CN106503448A - One kind freely flows road traffic noise probability forecasting method - Google Patents
One kind freely flows road traffic noise probability forecasting method Download PDFInfo
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Abstract
The present invention proposes a kind of freely to flow road traffic noise probability forecasting method based on Monte Carlo simulation, it is adaptable to freely flowing the dynamic analog calcutation of road traffic noise.Calculating process is：First the data set that a series of several parameters of random time point road vehicle numbers, type of vehicle, position and speed are constituted is obtained with the simulation of free traffic flow Monte Carlo simulation device, then by these data input vehicle noise discharge probabilistic models, obtain vehicle noise source strength and position data collection, finally a series of noise figure at receiving points is obtained with reference to noise transmission decay calculation model, show that noise probability is distributed so as to count.The method enormously simplify the process of traffic flow simulation, and simple with modeling, amount of calculation is little, simulate result of calculation accurately and reliably advantage.
Description
Technical field
The present invention relates to Road Traffic Noise Prediction Model and noise dynamic analog calcutation field, more particularly, to one
Plant and freely flow road traffic noise probability forecasting method, can be used for the traffic noise under the effect of accurate simulation road free traffic flow
Value and its probability distribution.
Background technology
While urban highway traffic offers convenience to people's lives, environmental pollution is also result in, wherein traffic noise is dirty
Dye problem becomes one of main Environmental Problems of interference people's normal life.It can be seen that the main big and medium-sized cities traffic of current China is made an uproar
Sound pollution is very serious, has caused great impact to the work of people, study and rest, or even has induced various diseases
Disease.With the growth of vehicles number, traffic noise pollution situation will also be increasingly severeer, especially in some big and medium-sized cities.
It is the important foundation work of traffic noise preventing and treating that the prediction of traffic noise is calculated.Traditional traffic noise prediction meter
Calculation method is static models calculating method, also referred to as equation, typically considers further that noise transmission declines on the basis of noise source emission
The correction term composition that each influence factor in subtracting is produced.These factors generally comprise the volume of traffic, propagation distance, barrier
Effect, air absorption, the effect on ground etc..The advantage of model calculating method be calculate easy, but can only reflect instantaneous noise value or
, there are prediction single, traffic noise cannot be reflected fluctuations of target etc. in the energy average level of noise in certain a period of time
Shortcoming, it is impossible to meet the needs of dynamic prediction.With the development of computer technology, using the random mistake such as computer simulation traffic flow
The method of journey is day by day ripe, and scholars propose and traffic noise computation model is combined with microscopic traffic flow simulation, Jin Ershi
The method that dynamic analog calcutation is carried out to traffic noise now, i.e. dynamic simulation method.
Existing traffic noise Dynamic Simulation Method generally comprises a Dynamic Traffic Flow simulation tool, this dynamic traffic
Flow field simulation instrument generally realizes using complicated traffic simulation software that advantage is computation model mature and reliable, but has calculating
Amount is big, modeling complexity is with noise calculation process the shortcomings of interacting inconvenience.Monte Carlo simulation is a kind of ripe probability mould
Plan method, can help people to state some extremely complex interactions in engineering with random mathematics.Due to Monte Carlo
Simulation has that modeling is simple, amount of calculation is little, analog result accurately and reliably, is therefore widely used in road friendship in recent years
Through-flow analog study.For the traffic flow on free runner road, set up Monte Carlo simulation process and be easier to realize, but be up till now
Only, there is not yet being realized based on Monte Carlo simulation to freely flowing the side that road traffic noise and probability distribution are predicted
Method.
Content of the invention
Present invention aim to overcome that the shortcoming of prior art, there is provided one kind is simple and effective freely to flow road traffic noise
Probability forecasting method.The method realizes the transient parameter probability calculation to traffic flow using Monte Carlo simulation, further with
Traffic flow simulation result realizes the calculating of traffic noise and its probability distribution.Have that model structure is simple, calculate using the method
The advantages of measuring probability distribution little, that traffic noise can be obtained, it is adaptable to freely flowing the prediction of road traffic noise, with very high
Accuracy.
For achieving the above object, the technical solution used in the present invention is as follows：
One kind freely flows road traffic noise probability forecasting method, and concrete prediction process is：Free traffic flow Monte Carlo is first used
Simulator simulation obtains a series of several parameters of random time point road vehicle numbers, type of vehicle, position and speed and constitutes
Data set, then by these data sets input vehicle noises discharge probabilistic model, obtain vehicle noise source strength and position data
Collection, finally obtains a series of noise figure at receiving points with reference to noise transmission decay calculation model, show that noise is general so as to count
Rate is distributed；
Wherein described free traffic flow Monte Carlo simulation device meets the feature of Poisson distribution according to free traffic flow time headway
The instantaneous shape of simulated roadway traffic flow, vehicle number, position on output road, speed；
Vehicle noise discharge probabilistic model is one and includes single vehicle noise normal state of the different automobile types under friction speed scope point
Cloth model.
Described vehicle noise discharge probabilistic model is drawn by testing the single vehicle noise emission data statistics for measuring.
Described noise transmission decay calculation module includes range attenuation calculating, air calculation in absorption and barrier decremeter
The parts such as calculation.
The traffic flow can be the mixed flow comprising large, medium and small three kinds of vehicles.
Car speed is divided into the km/h three above grades of 0 ~ 20 km/h, 20 ~ 50 km/h, 50 by methods described, respectively
To three kinds of vehicles respectively in the noise emission probabilistic model of three speed class.
Compared with prior art, advantages of the present invention is mainly reflected in：One is freely to flow road traffic compared to existing
Noise prediction model, the present invention not only can calculate the equivalent sound level of receiving point, can also calculate a series of the instantaneous of time points
Noise, obtains the dynamic rule of noise；Two is compared to existing traffic noise Dynamic Simulation Method, the traffic of the present invention
Flow field simulation process is simple, and amount of calculation is little.
Description of the drawings
Fig. 1 is the schematic diagram calculation of the inventive method.
Fig. 2 is that the traffic noise of the inventive method calculates scene graph.
Specific embodiment
Accompanying drawing being for illustration only property explanation, it is impossible to be interpreted as the restriction to this patent；In order to the present embodiment is described more preferably, attached
Scheme some parts to have omission, zoom in or out, do not represent the size of actual product；
To those skilled in the art, in accompanying drawing, some known features and its possible omission of explanation will be understood by.Under
Face is described further to technical scheme in conjunction with the accompanying drawings and embodiments.
As Fig. 1, one kind freely flow road traffic noise probability forecasting method, concrete prediction process is：Free traffic is first used
It is several that the device simulation of stream Monte Carlo simulation obtains a series of random time point road vehicle numbers, type of vehicle, position and speed
The data set that individual parameter is constituted, then by these data set input vehicle noise discharge probabilistic models, obtains vehicle noise source strength
And position data collection, finally a series of noise figure at receiving points is obtained with reference to noise transmission decay calculation model, so as to count
Show that noise probability is distributed；
Wherein described free traffic flow Monte Carlo simulation device meets the feature of Poisson distribution according to free traffic flow time headway
The instantaneous shape of simulated roadway traffic flow, vehicle number, position on output road, speed；
Vehicle noise discharge probabilistic model is one and includes single vehicle noise normal state of the different automobile types under friction speed scope point
Cloth model.
Described vehicle noise discharge probabilistic model is drawn by testing the single vehicle noise emission data statistics for measuring.
The specific implementation step of the method is as follows：
1st, 400 meters long of free flow path section according to the road scene shown in accompanying drawing 2, is chosen, the magnitude of traffic flow, vehicle ratio is set
The parameters such as example, number of track-lines.
2nd, traffic flow Parameter for Poisson Distribution is calculated according to the volume of traffic, and is generated using Monte Carlo simulation at random a certain instantaneous
Vehicle number on sectionm.
3rd, according to vehicle numbermGenerated with each parameter and probability-distribution function and using Monte Carlo simulation at randommCar
Property parameters, including type of vehicle, position coordinates, speed.
4th, vehicle number and property parameters that the 2nd step and the 3rd step generate rightabout road are repeated.
5th, vehicle noise discharge probabilistic model generates each car on this instantaneous road at random using Monte Carlo simulation
Produced noise intensity, calculates the wink at receiving point using principle of energy superposition and with reference to noise transmission decay calculation model
When sound level.During calculating, the single vehicle noise emission statistics that vehicle noise discharge probabilistic model can be measured using experiment is every kind of
Vehicle vehicle is in the equal Normal Distribution of lower noise such as each speed.Such as：Large car in 0 ~ 20 km/h isN(72.6,
7.482), in 20 ~ 50 km/h it isN(78, 4.972), in 50 more than km/h it isN(80.7, 5.352)；In-between car exists
During 0 ~ 20 km/h it isN(62.7, 6.362), in 20 ~ 50 km/h it isN(72.9, 4.782), in 50 more than km/h it isN(78.5, 6.132)；Compact car in 0 ~ 20 km/h isN(57.5, 4.682), in 20 ~ 50 km/h it isN(66.5,
3.882), in 50 more than km/h it isN(72.1, 3.232).
6th, step 2,3,4,5 are sequentially repeated n times, obtain N number of instantaneous sound level at receiving point.
7th, equivalent sound level L receiving point at is calculated according to N number of instantaneous sound leveleq, Statistics sound level L10、L50And L90, and draw
Go out noise probability distribution map.
The present invention proposes a kind of freely to flow road traffic noise probability forecasting method based on Monte Carlo simulation, it is adaptable to
To freely flowing the dynamic analog calcutation of road traffic noise.One free traffic flow Monte Carlo simulation device of the method, a car
Three major parts of noise emission probabilistic model and a noise transmission decay calculation model are constituted；Calculating process is：First use
The simulation of free traffic flow Monte Carlo simulation device obtains a series of random time point road vehicle numbers, type of vehicle, position
The data set constituted with the several parameters of speed, then by these data input vehicle noise discharge probabilistic models, obtains vehicle and makes an uproar
Sound source is strong and position data collection, finally obtains a series of noise figure at receiving points with reference to noise transmission decay calculation model, from
And count and show that noise probability is distributed.The method enormously simplify the process of traffic flow simulation, simple with modeling, amount of calculation
Little, simulate result of calculation accurately and reliably advantage.
Obviously, the above embodiment of the present invention is only intended to clearly illustrate example of the present invention, and is not right
The restriction of embodiments of the present invention.For those of ordinary skill in the field, may be used also on the basis of the above description
To make other changes in different forms.There is no need to be exhaustive to all of embodiment.All this
Any modification, equivalent and improvement that is made within the spirit and principle of invention etc., should be included in the claims in the present invention
Protection domain within.
Claims (6)
1. one kind freely flows road traffic noise probability forecasting method, it is characterised in that specifically prediction process is：First use and freely hand over
Through-flow Monte Carlo simulation device simulation obtains a series of random time point road vehicle numbers, type of vehicle, position and speed
The data set that several parameters are constituted, then by these data set input vehicle noise discharge probabilistic models, obtains vehicle noise source
Strong and position data collection, finally obtains a series of noise figure at receiving points with reference to noise transmission decay calculation model, so as to unite
Meter show that noise probability is distributed；
Wherein described free traffic flow Monte Carlo simulation device meets the feature of Poisson distribution according to free traffic flow time headway
The instantaneous shape of simulated roadway traffic flow, vehicle number, position on output road, speed；
Vehicle noise discharge probabilistic model is one and includes single vehicle noise normal state of the different automobile types under friction speed scope point
Cloth model.
2. according to claim 1 road traffic noise probability forecasting method is freely flowed, it is characterised in that its vehicle noise
Discharge probabilistic model is drawn by testing the single vehicle noise emission data statistics for measuring.
3. according to claim 1 road traffic noise probability forecasting method is freely flowed, it is characterised in that noise transmission declines
Subtracting computing module includes range attenuation calculating sub module, air calculation in absorption submodule and barrier decay calculation submodule.
4. range attenuation calculating sub module described in is according to the distance between sound source and receiving point and according to point sound source in semi-free sound
The energy dissipation principle of field calculates the range attenuation amount of noise；
The air calculation in absorption submodule calculates the air attenuation by absorption of noise according to parameters such as temperature, temperature, propagation distances
Amount；
The barrier decay calculation submodule calculates attenuation of the barrier to noise according to K-A formula；
The noise transmission decay calculation module result of calculation is the summation of three submodule result of calculations.
5. according to claim 1 road traffic noise probability forecasting method is freely flowed, it is characterised in that the traffic flow
It is the mixed flow comprising large, medium and small three kinds of vehicles.
6. according to claim 1 road traffic noise probability forecasting method is freely flowed, it is characterised in that car speed point
For the km/h three above grades of 0 ~ 20 km/h, 20 ~ 50 km/h, 50.
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Cited By (3)
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| CN107705566A (en) * | 2017-10-20 | 2018-02-16 | 吉利汽车研究院（宁波）有限公司 | A kind of City Road Traffic Noise Prediction method and system |
| CN111091828A (en) * | 2019-12-31 | 2020-05-01 | 华为技术有限公司 | Voice wake-up method, device and system |
| CN114880626A (en) * | 2022-06-30 | 2022-08-09 | 智联万维科技有限公司 | Data processing system for acquiring abnormal vehicles in geographic area |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107705566A (en) * | 2017-10-20 | 2018-02-16 | 吉利汽车研究院（宁波）有限公司 | A kind of City Road Traffic Noise Prediction method and system |
| CN107705566B (en) * | 2017-10-20 | 2020-04-28 | 吉利汽车研究院（宁波）有限公司 | Urban road traffic noise prediction method and system |
| CN111091828A (en) * | 2019-12-31 | 2020-05-01 | 华为技术有限公司 | Voice wake-up method, device and system |
| CN111091828B (en) * | 2019-12-31 | 2023-02-14 | 华为技术有限公司 | Voice wake-up method, device and system |
| CN114880626A (en) * | 2022-06-30 | 2022-08-09 | 智联万维科技有限公司 | Data processing system for acquiring abnormal vehicles in geographic area |
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