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The effects of traffic zoning with regular geometric shapes on the precision of trip production models

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  • Ghadiri, Mehdi
  • Rassafi, Amir Abbas
  • Mirbaha, Babak

Abstract

One of the first and most critical steps involved in transportation studies is to determine the traffic zoning scheme. A traffic analysis zone (TAZ) is the main unit of the transportation analysis. In most transportation planning studies, the focus is only on the modeling process, while ignoring aspects such as TAZ definition, configuration, and design. Although the definition of TAZs is one of the key stages in transportation planning studies, a proper approach for the definition is still one of the unsolved issues.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:jotrge:v:78:y:2019:i:c:p:150-159
    DOI: 10.1016/j.jtrangeo.2019.05.018
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    References listed on IDEAS

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    1. Cabrera Delgado, Jorge & Bonnel, Patrick, 2016. "Level of aggregation of zoning and temporal transferability of the gravity distribution model: The case of Lyon," Journal of Transport Geography, Elsevier, vol. 51(C), pages 17-26.
    2. Lee, Jaeyoung & Abdel-Aty, Mohamed & Jiang, Ximiao, 2014. "Development of zone system for macro-level traffic safety analysis," Journal of Transport Geography, Elsevier, vol. 38(C), pages 13-21.
    3. Luis Martínez & José Viegas & Elisabete Silva, 2009. "A traffic analysis zone definition: a new methodology and algorithm," Transportation, Springer, vol. 36(5), pages 581-599, September.
    4. Kang-Tsung Chang & Zaher Khatib & Yanmei Ou, 2002. "Effects of Zoning Structure and Network Detail on Traffic Demand Modeling," Environment and Planning B, , vol. 29(1), pages 37-52, February.
    5. 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.
    6. Huang, Helai & Song, Bo & Xu, Pengpeng & Zeng, Qiang & Lee, Jaeyoung & Abdel-Aty, Mohamed, 2016. "Macro and micro models for zonal crash prediction with application in hot zones identification," Journal of Transport Geography, Elsevier, vol. 54(C), pages 248-256.
    7. José Manuel Viegas & L Miguel Martinez & Elisabete A Silva, 2009. "Effects of the Modifiable Areal Unit Problem on the Delineation of Traffic Analysis Zones," Environment and Planning B, , vol. 36(4), pages 625-643, August.
    8. Abdel-Aty, Mohamed & Lee, Jaeyoung & Siddiqui, Chowdhury & Choi, Keechoo, 2013. "Geographical unit based analysis in the context of transportation safety planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 62-75.
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    Cited by:

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    3. Chandra, Aitichya & Sharath, M.N. & Pani, Agnivesh & Sahu, Prasanta K., 2021. "A multi-objective genetic algorithm approach to design optimal zoning systems for freight transportation planning," Journal of Transport Geography, Elsevier, vol. 92(C).
    4. Xu, Weiyan & Tu, Jielei & Xu, Ning & Liu, Zuming, 2024. "Predicting daily heating energy consumption in residential buildings through integration of random forest model and meta-heuristic algorithms," Energy, Elsevier, vol. 301(C).
    5. Yang, Binyu & Tian, Yuan & Wang, Jian & Hu, Xiaowei & An, Shi, 2022. "How to improve urban transportation planning in big data era? A practice in the study of traffic analysis zone delineation," Transport Policy, Elsevier, vol. 127(C), pages 1-14.
    6. Krug, Jean & Burianne, Arthur & Bécarie, Cécile & Leclercq, Ludovic, 2021. "Refining trip starting and ending locations when estimating travel-demand at large urban scale," Journal of Transport Geography, Elsevier, vol. 93(C).
    7. Wu, Xuanyi & Wang, Bingkun & Li, Wenling, 2024. "Comparing the accuracy of ANN with transformer models for sentiment analysis of tweets related to COVID-19 Pfizer vaccines," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    8. Khajavi, Hamed & Rastgoo, Amir, 2023. "Improving the prediction of heating energy consumed at residential buildings using a combination of support vector regression and meta-heuristic algorithms," Energy, Elsevier, vol. 272(C).

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