Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System
Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Siyuan Zhang [verfasserIn] Shijun Yu [verfasserIn] Shejun Deng [verfasserIn] Qinghui Nie [verfasserIn] Pengpeng Zhang [verfasserIn] Chen Chen [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Promet (Zagreb) - University of Zagreb, Faculty of Transport and Traffic Sciences, 2016, 31(2019), 6, Seite 621-632 |
|---|---|
| Übergeordnetes Werk: |
volume:31 ; year:2019 ; number:6 ; pages:621-632 |
| Links: |
Link aufrufen |
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| DOI / URN: |
10.7307/ptt.v31i6.3197 |
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DOAJ07486324X |
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| 520 | |a Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. | ||
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10.7307/ptt.v31i6.3197 doi (DE-627)DOAJ07486324X (DE-599)DOAJe1c845972e6446c4bb3b61fecb25fc2b DE-627 ger DE-627 rakwb eng TA1001-1280 Siyuan Zhang verfasserin aut Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. bike-and-ride dynamic demand generalised cost user equilibrium model frank-wolfe algorithm Transportation engineering Shijun Yu verfasserin aut Shejun Deng verfasserin aut Qinghui Nie verfasserin aut Pengpeng Zhang verfasserin aut Chen Chen verfasserin aut In Promet (Zagreb) University of Zagreb, Faculty of Transport and Traffic Sciences, 2016 31(2019), 6, Seite 621-632 (DE-627)864193793 (DE-600)2863683-1 18484069 nnns volume:31 year:2019 number:6 pages:621-632 https://doi.org/10.7307/ptt.v31i6.3197 kostenfrei https://doaj.org/article/e1c845972e6446c4bb3b61fecb25fc2b kostenfrei https://traffic.fpz.hr/index.php/PROMTT/article/view/3197 kostenfrei https://doaj.org/toc/0353-5320 Journal toc kostenfrei https://doaj.org/toc/1848-4069 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 31 2019 6 621-632 |
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10.7307/ptt.v31i6.3197 doi (DE-627)DOAJ07486324X (DE-599)DOAJe1c845972e6446c4bb3b61fecb25fc2b DE-627 ger DE-627 rakwb eng TA1001-1280 Siyuan Zhang verfasserin aut Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. bike-and-ride dynamic demand generalised cost user equilibrium model frank-wolfe algorithm Transportation engineering Shijun Yu verfasserin aut Shejun Deng verfasserin aut Qinghui Nie verfasserin aut Pengpeng Zhang verfasserin aut Chen Chen verfasserin aut In Promet (Zagreb) University of Zagreb, Faculty of Transport and Traffic Sciences, 2016 31(2019), 6, Seite 621-632 (DE-627)864193793 (DE-600)2863683-1 18484069 nnns volume:31 year:2019 number:6 pages:621-632 https://doi.org/10.7307/ptt.v31i6.3197 kostenfrei https://doaj.org/article/e1c845972e6446c4bb3b61fecb25fc2b kostenfrei https://traffic.fpz.hr/index.php/PROMTT/article/view/3197 kostenfrei https://doaj.org/toc/0353-5320 Journal toc kostenfrei https://doaj.org/toc/1848-4069 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 31 2019 6 621-632 |
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10.7307/ptt.v31i6.3197 doi (DE-627)DOAJ07486324X (DE-599)DOAJe1c845972e6446c4bb3b61fecb25fc2b DE-627 ger DE-627 rakwb eng TA1001-1280 Siyuan Zhang verfasserin aut Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. bike-and-ride dynamic demand generalised cost user equilibrium model frank-wolfe algorithm Transportation engineering Shijun Yu verfasserin aut Shejun Deng verfasserin aut Qinghui Nie verfasserin aut Pengpeng Zhang verfasserin aut Chen Chen verfasserin aut In Promet (Zagreb) University of Zagreb, Faculty of Transport and Traffic Sciences, 2016 31(2019), 6, Seite 621-632 (DE-627)864193793 (DE-600)2863683-1 18484069 nnns volume:31 year:2019 number:6 pages:621-632 https://doi.org/10.7307/ptt.v31i6.3197 kostenfrei https://doaj.org/article/e1c845972e6446c4bb3b61fecb25fc2b kostenfrei https://traffic.fpz.hr/index.php/PROMTT/article/view/3197 kostenfrei https://doaj.org/toc/0353-5320 Journal toc kostenfrei https://doaj.org/toc/1848-4069 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 31 2019 6 621-632 |
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10.7307/ptt.v31i6.3197 doi (DE-627)DOAJ07486324X (DE-599)DOAJe1c845972e6446c4bb3b61fecb25fc2b DE-627 ger DE-627 rakwb eng TA1001-1280 Siyuan Zhang verfasserin aut Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. bike-and-ride dynamic demand generalised cost user equilibrium model frank-wolfe algorithm Transportation engineering Shijun Yu verfasserin aut Shejun Deng verfasserin aut Qinghui Nie verfasserin aut Pengpeng Zhang verfasserin aut Chen Chen verfasserin aut In Promet (Zagreb) University of Zagreb, Faculty of Transport and Traffic Sciences, 2016 31(2019), 6, Seite 621-632 (DE-627)864193793 (DE-600)2863683-1 18484069 nnns volume:31 year:2019 number:6 pages:621-632 https://doi.org/10.7307/ptt.v31i6.3197 kostenfrei https://doaj.org/article/e1c845972e6446c4bb3b61fecb25fc2b kostenfrei https://traffic.fpz.hr/index.php/PROMTT/article/view/3197 kostenfrei https://doaj.org/toc/0353-5320 Journal toc kostenfrei https://doaj.org/toc/1848-4069 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 31 2019 6 621-632 |
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10.7307/ptt.v31i6.3197 doi (DE-627)DOAJ07486324X (DE-599)DOAJe1c845972e6446c4bb3b61fecb25fc2b DE-627 ger DE-627 rakwb eng TA1001-1280 Siyuan Zhang verfasserin aut Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. bike-and-ride dynamic demand generalised cost user equilibrium model frank-wolfe algorithm Transportation engineering Shijun Yu verfasserin aut Shejun Deng verfasserin aut Qinghui Nie verfasserin aut Pengpeng Zhang verfasserin aut Chen Chen verfasserin aut In Promet (Zagreb) University of Zagreb, Faculty of Transport and Traffic Sciences, 2016 31(2019), 6, Seite 621-632 (DE-627)864193793 (DE-600)2863683-1 18484069 nnns volume:31 year:2019 number:6 pages:621-632 https://doi.org/10.7307/ptt.v31i6.3197 kostenfrei https://doaj.org/article/e1c845972e6446c4bb3b61fecb25fc2b kostenfrei https://traffic.fpz.hr/index.php/PROMTT/article/view/3197 kostenfrei https://doaj.org/toc/0353-5320 Journal toc kostenfrei https://doaj.org/toc/1848-4069 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 31 2019 6 621-632 |
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| abstract |
Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. |
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Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. |
| abstract_unstemmed |
Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system. |
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Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System |
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https://doi.org/10.7307/ptt.v31i6.3197 https://doaj.org/article/e1c845972e6446c4bb3b61fecb25fc2b https://traffic.fpz.hr/index.php/PROMTT/article/view/3197 https://doaj.org/toc/0353-5320 https://doaj.org/toc/1848-4069 |
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| author2 |
Shijun Yu Shejun Deng Qinghui Nie Pengpeng Zhang Chen Chen |
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Shijun Yu Shejun Deng Qinghui Nie Pengpeng Zhang Chen Chen |
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864193793 |
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TA - General and Civil Engineering |
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10.7307/ptt.v31i6.3197 |
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TA1001-1280 |
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2024-07-04T00:53:33.537Z |
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