CN108205828A - Driver's driving habit analysis system and method - Google Patents
Driver's driving habit analysis system and method Download PDFInfo
- Publication number
- CN108205828A CN108205828A CN201611180751.1A CN201611180751A CN108205828A CN 108205828 A CN108205828 A CN 108205828A CN 201611180751 A CN201611180751 A CN 201611180751A CN 108205828 A CN108205828 A CN 108205828A
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- driving habit
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Classifications
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
Abstract
The present invention discloses a kind of driver's driving habit analysis system and method.The system includes safety air sac controller and the vehicle crash sensor, brake controller, engine controller and the steering controller that are electrically connected.The safety air sac controller includes event recorder and air bag control algolithm module.Event recorder is used to record the vehicle data before and after collision accident occurs, which includes the driving information obtained from vehicle crash sensor, brake controller and engine controller.The corresponding vehicle data of preset collision grade, driver history driving data and data corresponding with driving habit grade are stored in air bag control algolithm module, the vehicle data that air bag control algolithm module is recorded by extracting event recorder, the related data of related data and driving habit grade further according to collision grade, further go out the driving habit of car owner by driver history data analysis, obtain driving habit grade.
Description
Technical field
The present invention relates to vehicle passive safety technical fields, and system is analyzed in particular to a kind of driver's driving habit
System and method.
Background technology
With popularizing for vehicle, more and more traffic accidents all occur in life daily, traffic and automotive safety
Increasingly become the topic of people's care.Meanwhile more and more automobile vendors are also paying close attention to automotive safety problem.Many institute's weeks
Know, the undesirable custom of driving of driver can bring hidden peril of accident, vehicle trouble hidden danger and interior outer personnel's security risk.And
The undesirable behavior of driving is divided into as many kinds, for example, bring to a halt, it is anxious accelerate, step on the gas, optional turning, for a long time closing vehicle window
Deng.Existing traffic monitoring and driving monitoring are primarily directed to the position of automobile, speed or specific violation driving behavior quilt
It is monitored, actively the driver behavior of driver can't be monitored dynamicly, thus cannot effectively prevent dangerous driving
Occur or even after accident generation, can not also be effectively improved situation and avoid accident.
Invention content
For problems of the prior art, it is a primary object of the present invention to provide a kind of driver's driving habit point
Analysis system, the data based on event recorder (EDR, Event Data Recorder) record are analyzed, and obtain driver
Driving habit grade.
According to an aspect of the invention, there is provided a kind of driver's driving habit analysis system, including air bag
Controller and with safety air sac controller be electrically connected vehicle crash sensor, brake controller, engine controller and turn
To system controller.The safety air sac controller further comprises event recorder and air bag control algolithm module.Thing
Part logger is used to record the vehicle data before and after collision accident occurs, which includes from vehicle crash sensor, stops
The driving information that vehicle controller and engine controller obtain.Preset touch is stored in air bag control algolithm module
Hit the corresponding vehicle data of grade, driver history driving data and data corresponding with driving habit grade, air bag control
The vehicle data that algoritic module processed is recorded by extracting event recorder is practised further according to the related data and driving of collision grade
The related data of used grade, the driving habit of car owner is further gone out by driver history data analysis, obtains driving habit etc.
Grade.
As a kind of optional implementation, the driving information includes speed, brake information, engine speed, steering
It is one or more in information, brake pedal frequency and depth.
As a kind of optional implementation, the vehicle data includes the data of near collision and collision accident, root
The data record of different trigger condition trigger records devices is set to work according to different event types.
As a kind of optional implementation, the corresponding vehicle data of grade that collides can be made not according to vehicle difference
Same setting.
As a kind of optional implementation, each collision grade corresponds to different trigger datas, event recorder
Record collision accident and near collision event.
As a kind of optional implementation, event recorder record include collision accident, near collision event and
All data of normal driving event.
As a kind of optional implementation, the driving habit grade is determined according to the collision grade of driver history.
As a kind of optional implementation, the data according to event recorder record judge that the driver is remembering
The number that collision and near collision in the period occur is recorded, different numbers correspond to different driving habit grades.
As a kind of optional implementation, if the number that collision accident and near collision event occur is scheduled less than one
First numerical value, then driving habit grade is excellent；It is small that if the number that collision accident and near collision event occur is more than the first numerical value
In second value, then driving habit grade is good；If the number that collision accident and near collision event occur is more than second value
Less than third value, then driving habit grade is general；If the number that collision accident and near collision event occur is more than third
Numerical value, then driving habit grade is poor.
According to an aspect of the invention, there is provided a kind of driver's driving habit analysis method, drives suitable for described
The person's of sailing driving habit analysis system.Driver's driving habit analysis method includes：
Event recorder is obtained from vehicle crash sensor, brake controller, engine controller and steering controller
Driving information is taken, and records qualified event data；
The data that air bag control algolithm module records event recorder parse；
Judge collision grade；And
Judge driving habit grade, air bag control algolithm module is carried out according to the collision grade and historical data of judgement
Analysis obtains the driving habit grade of driver.
In the optional technical solution of the present invention, vehicle number is recorded by using the event recorder of safety air sac controller
According to, and analyzed, do not increase additional hardware cost.The drive routine that driver is obtained by reversed comprehensive analysis is accustomed to,
There is provided some area for vehicle supervision department and depot, driver's driving habit of region, localization for vehicle and
Applied to following insurance or vehicle supervision department data foundation is provided to the safety evaluation of driver.
Description of the drawings
Attached drawing described herein is used to provide further understanding of the present invention, and forms the part of the present invention, this hair
Bright illustrative embodiments and their description do not constitute improper limitations of the present invention for explaining the present invention.In the accompanying drawings：
Fig. 1 is the module map of driver's driving habit analysis system of a preferred embodiment of the present invention；And
Fig. 2 is the flow chart of driver's driving habit analysis method of a preferred embodiment of the present invention.
Specific embodiment
Come that the present invention will be described in detail below with reference to attached drawing and in conjunction with the embodiments.It should be noted that do not conflicting
In the case of, the feature in embodiment and embodiment in the present invention can be combined with each other.
A kind of driver's driving habit analysis system of present invention offer, the safety air sac controller of foundation vehicle indispensability,
Vehicular data recording function is provided by event recorder (EDR, Event Data Recorder), safety air sac controller leads to
It crosses bus to connect with vehicle, air bag control algolithm module is parsed to obtain the driving of driver to the EDR data recorded
Custom, the data analyzed can be obtained by diagnostic equipment by bus.
Specifically, refering to Figure 1, in a preferred embodiment of the present invention, the analysis of driver's driving habit is
System includes safety air sac controller 11 and vehicle crash sensor 12, brake controller 13, engine controller 14 and steering system
System controller 15.In the present embodiment, safety air sac controller 11 passes through bus and vehicle crash sensor 12, brake controller
13rd, engine controller 14 and steering controller 15 are electrically connected.
Safety air sac controller 11 further comprises EDR 110 and air bag control algolithm module 112.
Wherein, in the present embodiment, EDR 110 is the module belonged in safety air sac controller 11, is responsible for
It records collision accident and front and rear vehicle data occurs, including from vehicle crash sensor 12, brake controller 13 and engine control
One or more in speed, brake information, engine speed, direction information, brake pedal frequency and depth that device 14 processed obtains
Item driving information.
Vehicle data includes the data of near collision and real collision event, can be set according to different event types
Different trigger conditions works to trigger the data record of EDR 110.When the record vehicle operations of EDR 110 are abnormal situation
The CAN data of (bring to a halt, take a sudden turn), switch data, instrument board data etc., which can driving with comprehensive analysis driver
Sail custom.
The algoritic module 112 is also the important module belonged in safety air sac controller 11.Air bag control algolithm
The corresponding vehicle data of preset collision grade is stored in module 112, the driver history of EDR110 extractions drives number
According to and with the corresponding data of driving habit grade.Wherein, driving habit grade is determined according to the collision grade of driver history.
Classification of the driving habit analysis dependent on collision grade, it is in an embodiment of the present invention, described to collide the corresponding vehicle of grade
Data can be different according to vehicle and make different settings.For example, automobile vendor needs to demarcate corresponding vehicle according to sold vehicle
Data, so as to obtain corresponding collision grade according to vehicle.
It is described collision grade for example including：Urgent acceleration/braking events of collisionless danger, near collision event, collision
Event.Each collision grade corresponds to different trigger datas, it is preferable that EDR can only record collision accident and near collision thing
Part.By turning down the trigger data of near collision, EDR can also record all events, i.e., including collision accident, near collision
All data of event and normal driving event.For example, near collision can be defined as by bringing to a halt, taking a sudden turn etc., with really touching
The event of hitting is compared, and near collision danger level is relatively low, and excessive loss, injury does not occur, but due to the driving of driver
Custom is different, and the driving habits that might mean that the driver that near collision occurs not good more.
Pass through the acceleration number of degrees to the not speed of syn-collision level events, brake pedal frequency and depth, crash sensor
According to etc. recorded, further according to collision grade related data and driving habit grade related data, history can be passed through
Data analysis goes out the driving habit of car owner, such as excellent, good, general, poor etc. so as to provide driving habit grade.It can according to the grade
Data analysis is carried out to give traffic department, corresponding drive is formulated and limits, reduce traffic accident.The analysis data can
Also so that insurance department obtains, for the grading to driver, the expense of vehicle insurance can grade according to driver accordingly to be adjusted
It is whole, for example, the lower vehicle insurance expense for needing to pay of driver's grading is more, the awareness of safety of driver is thereby improved, reduces and hands over
The generation of interpreter's event.In addition, the analysis data supply automobile vendor in use, can analyze different geographical driving habit and partially
It is good, so as in Car design, formulate corresponding technical solution to improve vehicle and road safety.
The driving habit grade, such as the driver can be judged in record week according to the data recorded of EDR 110
The number that collision and near collision in phase occur, different numbers correspond to different driving habit grades, if for example, collision accident
And the number that near collision event occurs is less than scheduled first numerical value, then driving habit grade is excellent；If collision accident and
The number that near collision event occurs is more than the first numerical value and is less than second value, then driving habit grade is good；If collision accident
And the number that near collision event occurs is more than second value less than third value, then driving habit grade is general；If collision
The number that event and near collision event occur is more than third value, then driving habit grade is poor.
Specifically, according to the realization logic of above-mentioned driver's driving habit analysis system, the present invention is carried from another angle
For a kind of driver's driving habit analysis method, include the following steps：
S1：EDR 110 records qualified event data.Wherein, in the present embodiment, the event number of the records of EDR 110
According to including near collision and collision accident, that is, meet or exceed the event number of the trigger data of near collision or collision accident
According to.In another embodiment, it can also record EDR 110 arbitrary eligible by turning down the trigger data of near collision
Event data.EDR 110 is from vehicle crash sensor 12, brake controller 13, engine controller 14 and steering control
Device 15 processed obtains driving information, includes but not limited to speed, brake information, engine speed, direction information, brake pedal frequency
Rate and depth.
S2：Air bag control algolithm module 112 parses the data recorded of EDR 110, including extraction vehicle speed
The data such as degree, brake, sensor velocity amplitude, direction information；
S3：Judge collision grade.Air bag control algolithm module 112 according to the data of extraction, and with air bag control
The corresponding vehicle data of preset collision grade of 112 memory storage of algoritic module processed is compared, and judges that current drive is gone
For collision grade, and by the collision level data store.
S4：Judge the driving habit grade of driver.Air bag control algolithm module 112 is according to the collision grade of judgement
And the historical data that EDR 110 is recorded is analyzed, and can judge that the driver is recording according to the data recorded of EDR 110
The number that collision and near collision in period occur, so as to obtain the driving habit grade of driver.
Relative to the prior art, the beneficial effects of the invention are as follows：By the present invention in that the EDR with safety air sac controller 11
110 record data, and analyzed, do not increase additional hardware cost.The daily of driver is obtained by reversed comprehensive analysis
Driving habit provides some area, driver's driving habit of region, for the sheet of vehicle for vehicle supervision department and depot
Ground and be incorporated in future transportation administrative department to driver safety evaluation provide data foundation.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.All within the spirits and principles of the present invention, that is made any repaiies
Change, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (10)
- It is electrical including safety air sac controller and with safety air sac controller 1. a kind of driver's driving habit analysis system Vehicle crash sensor, brake controller, engine controller and the steering controller of connection, it is characterised in that：It is described Safety air sac controller further comprises event recorder and air bag control algolithm module；Event recorder touches for recording It hits event and front and rear vehicle data occurs, which is included from vehicle crash sensor, brake controller and engine control The driving information that device processed obtains；The corresponding vehicle number of preset collision grade is stored in air bag control algolithm module Pass through extraction according to, driver history driving data and data corresponding with driving habit grade, air bag control algolithm module The vehicle data of event recorder record, the related data of related data and driving habit grade further according to collision grade, Further go out the driving habit of car owner by driver history data analysis, obtain driving habit grade.
- 2. driver's driving habit analysis system according to claim 1, which is characterized in that the driving information includes vehicle It is one or more in speed, brake information, engine speed, direction information, brake pedal frequency and depth.
- 3. driver's driving habit analysis system according to claim 1 or 2, which is characterized in that the vehicle data packet Data containing near collision and collision accident set different trigger condition trigger records according to different event types The data record work of device.
- 4. driver's driving habit analysis system according to claim 1, which is characterized in that the collision grade is corresponding Vehicle data can make different settings according to vehicle difference.
- 5. driver's driving habit analysis system according to claim 3, which is characterized in that each collision grade pair Answer different trigger datas, event recorder record collision accident and near collision event.
- 6. driver's driving habit analysis system according to claim 3, which is characterized in that the event recorder record Include all data of collision accident, near collision event and normal driving event.
- 7. driver's driving habit analysis system according to claim 1, which is characterized in that the driving habit grade root It is determined according to the collision grade of driver history.
- 8. according to claim 3-7 any one of them driver's driving habit analysis systems, which is characterized in that according to the thing The data of part logger record judge the number that collision and near collision of the driver in record period occur, not homogeneous The corresponding different driving habit grade of number.
- 9. driver's driving habit analysis system according to claim 8, which is characterized in that if collision accident and approximation are touched The number for hitting event generation is less than scheduled first numerical value, then driving habit grade is excellent；If collision accident and near collision The number that event occurs is more than the first numerical value and is less than second value, then driving habit grade is good；If collision accident and approximation are touched The number for hitting event generation is more than second value less than third value, then driving habit grade is general；If collision accident and near It is more than third value like the number that collision accident occurs, then driving habit grade is poor.
- 10. a kind of driver's driving habit analysis method, suitable for claim 1,2,4-7 and 9 any one of them drivers Driving habit analysis system, which is characterized in that driver's driving habit analysis method includes：Event recorder is driven from the acquisition of vehicle crash sensor, brake controller, engine controller and steering controller Information is sailed, and records qualified event data；The data that air bag control algolithm module records event recorder parse；Judge collision grade；AndJudge driving habit grade, air bag control algolithm module is divided according to the collision grade and historical data of judgement Analysis obtains the driving habit grade of driver.
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| CN201611180751.1A CN108205828A (en) | 2016-12-20 | 2016-12-20 | Driver's driving habit analysis system and method |
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| CN201611180751.1A CN108205828A (en) | 2016-12-20 | 2016-12-20 | Driver's driving habit analysis system and method |
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| CN109147088A (en) * | 2018-07-17 | 2019-01-04 | 苏州车付通信息科技有限公司 | Intelligent driving behavioral data collector and acquisition method |
| CN109164788A (en) * | 2018-09-05 | 2019-01-08 | 苏州车付通信息科技有限公司 | Driving behavior acquisition system and its acquisition method |
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| CN111415437A (en) * | 2020-03-27 | 2020-07-14 | 大陆汽车电子（连云港）有限公司 | Collision event recording system and method |
| CN115601854A (en) * | 2022-09-29 | 2023-01-13 | 上海蕴业信息科技有限公司（Cn） | Driving behavior recording and analyzing equipment and system |
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Application publication date: 20180626 |