CN111612334A - Driving behavior risk rating judgment method based on Internet of vehicles data - Google Patents
Driving behavior risk rating judgment method based on Internet of vehicles data Download PDFInfo
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- CN111612334A CN111612334A CN202010431440.8A CN202010431440A CN111612334A CN 111612334 A CN111612334 A CN 111612334A CN 202010431440 A CN202010431440 A CN 202010431440A CN 111612334 A CN111612334 A CN 111612334A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/14—Receivers specially adapted for specific applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Abstract
The invention discloses a method for judging driving behavior risk rating based on Internet of vehicles data, which comprises the steps of collecting GPS satellite positioning data of a vehicle through a road transport vehicle satellite positioning system terminal; primarily processing GPS satellite data obtained by a terminal to obtain travel data; processing the travel data and obtaining risk factor data; scoring a risk of a vehicle driving behavior; a risk rating of the driving behavior of the vehicle is determined. According to the invention, the risk of the vehicle in the driving process is judged by analyzing the vehicle internet of vehicles data, so that the prevention consciousness of the driver on the driving risk is improved. Meanwhile, the invention improves the supervision on the driving safety of the vehicle and enhances the accuracy and stability of subsequent applications such as driving behavior analysis application and the like.
Description
Technical Field
The invention relates to a risk rating judging method, in particular to a driving behavior risk rating judging method based on Internet of vehicles data, and belongs to the technical field of Internet of vehicles data and driving behaviors.
Background
In modern life, widespread use of internet of vehicles data has benefited government regulators, insurance companies, host plants, automotive after-services and vehicle owners. The method strictly supervises the vehicles and guarantees the driving safety of the vehicles, is one of the problems which are hopefully solved by all the circles of the modern society, and the existing analysis method for the vehicle networking data cannot effectively supervise the vehicles and guarantee the road driving safety. Meanwhile, the accuracy and stability of subsequent applications such as driving behavior analysis application are also poor.
Disclosure of Invention
The present invention is directed to solving the above problems and providing a method for determining a driving behavior risk rating based on internet-of-vehicles data.
The invention realizes the purpose through the following technical scheme: a driving behavior risk rating judging method based on Internet of vehicles data comprises the following steps:
(1) collecting GPS satellite positioning data of the vehicle through a road transport vehicle satellite positioning system terminal;
(2) primarily processing the GPS satellite data obtained by the terminal to obtain travel data;
(3) processing the travel data and obtaining risk factor data;
(4) scoring the risk of the vehicle driving behavior;
(5) and judging the risk rating of the driving behavior of the vehicle.
As a further scheme of the invention: the GPS satellite positioning data of the vehicle collected by the road transport vehicle satellite positioning system terminal is as follows: the GPS satellite positioning data collected at the terminal comprises satellite positioning longitude, satellite positioning latitude, satellite positioning time, satellite positioning speed and satellite positioning direction.
As a further scheme of the invention: the step of obtaining the travel data by preliminarily processing the GPS satellite positioning data obtained by the terminal comprises the following steps:
A. carrying out stroke segmentation on the GPS satellite positioning data;
B. extracting stroke characteristics from the data after the stroke segmentation, wherein the stroke characteristics comprise a stroke running distance, a stroke running time, a stroke average speed, a stroke maximum speed, a stroke starting time, a stroke ending time, a stroke starting point longitude and latitude and a stroke ending point longitude and latitude;
as a further scheme of the invention: the step of processing the trip data and obtaining the risk factor data comprises:
C. filtering the travel data and reserving effective travel data;
D. n risk factors are extracted for the active trip data, which may include total distance traveled, total length of travel, average speed, start time, end time, and the like.
As a further scheme of the invention: the step of scoring the risk of vehicle driving behavior comprises:
E. observing the distribution of each risk factor, and dividing each risk factor into miAnd (4) grouping. Divide each risk factor group by sij，i＝1，2，3，...，n，j＝1，2，3，...，mi；
F. According to the formula
Calculating scores s of various factors of the vehiclei. When the ith risk factor of the vehicle belongs to the jth group, the ith risk of the vehicle is divided into s in the jth group by the factorijAnd a score of zero in the remaining groups, thus the vehicle ith factor score siIs s isij。
G. Defining each risk factor as a weight wi1, 2, 3, n, according to the formula
And obtaining the driving behavior score of the vehicle. The scoring range is 0 to 100 points, and higher scoring indicates lower risk of driving the vehicle.
As a further scheme of the invention: the step of determining a risk rating for driving behavior of the vehicle comprises:
H. and establishing a corresponding relation between the rating and the score. There are five risk ratings, A, B, C, D, E for risk in order from low to high. Score greater than a1And is less than or equal to 100 points, and the rating is A; score greater than a2And is less than or equal to a1And grading as B; score greater than a2And is less than or equal to a1Grading to be C; score greater than a3And is less than or equal to a2Grading as D; a score of greater than 0 and less than or equal to a3And the score is E.
I. And judging the risk level of the vehicle. Preferably, step I further comprises:
1) judging whether the vehicle driving behavior score is larger than a1And is less than or equal to 100 points, if yes, the driving behavior of the vehicle is rated as A; if not, executing the step 2);
2) judging whether the vehicle driving behavior score is larger than a2And is less than or equal to a1If yes, the driving behavior of the vehicle is rated as B; if not, executing the step 3);
3) judging whether the vehicle driving behavior score is larger than a3And is less than or equal to a2If yes, the driving behavior of the vehicle is rated as C; if not, executing the step 4);
4) judging whether the vehicle driving behavior score is larger than a3And is less than or equal to a4If yes, grading the driving behavior of the vehicle as D; if not, the driving behavior of the vehicle is graded as E, and the driving behavior of the next vehicle is graded to execute the step 1).
The invention has the beneficial effects that: the judgment method for the driving behavior risk rating based on the vehicle networking data is reasonable in design, based on analysis of the vehicle networking data, quantitative analysis is given to risks of vehicles in the driving process, and an important reference basis is provided for reducing the driving risks. Further, the invention further helps the supervision department and the insurance company to identify the driving behavior risk by rating the driving behavior. The method and the device can enhance the accuracy and stability of subsequent applications such as driving behavior analysis application, travel analysis drawing application and the like.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating an embodiment of a driving behavior risk determination method using Internet of vehicles data according to the present invention;
FIG. 2 is a schematic flow chart illustrating a process of obtaining travel data for GPS satellite positioning data obtained by a preliminary processing terminal according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart illustrating a process of obtaining risk factor data for processing travel data according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart of a method for scoring a risk of vehicle driving behavior according to an embodiment of the present invention;
FIG. 5 is a flow diagram illustrating a risk rating for determining vehicle driving behavior according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1 to 5, a method for determining a driving behavior risk rating based on internet of vehicles data includes the following steps:
in step S10, GPS satellite positioning data is obtained.
In this embodiment, the GPS satellite positioning data includes: the satellite positioning latitude, the satellite positioning time, the satellite positioning speed and the satellite positioning direction. Step S20, primary processing and warehousing;
in step S20, trip data is obtained.
As shown in fig. 2, the method comprises the following steps:
s2001: carrying out stroke segmentation on the GPS satellite positioning data;
s2002: extracting stroke characteristics from the data after the stroke segmentation, wherein the stroke characteristics comprise a stroke running distance, a stroke running time, a stroke average speed, a stroke maximum speed, a stroke starting time, a stroke ending time, a stroke starting point longitude and latitude and a stroke ending point longitude and latitude;
step S30, the trip data is processed and risk factor data is obtained.
As shown in fig. 3, the method comprises the following steps:
s3001: with respect to the trip data of step S20, it is determined whether the trip travel time period of the current trip data is greater than a set threshold value. If yes, sequentially executing step S3002; if not, marking as an invalid trip, and repeatedly executing the step S3001 on the next trip data;
s3002: and judging whether the driving mileage of the current travel data is larger than a set threshold value. If yes, marking as an effective stroke, and sequentially executing the step S3003; if not, marking as an invalid stroke, and repeatedly executing the step S3001 on the next stroke data;
s3003: calculating n risk factors of the effective travel data in the step S3002, such as the total travel distance, the total travel time, the average speed, the start time, the end time, and the like;
and step S40, scoring the risk of the driving behavior of the vehicle.
As shown in fig. 4, the method comprises the following steps:
s4001: for the risk factor data of step S30, the decile Q of each risk factor is calculatediI is 0, 1, 2, 10, and step S4002 is sequentially performed;
s4002: each risk factor was divided into 10 groups, each of which was [ Q ]0,Q1]、[Q1,Q2]、[Q2,Q3]、[Q3,Q4]、 [Q4,Q5]、[Q5,Q6]、[Q6,Q7]、[Q7,Q8]、[Q8,Q9]、[Q9,Q10]、[Q0,Q1]Score each risk factor sub-group by Sij1, 2, 3.. n, j 1, 2, 3.. 10. Step S4003 is sequentially executed.
S4003: calculating the score of each factor of a certain vehicleAnd driving behavior scoring. When the ith risk factor of the vehicle belongs to [ Qj，Qj+1]When j is 0, 1, 2, 3, 9, the vehicle ith risk score is SijAnd a score of zero in the remaining groups, according to the formula:
calculating the score S of each factor of the vehiclei. So the ith factor score S of the vehicleiIs Sij. Step S4004 is sequentially performed.
S4004: calculating a weight W that specifies each risk factori1, 2, 3,.., n, in accordance with the formula:
and obtaining a vehicle driving behavior score. The scoring range is 0 to 100 points, and the higher the scoring is, the lower the driving risk of the vehicle is. Step S4003 is sequentially performed for the next vehicle.
Step S50, a risk rating of the driving behavior of the vehicle is determined. As shown in fig. 5, the method comprises the following steps:
s5001: for the score data of step S40, 20 quantiles were calculated, each Q20，Q40，Q60，Q80。
S5002: judging whether the vehicle driving behavior score is greater than Q80And is less than or equal to 100 points, if yes, the driving behavior of the vehicle is rated as A; if not, step S5003 is executed.
S5003: judging whether the vehicle driving behavior score is greater than Q60And is less than or equal to Q80If yes, the driving behavior of the vehicle is rated as B; if not, step S5004 is executed.
S5004: judging whether the vehicle driving behavior score is greater than Q40And is less than or equal to Q60If yes, the driving behavior of the vehicle is rated as C; if not, step S5005 is executed.
S5005: judgment vehicleWhether the vehicle driving behavior score is greater than Q20And is less than or equal to Q40If yes, the driving behavior of the vehicle is graded as D; if not, the vehicle driving behavior is ranked as E, and step S5002 is performed on the driving behavior score of the next vehicle.
The working principle is as follows: when the method for judging the driving behavior risk rating based on the vehicle networking data is used, the risk of a vehicle in the driving process is judged through analysis of the vehicle networking data, and the prevention consciousness of a driver to the driving risk is improved. Meanwhile, the invention improves the monitoring and management on the driving safety of the vehicle and enhances the accuracy and stability of subsequent applications such as driving behavior analysis application and the like.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art will be able to make the description as a whole, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (6)
1. A driving behavior risk rating judging method based on Internet of vehicles data is characterized in that: the method comprises the following steps:
(1) acquiring GPS satellite positioning data of the vehicle through a road transport vehicle satellite positioning system terminal;
(2) primarily processing the GPS satellite data obtained by the terminal to obtain travel data;
(3) processing the travel data and obtaining risk factor data;
(4) scoring the risk of the vehicle driving behavior;
(5) and judging the risk rating of the driving behavior of the vehicle.
2. The method for determining the risk rating of driving behavior based on internet of vehicles data as claimed in claim 1, wherein: the GPS satellite positioning data of the vehicle collected by the road transport vehicle satellite positioning system terminal is as follows: the GPS satellite positioning data collected at the terminal comprises satellite positioning longitude, satellite positioning latitude, satellite positioning time, satellite positioning speed and satellite positioning direction.
3. The method for determining the risk rating of driving behavior based on internet of vehicles data as claimed in claim 1, wherein: the step of obtaining the travel data by preliminarily processing the GPS satellite positioning data obtained by the terminal comprises the following steps:
A. carrying out stroke segmentation on the GPS satellite positioning data;
B. and extracting stroke characteristics from the data after the stroke segmentation, wherein the stroke characteristics comprise a stroke running distance, a stroke running duration, a stroke average speed, a stroke maximum speed, a stroke starting time, a stroke ending time, a stroke starting point longitude and latitude and a stroke ending point longitude and latitude.
4. The method for determining the risk rating of driving behavior based on internet of vehicles data as claimed in claim 1, wherein: the step of processing the trip data and obtaining the risk factor data comprises:
C. filtering the travel data and reserving effective travel data;
D. extracting n risk factors for the effective travel data, which may include total travel distance, total travel time, average speed, start time, and end time.
5. The method for determining the risk rating of driving behavior based on internet of vehicles data as claimed in claim 1, wherein: the step of scoring the risk of vehicle driving behavior comprises:
E. observing the distribution of each risk factor, and dividing each risk factor into miAnd (4) grouping. Score each risk factor group sij，i＝1，2，3，...，n，j＝1，2，3，...，mi；
F. According to the formula
Calculating scores s of various factors of the vehiclei. When the ith risk factor of the vehicle belongs to the jth group, the ith risk of the vehicle is divided into s in the jth group by a factorijAnd a score of zero in the remaining groups, thus the vehicle ith factor score siIs s isij。
G. Defining each risk factor as a weight wi1, 2, 3, n, according to the formula
And obtaining a vehicle driving behavior score. The score ranges from 0 to 100, with higher scores indicating lower risk of vehicle driving.
6. The method for determining the risk rating of driving behavior based on internet of vehicles data as claimed in claim 1, wherein: the step of determining a risk rating for driving behavior of the vehicle comprises:
H. and establishing a corresponding relation between the rating and the score. There are five risk ratings, A, B, C, D, E for risk from low to high. Score greater than a1And is less than or equal to 100 points, and the rating is A; score greater than a2And is less than or equal to a1And grading as B; score greater than a2And is less than or equal to a1Grading to be C; score greater than a3And is less than or equal to a2Grading as D; a score of greater than 0 and less than or equal to a3And grading as E;
I. and judging the risk level of the vehicle. Preferably, step I further comprises:
1) judging whether the vehicle driving behavior score is larger than a1And is less than or equal to 100 points, if yes, the driving behavior of the vehicle is rated as A; if not, executing the step 2);
2) judging whether the vehicle driving behavior score is larger than a2And is less than or equal to a1If yes, the driving behavior of the vehicle is graded as B; if not, executing the step 3);
3) judging whether the vehicle driving behavior score is larger than a3And is less than or equal to a2If yes, the driving behavior of the vehicle is rated as C; if not, executing the step 4);
4) judging whether the vehicle driving behavior score is larger than a3And is less than or equal to a4If yes, the driving behavior of the vehicle is graded as D; if not, the driving behavior of the vehicle is graded as E, and the driving behavior of the next vehicle is graded to execute the step 1).
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