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分析公交客流规模的关联因素,梳理与公交客流规模有关的关联规则,有助于决策者把握整体态势、定义现状问题、细分问题类型。本文以深圳市为案例,以交通小区为分析单元,基于公交IC卡数据、人口数据、兴趣点数据、电子地图路径规划数据、微博签到数据等多源数据,从建成环境、人口密度、公交线网设施、交通可达性等维度,定量地表现影响公交客流规模的关联因素。通过构建决策树模型,揭示公交客流规模与关联因素间的映射关系,提取与公交客流规模有关的关联规则。研究结论为基于多源数据的公交客流规模评价方法提供了一种新的思路,也为公交线网规划提供了决策支持工具。
Analyzing the related factors of bus passenger flow scale and combing the association rules related to the size of bus passenger flow will help decision-makers grasp the overall situation, define the current status quo and classify the types of problems. Taking Shenzhen City as a case and taking the traffic community as the analysis unit, based on the multi-source data such as bus IC card data, population data, POI data, electronic map path planning data and Weibo check-in data, Network facilities, traffic accessibility and other dimensions, quantitatively reflect the impact of the size of the bus passenger correlation factors. By constructing a decision tree model, the mapping relationship between bus passenger flow scale and related factors is revealed, and the association rules related to the size of bus passenger flow are extracted. The conclusion of the study provides a new idea for the evaluation of bus passenger flow based on multi-source data and also provides a decision support tool for bus network planning.