A Stochastic Signal Processing in the Traffic Noise Prediction Problem with the Nonstationarity of Headway Distribution
Summary :
A ner trial of statistical evaluation for a nonstationary traffic flow and its traffic noise is proposed as a prediction method of its probability distribution function by considering the temporal change of distribution parameters especially from a structural viewpoint. First, a headway distribution of the nonstationary traffic flow passing through within a road segment is proposed on the basis of an Erlang distribution by reflecting a temporal change of its distribution parameters. Then, an initial phase density concerning with asynchronous counting method and the probability of counting n cars over a long time interval are derived from the above nonstationary expression of headway distribution. Thus, the statistics of noise intensity at an observation point has been predicted by combining the above probabilistic factors and deterministic factors related to noise propagation environment with use of a compound stochastic process model. Finally, te effectivenss of the proposed theory has been confirmed experimentally by applying it to the actual traffic flow on a highway.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E75-A No.8 pp.996-1003
- Publication Date
- 1992/08/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section on the 6th Digital Signal Processing Symposium)
- Category
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Mitsuo OHTA, Kiminobu NISHIMURA, Kazutatsu HATAKEYAMA, "A Stochastic Signal Processing in the Traffic Noise Prediction Problem with the Nonstationarity of Headway Distribution" in IEICE TRANSACTIONS on Fundamentals,
vol. E75-A, no. 8, pp. 996-1003, August 1992, doi: .
Abstract: A ner trial of statistical evaluation for a nonstationary traffic flow and its traffic noise is proposed as a prediction method of its probability distribution function by considering the temporal change of distribution parameters especially from a structural viewpoint. First, a headway distribution of the nonstationary traffic flow passing through within a road segment is proposed on the basis of an Erlang distribution by reflecting a temporal change of its distribution parameters. Then, an initial phase density concerning with asynchronous counting method and the probability of counting n cars over a long time interval are derived from the above nonstationary expression of headway distribution. Thus, the statistics of noise intensity at an observation point has been predicted by combining the above probabilistic factors and deterministic factors related to noise propagation environment with use of a compound stochastic process model. Finally, te effectivenss of the proposed theory has been confirmed experimentally by applying it to the actual traffic flow on a highway.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e75-a_8_996/_p
Copy
@ARTICLE{e75-a_8_996,
author={Mitsuo OHTA, Kiminobu NISHIMURA, Kazutatsu HATAKEYAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Stochastic Signal Processing in the Traffic Noise Prediction Problem with the Nonstationarity of Headway Distribution},
year={1992},
volume={E75-A},
number={8},
pages={996-1003},
abstract={A ner trial of statistical evaluation for a nonstationary traffic flow and its traffic noise is proposed as a prediction method of its probability distribution function by considering the temporal change of distribution parameters especially from a structural viewpoint. First, a headway distribution of the nonstationary traffic flow passing through within a road segment is proposed on the basis of an Erlang distribution by reflecting a temporal change of its distribution parameters. Then, an initial phase density concerning with asynchronous counting method and the probability of counting n cars over a long time interval are derived from the above nonstationary expression of headway distribution. Thus, the statistics of noise intensity at an observation point has been predicted by combining the above probabilistic factors and deterministic factors related to noise propagation environment with use of a compound stochastic process model. Finally, te effectivenss of the proposed theory has been confirmed experimentally by applying it to the actual traffic flow on a highway.},
keywords={},
doi={},
ISSN={},
month={August},}
Copy
TY - JOUR
TI - A Stochastic Signal Processing in the Traffic Noise Prediction Problem with the Nonstationarity of Headway Distribution
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 996
EP - 1003
AU - Mitsuo OHTA
AU - Kiminobu NISHIMURA
AU - Kazutatsu HATAKEYAMA
PY - 1992
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E75-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 1992
AB - A ner trial of statistical evaluation for a nonstationary traffic flow and its traffic noise is proposed as a prediction method of its probability distribution function by considering the temporal change of distribution parameters especially from a structural viewpoint. First, a headway distribution of the nonstationary traffic flow passing through within a road segment is proposed on the basis of an Erlang distribution by reflecting a temporal change of its distribution parameters. Then, an initial phase density concerning with asynchronous counting method and the probability of counting n cars over a long time interval are derived from the above nonstationary expression of headway distribution. Thus, the statistics of noise intensity at an observation point has been predicted by combining the above probabilistic factors and deterministic factors related to noise propagation environment with use of a compound stochastic process model. Finally, te effectivenss of the proposed theory has been confirmed experimentally by applying it to the actual traffic flow on a highway.
ER -
English
