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Honking noise corrections for traffic noise prediction models in heterogeneous traffic conditions like India.

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Title: Honking noise corrections for traffic noise prediction models in heterogeneous traffic conditions like India.
Authors: Kalaiselvi, R.1 kalaiarchi@gmail.com, Ramachandraiah, A.2 ramalur@gmail.com
Source: Applied Acoustics. Oct2016, Vol. 111, p25-38. 14p.
Subjects: Noise control, Traffic noise, Traffic engineering, Soundscapes (Auditory environment), Horn music, Prevention
Geographic Terms: India
Abstract: In developing countries like India, the nature of the composition of traffic is heterogeneous. A heterogeneous traffic flow consists of vehicles that have different sizes, speeds, vehicle spacing and operating characteristics. As a result of the widely varying speeds, vehicular dimensions, lack of lane disciplines, honking becomes inevitable. In addition, it changes the urban soundscape of developing countries. In heterogeneous traffic conditions, horn events increase noise level ( L den ) by 0.5–13 dB(A) as compared to homogenous traffic conditions. Therefore, the traffic prediction models that are used for homogenous traffic conditions are not applicable in heterogeneous traffic conditions. To increase the accuracy of noise prediction models, in depth understanding of heterogeneous traffic noise is required. Understanding the real traffic noise characteristics requires quantification of some of the basic traffic flow characteristics such as speed, flow, Level Of Service (LOS) and density. In a given roadway, the noise level changes with density and LOS on the road. In this paper, a new factor for horn correction is introduced with respect of Level Of Service (LOS). The horn correction values can be incorporated in traffic noise models such as CRTN, FHWA, and RLS 90, while evaluating heterogeneous traffic conditions. [ABSTRACT FROM AUTHOR]
Copyright of Applied Acoustics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 115367725
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PubType: Academic Journal
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  Data: Honking noise corrections for traffic noise prediction models in heterogeneous traffic conditions like India.
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  Data: <searchLink fieldCode="AR" term="%22Kalaiselvi%2C+R%2E%22">Kalaiselvi, R.</searchLink><relatesTo>1</relatesTo><i> kalaiarchi@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Ramachandraiah%2C+A%2E%22">Ramachandraiah, A.</searchLink><relatesTo>2</relatesTo><i> ramalur@gmail.com</i>
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  Data: <searchLink fieldCode="DE" term="%22Noise+control%22">Noise control</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+noise%22">Traffic noise</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+engineering%22">Traffic engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Soundscapes+%28Auditory+environment%29%22">Soundscapes (Auditory environment)</searchLink><br /><searchLink fieldCode="DE" term="%22Horn+music%22">Horn music</searchLink><br /><searchLink fieldCode="DE" term="%22Prevention%22">Prevention</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22India%22">India</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: In developing countries like India, the nature of the composition of traffic is heterogeneous. A heterogeneous traffic flow consists of vehicles that have different sizes, speeds, vehicle spacing and operating characteristics. As a result of the widely varying speeds, vehicular dimensions, lack of lane disciplines, honking becomes inevitable. In addition, it changes the urban soundscape of developing countries. In heterogeneous traffic conditions, horn events increase noise level ( L den ) by 0.5–13 dB(A) as compared to homogenous traffic conditions. Therefore, the traffic prediction models that are used for homogenous traffic conditions are not applicable in heterogeneous traffic conditions. To increase the accuracy of noise prediction models, in depth understanding of heterogeneous traffic noise is required. Understanding the real traffic noise characteristics requires quantification of some of the basic traffic flow characteristics such as speed, flow, Level Of Service (LOS) and density. In a given roadway, the noise level changes with density and LOS on the road. In this paper, a new factor for horn correction is introduced with respect of Level Of Service (LOS). The horn correction values can be incorporated in traffic noise models such as CRTN, FHWA, and RLS 90, while evaluating heterogeneous traffic conditions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Applied Acoustics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.apacoust.2016.04.003
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 14
        StartPage: 25
    Subjects:
      – SubjectFull: Noise control
        Type: general
      – SubjectFull: Traffic noise
        Type: general
      – SubjectFull: Traffic engineering
        Type: general
      – SubjectFull: Soundscapes (Auditory environment)
        Type: general
      – SubjectFull: Horn music
        Type: general
      – SubjectFull: Prevention
        Type: general
      – SubjectFull: India
        Type: general
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      – TitleFull: Honking noise corrections for traffic noise prediction models in heterogeneous traffic conditions like India.
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            NameFull: Ramachandraiah, A.
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              M: 10
              Text: Oct2016
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              Y: 2016
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