CN104851301A - Vehicle parameter identification method based on deceleration strip sound analysis - Google Patents

Abstract

The invention relates to a vehicle parameter identification method based on deceleration strip sound analysis. According to the invention, acoustic waveform is acquired by a senor in real time when a vehicle passes two deceleration strips, and the speed of the vehicle is acquired by using the wave crest time and the distance between the two deceleration strips; the wheelbase between two wheels of the vehicle is further acquired on the basis of acquiring the speed of the vehicle, and the acquired wheelbase is compared with basic vehicle type wheelbase information so as to deduce the type of the detected vehicle, thereby finishing vehicle classification. The vehicle parameter identification method only needs one sensor, thereby overcoming a defect of difficult synchronization in a multi-sensor detection environment. The method provided by the invention acquires the acoustic waveform of the deceleration strip easily, mainly completes vehicle speed measurement and vehicle type identification within a time domain, and is simpler and more accurate than other existing methods.

Description

A kind of vehicle parameter recognition methods based on deceleration strip phonetic analysis

Technical field

The invention belongs to wave form analysis field, relate in particular to detecting the speed of a motor vehicle by analyzing deceleration strip sound waveform, identifying the method for the vehicle parameters such as type of vehicle.

Background technology

Automobile automatic recognition and identification are the important component parts of intelligent traffic, and utilization ground waveform analysis, vehicle grew the method that voice signal etc. carries out vehicle identification in the past, and majority is the extraction completing waveform character point in multisensor and transform domain; Therefore there is following shortcoming:

1, under FUSION WITH MULTISENSOR DETECTION environment, the synchronous compare difficulty between sensor is completed;

2, to the extraction of waveform, many employing level threshold methods, consuming time more in the past;

3, the extraction comparison completing unique point in transform domain is loaded down with trivial details;

4, the drifting problem of multisensor is more serious.

Above shortcoming easily causes the inaccurate of result.

Summary of the invention

For the problems referred to above that prior art exists, the object of this invention is to provide a kind of simple, compared with the vehicle identification method based on deceleration strip acoustic waveform analysis of high-accuracy, good reliability.

For achieving the above object, the present invention adopts following technical scheme: a kind of vehicle parameter recognition methods based on deceleration strip phonetic analysis, comprises the steps:

S1: the road between two deceleration strips installs audio sensor;

S2: the real-time acoustic waveform formed when detecting by described audio sensor the road that Current vehicle crosses between these two deceleration strips and two deceleration strips, records Current vehicle simultaneously and crosses road time between these two deceleration strips and two deceleration strips;

S3: obtain being that real-time sound wave carries out following denoising to detection:

S3a: Filtering and smoothing process is carried out to described real-time waveform;

S3b: judge whether the crest value of the real-time waveform after S2a process is greater than threshold value A, threshold value A is empirical value, if the crest value of real-time waveform is greater than threshold value A, then this real-time waveform is doubtful waveform, and performs next step; Otherwise return step S2;

S3c: the rising edge speed calculating doubtful waveform, if rising edge speed is greater than threshold value B, threshold value B is empirical value, then determine this doubtful waveform be described vehicle cross between these two deceleration strips and two deceleration strips road time the acoustic waveform that formed, otherwise return step S2;

S4: the acoustic waveform determined through step S3c has two crest groups, the time point that in first crest group, i-th crest is corresponding is designated as the time point that in second crest group, a jth crest is corresponding is designated as the speed of a motor vehicle is calculated according to formula (1):

$v=\frac{L}{t_i^2-t_j^1},i=\mathrm{1,2},..,D---\left(1\right);$

Wherein v represents the speed of a motor vehicle of vehicle between two deceleration strips, and L represents the distance between two deceleration strips, and D represents total row of wheel.

As optimization, determine the classification of vehicle, step is as follows:

1) wheelbase of adjacent two row's wheels is calculated according to formula (2):

$s_k=v\·(t_i-t_{i-1})=\frac{L}{t_i^2-t_j^1}\·(t_i-t_{i-1}),i=j---\left(2\right);$

Wherein s _krepresent the wheelbase of adjacent two row's wheels;

2) the first-to-last of axle dimension s of vehicle is calculated according to formula (3):

$s=\underset{k=1}{\overset{D-1}{\mathrm{\Σ}}}{s}_k---\left(3\right);$

3) according to the first-to-last of axle dimension s of vehicle, contrast vehicle classification wheelbase information, just can obtain the classification of Current vehicle.

As optimization, described audio sensor is in the centre position of two isolation strip.

Relative to prior art, tool of the present invention has the following advantages:

1, the present invention only needs a sensor, under overcoming FUSION WITH MULTISENSOR DETECTION environment, and the shortcoming of synchronous difficulty;

2, the method easily obtains the live sound waveform that vehicle crosses the road between two deceleration strips and two deceleration strips;

3, in time domain, complete the mensuration of vehicle speed and the identification of vehicle, simpler than other existing methods, accurate.

Accompanying drawing explanation

Fig. 1 is that illustraton of model installed by this method sensor, and the dotted arrow in figure represents garage direction.

Fig. 2 is the overview flow chart of the inventive method.

Fig. 3 is the process flow diagram to real-time waveform denoising in step S3.

Fig. 4 is the sound waveform figure after step S3 process.

In figure, 1-first isolation strip, 2-second isolation strip, 3-audio sensor.

Embodiment

In describing the invention, it is to be appreciated that term " first ", " second " only for describing object, and can not be interpreted as instruction or hint relative importance or the implicit quantity indicating indicated technical characteristic.Thus, be limited with " first ", the feature of " second " can express or impliedly comprise one or more these features.In describing the invention, the implication of " multiple " is two or more, unless otherwise expressly limited specifically.

Below the present invention is described in further detail.

See Fig. 1 to Fig. 4, a kind of vehicle parameter recognition methods based on deceleration strip phonetic analysis, comprises the steps:

S1: select two deceleration strips on highway, the highway between two deceleration strips is then surveyed area, and this surveyed area comprises two deceleration strips self; Road between two deceleration strips installs audio sensor, namely in surveyed area, audio sensor is installed;

S2: the real-time acoustic waveform formed when detecting by described audio sensor the road that Current vehicle crosses between these two deceleration strips and two deceleration strips, records Current vehicle simultaneously and crosses road time between these two deceleration strips and two deceleration strips;

S3: obtain being that real-time sound wave carries out following denoising to detection:

S3a: Filtering and smoothing process is carried out to described real-time waveform, described Filtering and smoothing is treated to prior art;

S3b: judge whether the crest value of the real-time waveform after S2a process is greater than threshold value A, threshold value A is empirical value, if the crest value of real-time waveform is greater than threshold value A, then this real-time waveform is doubtful waveform, and performs next step; Otherwise return step S2, if namely the crest value of real-time waveform is less than or equal to threshold value A, then returns step S2 and again detect;

S3c: the rising edge speed calculating doubtful waveform, if rising edge speed is greater than threshold value B, threshold value B is empirical value, then determine this doubtful waveform be described vehicle cross between these two deceleration strips and two deceleration strips road time the acoustic waveform that formed, otherwise return step S2, if namely rising edge speed is greater than threshold value B and is less than or equal to threshold value A, then return step S2 and again detect;

The computing method of doubtful waveform rising edge speed are as follows:

1) each doubtful waveform all at least has two crest groups (wheels navigate often crosses a deceleration strip will produce a crest group, if vehicle has n to arrange wheel, n crest is then had in so each crest group, because the doubtful waveform gathered may exist noise jamming, therefore may have multiple crest group).

2) trough adjacent with first crest in first or second crest group is determined, choose the upcurve section between this trough to the first crest (first crest in first or second crest group), then in this upcurve section, choose arbitrarily one section as compute segment, adopt formula (a) to calculate rising edge speed:

Wherein the ordinate of compute segment two end points is amplitude f, and the horizontal ordinate of compute segment two end points is time t.

During concrete enforcement, preferably select upcurve Duan Zhongcong trough to be in the part of upcurve section 10%-90% (rise time, can the rapidity that changes of response waveform) as compute segment to primary peak, the rising edge speed determined is more accurate.

Or determine trough adjacent with last crest in first or second crest group, choose the decline curve section between last crest to this trough (last crest in first or second crest group), then in this decline curve section, choose arbitrarily one section as compute segment, adopt formula (a) rising edge speed.

During concrete enforcement, preferably select decline curve Duan Zhongcong trough to be in the part of decline curve section 25%-75% as compute segment to last crest, the rising edge speed determined is more accurate.S4: remember that the acoustic waveform determined through step S3c has two crest groups, wherein first crest group is that the wheel of Current vehicle produces through first isolation strip, first crest in primary peak group is that the first row wheel (i.e. vehicle front-wheel) of Current vehicle produces by during first isolation strip, secondary peak in primary peak group is that the second row wheel of Current vehicle produces by during first isolation strip, the like, sending out i-th crest in primary peak group is that i-th row's wheel of Current vehicle produces by during first isolation strip; Second crest group is that the wheel of Current vehicle produces through second isolation strip, first crest in secondary peak group is that the first row wheel (i.e. vehicle front-wheel) of Current vehicle produces by during second isolation strip, secondary peak in secondary peak group is that the second row wheel of Current vehicle produces by during second isolation strip, the like, in secondary peak group send out a jth crest be Current vehicle jth arrange wheel produce by during second isolation strip;

The time point that in first crest group, i-th crest is corresponding is designated as the time point that in second crest group, a jth crest is corresponding is designated as the speed of a motor vehicle is calculated according to formula (1):

$v=\frac{L}{t_i^2-t_j^1},i=\mathrm{1,2},..,D---\left(1\right);$

Wherein v represents the speed of a motor vehicle of vehicle between two deceleration strips, and L represents the distance between two deceleration strips, and D represents total row of wheel.

As optimization, the inventive method can also determine the classification of vehicle further, and step is as follows:

1) wheelbase of adjacent two row's wheels is calculated according to formula (2):

$s_k=v\·(t_i-t_{i-1})=\frac{L}{t_i^2-t_j^1}\·(t_i-t_{i-1}),i=j---\left(2\right);$

Wherein s _krepresent the wheelbase of adjacent two row's wheels;

2) the first-to-last of axle dimension s of vehicle is calculated according to formula (3):

$s=\underset{k=1}{\overset{D-1}{\mathrm{\Σ}}}{s}_k---\left(3\right);$

3) according to the first-to-last of axle dimension s of vehicle, contrast vehicle classification wheelbase information (vehicle classification wheelbase information is existing public data), just can obtain the classification of Current vehicle.

As optimization, audio sensor is in the centre position of two isolation strip.

Composition graphs 1, if sound transmission is t in the time of L/2 ₀, then calculate the speed of a motor vehicle according to formula (4):

$v=\frac{L}{(t_j^2-t_0)-(t_i^1-t_0)}=\frac{L}{t_j^2-t_i^1},i=j---\left(4\right);$

Formula (4) is identical with formula (1), but this position of sensor arranges the delay problem that can overcome single-sensor and cause, and improves the accuracy of detection.

What finally illustrate is, above embodiment is only in order to illustrate technical scheme of the present invention and unrestricted, although with reference to preferred embodiment to invention has been detailed description, those of ordinary skill in the art is to be understood that, can modify to technical scheme of the present invention or equivalent replacement, and not departing from aim and the scope of technical solution of the present invention, it all should be encompassed in the middle of right of the present invention.

Claims (3)

1., based on a vehicle parameter recognition methods for deceleration strip phonetic analysis, it is characterized in that, comprise the steps:

S1: the road between two deceleration strips installs audio sensor;

S2: the real-time acoustic waveform formed when detecting by described audio sensor the road that Current vehicle crosses between these two deceleration strips and two deceleration strips, records Current vehicle simultaneously and crosses road time between these two deceleration strips and two deceleration strips;

S3: obtain being that real-time sound wave carries out following denoising to detection:

S3a: Filtering and smoothing process is carried out to described real-time waveform;

S3b: judge whether the crest value of the real-time waveform after S2a process is greater than threshold value A, threshold value A is empirical value, if the crest value of real-time waveform is greater than threshold value A, then this real-time waveform is doubtful waveform, and performs next step; Otherwise return step S2;

S3c: the rising edge speed calculating doubtful waveform, if rising edge speed is greater than threshold value B, threshold value B is empirical value, then determine this doubtful waveform be described vehicle cross between these two deceleration strips and two deceleration strips road time the acoustic waveform that formed, otherwise return step S2;

S4: the acoustic waveform determined through step S3c has two crest groups, the time point that in first crest group, i-th crest is corresponding is designated as the time point that in second crest group, a jth crest is corresponding is designated as the speed of a motor vehicle is calculated according to formula (1):

$v=\frac{L}{t_i^2-t_j^1},i=j=\mathrm{1,2},..,D---\left(1\right);$

Wherein v represents the speed of a motor vehicle of vehicle between two deceleration strips, and L represents the distance between two deceleration strips, and D represents total row of wheel.

2., as claimed in claim 1 based on the vehicle parameter recognition methods of deceleration strip phonetic analysis, it is characterized in that, determine the classification of vehicle, step is as follows:

1) wheelbase of adjacent two row's wheels is calculated according to formula (2):

$s_k=v\·(t_i-t_{i-1})=\frac{L}{t_i^2-t_j^1}\·(t_i-t_{i-1}),i=j---\left(2\right);$

Wherein s _krepresent the wheelbase of adjacent two row's wheels;

2) the first-to-last of axle dimension s of vehicle is calculated according to formula (3):

$s=\underset{k=1}{\overset{D-1}{\mathrm{\Σ}}}{s}_k---\left(3\right);$

3) according to the first-to-last of axle dimension s of vehicle, contrast vehicle classification wheelbase information, just can obtain the classification of Current vehicle.

3., as claimed in claim 1 or 2 based on the vehicle parameter recognition methods of deceleration strip phonetic analysis, it is characterized in that, described audio sensor is in the centre position of two isolation strip.