CN106585636A - Method for vehicle running state description and driving behavior detection based on state machine - Google Patents
Method for vehicle running state description and driving behavior detection based on state machine Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
- B60W40/107—Longitudinal acceleration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
- B60W40/109—Lateral acceleration
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/0097—Predicting future conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
- B60W2050/143—Alarm means
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
- B60W2520/105—Longitudinal acceleration
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/12—Lateral speed
- B60W2520/125—Lateral acceleration
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- Automation & Control Theory (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Feedback Control In General (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention relates to a method for vehicle running state description and driving behavior detection based on a state machine. The method uses a finite state machine to describe driving behavior, collects data in the car running process through a triaxial acceleration sensor, constructs a finite state machine model in the process, and finally realizes detection and warning of the situation whether to slow down before turning and of frequent lane changing behavior, so as to guarantee the safety of a driver and a vehicle. Compared with the prior art, the method provided by the invention not only can carry out warning on the driving behavior of the driver in real time, but also can reasonably carry out judgment on the driving behavior habit of the driver, thereby guaranteeing the safety of the driver and the vehicle from both short-term and long-term aspects.
Description
Technical field
The present invention relates to a kind of method of vehicle running state description and driving behavior detecting, is based on more particularly, to one kind
The method of vehicle running state description and the driving behavior detecting of state machine.
Background technology
Automobile industry is highly developed in exploitation passive security technical elements, and passive security technology is passed through and developed and complete
It is kind, with the equipment such as seat belt, air bag, children's seat popularization and use, personnel are made vehicle accident is effectively reduced
Into injury, reduce casualty rate aspect play a significant role.But, at present, the effect of passive security technology is
Close saturation.To strengthen road safety, the incidence rate of vehicle accident is reduced, even preventing the generation of accident, it is necessary to which exploitation is actively
Safe practice.The key of active safety is to allow vehicle to become more " intelligence ", the danger that may occur is predicted in advance, by advance
Warning, is that driver wins the valuable response time, while assisting driver to take more quick response speed.
In passive security technology, how to model driving behavior is an important research contents.
The content of the invention
The purpose of the present invention provides a kind of based on state machine for the defect for overcoming above-mentioned prior art to exist
The method that vehicle running state is described and driving behavior is detected, driving condition, finite state machine are described using finite state machine
It is the mathematical model for representing the behaviors such as limited state and transfer between these states and action；By using limited shape
State machine is a kind of method of brand-new description driving behavior describing driving behavior；In effect, using standing state machine
Can effectively help realize detecting, the early warning to during car steering to whether slowing down with frequent lane change behavior before turning.
The purpose of the present invention can be achieved through the following technical solutions：
A kind of method of the vehicle running state description and driving behavior detecting based on state machine, it is characterised in that use
Finite state machine gathers the data in the middle of vehicle traveling process by 3-axis acceleration sensor describing driving behavior, and
Thus finite state machine model is built, and final detecting, the early warning for realizing whether slowing down with frequent lane change behavior before to turning,
Ensure the safety of driver and vehicle.
The method realizes that process is：
3-axis acceleration sensor is installed onboard, data of the vehicle under transport condition are measured；Then, data are entered
Row smoothing techniques, calculate the change slope curve of data, and setting up membership function carries out Fuzzy processing, and construction two is limited
State machine analyzes the transport condition of car to detect；The detecting analysis result whether slowed down before turning and frequent lane change behavior detecting point
Analysis result when dangerous driving behavior occurs, can effectively send alarm, lift driving safety, reduce accident rate.
It is as follows that the method implements process：
The first step：Come the acceleration and angular velocity of Real-time Collection automobile using 3-axis acceleration sensor；
Second step：Restless are eliminated by median smoothing filtering to the data of 3-axis acceleration sensor collection；
3rd step：According to the acceleration and deceleration of automobile and the slow degree of the urgency of left/right rotation, by the acceleration slope for calculating output, come
Judge the driving states of motor vehicles；
4th step：The foundation of membership function is carried out to driving states according to fuzzy control theory, domain is taken for [- 5-4
-3 -2 -1 0 1 2 3 4 5]；
5th step：Membership function is selected, according to X, the respective five kinds of situations of Y-axis, 25 fuzzy rules for forming 5*5 will
X, the acceleration output valve filtering post processing of Y-axis output, then calculate X through linear regression coeffficient, each dot frequency of Y-axis,
So as to draw driving states obfuscation output state figure, the transport condition of vehicle is judged according to fuzzy rule inquiry table, and according to
25 kinds of combinations of states actual acquisitions turning of state table is not slowed down, frequent lane change whether data draw the shape that vehicle is travelled
State figure.
Described 3-axis acceleration sensor exports in digital form the spin matrix of 6 axles, quaternary number, Eulerian angles forms
Fusion calculation data, and 16 bit resolutions are carried out to the up to acceleration of ± 16g and the angular velocity of ± 2000 °/sec (dps)
Measurement.
Three described shaft speed sensors in the X-axis direction more than 0 value be acceleration mode, less than null value be deceleration regime, Y
Direction of principal axis, to turn left, is worth to turn right more than 0 value less than 0.
3-axis acceleration sensor in the described first step is with reference to 3-axis acceleration sensor and three-axis gyroscope
Sensor, it is adaptable to mobile device, the acceleration and angular velocity of Real-time Collection mobile device；Described 3-axis acceleration sensing
The output direction of principal axis of device includes three directions of x-axis, y-axis and z-axis, and according to the position put the tool of each direction of principal axis output data is determined
Body implication, when static, ideally has two axles to be output as 0g, and the output of another axle is determined according to the position put
Output, the output -9.8g if identical with acceleration of gravity direction exports 9.8g if contrary.
The use of medium filtering is the optimal filter under " least absolute error " criterion, to one in described second step
Digital signal xjWhen (- ∞ ＜ j ＜+∞) is filtered process, first have to define L long window of the length for odd number, L=2N
+ 1, N are positive integer；Some moment is located at, the sample of signal in window is x (i-N) ..., and x (i) ... x (i+N), x (i) are
Positioned at the sample of signal value of window center, after arranging by order from small to large this L sample of signal value, its intermediate value, at i
Sample value, be just defined as the output valve of medium filtering, and it is restless finally to realize that smoothing processing is eliminated.
In the middle of the 3rd described step, output voltage gradient formula is calculated as follows
Wherein t is t-th discrete time point, and x (t) is the output valve of t, through constantly testing to m window values, most
After can obtain exit window and export 25 values, the slope of output is the most reasonable.
In the middle of the 4th described step, for the acceleration curve of output slope of acceleration transducer X-axis, five kinds of differences are defined
The fuzzy set of degree：
X-axis acceleration curve of output slope=it is anxious to slow down, slow down, normally, accelerate, anxious to accelerate
For the acceleration curve of output slope of acceleration transducer Y-axis, five kinds of different degrees of fuzzy sets are also defined：
Y-axis acceleration=it is big to turn right, turn right, normally, turn left, turn left greatly
Define 25 fuzzy control planning；
For X-axis accelerating curve slope and each 5 kinds of degree of Y-axis acceleration curve of output slope in the middle of the 5th described step
Fuzzy set, rule query table such as table 1 is obscured in 25 will being formed, running state of automotive vehicle is just drawn by rule list,
Table 1
By X, the acceleration output valve filtering post processing of Y-axis output, then X is calculated through linear regression coeffficient, Y-axis
Each dot frequency, so as to draw driving states obfuscation output state figure, according to fuzzy rule inquiry table the row of vehicle is just can determine whether
Sail state.
Compared with prior art, the present invention except can in real time to the driving behavior early warning of driver in addition to, can also close
Reason ground is passed judgment on the vehicular behavior custom of driver, and the safety of driver and vehicle is ensured in terms of short-term and long-term two.
Description of the drawings
Fig. 1 is original acceleration signal curve chart；
Fig. 2 is smoothing processing post-acceleration signal curve figure；
Fig. 3 is linear regression post-acceleration slope curve figure；
Fig. 4 is the membership function figure of X-axis acceleration signal；
Fig. 5 is the membership function figure of Y-axis acceleration signal；
Fig. 6 is the state diagram of vehicle traveling；
Fig. 7 is the state diagram of non-deceleration regime machine before turning；
Fig. 8 is flow chart of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawings the present invention is described in detail with specific embodiment.
Embodiment
This method utilizes the acceleration transducer of autonomous Design, while gathering the acceleration information of two different directions.Will
The harvester is installed onboard, measures data of the vehicle under transport condition.Then, smoothing techniques are carried out to data, is counted
The change slope curve of the evidence that counts, setting up membership function carries out Fuzzy processing, and two finite state machines of construction are detecting point
The transport condition of analysis car.The acceleration information of two of which different directions can be used as |input paramete, by median filtering algorithm
To realize the Error processing to data, the calculating that the data for optimizing carry out slope curve is ensured into stablizing for acceleration, while
Carry out the final finite state machine for realizing description vehicle running state of Fuzzy Processing matching based on membership function.
The first step, according to the concrete meaning for setting the position that sensor puts certainly and determining each direction of principal axis output data.Static
When, ideally there are two axles to be output as 0g, the output of another axle determines output according to the position put, and if gravity
The identical then output -9.8g in acceleration direction, if contrary 9.8g is exported.It is 3 data that sensor is sent to the data of single-chip microcomputer
Bag, respectively acceleration bag, angular velocity bag and angle bag, three packet Sequential outputs.Thus, single-chip microcomputer is obtained from sets sensing
The acceleration when driving of device collection and angular velocity and angle, and data process＆analysis are carried out to it, finally give
The state of running car.
Second step, because the accekeration that 3-axis acceleration sensor is exported under plateau is near 0 value, with pendulum
The value of the different outputs in position put also has a little fluctuation, and the velocity sensor is in the X-axis direction acceleration mode more than 0 value,
It is deceleration regime less than null value, Y direction, to turn left, less than 0 value to turn right, is read more than 0 value by acceleration transducer
Data can cause some to fluctuate due to outside some factors.Therefore to a digital signal xj(- ∞ ＜ j ＜+∞) is filtered
During process, first have to define L long window of the length for odd number, L=2N+1, N are positive integer.It is located at some moment, window
Sample of signal in mouthful is x (i-N) ..., and x (i) ... x (i+N), x (i) are the sample of signal value positioned at window center.To this L
After individual sample of signal value is by order arrangement from small to large, its intermediate value, the sample value at i is just defined as the output of medium filtering
Value.Fig. 1 and Fig. 2 is respectively the raw experimental data curve and the data and curves after median smoothing process for reading.
3rd step, when running state of automotive vehicle is analyzed, pays close attention to the slow degree of the urgency of acceleration and deceleration and left/right rotation of automobile, so
By calculate output acceleration slope it may determine that the enforcement state of motor vehicles, from the theoretical derivation of method of least square
Go out one-variable linear regression slope calculations.
Wherein t is t-th discrete time point, and x (t) is the output valve of t, through constantly testing to m window values, most
After can obtain exit window and export 25 values, the slope of output is the most reasonable.It is as shown in Figure 3 by being calculated corresponding output voltage gradient.
Driving states are carried out the foundation of membership function by the 4th step, take domain for [- 5-4-3-2-1 0123
4 5],
For the acceleration curve of output slope of acceleration transducer X-axis, five kinds of different degrees of fuzzy sets are defined：
X-axis acceleration curve of output slope=it is anxious to slow down, slow down, normally, accelerate, anxious to accelerate
For the acceleration curve of output slope of acceleration transducer Y-axis, five kinds of different degrees of fuzzy sets are also defined：
Y-axis acceleration=it is big to turn right, turn right, normally, turn left, turn left greatly
Define 25 fuzzy control planning.Here membership function is from conventional rectangle membership function, its X-axis with
Y-axis membership function such as Fig. 4, shown in Fig. 5；
5th step, selects first membership function, and according to X, the respective five kinds of situations of Y-axis, can form 5*5 25 obscure
Rule, its fuzzy rule inquiry table is as follows, the transport condition under serial number automobile different situations.
For X-axis accelerating curve slope and the fuzzy set of each 5 kinds of degree of Y-axis acceleration curve of output slope, will
Rule query table such as table 1 is obscured in forming 25, running state of automotive vehicle can just be drawn by rule list.By X, Y-axis output
Acceleration output valve filtering post processing, then calculate X, each dot frequency of Y-axis, such that it is able to draw through linear regression coeffficient
Driving states obfuscation output state figure.According to fuzzy rule inquiry table it may determine that the transport condition of vehicle.
According to 25 kinds of combinations of states actual acquisitions of above state table turn do not slow down, frequent lane change whether data
The state diagram for drawing vehicle traveling is as shown in Figure 6
6th step, under normal behaviour people's normally travel state, can all make some preparation shapes before next action is made
State, for example running into turning can lower road speed, and the finite state analysis machine that we design is exactly that detecting vehicle is being turned
Whether front to slow down, the input of state machine is vehicle running state numbering, and output 1 is precarious position, and output 0 is safe condition, is detectd
The state table of state before turning is surveyed as shown in table 2 and table 3, state diagram is as shown in Figure 7.
Table 2
Table 3
Above step may be referred to Fig. 8, intuitively give the implementing procedure of the present invention.Can be had using standing state machine
Effect ground helps realize detecting, the early warning to during car steering to whether slowing down with frequent lane change behavior before turning.
Claims (9)
1. a kind of method of the vehicle running state description and driving behavior detecting based on state machine, it is characterised in that using having
Limit state machine gathers the data in the middle of vehicle traveling process by 3-axis acceleration sensor describing driving behavior, and by
This builds finite state machine model, and final detecting, the early warning for realizing whether slowing down with frequent lane change behavior before to turning, and protects
Barrier driver and the safety of vehicle.
2. method according to claim 1, it is characterised in that the method realizes that process is：
3-axis acceleration sensor is installed onboard, data of the vehicle under transport condition are measured；Then, data are put down
Cunningization process, calculates the change slope curve of data, and setting up membership function carries out Fuzzy processing, constructs two finite states
Machine analyzes the transport condition of car to detect；The detecting analysis result whether slowed down before turning and frequent lane change behavior detecting analysis knot
Fruit when dangerous driving behavior occurs, can effectively send alarm, lift driving safety, reduce accident rate.
3. method according to claim 2, it is characterised in that it is as follows that the method implements process：
The first step：Come the acceleration and angular velocity of Real-time Collection automobile using 3-axis acceleration sensor；
Second step：Restless are eliminated by median smoothing filtering to the data of 3-axis acceleration sensor collection；
3rd step：According to the acceleration and deceleration of automobile and the slow degree of the urgency of left/right rotation, judged by calculating the acceleration slope of output
The driving states of motor vehicles；
4th step：The foundation of membership function is carried out to driving states according to fuzzy control theory, take domain for [- 5-4-3-
2 -1 0 1 2 3 4 5]；
5th step：Membership function is selected, according to X, the respective five kinds of situations of Y-axis form 25 fuzzy rules of 5*5 by X, Y
The acceleration output valve filtering post processing of axle output, then calculate X through linear regression coeffficient, each dot frequency of Y-axis, so as to
Driving states obfuscation output state figure is drawn, the transport condition of vehicle is judged according to fuzzy rule inquiry table, and according to state
25 kinds of combinations of states actual acquisitions turning of table is not slowed down, frequent lane change whether data draw the state that vehicle is travelled
Figure.
4. method according to claim 3, it is characterised in that described 3-axis acceleration sensor is exported in digital form
The spin matrix of 6 axles, quaternary number, the fusion calculation data of Eulerian angles form, and to the up to acceleration of ± 16g and ±
The angular velocity of 2000 °/sec (dps) carries out 16 bit resolution measurements.
5. method according to claim 3, it is characterised in that three described shaft speed sensors are more than in the X-axis direction 0
Be worth for acceleration mode, be deceleration regime less than null value, Y direction more than 0 value to turn left, less than 0 value to turn right.
6. method according to claim 3, it is characterised in that the 3-axis acceleration sensor in the described first step is knot
Close the sensor of 3-axis acceleration sensor and three-axis gyroscope, it is adaptable to mobile device, the acceleration of Real-time Collection mobile device
Degree and angular velocity；The output direction of principal axis of described 3-axis acceleration sensor includes three directions of x-axis, y-axis and z-axis, according to
The position put determines the concrete meaning of each direction of principal axis output data, when static, ideally has two axles to be output as
0g, the output of another axle determines to export according to the position put, the output -9.8g if identical with acceleration of gravity direction, if
It is contrary then export 9.8g.
7. method according to claim 3, it is characterised in that in described second step, is " minimum using medium filtering
Optimal filter under absolute error " criterion, to a digital signal xjWhen (- ∞ ＜ j ＜+∞) is filtered process, first have to
L long window of the length for odd number is defined, L=2N+1, N are positive integer；Some moment is located at, the sample of signal in window
For x (i-N) ..., x (i) ... x (i+N), x (i) are the sample of signal value positioned at window center, and this L sample of signal value is pressed
After order arrangement from small to large, its intermediate value, the sample value at i is just defined as the output valve of medium filtering, and finally realizes flat
Sliding process eliminates restless.
8. method according to claim 3, it is characterised in that in the middle of the 3rd described step, calculates output voltage gradient formula such as
Under
Wherein t is t-th discrete time point, and x (t) is the output valve of t, through constantly testing to m window values, finally may be used
It is worth with obtaining exit window output 25, the slope of output is the most reasonable.
9. method according to claim 3, it is characterised in that in the middle of the 4th described step, for acceleration transducer X-axis
Acceleration curve of output slope, define five kinds of different degrees of fuzzy sets：
X-axis acceleration curve of output slope=it is anxious to slow down, slow down, normally, accelerate, anxious to accelerate
For the acceleration curve of output slope of acceleration transducer Y-axis, five kinds of different degrees of fuzzy sets are also defined：
Y-axis acceleration=it is big to turn right, turn right, normally, turn left, turn left greatly
Define 25 fuzzy control planning；
For X-axis accelerating curve slope and the mould of each 5 kinds of degree of Y-axis acceleration curve of output slope in the middle of the 5th described step
Paste set, obscures rule query table such as table 1 in will forming 25, by rule list running state of automotive vehicle is just drawn,
Table 1
By X, the acceleration output valve filtering post processing of Y-axis output, then X, each point of Y-axis are calculated through linear regression coeffficient
Frequency, so as to draw driving states obfuscation output state figure, according to fuzzy rule inquiry table the traveling shape of vehicle is just can determine whether
State.
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| CN108622105A (en) * | 2018-04-16 | 2018-10-09 | 吉林大学 | Vehicle bend safe speed prediction based on multiple regression analysis and early warning system |
| CN108791303A (en) * | 2018-06-25 | 2018-11-13 | 北京嘀嘀无限科技发展有限公司 | Driving behavior detection method, device, electronic equipment and computer-readable medium |
| CN109094573A (en) * | 2017-06-20 | 2018-12-28 | 百度（美国）有限责任公司 | For determining the method and system of the optimum coefficient of the controller of automatic driving vehicle |
| CN109109866A (en) * | 2018-08-24 | 2019-01-01 | 深圳市国脉畅行科技股份有限公司 | Vehicle running state monitoring method, device, computer equipment and storage medium |
| CN110311651A (en) * | 2018-12-05 | 2019-10-08 | 林德（中国）叉车有限公司 | A kind of filter method and filter device of the accelerator pedal potentiometer voltage signal of vehicle |
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| CN111131617A (en) * | 2019-12-28 | 2020-05-08 | 长安大学 | Driving behavior analysis and feedback method based on smart phone |
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