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Transit Traffic Analysis Zone Delineating Method Based on Thiessen Polygon

Author

Listed:
  • Shuwei Wang

    (College of Metropolitan Transportation, Beijing University of Technology, No.100 Pingleyuan, Chaoyang District, Beijing 100124, China
    These authors contributed equally to this work.)

  • Lishan Sun

    (College of Metropolitan Transportation, Beijing University of Technology, No.100 Pingleyuan, Chaoyang District, Beijing 100124, China
    These authors contributed equally to this work.)

  • Jian Rong

    (College of Metropolitan Transportation, Beijing University of Technology, No.100 Pingleyuan, Chaoyang District, Beijing 100124, China)

  • Zifan Yang

    (College of Metropolitan Transportation, Beijing University of Technology, No.100 Pingleyuan, Chaoyang District, Beijing 100124, China)

Abstract

A green transportation system composed of transit, busses and bicycles could be a significant in alleviating traffic congestion. However, the inaccuracy of current transit ridership forecasting methods is imposing a negative impact on the development of urban transit systems. Traffic Analysis Zone (TAZ) delineating is a fundamental and essential step in ridership forecasting, existing delineating method in four-step models have some problems in reflecting the travel characteristics of urban transit. This paper aims to come up with a Transit Traffic Analysis Zone delineation method as supplement of traditional TAZs in transit service analysis. The deficiencies of current TAZ delineating methods were analyzed, and the requirements of Transit Traffic Analysis Zone (TTAZ) were summarized. Considering these requirements, Thiessen Polygon was introduced into TTAZ delineating. In order to validate its feasibility, Beijing was then taken as an example to delineate TTAZs, followed by a spatial analysis of office buildings within a TTAZ and transit station departure passengers. Analysis result shows that the TTAZs based on Thiessen polygon could reflect the transit travel characteristic and is of in-depth research value.

Suggested Citation

  • Shuwei Wang & Lishan Sun & Jian Rong & Zifan Yang, 2014. "Transit Traffic Analysis Zone Delineating Method Based on Thiessen Polygon," Sustainability, MDPI, vol. 6(4), pages 1-12, April.
    • Handle: RePEc:gam:jsusta:v:6:y:2014:i:4:p:1821-1832:d:34873
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    Citations

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    Cited by:

    1. Jingzhao Wang & Jincheng Yan & Keyuan Ding & Qian Li & Yehao Liu & Xueliang Liu & Ran Peng, 2022. "A Reflection on the Response to Sudden-Onset Disasters in the Post-Pandemic Era: A Graded Assessment of Urban Transportation Resilience Taking Wuhan, China as an Example," Sustainability, MDPI, vol. 14(17), pages 1-20, September.
    2. Pani, Agnivesh & Sahu, Prasanta K. & Chandra, Aitichya & Sarkar, Ashoke K., 2019. "Assessing the extent of modifiable areal unit problem in modelling freight (trip) generation: Relationship between zone design and model estimation results," Journal of Transport Geography, Elsevier, vol. 80(C).
    3. Meijie Chen & Yumin Chen & Xiaoguang Wang & Huangyuan Tan & Fenglan Luo, 2019. "Spatial Difference of Transit-Based Accessibility to Hospitals by Regions Using Spatially Adjusted ANOVA," IJERPH, MDPI, vol. 16(11), pages 1-20, May.
    4. Shaoying Li & Xiaoping Liu & Zhigang Li & Zhifeng Wu & Zijun Yan & Yimin Chen & Feng Gao, 2018. "Spatial and Temporal Dynamics of Urban Expansion along the Guangzhou–Foshan Inter-City Rail Transit Corridor, China," Sustainability, MDPI, vol. 10(3), pages 1-18, February.
    5. Ghadiri, Mehdi & Rassafi, Amir Abbas & Mirbaha, Babak, 2019. "The effects of traffic zoning with regular geometric shapes on the precision of trip production models," Journal of Transport Geography, Elsevier, vol. 78(C), pages 150-159.
    6. Stefania Bertazzon & Rizwan Shahid, 2017. "Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada," IJERPH, MDPI, vol. 14(8), pages 1-16, July.
    7. Lin Li & Lei Yang & Haihong Zhu & Rongrong Dai, 2015. "Explorative Analysis of Wuhan Intra-Urban Human Mobility Using Social Media Check-In Data," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-19, August.

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