TY - JOUR AU - Siyuan Zhang AU - Shijun Yu AU - Shejun Deng AU - Qinghui Nie AU - Pengpeng Zhang AU - Chen Chen PY - 2019/12/11 Y2 - 2024/03/28 TI - Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System JF - Promet - Traffic&Transportation JA - Promet VL - 31 IS - 6 SE - Articles DO - 10.7307/ptt.v31i6.3197 UR - http://traffic.fpz.hr/index.php/PROMTT/article/view/3197 AB - 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. ER -