Exterior Auralization of Traffic Noise within the LISTEN project Andrew Peplow

Hoare Lea Acoustics, 140 Aztec West, Bristol, BS32 4TX, UK

Jens Forssn

Applied Acoustics, Chalmers University of Technology, SE-412 96 Gteborg, Sweden

Peter Lundn

Interactive Institute, SoundSpace studio, SE-164 26 Kista, Sweden

Mats E. Nilsson

Institute of Environmental Medicine, Karolinska Institutet and Department of Psychology,

Stockholm University, SE-106 91, Stockholm, Sweden

Summary

In the present paper, computational auralizations of a single pass-by of a passenger car and

passenger train are investigated. Auralization of future traffic noise scenarios would be a valuable

tool for city planners, noise consultants and decision makers, since it would make it possible to

evaluate various noise mitigation solutions already at the planning stage. The main goal of the

Swedish multidisciplinary research project LISTEN has been to develop such a tool. This paper

reports recent listening experiments conducted to perceptually evaluate the auralizations and

subsequent improvements on computational methodologies regarding road and rail traffic noise and

passenger train source models.

PACS no. 43.20.Ei, 43.66.Lj

1. Introduction1

Traffic noise is a major environmental problem,

affecting the health and wellbeing of a large part of

the population. Within the Swedish multi-

disciplinary research project LISTEN, we are

developing a demonstrating tool for noise and noise

abatement of road and rail traffic, which is aimed at

helping assessment processes at various levels of

decision making. The project started in September

2008. The work presented here shows results of

auralization of single pass-bys of passenger cars

and passenger trains. The auralization methodology

is mainly based on a time-domain approach.

Psychoacoustic evaluation was conducted on all car

simulations concerning perceived realism,

annoyance and speed.

2. Methodology for auralization

In the processes of auralizing road traffic noise, for

a still-standing person at a position exterior to the

vehicle, a number of parameters need to be

considered. The path of the sound that reaches the

listener from a single vehicle can be described as

starting from a set of sources that each has its own

property concerning directivity and spectral

content, including noisy and tonal characteristics.

1(c) European Acoustics Association

For the passenger car modelled here, two sources

are used, (i) a propulsion source, which models

engine, air intake, air exhaust, fans, compressors

(traction), etc., and (ii) a road/tyre source, which

models the noise generated by the contact between

tyre and road surface. This set is modelled

according to current engineering methods

(Harmonoise and Nord2000 [1,2]), with the sources

located on a vertical line at heights (i) 0.3 m and (ii)

0.01 m. For the auralization, the source signals are

modelled as steady-state noises and steady-state

tones. After leaving the source, the sound on its

path will be influenced by: decaying amplitude due

to spherical spreading; air attenuation, which leads

to a larger reduction of the higher frequencies than

of the lower frequencies; and the reflection in the

ground surface, which leads to an interference

pattern over frequency. The theoretical interference

pattern for a point source can show very deep dips.

The real interference pattern is however usually

weakened due to smearing effects like decorrelation

caused by random ground roughness and air

turbulence as well as effects of the finite sized

sources, which has been considered here. For the

moving source, relative to the receiver, we also

have the Doppler effect. Here, we have not

considered the effects of refraction, i.e. the curved

sound paths due to wind or height varying

temperature, which however will be influential at

longer distances. Finally, the sound entering our

ears is influenced by our head and torso, which here

FORUM ACUSTICUM 2011 Forssn, Exterior auralization of traffic noise within the LISTEN project

27. June - 1. July, Aalborg

is modelled using head related transfer functions (HRTFs) from the CIPIC database, subject 165, a KEMAR manikin [3]. The whole auralization process can in our modelling be summarized as starting with the creation of the noises and tones of the sources followed by the modelling of the air attenuation, the ground effect, the directivity, the Doppler effect, the spherical spreading and ending with the HRTFs. Modelling in 1/3 octave bands is undertaken for the noise signals, the air attenuation, the ground effect and the directivity, whereas the remaining effects are modelled directly on the time signal. The creation of the source signals is based on mono recordings of straight-line pass-bys at fixed points (6 second long recordings). The recorded signals are then reshaped into to source signals by applying the knowledge of the sound propagation as an inverse problem. Similar approaches have been published previously [4,5]. Following the above description of the methodology, the process of going from the mono recording to the source signal can be described as inverting the effect of spherical spreading, the Doppler effect, the ground effect, and the air-attenuation. The signal resulting from the inversion process is seen as a first estimate of the source signal. The estimated source signal resulting from the inversion process described above is seen to contain a steady-state signal shaped by the source directivity. The slowly varying amplitudes (envelopes) of each 1/3 octave band are hence referred to as source directivity. For cars the pass-by pattern (in dB) is separated into forward and backward direction, to which second-degree polynomials are fitted. At midrange between forward and backward direction, i.e. perpendicular to the driving direction, the two polynomials are adjusted to give a continuous curve. In this way the polynomial coefficients for each 1/3 octave band are estimated and saved for later use in the auralization. The transition frequency of source dominance is estimated from the Harmonoise source model [1]. The remaining signal, after compensating for the estimated directivity patterns, is in most cases a fairly steady signal. However, at midrange position transient characteristics are still present, not captured by the polynomial fitting. Therefore, a period shortly after passage at midrange position is used as an estimate of the source signal. (Here, a 1 s long signal is used, starting 1 s after passage at

midrange position.) The tonal characteristics are modelled from peaks of a narrow band spectrum of the source signal, here using one tone per 1/3 octave band. The modelling of the propagation effects within the auralization process uses the same tools as the inversion process for the estimate of the source character, as described above. value used here for a dense asphalt surface is 2108 Nsm-4. From that, the ground impedance is calculated (e.g. [1]), which enables calculation of the spherical reflection factor. The remaining distance effect is according to spherical spreading. Finally, the Doppler effect is calculated simply using a resampling of the signal or, equivalently, seen as a delay line. For the train auralizations a directivity factor has been included in the methodology according to the work by Bongini and Bonnet [6] for the traction noise and the rolling noise. The switch from monopole to a dipole-like source was implemented for rolling noise whereas for traction sources which dominate low-frequency ranges any modifications to directivity did not influence the global pass-by signature.

3. Perceived realism, speed and annoyance

In the first listening experiment of car pass-bys, pairs of sounds were presented, each pair consisting of one real recording and one auralization of the same recording. The task was to decide which of the two sounds that was the real recording. If a listener clearly could hear which sound was real and which was auralized, then the proportion of correct responses, p(c), would be close to 1.0. If a listener could not discriminate between the two sounds, the expected p(c) would be 0.5. It is also possible that a listener could discriminate between the two sounds, but could not identify which was real and which was auralized. Such a listener would have a p(c) close to 0.0 (mainly incorrect choices) or a p(c) close to 1.0 (mainly correct choices). Figure 2 illustrates these results for a car pass-by. Further details of the results may be found in [7]. The listening panel also assessed which of two car passages, a real recording and its auralization, that was more (a) annoying or (b) was perceived as having the higher speed. For the auralized sounds these were assessed as more annoying than the real sounds in about 50 % of the cases, suggesting that auralized and real sounds were approximately

FORUM ACUSTICUM 2011 Forssn, Exterior auralization of traffic noise within the LISTEN project

27. June - 1. July, Aalborg

Figure 2 : Proportion of responses correctly identifying which of two sounds corresponds to real recording. equally annoying. The pattern of results for perceived speed was found to be similar as for perceived annoyance.

Figure 3. Result from a same-different experiment Figure 3 illustrates a test where listeners had to decide whether two sounds were identical or different. The sounds were 2-s segment from the start, middle or end part of a 6-s car passage. The sound pairs consisted of either two identical (both real recordings or both auralized ) or two different sounds (one real and one auralized). The average percent of correct responses (+/- 1 standard error) from 10 listeners are shown separately for the five

distances and the three segments of the car passage. Chance performance corresponds to 50 % correct responses, perfect performance to 100 % correct responses. 4. Train auralisation

In adopting the synthesis method described in section 2 one has to define the rolling stock, traction and track as a set of noise point sources. The synthesis method determines each noise source pass-by into a time-frequency environment, taking into account, its time-evolution (depending on pass-by scenario), the Doppler effect and the ground effect. The time-frequency plans, each of them corresponding to an equivalent point source contribution towards the pass-by noise, are summed. The global time-frequency plan is therefore transposed into the time domain. The main consequence of the synthesis method on the source model, is that the point source model is considered for equivalent source. For passenger car realizations this adoption of point source models seems reasonable upon listening panel analysis. However, for train auralizations it is still unclear whether a global point-source methodology is viable for all passenger train types. It must be pointed out that most of trains in urban

Figure 4: Illustration showing location of equivalent point sources in the train model for IC6 inter-city train. rolling conditions are composed of about twenty real noise sources. Moreover, since this method has been developed to carry out parametric studies on the influence of each noise source on the global pass-by noise, the equivalent sources have to be easily handled according to the modifications managed on real sources. Consequently, it is

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FORUM ACUSTICUM 2011 Forssn, Exterior auralization of traffic noise within the LISTEN project

27. June - 1. July, Aalborg

recommended to represent one physical noise source by very few point sources preferably only one. An RC6 intercity train shown in Figure 4 was modeled by 17 point sources, whereas a smaller commuter train Regina was modelled according to a seven equivalent point source scheme. Measurements undertaken by WSP Sweden correspond to rail measurements adopted in the ISO 3095 standard for the pass-by measurement. This method consists on recording pass-by noise with a microphone located at 7.5m from the track. It allows a characterisation of an isolated source level spectrum. However, as soon as several sources are close together, the contribution of each physical source cannot be separated. Since it does not locate equivalent point source it does not provide directivity patterns. These short-comings are partially resolved in the auralization de-dopplerisation methodology. Results showing time signals for an auralization of an original recording and a scenario including a small screen at track-side are presented in the following figures. The train length is 55.0m and estimated to travel at 90 km/h. The noise level at the receiver is estimated at LAFmax=95 dB(A).

Figure 5: Time signal recording for Regina commuter train Figure 5 shows the time signal derived from a Regina pass-by recording. Inspection of the figure showing the onset of a pulse-type wave, as the first wagon passes by the microphone, is clearly evident. This is an aerodynamic effect, and evidence of the difficulty in modelling this as a source may be seen in Figure 6, where an auralization for this situation has been performed.

Figure 6: Time signal auralization for Regina commuter train corresponding to Figure 4. A small rigid noise screen 0.5m high and 1.5m from the track-side was included in the auralization incorporating the Hadden-Pierce diffraction model [8]. A reduced noise level compared to Figure 6 calculated at 7.5 m from the source, around LAFmax=85 dB(A), is clearly displayed in Figure 7. Although not visible here, the high frequency squeal noise has been attenuated significantly.

Figure 7: Time signal auralization for Regina commuter train including a small noise screen. 5. Conclusions

The results for passenger cars showed a useful auralization methodology. Although listeners could identify which of two sounds was the real recording more often than expected by chance, they were never 100 percent accurate, and in several cases close to chance level, especially for higher speeds. For the auralized sounds from passenger cars, further listening test results will be presented in the technical sessions. Results for train auralizations are promising, technical results and auralizations will also be presented.

Acknowledgement

This research was conducted within the Swedish research program LISTEN. Auralization of Urban Soundscapes funded by The Knowledge Foundation, Invest in Sweden Agency, Swedish Governmental Agency for Innovation Systems

FORUM ACUSTICUM 2011 Forssn, Exterior auralization of traffic noise within the LISTEN project

27. June - 1. July, Aalborg

(VINNOVA), Swedish Foundation for Strategic Research, and The Vrdal Foundation. Co-funding was provided by the LISTEN projects end-user partners: The Swedish Road Administration, Swedish Rail Administration, Stockholm City, WSP Acoustics, F-Ingemansson, and Rambll Denmark A/S.

References

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[2.] Jonasson, H. Acoustic Source Modelling of Nordic Road Vehicles. SP Rapport 2006:12, 2006.

[3.] Algazi, V. R., Duda, R. O., Thompson, D. M., Avendano, C. The CIPIC HRTF Database. Proc. 2001 IEEE Workshop on Applications of Signal Processing to Audio and Electroacoustics, 99-102.

[4.] Maillard, J., Martin, J. A simulation and restitution technique for the perceptive evaluation of road traffic noise. Proc. 2008 Euronoise, Paris.

[5.] T. Kaczmarek. Road-vehicle simulation for psychoacoustic studies. Proc. 2007 ICA, Madrid.

[6.] E. Bongini and E. Bonnet. Railway noise sources definition within the scope of pass-by sound synthesis. Proc 2009, Euronoise, Edinburgh.

[7.] J. Forssen, T. Kaczmarek, J. Alvarsson, P. Lunden, M.E. Nilsson, Auralization of traffic noise within the LISTEN project Preliminary results for passenger car pass-by.

[8.] A. D. Pierce. Diffraction of sound around corners and over wide barriers. J. Acoust. Soc. Am. 97(4) (1995) 2028-2040.