Investigation of the extent of field data required for reliable calibration and validation of large scale traffic simulation models: A case study | Kütüphane.osmanlica.com

Investigation of the extent of field data required for reliable calibration and validation of large scale traffic simulation models: A case study

İsim Investigation of the extent of field data required for reliable calibration and validation of large scale traffic simulation models: A case study
Yazar Bartın, Bekir Oğuz, Ozbay, K., Gao, J., Kurkcu, A.
Basım Tarihi: 2020-09-20
Basım Yeri - IEEE
Tür Belge
Dil İngilizce
Dijital Evet
Yazma Hayır
Kütüphane: Özyeğin Üniversitesi
Demirbaş Numarası 2-s2.0-85099647863
Kayıt Numarası 808bec98-1961-45e9-b77f-18d8a9a050bf
Lokasyon Civil Engineering
Tarih 2020-09-20
Örnek Metin Availability, accuracy and relevance of field data are essential for developing a reliable simulation model. Large scale simulation models in particular require data from many sources and in great detail. Considering the sheer size of many simulation models used in practice, collecting all the required data is both costly and time-consuming, and in many cases even impossible. Therefore a trade-off is usually made in terms of the amount of data collected or the number of selected data collection locations used for the calibration and validation process. The fundamental question addressed in this paper is the following: what is the marginal gain in using an additional type of field data for the calibration and validation process? Using a case study where the calibration and validation of a test network is performed under different scenarios of available data types, and the results are compared in hindsight. The results indicate that only traffic flow and travel time data would suffice for the calibration and validation process, and that the marginal benefit of acquiring additional data such as, queue length, in this case study, is likely to be insignificant.
DOI 10.1109/ITSC45102.2020.9294460
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Investigation of the extent of field data required for reliable calibration and validation of large scale traffic simulation models: A case study

Yazar Bartın, Bekir Oğuz, Ozbay, K., Gao, J., Kurkcu, A.
Basım Tarihi 2020-09-20
Basım Yeri - IEEE
Tür Belge
Dil İngilizce
Dijital Evet
Yazma Hayır
Kütüphane Özyeğin Üniversitesi
Demirbaş Numarası 2-s2.0-85099647863
Kayıt Numarası 808bec98-1961-45e9-b77f-18d8a9a050bf
Lokasyon Civil Engineering
Tarih 2020-09-20
Örnek Metin Availability, accuracy and relevance of field data are essential for developing a reliable simulation model. Large scale simulation models in particular require data from many sources and in great detail. Considering the sheer size of many simulation models used in practice, collecting all the required data is both costly and time-consuming, and in many cases even impossible. Therefore a trade-off is usually made in terms of the amount of data collected or the number of selected data collection locations used for the calibration and validation process. The fundamental question addressed in this paper is the following: what is the marginal gain in using an additional type of field data for the calibration and validation process? Using a case study where the calibration and validation of a test network is performed under different scenarios of available data types, and the results are compared in hindsight. The results indicate that only traffic flow and travel time data would suffice for the calibration and validation process, and that the marginal benefit of acquiring additional data such as, queue length, in this case study, is likely to be insignificant.
DOI 10.1109/ITSC45102.2020.9294460
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