Civil Engineering Department, Sichuan University of Science and Engineering, Zigong, 643000, China.
Sichuan University, Chengdu, 610065, China.
Sci Rep. 2022 Sep 27;12(1):16120. doi: 10.1038/s41598-022-20209-4.
Nowadays, Transit-Oriented Development (TOD) plays a vital role for public transport planners in developing potential city facilities. Knowing the necessity of this concept indicates that TOD effective parameters such as network accessibility (node value) and station-area land use (place value) should be considered in city development projects. To manage the coordination between these two factors, we need to consider ridership and peak and off-peak hours as essential enablers in our investigations. To aim this, we conducted our research on Chengdu rail-transit stations as a case study to propose our Node-Place-Ridership-Time (NPRT) model. We applied the Multiple Linear Regression (MLR) to examine the impacts of node value and place value on ridership. Finally, K-Means and Cube Methods were used to classify the stations based on the NPRT model results. This research indicates that our NPRT model could provide accurate results compared with the previous models to evaluate rail-transit stations.
如今，公共交通规划者在开发潜在城市设施时，过境导向型发展（TOD）发挥着至关重要的作用。了解这一概念的必要性表明，在城市发展项目中应考虑 TOD 的有效参数，如网络可达性（节点值）和车站区域土地利用（位置值）。为了管理这两个因素之间的协调，我们需要将客流量以及高峰和非高峰时段视为调查中的基本促成因素。为此，我们以成都轨道交通站为例进行了研究，提出了我们的节点-位置-客流量-时间（NPRT）模型。我们应用多元线性回归（MLR）来检验节点值和位置值对客流量的影响。最后，使用 K-Means 和立方方法根据 NPRT 模型的结果对车站进行分类。这项研究表明，与之前的模型相比，我们的 NPRT 模型可以为评估轨道交通站提供更准确的结果。
