Original scientific paper
https://doi.org/10.7307/ptt.v31i6.3197
Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System
Siyuan Zhang
; Yangzhou University
Shijun Yu
; Yangzhou University
Shejun Deng
; Yangzhou University
Qinghui Nie
; Yangzhou University
Pengpeng Zhang
; Yangzhou University
Chen Chen
; Oregon State University
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.
Keywords
Hrčak ID:
231505
URI
Publication date:
14.11.2019.
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