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Correlation between traffic flows and noise reduction in HUSH project strategic actions Salvatore Curcuruto, Rosalba Silvaggio, Massimo Stortini Italian National Institute for Environmental Protection and Research (ISPRA), Italy

Raffaella Bellomini, Sergio Luzzi Vie En.Ro.Se. Ingegneria, Florence, Italy

Giorgio Baldinelli University of Perugia, Industrial Engineering Department, Italy

Francesco Borchi, Monica Carfagni Department of Mechanics and Industrial Technology, University of Florence, Italy

SummaryH.U.S.H. “Harmonization of Urban Noise reduction Strategies for Homogeneous action plans” is a project co-funded by European Community’s Life+ Program and it has the general goal to contribute to the harmonization of the national and European legislations, regarding the noise management tools, introduced by the END Directive 49/2002, starting from the realization of interventions in two areas of the city of Florence, identified by the Noise Abatement Plan and the Strategic Action Plan as critical areas, considered as pilot cases. Concerning the largest area considered, Peretola-Brozzi, characterized by the presence of many and different noise sources (air, rail and road transport), the attention has been focused on the critical situation analysis resulting from vehicular traffic scenarios. Tools regarding design and traffic management have been used for analysis and evaluation, as well as a computational model for traffic management (Traffic Management Model - TMM) validated with measured data, in order to analyze the current situation and to provide estimates on projected changes, in terms of traffic flows. The results of simulations carried out on traffic flows, related to the different scenarios considered, have been used as input data for the acoustic model, leading to the definition of relationships existing between changing traffic flows and the reducing environmental noise.

PACS 43. 50.Rq, 43.50.Rq

1. Introduction

H.U.S.H. “Harmonization of Urban Noise reduction Strategies for Homogeneous action plans” has the main aim to contribute to the harmonization of the national noise management standards and tools with European measures introduced by the Directive 2002/49/EC, supporting the process of transposition, implementation and, currently, revision of the Directive. The structure of the project, aimed to obtain homogeneous noise action plan, may be distinct into the following steps: analysis of the conflicts identified among current standards at Regional, National and European level and proposal of methodological solutions; definition of a new development system (procedures and database) for an integrated action planning, considering the different standards which are involved; test of the procedures identified in two pilot cases in Florence, representative of different

problems found in urban areas, at different scale of operation; proposal of a methodology, able to be applied in different contexts and editing of guidelines to support government, competent authorities and policymakers [1]. The collection and analysis of legislations had pointed out eight macro areas, produced by the aggregation of critical points , in respect of whom methodological solutions have been identified [2]. Different types of strategic solutions (changes to the traffic plan, strategic actions on residential areas, switch to other transport systems) have been subsequently proposed and submitted to an evaluation of effectiveness, especially in terms of noise reduction and cost, and different methods able to be used, at different level, have been identified, in order to evaluate the application in the two pilot areas selected. The analysis of the characteristics of the two pilot areas, identified by the Noise Abatement Plan and the Strategic Action Plan of the City of Florence as critical areas, has been

(c) European Acoustics Association, ISBN: 978-84-694-1520-7, ISSN: 221-3767 659

started. The first area, named Peretola-Brozzi, is a large and delimited area, characterized by the presence of many and different noise sources, the second area, Rifredi Careggi, is characterized by the presence of the Hospital of Careggi and some school buildings one of which, the School Don Minzoni, is the object of intervention. Concerning the largest area, Peretola-Brozzi, the attention was focused on the critical situation analysis resulting from vehicular traffic and on problem-solving scenarios, using traffic planning and a computational model for traffic flows (Traffic Model Management, TMM), validated with in situmonitoring. The output data of different scenarios analyzed by the TMM have been used as input data for noise computational model. The comparison of the results allows the identifications of the correlation existing between changing traffic flows and the entity of noise reduction.

2. Peretola- Brozzi pilot area

This suburbian area includes the historical quarters of Brozzi and Quaracchi, in the north-west of Florence. The area is delimited by two major road: Via Pratese and Via Pistoiese. It is a densely populated area with the presence of a community deeply rooted in its territory. The traffic, causing noise disturbance to the population, is mainly caused by the flow of vehicles between the two main roads crossing the urban area mainly using the inner local streets system, rather than the outer ring. So the project proposes to change the traffic condition creating a limited traffic zone only for residents and moving cross-traffic from local streets to external road system. The main points of the area with public interest (public gardens, squares, schools, public libraries, churches, etc..) will be connected through pedestrian/bicycle paths. Some specific soundscapes will be designed for some strategic areas as “sonorous-stops” along the paths.

3. Traffic Model Management (TMM)

The mobility simulation of Peretola-Brozzi pilot area is based on the definition of three models: the demand model, the supply model and the allocation model [3]. The demand model, represented by a origin-destination matrix, allows the definition and the

simultaneous treatment of the demand segments for the individual transport constituted by light and heavy vehicles, and distinguishing among internal, exchange and crossing fluxes. The matrix was built by a traffic monitoring campaign conducted in the area under examination; this method of investigation is preferred to other indirect approaches, as it gives more reliable results; it was possible to proceed with the in situ analysis since the zone has a limited extension and a low number of access roads. The supply system consists of the local net modeling through a georeferenced graph made of segments and junctions characterized, for instance, by the speed limit (segments) or priority signs (junctions). The allocation procedures permit:

the evaluation of the traffic flows on segments and junctions; the definition of the indicators for the description of the service quality among traffic zones; the estimation of the number of the private users that choose an itinerary with the objective of minimizing their own generalized transport cost.

Delay functions complete the characterization of the travelling time in each element of the net [4]. If updated traffic data are available, it is therefore possible to evaluate the allocation: the coherence between the model values and the registered ones, eventually improving the convergence with a fuzzy procedure.

3.1 In situ monitoring of traffic flows

The Traffic Model Management calibration consisted of the traffic flows definition in all the roads of the investigated district. Besides, by means of interviews given to drivers transiting on these roads, the fluxes origins and the main attractors were individuated. It emerged that the area under examination is interested by a crossing traffic flow linked to the direct connection between two important roads (Via Pistoiese and Via Pratese) that enclose the zone. The results of the interviews, together with data obtained by a series of traffic counting systems (Figure 1), allowed the definition of the “scenario 0”, validating at the same time the Traffic Model.

(c) European Acoustics Association, ISBN: 978-84-694-1520-7, ISSN: 221-3767660

Figure 1. Location of traffic counting systems and the points where the interviews were proposed to people.

In figure 2 is reported the fluxogram relative to the calibrated net at the hour of maximum traffic (08:00-09.00 a.m.) [5].

Figure 2. Traffic flows in the scenario 0.

3.2 Simulation of alternative scenarios through the TMM

The main strategic intervention to lighten the traffic pressure in the district is individuated in the translation of the transit of the crossing flow, bypassing the most congested roads with the

involvement of the existing passages in the west part of the district Brozzi. Beyond this action, it is possible to explore other alternatives linked to local interventions aimed to rationalize the vehicular distribution inside the zone. In figure 3 the net of differences is presented for one of the solutions proposed: the thickness of blue lines is proportional to the decrease of the traffic flow in each segment and for each direction, while the red lines are related to the enhancement of the vehicles number. The values of the differences are also indicated with numbers. The example shows how it is possible to diminish the traffic pressure on the internal paths of the district, without charging excessively the other roads; with these modifications a higher standard of safety is guaranteed for the inhabitants, as well as a probable improvement of the area acoustic environment.

Fig. 3. Net of the traffic flows differences for one of the alternative scenarios proposed.

4. The Acoustic model

The CadnaA (ver 3.7.124) package, developed by DataKustik GmbH, has been used for acoustic modeling. It implements several algorithms for outdoor noise propagation simulations based on ray-tracing technique, in accordance with the most recent EU standards. In particular, for the case study the official French method NMPB_Route-96, suggested by EU guidelines for modeling Traffic Noise emission.


The model has been validated by means of a noise measurement campaign and traffic flows collection and cataloguing in five significant points: P01, P02, P03, P04, P05 (see figure 4) corresponding to the more critical road sources (via di Cammori, via di Quaracchi, via del Ponte del Pecora, via di Brozzi, via della Saggina).

Fig. 4. Points of measurement for model validation.

For the validation of the acoustic model, values of LAeq,TR, where TR is the national time interval (daytime= 6-22 and nighttime=22-6) measured in P01, P02, P03, P04, P05 has been compared with the calculated values produced as output by the model, being the hourly average of equivalent light vehicles and equivalent heavy vehicles the input. Equivalent values for light and heavy vehicles are calculated applying to collected traffic data the conversion parameters (relative to emission data of NMPB method, found on “Guide du bruit des transports terrestres, fascicule prevision des niveaux sonores, CETUR 1980”) and identified in the frame of the acoustic study of Florence city roads, performed by ARPAT [6]. According to the results of the described comparison between measured and calculated data in the five points the model, the model can be considered validated when and where the difference between measured and calculated corresponding data is lower than 3 dB(A). Otherwise the model must be revised, correcting it, usually increasing the level of detail before repeating the test. In the following tables, input data and results of the validation comparison are reported.

Tab.I. Input data for validation

Tab.II. Model validation results – daytime

Daytime (6.00 – 22.00)

Point Meas. Calc. Diff. Validation

P01 63.2 64.4 1.2 yes

P02 59.9 57.4 -2.5 yes

P03 64.4 64.0 -0.4 yes

P04 64.3 66.8 2.5 yes

P05 64.0 61.3 -2.7 yes

Tab.III. Model validation results – nighttime

Nightime (22.00 – 6.00)

Point Meas. Calc. Diff. Validation

P01 54.3 54.9 0.6 yes

P02 50.9 48.6 -2.3 yes

P03 56.0 54.1 -1.9 yes

P04 53.6 56.7 2.9 yes

P05 54.7 53 -1.7 yes

The main strategic action for the reduction of local traffic volumes can be done as far as possible, moving the area crossing traffic towards the main roads, bypassing the inhabited areas. Also some local alternatives at the present viability can be considered, aiming to a more rational distribution of vehicles transits, thus determining a reduction of noise pollution for residents. In particular, data corresponding to different traffic scenarios, derived as output of the TMM traffic

Measure-ment Point

% HEAVY Veichles

Nr. of vehicles (Average)

D E N D E N

P01 0.7 0.2 0.6 131 72 14

P02 0.4 0.1 0.0 145 55 15

P03 1.0 0.6 0.4 165 65 18

P04 2.9 2.4 2.7 201 86 24

P05 0.9 0.6 0.2 124 78 19


model, can be inserted as input into the above validated acoustic model. However, output data of traffic model need to be adapted, since they are referred to peak time (8:00-9:00), while for a correct acoustic model construction the average data relative to Day time period (6.00-20.00, namely D), Evening time period (20:00-22:00, namely E) and Night time period (22:00-6:00, namely N) are required. So, a specific procedure for the determination of a parameter (namely PTC i.e. Peak Time Coefficient) has been developed and tested. The procedure is summarized as follows.

1. Hourly measured traffic data has been grouped for the calculation of EHV (number of Equivalent Heavy Vehicles number) and ELV (number of Equivalent Light Vehicles) in the three time intervals : DAY = 6:00-20:00; EVENING = 20:00-22:00; NIGHT = 22:00- 06:00.

2. The percentage of EHV relative to the total Equivalent vehicles (100*EHV/ETV where ETV is the number of Equivalent Total Vehicles)

3. The AEV (Average Equivalent Vehicles for the three time intervals) has been calculated as follows : AEV DAY = ETV DAY / 14 AEV EVENING = ETV EVENING / 2 AEV NIGHT = ETV NIGHT / 8

4. The conversion parameter PTC needed to normalize the hourly peak vehicles number to the hourly average number of vehicles in DAY, EVENING, NIGHT intervals, has been calculated as follows, considering PTV (number of Peak Time Vehicles) as the direct output of TMM model :

PTC (D-E-N) = PTV / AEV (D-E-N)

In the following table the PTC, calculated as above for the considered points, are shown.

Tab.IV. Calculation of Peak Time Coefficient

Point

PTC (Peak Time Coeff.)

D E N

P01 2.3 4.1 20.8

P02 3.0 8.0 29.8

P03 1.8 4.5 16.8

P04 2.3 5.3 19.3

P05 1.8 2.9 11.7

5. For roads where the 24 hours counting of traffic flows PTC has been used to convert values produced by TMM model in values suitable as input for acoustic model for the present situation and then to the four proposed solution of road network planning. Referring to the percentage of heavy vehicles, it has been calculated according to the point 2 procedure.

6. For the roads where the 24H hourly counting is not available, the same conversion procedure has been considered, using PTC and EHV values derived by a similar road having similar traffic flows coming out from in situ analysis considerations.

Thus, starting from the TMM output for different peak time scenarios in different points of the considered area and road network, the traffic flows data has been determined and, using them as input of acoustic model, the acoustic simulations have been performed, produced the noise exposure levels corresponding to each of the considered traffic flows and road network scenarios. The maps of the façade levels, determined in this way, will be correlated to the corresponding number of residents, giving the noise exposure level map in different scenarios and providing elements for a comparison analysis among them.


5. Conclusions

In the frame of HUSH project [7] a methodology for the scenario analysis that combines traffic model and noise propagation model has been developed. The main problem encountered in the implementation of this action has been the uneasy interconnection between the two typologies of model, mainly due to the general habit of considering traffic flows for traffic modeling referred to peak time intervals. To overcome this difficulty a specific procedure has been developed and tested. In this way peak time values have been converted in average values, as required by acoustic model algorithm and softwares. The noise assessment and mapping, derived by the application of the procedure described in this paper has made possible the comparison of different traffic scenarios, as tentative choices for the project, involving in the simulations traffic flows data as well as noise levels and consequent noise exposure levels.

Acknowledgement This project has been co-financed by the European Commission into the Environment LIFE+2008 Programme.

References[1] F.Borchi, M.Carfagni “The H.U.S.H. project – The

geographical data platform for city noise action planning” Proceedings of 20th International Congress on Acoustics, ICA 2010

[2] R.Bellomini, S. Luzzi “The H.U.S.H. project – database of noise reduction measures for city noise action planning” Proceedings of 20th International Congress on Acoustics, ICA 2010

[3] Ennio Casetta, Modelli per i sistemi di trasporto. Teoria e applicazioni, Utet 2006

[4] Gentile G., Meschini L., Un approccio fattibile alla correzione dinamica delle matrici OD da conteggi di traffico. Incontro di studio: Stima combinata della matrice OD mediante conteggi di traffico, Rome, Italy, 2010.

[5] PTV, Visum user manual, PTV, Karlsruhe, 2001 [4] J. Bowman, T. Senior: The wedge. - In: Electromag-netic and acoustic scattering by simple shapes. J. Bowman, T. Senior, P. Uslenghi (eds.). Hemisphere Publishing Corporation, New York, 1969.

[6] L. Moran, D.Casini, A. Poggi “Fattori correttivi per i dati di emissione da utilizzare nei modelli previsionali di rumore stradale in ambito urbano”, in Atti del XXXII Convegno Nazionale dell’Associazione Italiana di Acustica

[7] www.hush-project.eu


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