Traffic noise and traffic light control

Stoilova, Krasimira; Stoilov, Todor

doi:10.1016/s1361-9209(98)00017-0

Cited by 29 publications

(22 citation statements)

References 7 publications

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“…Aside from environmental and health impacts, predictions and measurements of road traffic noise levels are essential for roadway planning, residential entitlement for sound insulation, and for the control of noise. Additionally, traffic noise monitoring and prediction can be used to estimate the traffic intensity and the queue lengths of vehicles (Stoilova and Stoilov, 1998).…”

Section: Objectives and Methodologymentioning

confidence: 99%

“…Theebe (2004) reported that, in a rising market, the impacts of traffic noise on house prices reached a maximum of 12 percent with an average of about 5 percent. This has lead researchers in many countries to investigate and characterize traffic noise pollution problems (Sommerhoff et al, 2004;Piccolo et al, 2004;Georgiadou, 2004;Theebe, 2004;Abo-Qudais and Alhiary, 2004;Pandya, 2003;Ramis et al, 2003;Bhadram, 2003;Zannin et al, 2001Zannin et al, , 2002Abdel-Raziq et al, 2000;Zeid et al, 2000;Suksaard et al, 1999;Funk and Rabl, 1999;Stoilova and Stoilov, 1998;Mateu and Vicente, 1997;Zheng, 1996).…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Traffic Noise Pollution in Amman, Jordan

Jamrah

Al‐Omari

Sharabi

2006

Environ Monit Assess

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The City of Amman, Jordan, has been subjected to persistent increase in road traffic due to overall increase in prosperity, fast development and expansion of economy, travel and tourism. This study investigates traffic noise pollution in Amman. Road traffic noise index L10(1 h) was measured at 28 locations that cover most of the City of Amman. Noise measurements were carried out at these 28 locations two times a day for a period of one hour during the early morning and early evening rush hours, in the presence and absence of a barrier. The Calculation of Road Traffic Noise (CRTN) prediction model was employed to predict noise levels at the locations chosen for the study. Data required for the model include traffic volume, speed, percentage of heavy vehicles, road surface, gradient, obstructions, distance, noise path, intervening ground, effect of shielding, and angle of view. The results of the investigation showed that the minimum and the maximum noise levels are 46 dB(A) and 81 dB(A) during day-time and 58 dB(A) and 71 dB(A) during night-time. The measured noise level exceeded the 62 dB(A) acceptable limit at most of the locations. The CTRN prediction model was successful in predicting noise levels at most of the locations chosen for this investigation, with more accurate predictions for night-time measurements.

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Section: Objectives and Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of Traffic Noise Pollution in Amman, Jordan

Jamrah

Al‐Omari

Sharabi

2006

Environ Monit Assess

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“…Instantaneous sound pressure levels at a given reception point are obtained by considering each vehicle as a mobile line source. Based on this approach, a few studies attempt to derive equivalent sound pressure formula in terms of the number of freely-moving and stopping vehicles (Makarewicz et al, 1999) or the number of queuing vehicles at traffic signals (Stoilova and Stoilov, 1998). Contrary to static noise procedures, analytic models account for single vehicle dynamics (i).…”

Section: Introductionmentioning

confidence: 99%

Improving noise assessment at intersections by modeling traffic dynamics

Chevallier

Can

Nadji

et al. 2009

Transportation Research Part D: Transport and Environment

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Three families of road noise prediction models can be distinguished depending on the way they account for traffic flow. Static noise models only consider free-flow constant-speed traffic with uniformly distributed vehicles. Analytic noise models assume that all vehicles are isolated from one another but account for their mean kinematic profile over the network. Micro-simulation noise models relax the hypothesis of no interaction between vehicles and fully capture traffic flow dynamic effects such as queue evolution. This study compares the noise levels obtained by these three methodologies at signalized intersections and roundabouts. It reveals that micro-simulation noise models outperform the other approaches. Particularly, they are able to capture the effects of stochastic transient queues in undersaturated conditions as well as stop-and-go behaviors in oversaturated regime. Accounting for traffic dynamics is also shown to improve predictions of noise variations due to different junction layouts. In this paper, a roundabout is found to induce a 2.5dB(A) noise abatement compared to a signalized intersection in undersaturated conditions while the acoustic contributions of both kinds of junctions balance in oversaturated regime.

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“…Traffic noise is indicated to be the main source of annoyance and complaints relative to other sources such as industrial activities, airport, and community noise (Stoilova and Stoilov 1998;Zannin et al 2003). Considering this phenomenon, in this study we aimed:…”

Section: Introductionmentioning

confidence: 99%

Analysing and mapping spatial and temporal dynamics of urban traffic noise pollution: a case study in Kahramanmaraş, Turkey

Doygun

Gurun

2007

Environ Monit Assess

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This study aimed at quantifying noise pollution from urban traffic in the city of Kahramanmaraş, Turkey. A total of 114 measurements for the equivalent noise level (L (Aeq)) were made at 38 urban locations classified as "residential areas", "residential and commercial areas" and "industrial areas" according to the national regulations, during morning, mid-day and evening hours. Our findings tabulated and mapped revealed that mean noise level in "residential and commercial areas" was highest relative to the other land-use types. Minimum and maximum values of noise pollution were recorded during the mid-day and evening hours, regardless of the land-use types. Noise limit values were exceeded at two locations only out of 38 based on the national regulation criteria and at over half of the locations based on the international criteria.

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Traffic noise and traffic light control

Cited by 29 publications

References 7 publications

Evaluation of Traffic Noise Pollution in Amman, Jordan

Evaluation of Traffic Noise Pollution in Amman, Jordan

Improving noise assessment at intersections by modeling traffic dynamics

Analysing and mapping spatial and temporal dynamics of urban traffic noise pollution: a case study in Kahramanmaraş, Turkey

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