Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System - Siyuan Zhang; Shijun Yu; Shejun Deng; Qinghui Nie; Pengpeng Zhang; Chen Chen (Promet - Traffic&Transportation, 2019)
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.