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Assessing the noise reduction potential of speed limit 30 km/h

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Abstract and Figures

Speed reductions and low-noise pavements often represent the only option to reduce excessive traffic noise at the source. Noise abatement projects in urban areas, therefore, increasingly focus on decreasing the speed limit to 30 km/h to bring noise levels below acceptable limits. Commonly, noise calculation models are used in order to assess whether the introduction of a lower speed limit brings about the required noise reduction. Existing noise emission models, however, are commonly not designed for such low speeds. Hence, the basis for a reliable prediction of the noise reduction potential of speed reductions to 30 km/h is currently missing. This study addresses this gap by presenting the key findings of a national research project which was designed to provide a basis for more reliable prediction of the noise reduction potential of speed limit 30 km/h as a noise abatement measure. During a comprehensive measurement campaign with an up-to-date vehicle fleet, noise emissions were systematically assessed and characterised regarding rolling noise and propulsion noise contributions taking into account the specific driving behaviour of the low speed range, i.e. gear selection, discontinuous driving, and driving style. The acquired data were used to formulate two distinct emission approaches for constant and accelerated driving behaviour. These emission approaches were combined with a statistical survey on the actual driving behaviour in existing 30 km/h speed limit situations and extended with an adapted emission approach for heavy vehicles from the European noise emission model CNOSSOS. The resultant approach allowed for the prediction of the noise reduction of planned speed reductions to 30 km/h with high reliability. The study, moreover, showed that substantial noise reduction can be achieved by reducing the speed limits to 30 km/h since noise levels (Leq) can be reduced between approx. 1 dB and 5 dB, depending on a range of decisive influencing factors.
Rolling (red), propulsion (green) and total noise emissions (black) for light vehicles travelling at constant speeds between 1 and 60 km/h. Propulsion noise for single gear selections is presented in gray. As Figure 2 shows, rolling noise dominates already from a speed of around 16 km/h with an up-to-date passenger car fleet (EU-mix). An earlier conference paper based on the same data (11), moreover, showed that the cross-over speed only varies relatively little in function of vehicle and engine type: 14.8 km/h for hybrid cars, 15.2 km/h for petrol cars, 15.8 km/h for diesel cars, and 33.7 km/h for diesel light duty vehicles. These derived cross-over speeds are rather low compared to previous studies showing cross-over speeds usually above 25 km/h for passenger cars (15-17). For this study it was, however, intended to investigate a more modern vehicle fleet to establish a model for present and future use (the average year of construction of the investigated vehicle fleet was 2011). The trend towards significantly lower cross-over speeds can be explained by recent tendencies towards more silent motor units, which reduces the contribution of propulsion noise, and heavier passenger cars with larger tyres, which simultaneously increases the rolling noise component. Figure 2, moreover, shows that propulsion noise is only dominant around the 1 st gear peak at around 12 to 13 km/h, where a majority of vehicles still drive in the first gear. From the cross-over speed onwards the majority of vehicles drive in the second or higher gears and rolling noise becomes the
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Assessing the noise reduction potential of speed limit 30 km/h
Erik BÜHLMANN1 and Sebastian EGGER2
1,2 Grolimund + Partner AG environmental engineering, Switzerland
ABSTRACT
Speed reductions and low-noise pavements often represent the only option to reduce excessive traffic noise at
the source. Noise abatement projects in urban areas, therefore, increasingly focus on decreasing the speed
limit to 30 km/h to bring noise levels below acceptable limits. Commonly, noise calculation models are used
in order to assess whether the introduction of a lower speed limit brings about the required noise reduction.
Existing noise emission models, however, are commonly not designed for such low speeds. Hence, the basis
for a reliable prediction of the noise reduction potential of speed reductions to 30 km/h is currently missing.
This study addresses this gap by presenting the key findings of a national research project which was
designed to provide a basis for more reliable prediction of the noise reduction potential of speed limit
30 km/h as a noise abatement measure. During a comprehensive measurement campaign with an up-to-date
vehicle fleet, noise emissions were systematically assessed and characterised regarding rolling noise and
propulsion noise contributions taking into account the specific driving behaviour of the low speed range, i.e.
gear selection, discontinuous driving, and driving style. The acquired data were used to formulate two
distinct emission approaches for constant and accelerated driving behaviour. These emission approaches
were combined with a statistical survey on the actual driving behaviour in existing 30 km/h speed limit
situations and extended with an adapted emission approach for heavy vehicles from the European noise
emission model CNOSSOS. The resultant approach allowed for the prediction of the noise reduction of
planned speed reductions to 30 km/h with high reliability. The study, moreover, showed that substantial noise
reduction can be achieved by reducing the speed limits to 30 km/h since noise levels (Leq) can be reduced
between approx. 1 dB and 5 dB, depending on a range of decisive influencing factors.
Keywords: Road traffic noise, Noise emission modelling, Lower speeds, I-INCE Subject Numbers: 13; 76
1. INTRODUCTION
In urban areas and cities, noise levels from road traffic frequently exceed acceptable limits at
neighbouring residential buildings (15). Since there is growing evidence that noise pollution is not
merely an annoyance, but has wide-ranging adverse health, social and economic effects (68), cities
and counties are increasingly addressing noise in their planning efforts. With existing road networks,
noise abatement projects are undertaken in order to reduce road traffic noise. Speed reduction and
low-noise pavements, thereby, often represent the only option to reduce excessive traffic noise at the
source. Noise abatement projects in urban areas therefore, increasingly focus on a decrease in the
speed limit to 30 km/h as a noise abatement measure. The study (9) showed that existing noise
emission models display a large variability in noise prediction at speeds below 40 km/h. This suggests
that they are not designed for such low speeds. Hence, the basis for a reliable predicti on of the noise
reduction potential of such speed reductions is currently missing.
This study addresses this gap and presents key findings of a national research project (10)
designed to provide an up-to-date basis for more reliable predictions of the noise reduction potential
when assessing the introduction of a 30 km/h speed limit as a noise abatement measure. Firstly, a noise
emission model for passenger cars specifically elaborated for the lower speed range is presented,
separating the two main noise sources rolling noise and propulsion noise. Secondly, the study
investigates variables potentially causing variation in the expected noise reduction potential. Finally,
this study provides data for the estimation of the noise reduction potential of speed reductions based on
1 erik.buehlmann@grolimund-partner.ch
2 sebastian.egger@grolimund-partner.ch
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the most decisive influencing factors.
2. MATERIALS AND METHODS
The data basis for the low speed noise emission approach was collected during a measurement
campaign with 22 modern passenger cars at a testing site in Switzerland. The influence of the varying
driving behavior and gear selection at different speeds was acquired in a statistical survey at five
different traffic situations with a speed limit of 30 km/h and one reference situation with a speed limit
of 50 km/h.
2.1 Noise emission measurements at low speeds
The measurement campaign on noise emissions at low speeds took place at the Dynamic Test
Centre in Vauffelin, Switzerland on 22 April 2015 and was particularly designed firstly, to illustrate
the complex transition between rolling and propulsion noise at lower speeds and secondly, to
determine the influence of driving behaviour and gear selection to the total noise emission. A set of 22
representative and modern passenger cars of common size and type (see Table 1) delivered rolling
noise, total noise and acceleration noise emission levels for 18 instructed pass-by scenarios between
20 and 50 km/h and for the gears 1 to 4. More detailed information on the vehicles and tyres are
provided in (11).
Table 1: Analyzed vehicles and tires during the measurement campaign (10).
vehicle
ID
V
ehicle
engine
cubic capacity
[ccm]
date of 1st
registration
tyre
1
Ford USA, Mustang 5.0i
-V8 GT
petrol
4951 2015
Pirelli Pzero
2
Volkswagen Touran
petrol
1390
12.03.2009
Michelin EnergySaver Xgreen
3
Toyota Highlander
hybrid
3331
30.07.2014
Toyo A20 OpenCountry
4
Audi A1 1.4 TFSI CoD Sb
petrol
1395
07.11.2013
Continental PremiumContact 2
5
Toyota Auris HSD
hybrid
1798
15.04.2014
Dunlop SportFastResponse
6
Volkswagen Touran 2.0D Blue Motion
diesel
1968
06.01.2012
Michelin EnergySaver
7
Subaru Impreza
diesel
1998
05.04.2011
Dunlop SportBlueResponse
8
Volkswagen T5 California TDI
diesel
1968
27.02.2012
Bridgestone Duravis
9
Volkswagen Golf VII 1.4 TSI 5
petrol
1395
11.04.2013
Bridgestone Turanza ER300
10
Volvo XC60 D3 AWD
diesel
2400
15.10.2010
Pirelli Scorpion Zero
11
Citroen C4 Picasso 1.6i
petrol
1598
28.09.2010
Michel in Pr imacy HP
12
Volkswagen Golf VI 1.4 TFSI
petrol
1390
26.07.2011
Continental WinterContact
13
Renault Espace 2.0 DCI
diesel
1995
18.05.2006
Nokian ZG2
14
BMW i3
electric
n/s
25.09.2014
Bridgestone EcoPia EP500
15
Skoda Octavia C 1.8 TFSI
petrol
1798
16.12.2011
Dunlop SportMaxx RT
16
Audi A3 SB 2.0 TDI
diesel
1968
22.02.2013
Continental SportCo
ntact 5
17
Peugeot308 SW 1.6 HDI FAP
hybrid
1560
04.10.2012
Continental WinterContact TS830
18
VW e-Golf
electric
n/s
29.07.2014
Continental WinterContact TS850
19
Mini Cooper
petrol
1598
14.06.2002
Star Performer Winter A
20
Toyota Previa 2.4
petrol
2362
15.10.2004
Michelin EnergySaver
21
Mercedes
-Benz Viano 3.0 CDI
diesel
2987
01.07.2013
Dunlop SportMaxx RT
22
Mercedes
-Benz 313 CDI
diesel
2143
05.11.2012
Continental Vanco Winter 2
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Figure 1 Analyzed vehicle fleet displayed by vehicle tare weight and cubic capacity of the engine.
To separate the rolling and propulsion noise, acoustical Coast-by and Controlled Pass-by
measurements according to (12) were performed at constant speeds. In order to assess the influence of
unsteady driving behavior due to traffic calming measures (e.g. speed bump, non-priority crossings
etc.) on noise emissions, real accelerated pass-by events were reproduced by carrying out Acceleration
pass-by measurements for two different driving styles prudent and aggressive once after a full stop
and once simulating an unsteady traffic flow (acceleration after slowing down).
2.2 Statistical survey of driving behavior
To incorporate the influence of specific driving behavior at different speeds, it was necessary to
gain a detailed knowledge on the effective driving behavior in real situations, as well as on the
effective gear-speed-distribution. Both were acquired in a statistical survey on driving behavior
carried out at five different traffic situations with a speed limit of 30 km/h, as well as one reference
situation with a speed limit of 50 km/h. All measurement sites were situated in two large Swiss
agglomerations and had moderate to high traffic volumes. The measurements were carried out at three
different times of the day: daytime, rush hour and night time. During the measurement, the speed of
every passing car was measured with a Sierzega SR4 radar. The gear of each passing car was estimated
by acoustically categorizing engine speed into two groups (“high” and “low”) and assigning the
expected gear for the corresponding speed (for instance, assigning gear 3 for a vehicle passing at
30 km/h while being assigned to the engine speed group “low”). Additionally, the acceleration type
(discontinuous or after stopping) and driving style (prudent or impetuous) were estimated acoustically
and categorized (these results are discussed in detail in [4]). In this manner, almost 4'700 cars were
measured and rated, and formed a unique dataset of effective driving behavior.
2.3 Establishing the emission approach
The emission approach in this study is established by combining the emission data acquired from
the measurement campaign with the statistical data acquired from the survey of drivin g behavior at
real low-speed situations. The emission approach considers (a) rolling noise and the influence of the
pavement, (b) propulsion noise and (c) acceleration noise. Whilst the rolling noise model is directly
derived from the coast-by measurements, the propulsion noise model is based on the assumption that
rolling noise and propulsion noise add up to the total noise at constant speed and gear. Acceleration
events are considered based on the total noise emissions from the corresponding acceleration scenario.
For some passenger cars with hybrid engines a declutching of the engine was not possible. For
those cars it was not possible to measure valid rolling noise emissions. Under the assumption that
driving at low-speeds is powered by the battery, these cars are treated as electric vehicles without any
noise emissions of the engine.
A detailed description of the methods including the measurement campaign, the statistical survey
and the emission approach is presented in (10).
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3. RESULTS & DISCUSSION
This section presents and discusses the results of an extensive measurement campaign undertaken
to elaborate road traffic noise emissions of passenger cars at lower speeds. Firstly, a series of
influencing factors of road traffic noise emissions at lower speeds are evaluated from the different
driving scenarios carried out during the measurement campaign. Secondly, this section provides a
basis for the estimation of the noise reduction potential of speed limit 30 km/h in a particular situation
and, hence, its suitability as a noise abatement measure.
3.1 Influencing factors
3.1.1 Rolling and propulsion noise in function of actual driving speed and gear selection
In order to allow for the separation of rolling and propulsion noise, several paired scenarios
involving coast-by measurements (with the engine switched off) and controlled pass-by measurements
(with the engine running in a specified gear) at different speeds were undertaken and evaluated. The
resulting emission model for passenger cars for the low speed range is presented in Figure 2. The
model is designed for a European vehicle fleet driving at constant speed with a composition of 53%
petrol cars (incl. gas powered cars), 38% diesel cars, 1.4% hybrid cars, 0.7% electric cars and 6.9%
light-duty commercial vehicle (13,14) and assumes a mix of pavements DAC (dense asphalt concrete)
and SMA (split mastic asphalt), both with maximum chipping size 11 mm. The speed at which the
rolling noise becomes more dominant than the propulsion noise is called cross-over speed and is
indicated with a dashed line.
Figure 2 Rolling (red), propulsion (green) and total noise emissions (black) for light vehicles travelling at
constant speeds between 1 and 60 km/h. Propulsion noise for single gear selections is presented in gray.
As Figure 2 shows, rolling noise dominates already from a speed of around 16 km/h with an
up-to-date passenger car fleet (EU-mix). An earlier conference paper based on the same data (11),
moreover, showed that the cross-over speed only varies relatively little in function of vehicle and
engine type: 14.8 km/h for hybrid cars, 15.2 km/h for petrol cars, 15.8 km/h for diesel cars, and
33.7 km/h for diesel light duty vehicles. These derived cross-over speeds are rather low compared to
previous studies showing cross-over speeds usually above 25 km/h for passenger cars (1517). For this
study it was, however, intended to investigate a more modern vehicle fleet to establish a model for
present and future use (the average year of construction of the investigated vehicle fleet was 2011).
The trend towards significantly lower cross-over speeds can be explained by recent tendencies towards
more silent motor units, which reduces the contribution of propulsion noise, and heavier passenger
cars with larger tyres, which simultaneously increases the rolling noise component.
Figure 2, moreover, shows that propulsion noise is only dominant around the 1st gear peak at around
12 to 13 km/h, where a majority of vehicles still drive in the first gear. From the cross-over speed
onwards the majority of vehicles drive in the second or higher gears and rolling noise becomes the
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dominant emission source. The propulsion noise curve shows a wave shape with slight dips whenever
a majority of vehicles change to the next higher gear and propulsion noise emission start increasing
again in function of engine speed. The propulsion noise component, however, remains well below the
rolling noise curve regardless of the driving speed and the selected gear. This means that, above speeds
of the first gear peak, gear selection constitutes only a secondary influencing factor when modelling
road traffic noise emissions at lower speeds and can, hence, be neglected in most cases. The rather
small importance of gear selection observed for a modern vehicle fleet is attributed in part to the
emergence of stronger engines which permit the driver to operate the engine at lower gears and engine
speeds.
3.1.2 Unsteady driving behaviour
At lower speeds the influence of unsteady driving behaviour on noise emissions may become more
important than it is at higher speeds. This may be even more the case as occasionally the introduction
of speed limit 30 km/h is accompanied with traffic calming measures, such as speed bumps, narrow
zones to prevent crossing, non-priority crossings etc. to enforce lower speeds. To evaluate the
influence of different traffic calming measures (and associated driving behaviours) on noise emissions,
a series of acceleration pass-by driving scenarios were carried out. The driving scenarios, separately
investigated aggressive acceleration behaviour and a more prudent driving style, both undertaken,
firstly, after a full stop and, secondly, after merely slowing down (e.g. unsteady driving behaviour
because of a non-priority crossing). The influence of unsteady driving behaviour on noise emissions at
lower speeds is shown in Figure 3.
prudent / stop
prudent / discon.
aggressive / stop
aggressive / discon.
Figure 3 The influence of unsteady driving behaviour on noise emissions (Lmax) from acceleration pass-by
measurements of 22 vehicles, normalized to the noise levels of the average vehicle at constant speed 30 km/h.
As Figure 3 illustrates, unsteady driving behaviour leads to significantly higher noise levels when
compared with the average noise emissions of vehicle driving at 30 km/h at constant speed (here
normalised to the noise emissions when driving in 3rd gear). While the noise emissions increase by 3 to
4 dB with prudent acceleration behaviour, aggressive acceleration leads to increases of between 7 and
9 dB. This suggests, that unsteady driving behaviour should be avoided when introducing speed limit
30 km/h for noise abatement purposes. When comparing the noise levels of unsteady driving behaviour
with the ones at constant speed 50 km/h, unsteady driving behaviour can even lead to a decrease in
noise levels (except for the aggressive accelerations after a full stop). The reason for this may be that
vehicles in order to be able to accelerate mostly drive at speeds below the speed limit at the time of
acceleration (which causes a decrease in rolling noise). The increase in propulsion noise during
acceleration, thereby, does not offset the decrease in rolling noise. This leads to the conclusion that
unsteady driving behaviour at a speed of 30 km/h leads to an increase in noise levels, whereas the
opposite is true at a speed of 50 km/h and above.
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3.1.3 Road design
The significant increase of noise levels attributed to unsteady driving behaviour at speed limits of
30 km/h (as shown in section 3.1.2) leads to the assumption that the noise reducing effect of speed
limit 30 km/h may be compromised by traffic calming measures that lead to unsteady driving
behaviour. In order to investigate the influence of road design on the noise reduction potential of speed
limit 30 km/h, Figure 4 cross-compares the statistical occurrence of unsteady driving behaviour for
three different types of situations with speed limit 30 km/h:
x 30 km/h zone narrow: two situations with a range of traffic calming measures: speed bumps,
narrowing of the road to unable crossing of vehicles, no-priority crossings;
x 30 km/h zone spacious: two situations with spacious road design, transverse pavement
markings at entries and a continuous multifunctional strip (marking) in the middle of the
road as space for turning vehicles and pedestrians wishing to cross the road;
x 30 km/h street with signalling only: one situation with no additional measures apart from
signalling speed limit 30 km/h.
-5.1 dB
29.4 km/h
Proportion of total traffic
Unsteady driving behavior
aggressive / discon.
aggressive / stop
prudent / discon.
prudent / stop
constant
Noise Distribution of driving speed
31.7 km/h24.6 km/h
Speed [km/h]
median speed:
Noise reduction:
Comparison to
Ref. @ 50 km/h,
100% cars
-4.4 dB-4.9 dB
rush hour
night
day
Driving behavior
Time period
Figure 4 Influence of road design on unsteady driving behavior, statistical distribution of speed, and noise
reduction (Leq).
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Figure 4 shows that the lowest average driving speed (24.6 km/h) is obtained for the situations zone
narrow with additional traffic calming measures. Despite the greatest reduction in actual driving speed,
this situation does not yield in the largest noise reduction. The largest noise reduction was obtained for
the situations zone spacious limited accompanied traffic calming measures. The reason for the smaller
noise reduction for the situations with additional traffic calming measures primarily is that the noise
reducing effect of the additional drop in driving speed is offset by the adverse effect of the increase of
unsteady driving behaviour associated with them (due to a larger share of vehicles forced to
slow-down or stop and then accelerate again). The situation street with signalling only leads also to
significant noise reductions because the effect of the somewhat higher driving speed is partially
compensated by the smaller share of acceleration events. Hence it can be concluded that it is not
necessarily desirable to further slowdown road traffic by accompanying traffic calming measures
when implementing speed limit 30 km/h for pure noise abatement reasons. It, however, may be that out
of road safety requirements (e.g. due to nearby schools), traffic calming measures nevertheless
represent the most favourable option.
3.1.4 Pavement
Due to the fact that rolling noise becomes dominant already from a speed of around 16 km/h (see
section 3.1.1), the acoustic properties of a pavement may also have an effect on the noise reduction
potential of introducing speed limit 30 km/h. The pavement may, thereby, influence the noise
reduction both in a positive and in a negative way. As it is mainly rolling noise that changes with speed
(see Figure 2), one can assume that a noisier pavement generally increases the chances for a high noise
reduction when introducing speed limit 30 km/h (because the loud pavements increases the dominance
of the rolling noise component). As the rolling noise changes with speed differently depending on the
pavement type (18,19), this pavement specific speed dependency may also have an impact on the noise
reduction achieved by speed limit 30 km/h.
The effect of low-noise pavements at lower speeds was assessed in detail in a separate study (20).
The study revealed that low-noise pavements can constitute an effective measure also in the low-speed
range. Moreover, it suggested that the combination of low-noise surfaces with speed reductions has the
potential to further reduce noise levels than a speed reduction alone. This may especially be promising
for inner-city roads with high traffic volumes where large noise reductions are required to mitigate the
problem. The study, however, raised caution about the effectiveness of low-noise pavements on roads
with high proportions of heavy vehicles and for speeds below 20 km/h.
3.1.5 Heavy vehicles
No measurements regarding the noise emissions of heavy vehicles were carried out in the scope of
this project. To estimate the noise reduction potential of speed limit 30 km/h on roads with higher
percentage of heavy vehicles, the rolling and propulsion noise emissions of the CNOSSOS model for
vehicle category 2 were added to those for light vehicles. The accuracy of the predictions for heavy
vehicles may be limited since the CNOSSOS model was not designed for such low speeds. The
estimations may nevertheless help to obtain a better understanding of this influencing factor. The
influence of heavy vehicles on the noise emissions at 30 km/h is illustrated in Figure 5 and compared
to the one at 50 km/h. Figure 5 shows that the influence of heavy vehicles on the noise emissions is
much stronger at 30 km/h than it is at 50 km/h because the emissions of heavy vehicles decrease to a
far lesser degree with speed than the emissions of light vehicles. In practice this means that the noise
reduction effect of 30 km/h will be diminished by higher proportions of heavy vehicles.
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Noise level increase [dB]
in comparison to 100% light vehicles at respective speed
Proportion of heavy vehicles
Figure 5 Influence of different proportions of heavy vehicles on the noise emissions (Lmax) at 30 km/h and
50 km/h (normalized to the noise emissions of 100% light vehicles at constant speed).
3.2 Estimating the noise reduction potential
Integrating all previous findings, this study provides a guide for the estimation of the noise
reduction potential of 30 km/h based on the two main influencing factors. The results presented in
Figure 6 are based upon the noise emissions of an up-to-date European vehicle fleet and incorporate
the statistically determined speed distributions, gear selection, unsteady driving behavior as well as
the effect of heavy vehicles.
Proportion of
heavy vehicles
Speed [km/h]
Figure 6 Guide for estimating the noise reduction potential (Leq) of speed limit 30 km/h (when signaled
down from 50 km/h) in function of the two main influencing factors effective driving speed (median value)
and the proportion of heavy vehicles.
Instructions:
1. Select target speed on x-axis (as it is likely to occur in the target situation; consider local practical experiences if available).
2. Select proportion of heavy vehicles on the road section (current and target situation) on the y-axis.
3. Determine the approximate noise reduction potential by using color legend and gradients.
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Figure 6 shows that introducing a speed limit of 30 km/h as a noise abatement measure may lead to
noise reductions of between 1.5 to 5 dB depending upon effective driving speed and the proportion of
heavy vehicles. The fact that such noise reductions can be achieved also without substantial traffic
calming measure, makes speed reductions an efficient and cost-effective noise abatement measure
which potentially reduced road traffic noise a t the source considerably. On road sections with higher
proportion of heavy vehicles, however, the noise reduction becomes smaller. Above a proportion of
heavy vehicles of 10%, the introduction of speed limit 30 km/h loses much of its effectivity. Moreover,
the actual driving speed in the situation before the introduction of 30 km/h should be considered.
Especially in inner-cities the statistical driving speed can be much lower than the signaled speed which
further decreases the speed reduction’s acoustic benefit.
4. CONCLUSIONS
This paper presented the results of a national research project in which the noise reduction effect of
introducing 30 km/h as a noise abatement measure was investigated by means of an extensive
measurement campaign. This study revealed that introducing speed limit 30 km/h leads potentially to
substantial noise reductions, but with a large spread in its effectivity. It, moreover, found that no
accompanying traffic calming measures are needed in order to achieve the acoustic benefit. This
means that speed limit 30 km/h can also be implemented on main roads with high traffic volumes and
makes speed reductions an efficient and cost-effective noise abatement measure which potentially
reduced road traffic noise at the source considerably. The potential noise reduction, however, can be
compromised by two main influencing factors: higher actual driving speeds and high proportion of
heavy vehicles. These factors are taken into account by the guide for the estimation of the noise
reduction potential provided in this paper. Influencing factors of secondary order comprise the design
of the road (and the corresponding statistical distribution of driving speed, gear selection and driving
behavior) and the acoustic characteristics of the pavement (and its acoustic behavior in function of
speed). It should be noted that the noise emissions of heavy vehicles were calculated with the
European model CNOSSOS and were not subject of the measurement campaign. They, therefore,
constitute a limitation of this study. We propose that future research efforts should be directed towards
improving the available data on the statistical noise emissions for heavy vehicles, busses and other
loud vehicles.
ACKNOWLEDGEMENTS
This work was supported by the Federal Office of Environment (FOEN) and Federal Road Office
(FEDRO). We thank David Murton for language editing
REFERENCES
1. Lin-hua X, Ming C, Er-da L. Comprehensive Evaluation of Traffic Noise Pollution Based on Population
Exposure. Procedia - Soc Behav Sci. 2013;96:217986.
2. Hunashal RB, Patil YB. Assessment of Noise Pollution Indices in the City of Kolhapur, India. Procedia
- Soc Behav Sci. 2012;37:44857.
3. Ozer S, Yilmaz H, Yeil M, Yeil P. Evaluation of noise pollution caused by vehicles in the city of Tokat,
Turkey. Sci Res Essay. 2009;4(11):120512.
4. Barrigón Morillas JM, Gómez Escobar V, Méndez Sierra JA, Vílchez Gómez R, Trujillo Carmona J. An
environmental noise study in the city of Cáceres, Spain. Appl Acoust. 2002;63(10):106170.
5. Zannin PHT, Diniz FB, Barbosa WA. Environmental noise pollution in the city of Curitiba, Brazil. Appl
Acoust. 2002;63(4):3518.
6. Roswall N, Høgh V, Envold-Bidstrup P, Raaschou-Nielsen O, Ketzel M, Overvad K, et al. Residential
exposure to traffic noise and health-related quality of life-A population-based study. PLoS One.
2015;10(3):113.
7. Hammer M.S., Swinburn T.K., Neitzel R.L. Environmental Noise Pollution in the United States:
Developing an Effective Public Health Response. Environ Health Perspect. 2014;122(2):1159.
8. Goines L, Hagler L. Noise Pollution: A Modern Plague. South Med J. 2007;100(3):28794.
9. Probst W. Accuracy and Precision in Traffic Noise Prediction. Internoise 2010. Lisbon, Portugal; 2010.
p. 16.
10. Bühlmann E, Egger S, Hammer E, Ziegler T. Basic information for assessing noise effects at speed
limit 30 km/h (in German and French) [Internet]. Forschungsprojekt VSS 2012/214 auf Antrag des
4047
Schweizerischen Verbands der Strassen- und Verkehrsfachleute (VSS). Bern; 2017. Available from:
http://www.mobilityplatform.ch
11. Hammer E, Egger S, Saurer T, Bühlmann E. Traffic noise emission modelling at lower speeds. Conf
Proceeding ICSV 2016. 2016;18.
12. UN ECE R117. Uniform provisions concerning the approval of tyres with regard to rolling sound
emissions and to adhesion on wet surfaces. 2007.
13. International council on clear transportation (ICCT). European vehicle Market Statistics. 2016.
14. European Environment Agency (EEA). Monitoring and reporting of average CO2 emissions
(passenger cars). 2016.
15. Kephalopoulos S, Paviotti M, Anfosso-Ledee. Common Noise Assessment Methods in Europe
(CNOSSOS-EU). Luxembourg: Publications Office of the European Union; 2012. 180 p.
16. Hanson DI, James RS. Colorado DOT tire/pavement noise study. 2004.
17. Czyzewski A, Ejsmont JA. Validation of Harmonoise/Imagine Traffic Noise Prediction Model by
Long Term Noise and Traffic Monitoring. Joint Baltic-Nordic Acoustics Meeting 17. 2008.
18. Schwanen W, van Leeuwen HM, Peeters AAA. Acoustic optimization tool - RE3: Measurement data
Kloosterzande test track. Aalsmeer; 2007.
19. Bühlmann E, Sandberg U, Mioduszewski P. Speed dependency of temperature effects on road traffic
noise. Internoise 2015. San Francisco;
20. Egger S, Saurer T, Hammer E, Bühlmann E. A new method for reliable determination of the acoustic
performance of low-noise pavements at speeds below 50 km / h. Internoise 2016. Hamburg; 2016. p.
694251.
4048
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