This may be the author s version of a work that was submitted/accepted for publication in the following source:

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This may be the author’s version of a work that was submitted/accepted for publication in the following source:

Oshino, Y., Tsukui, Keisuke, Hanabusa, Hisatomo, Bhaskar, Ashish,

Chung, Edward, & Kuwahara, Masao (2007)

Study on road traffic noise prediction model taking into account the city-wide network.

In Belek, H T (Ed.) Proceedings of the 36th International Congress and Exhibition on Noise Control Engineering, Volume 7.

Curran Associates, Inc. / Turkish Acoustical Society, Turkey, pp. 4770-4775.

This file was downloaded from: https://eprints.qut.edu.au/49946/

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INTER-NOISE 2007

28-31 AUGUST 2007 ISTANBUL, TURKEY

Study on road traffic noise prediction model taking into account

the citywide road network

Yasuo Oshinoa, Keisuke Tsukuib, Hisatomo Hanabusac, Ashish Bhaskard, Edward Chunge and Masao Kuwaharaf

a,b

Japan Automobile Research Institute 2530 Karima, Tsukuba, Ibaraki 305-0822, Japan

c,e,f

Institute of Industrial Science, University of Tokyo

d

Traffic Facilities Laboratory, Ecole Polytechnique Federale de Lausanne

ABSTRACT

For the further noise reduction in the future, the traffic management which controls traffic flow and physical distribution is important. To conduct the measure by the traffic management effectively, it is necessary to apply the model for predicting the traffic flow in the citywide road network. For this purpose, the existing model named AVENUE was used as a macro-traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model, and the new road traffic noise prediction model was established. By using this prediction model, the noise map of entire city can be made. In this study, first, the change of traffic flow on the road network after the establishment of new roads was estimated, and the change of the road traffic noise caused by the new roads was predicted. As a result, it has been found that this prediction model has the ability to estimate the change of noise map by the traffic management. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

1 INTRODUCTION

Road traffic noise prediction model is very useful for the investigation of the noise reduction measures. Therefore, we have developed the micro-traffic flow model and the sound power level model. The former model is able to estimate the running behavior of the individual vehicles in the urban roads, and the latter model is able to estimate the noise generation from the running behavior of the vehicles. The road traffic noise prediction model was established by combining the above two calculation models [1], and the effects of the noise reduction measures for the road vehicles, pavements, road side environments etc. were investigated by using the prediction model. To advance the investigations for the noise reduction measures further, it is necessary to examine the noise abatement according to the control of the traffic flow and physical distribution in the city. To examine the effects of the noise reduction due to such traffic flow managements, it is necessary to apply the macro-traffic flow model taking into account the citywide road network. The AVENUE was used as the macro-traffic flow prediction model in this study [2]. The macro-traffic flow model was integrated with the road vehicles' sound power level model, and the new road traffic noise prediction model was established [3]. In this study, first, to investigate the possibility for

a

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examining the noise reduction effect by the traffic flow control, the change of road network traffic flow after the opening of the new establishment roads was estimated. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

2 SCALE OF STUDY AREA AND PREDICTION MODELS

Figure 1 shows the scale of the study area for the road traffic noise prediction. The traffic flow is estimated as the first step for the noise prediction. Because in general the noise reduction measures are executed in the local area as shown in Fig.1 (b), the micro-traffic flow model is useful to estimate the traffic conditions in detail. For this purpose, we have developed the micro-traffic flow model which is applicable to estimate the running behavior of the individual vehicles. This model was integrated with the sound power level model, and an original road traffic noise prediction model has been established. By using this prediction model, it is possible to estimate the effects of the noise reduction measures for the road vehicle, the pavements, the road side environments and so on. For the further noise reduction measures, it is necessary to examine the noise abatement by the control of the traffic flow and physical distribution in the city. In this case, the investigation of the traffic flow of the citywide road network is very important. Therefore, the whole city as shown in Fig.1 (a) becomes a study area and the application of the macro-traffic flow model is indispensable.

(a) Citywide area (b) Local area

3 ROAD TRAFFIC NOISE PREDICTION MODEL WITH MACRO-TRAFFIC FLOW MODEL 3.1 Structure of prediction model

Figure 2 shows a calculation flow of the road traffic noise prediction model developed in this study. This model consists of the calculation models of the traffic flow and the road vehicle noise and the interface for integrating these two models. The traffic flow model was linked with a database of the digital road map of the citywide road network. The calculation models and the input data are described as follows.

3.2 Calculation model

In the macro-traffic flow model adopted in this study, the traffic flow is assumed to be compressible fluid and the vehicle running behavior is expressed as a flow of the fluid, and the running conditions of a lot of vehicles can be estimated by few calculation loads. Concretely, the road network is divided into a minute block of about 10m in length, and the vehicle movement between the adjoining blocks is calculated based on the traffic flow theory.

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To calculate the traffic noise in the citywide road network, a sound power level model of the ASJ RTN-Model 2003 proposed by the Acoustical Society of Japan was adopted [4]. Because the main purpose of this study is to predict the noise at the road side, in the calculation of the sound propagation, only the distance attenuation in the hemi-space free field was calculated, and neither the reflection nor the diffraction of the sound were considered. To calculate the road traffic noise in the entire city efficiently, the interface for integrating the macro-traffic flow model and the sound power level model was established. The traffic volume and the vehicle speeds calculated by the macro-traffic flow model were input to the sound power level model, and the traffic noise generated from each block of the road network was calculated. - Vehicle category - Vehicle speed - Road surface Traffic flow calculation model

Vehicles’ sound power calculation model

Sound propagation model

Noise map of road traffic Integration - Digital road map

- Nodes and Links - OD traffic volume

Figure 2 : Calculation flow of the road traffic noise

3.3 Input data

To predict the road traffic noise, information of the road map in the whole city is needed. The database of a digital road map is linked to the macro-traffic flow model. Tsukuba city was selected as the study area. This city is located at about 60km away from Tokyo in the direction of northeast. In this area, there are two major roads, the national highway and the Joban expressway.

Based on the above-mentioned road map, the nodes and the links were set to the intersections and between them, respectively. Figure 3 shows the nodes and the links in Tsukuba city. In the figure, the small squares and the solid lines indicate the nodes and the links, respectively. In this area, the numbers of nodes and links were 1,723 and 4,832, respectively.

Figure 3 : Nodes and links in the study area

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The traffic volume toward each destination is given to each edge node of the road network as an OD traffic volume. The vehicles that arrive at the destination disappear from the network. The generation and the disappearance of the vehicles in the road network are also considered.

4 CALCULATION RESULTS OF TRAFFIC NOISE IN CITYWIDE ROAD NETWORK 4.1 Application of macro-traffic flow model

The citywide road traffic noise was calculated from the traffic volume, the vehicle speeds and the percentage of the heavy vehicles, and the noise map shown in Fig.4 was made. The road traffic noise on the road network including not only the main roads but also the minute streets can be estimated by using this prediction model. From Fig.4 (a), it is found that the levels in the area along the main urban roads and the expressway are high. Fig.4 (b) shows more detailed noise distribution in the city center. The noise from the main urban road (the road indicated by the arrow in the figure) is higher than that from the other roads. To examine the accuracy of the noise map, the calculated noise values at the main roads were compared with the measured values. As the results, the calculated values were corresponding to the measured ones within 2 dB. However, since there are the streets in which the errors of five decibels or more are detected, the investigation for the accuracy improvement will be necessary. City center 2km LAeq

Prefectural road No.237

400m

(a) Noise map of the citywide area (b) Noise map of the city center

4.2 Possibility of application to traffic flow management

As an example of the traffic flow managements, the changes of the traffic flow and the noise caused by the opening of the new establishment roads were examined. Because the new establishment roads opened in the study area recently, the traffic flow both before and after the opening of the new roads was estimated. Figure 5 shows one frame of the traffic flow animations before and after the opening of the new roads. In the figure, a lot of points on the roads indicate the individual vehicles. It was confirmed that the opening of the new establishment roads influences the traffic flow of the road network in the wide area. Figure 6 shows the noise maps estimated from the traffic flow before and after the opening of the new roads. The traffic volume in the surrounding roads decreased according to the opening of the new roads. The effect of the noise reduction was hardly seen because the speed of the traffic flow was increased. This result indicates the difficulties of the noise reduction measure.

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However, it is expected that other kinds of environment problems (e.g. CO2) will be reduced

by the opening of the new roads.

2006

2005

(a) Before the opening of the new roads (b) After the opening of the new roads Figure 5 : Change of the traffic flow according to the opening of the new roads

2005 2006

2005

2005 20062006

(a) Before the opening of the new roads (b) After the opening of the new roads

4.3 Integration of macro-traffic flow model and micro-traffic flow model

By combining the macro-traffic flow model and the micro-traffic flow model, the coverage of the noise prediction model is able to be expanded. Then, the integration of two traffic flow models was tried according to the following procedures. First of all, the traffic flow on the road network is estimated by using the macro-traffic flow model, and the traffic volume that flows into the study area is calculated. Next, this inflow traffic volume is input to the micro-traffic flow model, and the running behavior of the individual vehicles is calculated. After the sound power levels of the individual vehicles are calculated from the running behavior, the road traffic noise is predicted. Figure 7 shows the one frame of the traffic flow animations simulated by the macro-traffic flow model and the micro-traffic flow model. The graph in the figure indicates the time dependence of the road traffic noise in the vicinity of the intersection.

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Figure 7 : Integration of citywide traffic flow model and micro-traffic flow model

5 CONCLUSIONS

The new prediction model of the road traffic noise taking into account the road network traffic flow was established in this study. The main results are as follows.

(1) The prediction model of the road traffic noise with the macro-traffic flow model is very useful for the noise mapping of the citywide road network.

(2) The noise prediction model developed in this study has a possibility to be able to estimate the noise reduction caused by the traffic flow controls and the physical distribution measures.

(3) By combining the macro-traffic flow model and the micro-traffic flow model, the coverage of the noise prediction model is able to be expanded.

6 REFERENCES

[1] T.Suzuki, K.Tsukui, Y.Oshino and H.Tachibana, “Road traffic noise prediction model around signalized intersections”, Proceedings of Inter-noise 2003 (2003).

[2] R.Horiguchi, M.Kuwahara, M.Katakura, H.Akahane and H.Ozaki, “A Network Simulation Model for Impact Studies of Traffic Management 'AVENUE Ver. 2' ”, Proceedings of the Third Annual World Congress on Intelligent Transport Systems, Orlando, CD-ROM, 1996.

[3] Y.Oshino, K.Tsukui, H.Hanabusa, A.Bhasker, E.Chung and M.Kuwahara, “Investigation into the noise map based on traffic flow prediction in the citywide road network”, Proceedings of Euronoise 2006.

[4] S.Kono, Y.Oshino, T.Iwase, T.Sone and H.Tachibana, “Road traffic noise prediction model ‘ASJ RTN-Model 2003’ proposed by the Acoustical Society of Japan - Part 2 : Calculation model of sound power emission of road vehicles”, Proceedings of ICA 2004, Kyoto, Japan.