as follows: terminal number | data time |0000110010011010100000000111000000000000000000001010000000000000 where 0 indicates that the switch is closed and 1 indicates that the switch is open;
the standardized format of the pulse data acquisition is: a terminal number | data time | pulse vehicle speed | pulse mileage | total number of pulses | pulse rotating speed;
the standardized format for acquiring the CAN data is as follows: terminal number | data time | torque | engine oil temperature | coolant temperature | accelerator pedal opening;
the standardized format for the acquisition of GPS data is: terminal number | data time | latitude and longitude | altitude.
Preferably, the multi-source data fusion module sets a time window according to sampling frequencies of different source data, fuses data collected by different sources, and obtains multi-dimensional data of the vehicle at the same moment, and the data format is as follows: terminal number | data time | torque | engine oil temperature | coolant temperature | accelerator pedal opening | longitude and latitude | altitude
|0000110010011010100000000111000000000000000000001010000000000000| pulse vehicle speed | pulse mileage | total number of pulses | pulse rotational speed.
Preferably, the fusing of the data by the multi-source data fusing module comprises the following steps:
traversing GPS data, and searching switching value data according to the data time of the GPS;
when switching value data with the time equal to that of the GPS data exist, the switching value data are fused into the GPS data;
continuously traversing the GPS data fused with the switching value data, and searching CAN data according to the data time of the GPS;
when CAN data with the time equal to that of the GPS data exist, the CAN data are fused into the GPS data;
continuously traversing the GPS data fused with the CAN data, and searching pulse data according to the data time of the GPS;
and when pulse data with the time equal to that of the GPS data exist, fusing the pulse data into the GPS data to obtain multidimensional fused data of the vehicle at the same time.
Preferably, the fusing of the data by the multi-source data fusing module further comprises:
when the switching value data with the same time as the GPS data does not exist, judging whether the switching value data exist in the switching value adopting period of 3 switching values before and after the GPS data time;
if so, the switching value data with the closest time to the GPS data is fused into the GPS data, otherwise, the switching value data is judged to be lacking, and traversal is finished;
when CAN data with the time equal to that of the GPS data does not exist, judging whether CAN data exist in the sampling period of 3 switching values before and after the GPS data time;
if so, taking CAN data closest to the GPS data time and fusing the CAN data into the GPS data, otherwise judging that the position lacks the CAN data, and ending traversal;
when pulse data with the time equal to that of the GPS data does not exist, judging whether the pulse data exist in the sampling period of 3 switching values before and after the GPS data time;
and if so, fusing the pulse data closest to the GPS data time into the GPS data, otherwise, judging that the bit lacks the pulse data, and ending traversal.
Preferably, the vehicle driving behaviors comprise idling, accelerator pressing, rapid acceleration, rapid deceleration, long-time braking, fatigue driving, rotating speed outside a green area, overspeed, accelerator pressing during parking, and immediate flameout during parking.
Preferably, the vehicle driving behavior data includes the number of times and duration of the vehicle driving behavior.
Preferably, the driving behavior analysis module analyzes and counts the minimum value, the first quartile, the third quartile and the maximum value of each driving behavior according to the boxplot, and calculates the comprehensive score of the driving behavior of the vehicle according to the preset weight to obtain the comprehensive evaluation result of the driving behavior.
Preferably, the driving behavior analysis module analyzes and counts the minimum value, the first quartile, the third quartile and the maximum value of each driving behavior according to the boxplot, and the specific calculation process is as follows:
the first quartile Q1 is equal to the 25 th% of all numerical values in various driving behavior samples after being arranged from small to large;
the third quartile Q3 is equal to the 75% of the numbers of all the numerical values in the various driving behavior samples after being arranged from small to large;
IQR = Q3-Q1, where IQR is the span over which the data falls at the middle 50%;
maximum = Q 3 +1.5IQR
Minimum = Q 1 －1.5IQR。
The vehicle driving behavior scoring system based on the data collected by the vehicle-mounted terminal has the following beneficial effects:
(1) The multi-source data fusion module is used for performing time-dimension structured leveling on the state data of a certain vehicle running state, so that driving behavior indexes can be conveniently calculated in the same time dimension;
(2) The output of the multi-source data fusion module is used as the input of the driving behavior calculation module, so that the driving behavior characteristics of the vehicle are comprehensively covered, and the driving behavior data of the vehicle are obtained through calculation;
(3) The driving behavior analysis module gives different weights to different vehicle driving behavior data, comprehensively evaluates and analyzes the vehicle driving behaviors, helps a driver to standardize the driving behaviors, and avoids traffic accidents.
Drawings
In order to more clearly illustrate the embodiments of the present invention and the design thereof, the drawings required for the embodiments will be briefly described below. The drawings in the following description are only some embodiments of the invention and it will be clear to a person skilled in the art that other drawings can be derived from them without inventive effort.
Fig. 1 is a block diagram of a vehicle driving behavior scoring system based on data collected by a vehicle-mounted terminal according to embodiment 1 of the present invention;
FIG. 2 is a flow diagram of a multi-source data fusion module logic decision;
FIG. 3 is a flow chart of a large throttle logic decision in driving behavior;
FIG. 4 is a box plot schematic;
fig. 5 is a driver score distribution situation.
Detailed Description
In order that those skilled in the art will better understand the technical solutions of the present invention and can practice the same, the present invention will be described in detail with reference to the accompanying drawings and specific examples. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of describing technical solutions of the present invention and simplifying the description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.
Furthermore, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In the description of the present invention, it should be noted that, unless explicitly stated or limited otherwise, the terms "connected" and "connected" are to be interpreted broadly, e.g., as a fixed connection, a detachable connection, or an integral connection; can be mechanically or electrically connected; may be directly connected or indirectly connected through an intermediate medium. 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 description of the present invention, unless otherwise specified, "a plurality" means two or more, and will not be described in detail herein.
Example 1
The invention provides a vehicle driving behavior scoring system based on data collected by a vehicle-mounted terminal, which is specifically shown in figure 1 and comprises a data storage module, a multi-source data preprocessing module, a driving behavior calculation module and a driving behavior analysis module.
Specifically, the data storage module is used for storing state data acquired by the vehicle-mounted terminal in the vehicle running process.
The multi-source data preprocessing module is used for analyzing, filtering and converting the state data to obtain standardized format data.
The multi-source data fusion module is used for fusing the standardized format data of different sources according to the time window to obtain the multi-dimensional data of the vehicle at the same moment.
The driving behavior calculation module is used for analyzing and extracting driving behavior characteristics from the multi-dimensional data and calculating vehicle driving behavior data through the driving behavior characteristics.
And the driving behavior analysis module is used for giving different weights to different vehicle driving behavior data and carrying out comprehensive evaluation on the vehicle driving behavior according to the assignment result.
Further, in this embodiment, the data storage module stores state data in a vehicle running process, which is collected by the vehicle-mounted terminal, by using an Hbase database, wherein the state data includes data such as switching value data, pulse data, CAN data, GPS data, and the like, and CAN perform early warning on dangerous driving behaviors and analyze historical driving behaviors of a driver in real time.
Further, in this embodiment, the standardized format for acquiring the switching value data is as follows: terminal number | data time
L 0000110010011010100000000111000000000000000000001010000000000000 where 0 represents switch closed and 1 represents switch open; here, "terminal number | data time" and a series of subsequent data are the same line data, and belong to a parallel relationship.
The standardized format for pulse data acquisition is: terminal number | data time | pulse vehicle speed | pulse mileage | total number of pulses | pulse rotational speed, etc.
The standardized format for CAN data acquisition is: terminal number | data time | torque | engine oil temperature | coolant temperature | accelerator pedal opening, etc.
The standardized format for GPS data acquisition is: terminal number | data time | longitude and latitude | altitude. Vertical bar segmentation data is a common form of large data storage text format data, and a data processing system can segment data of different fields through vertical bars.
Further, in this embodiment, the multi-source data fusion module sets a time window according to sampling frequencies of different source data, fuses data collected by different sources, and obtains multi-dimensional data of the vehicle at the same time, where the data format is: terminal number | data time | torque | engine oil temperature | coolant temperature | accelerator pedal opening | longitude and latitude | altitude
|0000110010011010100000000111000000000000000000001010000000000000| pulse vehicle speed | pulse mileage | total number of pulses | pulse rotational speed.
Further, in this embodiment, as shown in fig. 2, the fusing of the data by the multi-source data fusing module includes the following steps:
and traversing the GPS data, and searching the switching value data according to the data time of the GPS.
When there is switching amount data equal in time to the GPS data, the switching amount data is fused into the GPS data.
When the switching value data with the same time as the GPS data does not exist, judging whether the switching value data exist in the switching value adopting period of 3 switching values before and after the GPS data time; if so, the switching value data with the closest time to the GPS data is fused into the GPS data, otherwise, the switching value data is judged to be lacking, and traversing is finished.
And continuously traversing the GPS data fused with the switching value data, and searching the CAN data according to the data time of the GPS.
When CAN data with the time equal to that of the GPS data exist, the CAN data are fused into the GPS data;
when CAN data with the time equal to that of the GPS data does not exist, judging whether CAN data exist in the sampling period of 3 switching values before and after the GPS data time; if so, the CAN data closest to the GPS data time is taken and fused into the GPS data, otherwise, the CAN data is judged to be lacking, and the traversal is finished.
And continuously traversing the GPS data fused with the CAN data, and searching pulse data according to the data time of the GPS.
And when pulse data with the time equal to that of the GPS data exist, fusing the pulse data into the GPS data to obtain multidimensional fused data of the vehicle at the same time.
When pulse data with the time equal to that of the GPS data does not exist, judging whether the pulse data exist in the sampling period of 3 switching values before and after the GPS data time; and if so, fusing the pulse data closest to the GPS data time into the GPS data, otherwise, judging that the bit lacks the pulse data, and ending traversal.
The flowchart of fig. 2 describes that the multi-source data fusion module performs fusion processing on data that are not in the same time dimension, and the data are structured into data in a unified time axis, so that driving behavior indexes can be calculated conveniently at the same time. The fusion process takes a time axis with GPS data as a main line and mainly comprises three parts, namely GPS and switching value data matching, GPS and CAN data matching and GPS and pulse data matching.
Further, in this embodiment, the driving behavior of the vehicle includes idling, pressing the accelerator suddenly, accelerating suddenly, decelerating suddenly, braking for a long time, driving fatigue, rotating speed outside the green area, speeding, pressing the accelerator when parking, and stopping immediately.
Further, in this embodiment, the vehicle driving behavior data includes the number of times and duration of the vehicle driving behavior.
The driving behavior calculation module calculates the times and duration of the driving behaviors of the vehicle by analyzing the characteristics of the driving behaviors such as rapid acceleration, rapid deceleration, sudden accelerator stepping, long-time braking, fatigue driving, overspeed, neutral sliding, large accelerator and the like. Fig. 3 is a flow chart of large throttle logic determination in driving behavior, and the number of times of large throttle can be obtained.
Further, in this embodiment, the driving behavior analysis module analyzes and counts the minimum value, the first quartile, the third quartile and the maximum value of each driving behavior according to the boxplot, and calculates a comprehensive score of the driving behavior of the vehicle according to a preset weight to obtain a comprehensive evaluation result of the driving behavior, and the specific calculation process is as follows:
the first quartile Q1 is equal to the 25 th percentile of all values in various driving behavior samples after the values are arranged from small to large.
The third quartile Q3 is equal to the 75 th percentile of all values in various driving behavior samples after being arranged from small to large.
IQR = Q3-Q1, where IQR is the span over which the data falls in the middle 50%.
Maximum = Q 3 +1.5IQR
Minimum = Q 1 －1.5IQR。
The specific calculation rules are shown in the vehicle driving behavior comprehensive scoring table provided in table 1.
TABLE 1 comprehensive evaluation chart of vehicle driving behavior
The multi-source data fusion module performs structured leveling of time dimension on data of a plurality of subject sources through the logic defined by the graph 2, so that driving behavior indexes can be conveniently calculated in the same time dimension; the driving behavior index input by the calculation module comprises multiple aspects of driving behaviors, and the driving behavior index comprehensively covers the driving behavior characteristics of the commercial vehicle; the threshold value of the driving behavior scoring module is set in combination with the distribution of driving behavior index data, such as the score distribution situation of drivers shown in fig. 5, and a reasonable scoring system and rules are set through the score evaluation.
The above-mentioned embodiments are only preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any simple modifications or equivalent substitutions of the technical solutions that can be obviously obtained by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (10)
1. The utility model provides a vehicle driving behavior scoring system based on vehicle-mounted terminal data collection which characterized in that includes:
the data storage module is used for storing state data acquired by the vehicle-mounted terminal in the vehicle running process;
the multi-source data preprocessing module is used for analyzing, filtering and converting the state data to obtain standardized format data;
the multi-source data fusion module is used for fusing different sources of standardized format data according to a time window to obtain multi-dimensional data of the vehicles at the same moment;
the driving behavior calculation module is used for analyzing and extracting driving behavior characteristics from the multi-dimensional data and calculating vehicle driving behavior data through the driving behavior characteristics;
and the driving behavior analysis module is used for giving different weights to different vehicle driving behavior data and carrying out comprehensive evaluation on the vehicle driving behavior according to the assignment result.
2. The vehicle driving behavior scoring system based on data collected by the vehicle-mounted terminal according to claim 1, wherein the data storage module uses an Hbase database to store state data collected by the vehicle-mounted terminal during the running process of the vehicle, and the state data comprises switching value data, pulse data, CAN data and GPS data.
3. The vehicle driving behavior scoring system based on data collected by the vehicle-mounted terminal as claimed in claim 2, wherein the standardized format of the switching value data acquisition is as follows: terminal number | data time |0000110010011010100000000111000000000000000000001010000000000000 where 0 indicates that the switch is closed and 1 indicates that the switch is open;
the standardized format of the pulse data acquisition is: a terminal number | data time | pulse vehicle speed | pulse mileage | total number of pulses | pulse rotating speed;
the standardized format for acquiring the CAN data is as follows: terminal number | data time | torque | engine oil temperature | coolant temperature | accelerator pedal opening;
the standardized format for the acquisition of GPS data is: terminal number | data time | latitude and longitude | altitude.
4. The vehicle driving behavior scoring system based on data collected by the vehicle-mounted terminal according to claim 3, wherein the multi-source data fusion module sets a time window according to sampling frequency of different source data, fuses the data collected by different sources to obtain multi-dimensional data of the vehicle at the same moment, and the data format is as follows: terminal number | data time | torque | engine oil temperature | coolant temperature | accelerator pedal opening | longitude and latitude | altitude
|0000110010011010100000000111000000000000000000001010000000000000| pulse vehicle speed | pulse mileage | total number of pulses | pulse rotational speed.
5. The vehicle driving behavior scoring system based on data collected by the vehicle-mounted terminal according to claim 4, wherein the data fusion by the multi-source data fusion module comprises the following steps:
traversing GPS data, and searching switching value data according to the data time of the GPS;
when switching value data with the time equal to that of the GPS data exist, the switching value data are fused into the GPS data;
continuously traversing the GPS data fused with the switching value data, and searching CAN data according to the data time of the GPS;
when CAN data with the time equal to that of the GPS data exist, the CAN data are fused into the GPS data;
continuously traversing the GPS data fused with the CAN data, and searching pulse data according to the data time of the GPS;
and when pulse data with the time equal to that of the GPS data exist, fusing the pulse data into the GPS data to obtain multidimensional fused data of the vehicle at the same time.
6. The vehicle driving behavior scoring system based on data collected by the vehicle-mounted terminal according to claim 5, wherein the data fusion of the multi-source data fusion module further comprises:
when the switching value data with the same time as the GPS data does not exist, judging whether the switching value data exist in the switching value adopting period of 3 switching values before and after the GPS data time;
if so, fusing the switching value data closest to the time of the GPS data into the GPS data, otherwise, judging that the bit lacks the switching value data, and ending traversal;
when CAN data with the time equal to that of the GPS data does not exist, judging whether CAN data exist in the sampling period of 3 switching values before and after the GPS data time;
if so, fusing CAN data closest to the GPS data time into the GPS data, otherwise judging that the position lacks the CAN data, and ending traversal;
when pulse data with the time equal to that of the GPS data does not exist, judging whether the pulse data exist in the sampling period of 3 switching values before and after the GPS data time;
and if so, fusing the pulse data closest to the GPS data time into the GPS data, otherwise, judging that the bit lacks the pulse data, and ending traversal.
7. The vehicle driving behavior scoring system based on data collected by the vehicle-mounted terminal according to claim 6, wherein the vehicle driving behaviors comprise idling, accelerator being suddenly stepped on, sudden acceleration, sudden deceleration, long-time braking, fatigue driving, rotating speed outside a green area, overspeed, accelerator being stepped on when parking, and flameout when parking.
8. The vehicle driving behavior scoring system based on the data collected by the vehicle-mounted terminal as claimed in claim 7, wherein the vehicle driving behavior data comprises the times and duration of vehicle driving behaviors.
9. The vehicle driving behavior scoring system based on the data collected by the vehicle-mounted terminal as recited in claim 8, wherein the driving behavior analysis module analyzes and counts the minimum value, the first quartile, the third quartile and the maximum value of each driving behavior according to the boxplot, and calculates the comprehensive score of the driving behavior of the vehicle according to the preset weight to obtain the comprehensive evaluation result of the driving behavior.
10. The vehicle driving behavior scoring system based on the data collected by the vehicle-mounted terminal according to claim 9, wherein the driving behavior analysis module analyzes and counts the minimum value, the first quartile, the third quartile and the maximum value of various driving behaviors according to the boxplot, and the specific calculation process is as follows:
the first quartile Q1 is equal to the 25 th% of all numerical values in various driving behavior samples after being arranged from small to large;
the third quartile Q3 is equal to the 75% of the numbers of all the numerical values in the various driving behavior samples after being arranged from small to large;
IQR = Q3-Q1, where IQR is the span over which the data falls at the middle 50%;
maximum = Q 3 +1.5IQR
Minimum = Q 1 －1.5IQR。
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| CN113942521A (en) * | 2021-11-18 | 2022-01-18 | 北京航空航天大学 | Method for identifying style of driver under intelligent vehicle road system |
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| CN117171701A (en) * | 2023-08-14 | 2023-12-05 | 陕西天行健车联网信息技术有限公司 | Vehicle running data processing method, device, equipment and medium |
| CN117171701B (en) * | 2023-08-14 | 2024-05-14 | 陕西天行健车联网信息技术有限公司 | Vehicle running data processing method, device, equipment and medium |
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