Catchment-Area Delineation Approach Considering Travel Purposes for Station-Level Ridership Prediction Task

集水区 运输工程 旅游调查 流域 环境科学 计算机科学 旅游行为 地理 工程类 地图学
作者
Chen Ma,Yanqiu Cheng,Shuang Zhang,Kuanmin Chen,Jie Wei,Xianbiao Hu
出处
期刊:Transportation Research Record [SAGE Publishing]
卷期号:2678 (5): 397-415 被引量:8
标识
DOI:10.1177/03611981231189738
摘要

Station-catchment-area delineation is a key component of direct ridership models for urban rail-transport systems as it can determine the relationship between the urban-rail-transit station-level ridership and the variables within the station catchment area. The neglect of differences in the passenger-flow distribution for different travel purposes in previous studies has led to low accuracy of the obtained walk-to-station distances. Therefore, this paper proposes a station-catchment-area delineation method which is based on web map data to obtain accurate walk-to-station distances and considers differences in the distance thresholds and the ridership attraction intensity (RAI) for six travel purposes (corresponding to commercial, medical, residential, educational, administrative, and recreational land uses). In the case study, the ridership data of Xi’an Metro, the 2015 Xi’an Residential Travel Survey data, and the corresponding Gaode Map data are employed to extract passengers’ walking-distance distribution for several travel purposes to delineate the station catchment areas and build direct ridership models. Several geographically weighted regression (GWR) models are constructed to evaluate and examine the effects of the various station-catchment-area delineation methods on the model findings. The obtained results show that the proposed station-catchment-area delineation method significantly improves the ridership prediction performance compared with the traditional circular-buffer method, with the entry and exit ridership prediction accuracy improving by 3.57% and 6.65% on average, respectively. Finally, this study will guide transportation planners on how to delineate station catchment areas when constructing direct-demand models for urban rail stations.
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