PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Road Traffic Noise Prediction Model “ASJ RTN-Model 2018”
Proposed by The Acoustical Society of Japan– Part 5: Study on prediction accuracy
Katsuya YAMAUCHI1; Terutoshi TAJIKA2; Akinori FUKUSHIMA3; Ken ANAI4
1
2

Faculty of Design, Kyushu University, Japan

Environmental Technical Laboratory Ltd., Japan
3

4

NEWS Environmental Design Inc., Japan

Faculty of Engineering, Fukuoka University, Japan

ABSTRACTThis paper introduces the study on prediction accuracy of the ASJ RTN-Model 2018, as a part of the series offive papers which has same main title in this congress, on behalf of the research committee on road traffic
noise in the Acoustical Society of Japan. It is very important to examine the prediction accuracy of the newmodel, because some assumptions are included in modeling the source power level of each type of vehicles
and in simplifying the calculation of noise propagation. Some examination of the correspondence between
the predicted values and measured traffic noise levels are introduced in this paper. The accuracy of themethod of prediction for noise behind building complex are also examined. The measured values wereobtained recently in Japan on flat and strait section of general roads and on expressways. This paper also
introduces the examination on assumed causes of errors that are thought to be important in considering
prediction accuracy, such as the condition setting of hypothetical traffic lanes, vehicle type classification, andsome typical causes of uncertainty on actual measurement.
Keywords: Road Traffic Noise, Prediction Model, ASJ RTN-Model 2018, Prediction Accuracy

1. INTRODUCTION
The Technical Committee on Road Traffic Noise in the Acoustical Society of Japan has developed
a series of the road traffic noise prediction model, named ASJ RTN-Model. After releasing theprevious model, ASJ RTN-Model 2013 (1) published in 2014, the research committee has beenworking to improve the prediction model on the basis of the latest data and knowledge for five years,
and the latest version named “ASJ RTN-Model 2018” was published April 2019. The updates are
introduced in the series of papers (2–5). The calculation models of sound power levels of road vehicles
and calculation methods of sound propagation were updated so that the calculated value becomes moreaccurate to the measured road traffic noise. It is necessary to examine the prediction accuracy of thelatest model.
In this paper, the examinations of the prediction accuracy of the latest model, ASJ RTN-Model
2018, are provided by the comparison between the predicted and actual measured values. The
examinations were performed for the measurement data obtained on general road and expressway. The
prediction accuracy of the practical method for areas behind buildings in urban districts is also
examined and described in the other publication (5). In addition, it is necessary to note that several
types of uncertainty are included in the actual measurement values. We also examine the causes oferrors that are likely to be significant when considering the prediction accuracy of the ASJ RTN-Model2018.
1yamauchi@design.kyushu-u.ac.jp
fuku-new@wonder.ocn.ne.jp
4
anai@fukuoka-u.ac.jp

3

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2. CORRESPONDENCE BETWEEN PREDICTED AND MEASURED VALUES AT
GENERAL ROAD SECTION
In the ASJ RTN-Model 2018, the calculation model of sound emission of read vehicles was updated.
On the dense asphalt pavement, which is common for general road in Japan, the A-weighted soundpower level L WA of road vehicles is given by

𝐿"# = 𝑎 + 𝑏 log+, 𝑉 + 𝐶(1)

where V is the vehicle running speed [km/h], a and b are regression coefficients, and C is the correction
term. The term a was changed for each vehicle category based on accumulated data in last decade. In
this section, the correspondence between the predicted values and measured traffic noise levels is
examined.
2.1 Measured Data
The actual measurement data were obtained at straight sections of general roads in fiscal year 2013
based on the manual of constant monitoring of motor vehicle traffic noise (6) by the Ministry ofEnvironmental Government of Japan. The measurements were in accordance with JIS Z8731:1999,
which is almost identical to ISO 1996-1:2003. The measurement conditions of these data are as
follows.
(1) Noise levels considered
L Aeq and L AN (L A5 , L A10 , L A50 , L A90 , L A95 ). Measurement duration was 10 minutes, and multiple
measurement were performed over 24 hours at each location.
(2) Measurement point
1.2 m above the ground on a public/private boundary. The selected measurement points were awayfrom juxtaposed roads or road intersections, and without obstructions or glass-ground in the soundpropagation path. The number of lanes was from 1 to 4.
(3) Traffic conditions
Number of traffics were counted in three-category or two-category vehicle classification for eachdirection. Number of motorcycles were also counted separately. Since it will be assumed the steadytraffic flow section in the prediction, the measurement data of traffic flow with running speed less than
40 km/h were excluded from the examination. The traffic volumes of the target roads were less than
4,500 per hour, and the ratio of heavy vehicles were varied widely (from 0% to 100%).
2.2 Calculation
The predicted values were obtained using the simple method for estimation L Aeq described in the
ASJ RTN-Model 2018. In the case of simple road conditions and steady traffic flow, the L Aeq,T can becalculated using the following formula involving the single-event sound exposure level L AE [dB] andthe traffic volume N T [number of vehicles] passing a prediction point during the time T [s]:𝐿#/0,2 = 𝐿#3 + 10 log+,

67
2

(2)

When and omni-directional point source with the A-weighted sound power level L WA [dB] moves
along a straight road of infinite length at the constant speed V [km/h], L AE at the distance l from thelance can be analytically derived from the following formula obtained by applying the inverse-square
low in a hemi-free field and integrating over time up infinity:

𝐿#3 = 𝐿"# + 10 log+,

8.:
;<=

(3)

To simplify the calculations, multiple lanes of traffic traveling in the same direction were combined
into a hypothetical single lane at the center of the traffic stream. The correction term C was set to 0 dB
in this examination.

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2.3 Comparison between Predicted and Measured Values
The correspondence between predicted values and actual measurement values for daytime (6:00–
22:00) and night (22:00–6:00) are shown in Figure 1. In the scatter diagrams, the line where thepredicted and measured value coincide and its 3 dB range are also shown. The correlation coefficientswere 0.81 for daytime and 0.85 for night. The mean difference between predicted and measured values(∆, predicted L Aeq minus actual measurement values) were +0.4 dB and -0.8 dB for daytime and night,
respectively, indicating excellent agreement of two values. For daytime, 87% of the prediction were
included within the ±3 dB range, where 78% were included for night.

Figure 1 – Correspondence between predicted and measured LAeq at flat and straight general road section.

3. CORRESPONDENCE BETWEEN PREDICTED AND MEASURED VALUES ON
THE ROADSIDE OF EXPRESSWAY
3.1 Measured Data
The actual measurement data were obtained at the expressway with bank and cut road structure infiscal year from 2014 to 2018. The summary of selected 7 measured point are shown in Table 1.
Table 1 – Summary of the measured data used for the examination
Structure

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Pavement

Number of measurement points

Noise barriers

type

Type

Age

Reference

Roadside1

bankporous

8.0

1

1

none

2

bank

porous

6.3

1

1

none

3

bank

porous

7.3

1

1

none

4

bank

porous

8.3

1

1

none

5

bank

porous

0.5

1

1

none

6

bank

KOUKINOU II

1.3

1

1

none

7

cut

porous3.0

1

2

2 m height(1) Noise levels considered
L Aeq and L A95 (the lower limit of the 90% percentile range). Measurement duration was 2 hours,
while only for the road 7 the duration was 15 minutes.
(2) Measurement point
The reference measurement points for bank roads were 1.2–2.0 m height above the road surface at
7.5 m away from the center of the closest cruising lane. For the cut road, the reference point was 3.0 m
above the 2.0 m height noise barrier on the top of slope (5.0 m height above the road surface). The roadside measurement points were 25 to 66 m away from the center of the road, and the heights were 1.2 m
above the ground surface. The pavement types were porous asphalt or gap-graded asphalt mixture thatis referred as “KOUKINOU II”.
(3) Traffic conditions
Number of traffics were counted for three-category vehicle classifications for each direction. Busesand motorcycles were separately counted. The traffic volumes of the target roads were from 800 to
4,000 per hour, and the ratio of heavy vehicles were varied from 17% to 32%. The traffics were steady,and their mean traffic speed were from 80 to 110 km/h.
3.2 Calculation
The predicted values were obtained using the ASJ RTN-Model 2018. Regarding the porous asphalt
and KOUKINOU II pavement, the sound power level L WA for each type of road vehicles is given asfunctions of the running speed and the age of the pavement after construction.
In the propagation calculation, the correction for diffraction due to acoustical obstacles such as
noise barriers is involved. The correction for the diffraction on the top of slope of the bank structures
were calculated by the method for the wedge with an opening angle, which were newly developed in
the model. The correction for the noise barrier was calculated by the method for the knife-wedge. The
correction for the absorptive barrier was also involved. Regarding the correction of ground effect forthe slope surface, the coefficients for loose soil were used, while the correction was set to 0 dB for the
ground of measurement side since the surfaces were covered by asphalt pavement. The correction foratmospheric absorption was also involved.

Predicted LAeq [dB]

75
70
65
60

KOUKINOU II
Reference := 0.8 dB, N = 1
Road side := 1.5, N = 1

45
40
40

45

Refelence point= - 0.5 dB
N=1

75

55
50

Reference point
Road side points

80

PorousReference := 0.6 dB
= 1.70 dB
N=5Road side := 0.8 dB
= 2.10 dB
N=550 55 60 65 70
Measured LAeq [dB]7580Predicted LAeq [dB]80

Porous (Reference)
Porous (Road side)
KOUKINOU II (Reference)
KOUKINOU II (Road side)

70
65
60
55
50

Road side points= 0.3 dB
= 0.14 dB
N=2

45
40
40

45

50 55 60 65 70
Measured LAeq [dB]7580(a). Bank road(b). Cut road
Figure 2 – Correspondence between predicted and measured LAeq on the roadside of expressways3723

3.3 Comparison between Predicted and Measured Values
The correspondence between predicted values and actual measurement values for each roadstructure are shown in Figure 2. Since the measured L Aeq were higher than 10 dB than L A95 , which isassumed to be equivalent to the background noise level, the correction of background noise was not
performed.
For the bank roads, the predicted values corresponded to within 3 dB of the measured values. With
regard to the porous asphalt pavements, the mean differences between predicted and measured values(∆, predicted L Aeq minus actual measurement values) were +0.6 dB and +0.8 dB at reference androadside points, respectively. The mean differences for KOUKINOU II pavement were +0.8 dB at thereference, and +1.5 dB at the roadside points.
For the road 7 (cut road), the mean difference between prediction and measurement at the roadsidepoint, where was behind the noise barrier, was +0.3 dB.

4. CAUSES OF ERRORS IN ASJ RTN-MODEL 2018
Since many assumptions are included in setting the power level of running-vehicle noise and insimplifying the calculation of noise propagation in the prediction model, it is necessary to examine thecauses of errors that are likely to be significant when considering the prediction accuracy of the model.
In the ASJ RTN-Model 2018, as a part of references, several investigations on the effect of the error
factors are provided.
4.1 Setting of Hypothetical Traffic Lanes
In the model, it is allowed to combine two or more lanes into a single hypothetical lane forsimplicity of the calculation. According to the previous investigation (7), the difference in L Aeq causedby combining the lanes into single was less than 1 dB even in the case of a road with eight lanes, if the
distance from the center of the nearest lane to the receiver was 5 m or more. However, the error
increases drastically when the distance to the receiver is less than 5 m. Thus, when noise is predictedin the vicinity of roads with multiple lanes, it is recommended to increase the number of hypotheticallanes.
4.2 Road Traffic Conditions
The classification of road vehicle has been changed from the conventional model. In the ASJ
RTN-Model 2018, three-category classification (large-sized, medium-sized and light vehicles) whichis recommended from an acoustical viewpoint, while two-category classification (heavy and lightvehicles) is also provided as an alternative considering practicality. As the result of the investigation,
the prediction error caused by replacing three-category with two-category classification was less than
1 dB, if the ratio of medium-sized vehicles to heavy vehicles ranged 10 to 80%.
In the prediction model, the sound power level of a road vehicle is calculated under the assumptionthat all vehicles classified in each category run at the same speed (i.e., at the mean speed of all
vehicles). According to the results of examination from a stochastic viewpoint (8), the change in L Aeq
due to the variation of running speed is extremely small. Furthermore, the change in L Aeq is 1 dB or lessif the standard deviation of the power level is 3 dB or less.
4.3 Range of Unit Pattern Calculation
In the general calculation procedure of the model, point sources are discretely set on lanes to obtainthe unit pattern at the receiver, and then L Aeq is calculated. In this case, it is necessary to determine therange over which the point sources must be arranged, the range of the unit pattern calculation in otherwords. According to the previous examination (7), it was found that the difference in L Aeq caused byremoving low-level portions 10 dB below the maximum were approximately 1 dB or less for flat roads
and for interchange sections. Those were also less than 1 dB for the areas surrounding a tunnel portal
when the low-level portions 15 dB below the maximum were removed.
However, since L Aeq strongly depends on the energy integration over the entire unit pattern, it isnecessary to be noted that a significant error may occur owing to the lack of consecutive portions of theunit pattern. Hence, it is necessary to avoid the excessive removal of portions, even if the A-weighted
sound pressure levels are sufficiently smaller than the maximum.

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4.4 Problems encountered in actual measurements
In addition to considering problems in the prediction calculation, it is necessary to consider thecauses of uncertainties in the actual measurements of road traffic noise. Typical causes of uncertainties
are discussed below. It is also necessary to consider the measurement duration necessary to stabilize
the values of L Aeq statistically.
(1) Influences of meteorological factors
When sounds propagate outdoors, the influences of the temperature profile and wind in theatmosphere appear as propagation distance increases. Attenuation may also occur owing toatmospheric absorption, which depends on atmospheric temperature and humidity. Among these
influences, the wind and temperature profiles are extremely complicated phenomena, and it is still
difficult to take these influences into account in practical noise prediction. Thus, only the variation ofroad traffic noise as influenced by wind, which is based on actual measurement results, is introduced in
the model. Sound propagation may also be influenced by the temperature gradient, however, its
influence can be ignored for propagation distances of up to approximately 200 m, unless extreme
temperature inversion occurs. For attenuation caused by atmospheric absorption, a comparatively
precise calculation is available in the model.
(2) Influence of background noise
In the measurement of road traffic noise, other types of noise (background noise) always influence
the measurement results to some extent. In particular, the influence of background noise is larger when
the receivers are far from the road or noise reduction measures such as noise barriers are provided.
Although several methods of estimating the degree of background noise have already been
investigated, an approximate background noise level can be estimated by simultaneously measuring
the percentile level, L A90 or L A95 , along with L Aeq .
(3) Influence of other factors
Since road traffic noise may be measured under circumstances that are not taken into account in theprediction, not only the causes described above but also various other causes of errors must be
considered, for instance, errors caused by traffic flow conditions that are different from those set in theprediction or a difference in the performance of noise reduction measures such as noise barriers due totheir installation condition. For drainage asphalt pavement, although the noise reduction effect and itschange with time after the installation are taken into account in the model, the deterioration of its
performance caused by the blockage of air pores may significantly depend on its location. In the caseof a viaduct, not only structure-borne noise, which is already taken into consideration in the model, butalso noise from the expansion joints of the road may often be included in actual measurement values.

REFERENCES
1. S. Sakamoto, Road traffic noise prediction model “ASJ RTN-Model 2013”: Report of the ResearchCommittee on Road Traffic Noise, Acoust. Sci. & Tech., 2015; 36, 49-108.
2. S. Sakamoto, et al., Road Traffic Noise Prediction Model “ASJ RTN-Model 2018” Proposed by The
Acoustical Society of Japan – Part 1: Outline of the calculation model, Proc. ICA 2019; 9-13 September
2019, Aachen, Germany 2019.
3. Y. Okada, et.al., Road Traffic Noise Prediction Model “ASJ RTN-Model 2018” Proposed by The
Acoustical Society of Japan – Part 2: Calculation model of sound emission of road vehicles, Proc. ICA
2019; 9-13 September 2019, Aachen, Germany 2019.
4. A. Fukushima, et.al., Road Traffic Noise Prediction Model “ASJ RTN-Model 2018” Proposed by The
Acoustical Society of Japan – Part 3: Calculation model of sound propagation, Proc. ICA 2019; 9-13
September 2019, Aachen, Germany 2019.
5. K. Anai, et.al., Road Traffic Noise Prediction Model “ASJ RTN-Model 2018” Proposed by The
Acoustical Society of Japan –Part 4: Accuracy Verification of a Practical Method for Areas behind
Buildings in Urban Districts, Proc. ICA 2019; 9-13 September 2019, Aachen, Germany 2019.
6. Ministry of Environmental Government of Japan, manual of constant monitoring of motor vehicle
traffic noise. https://www.env.go.jp/air/car/noise/note/kanshimanual.pdf (Accessed: 31-May-2019)7. S. Yamaguchi, T. Tamesue, T. Saeki and M. Sasaki, Effects of approximation of types of vehicles, thenumber of lanes of road and the unit pattern on prediction error of LAeq,, J. Acoust. Soc. Jpn. (J), 58,3725

647-653 (2002) (in Japanese).
8. K. Yamauchi, et al., Examination on Prediction Accuracy of the Road Traffic Noise Prediction Model“ASJ RTN-Model 2018”, Tech. Rep. Noise and Vib. Acoust. Soc. Jpn., N-2019-19 (2019) (in Japanese).

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