交通运输系统工程与信息 ›› 2021, Vol. 21 ›› Issue (3): 268-274.

• 工程应用与案例分析 • 上一篇    下一篇

天气因素对福州地铁客流的影响分析

江世雄*a, b,蔡灿煌a, b,林宇晨a, b,陈德旺a, b   

  1. 福州大学,a. 数学与计算机科学学院;b. 智慧地铁福建省高校重点实验室,福州 350108
  • 收稿日期:2021-03-25 修回日期:2021-05-07 出版日期:2021-06-25 发布日期:2021-06-25
  • 作者简介:江世雄(1991- ),男,福建南平人,讲师,博士。
  • 基金资助:

    国家自然科学基金/National Natural Science Foundation of China(61976055)。

Analysis of Weather's Influences on Metro Ridership in Fuzhou

JIANG Shi-xiong*a, b, CAI Can-huang a, b, LIN Yu-chen a, b, CHEN De-wang a, b   

  1. a. College of Mathematics and Computer Science; b. Key Laboratory of Intelligent Metro of Universities in Fujian Province, Fuzhou University, Fuzhou 350108, China
  • Received:2021-03-25 Revised:2021-05-07 Online:2021-06-25 Published:2021-06-25

摘要:

地铁作为一种绿色出行方式,是缓解城市交通拥堵的重要手段。地铁客流受到多种因素影响,其中天气因素变化较快,会造成地铁客流的快速变化。了解天气因素对地铁客流的影响,有助于建立相应的运输组织响应措施。本文旨在量化分析天气因素对福州地铁客流量的影响,并考虑原始天气指标的局限性,引入体现舒适度的指标。建立地铁客流与天气因素(包括气压、相对湿度、风力、降水、风寒指数等级、综合舒适度指数等级等)之间的多元线性回归模型,量化影响方向和影响程度。此外,工作日与非工作日的客流模式差异较大,将两者分别建模分析。研究发现:工作日,降水、风寒指数等级和综合舒适度指数等级对地铁客流有显著影响;非工作日,降水、气压、相对湿度、风寒指数等级和综合舒适度指数等级对地铁客流有显著影响。总体而言,非工作日地铁客流对天气因素更加敏感。

关键词: 城市交通, 天气因素, 多元线性回归, 地铁客流, 舒适度指数, 降水

Abstract:

Metro is a green travel mode, which is an important approach to mitigate urban traffic jams. Metro ridership is influenced by many factors. Weather changes quickly and can lead to variations in ridership. Understanding the relationship between metro ridership and weather can help to set up the corresponding measures for transportation organization. This paper aims to analyze weather's impacts on metro ridership. Due to the limitation of the traditional weather index, a comfort index is incorporated. The multiple linear regression is built between metro ridership and weather factors (atmosphere pressure, relative humidity, wind velocity, rainfall, wind-chill index, comprehensive comfort index, etc.) to quantify the influence. As the travel patterns are different on workdays and non-workdays, two regression models are developed. Results show that rainfall, wind-chill index, and comprehensive comfort index are significant for metro ridership on workdays, and rainfall, atmospheric pressure, relative humidity, wind-chill index, and comprehensive comfort index are significant for metro ridership on non- workdays. In general, the ridership is more sensitive to weather factors on non-work days.

Key words: urban traffic, weather factors, multiple linear regression, metro ridership, comfort index, rainfall

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