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Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows

Author

Listed:
  • Crispin H. V. Cooper

    (Cardiff University)

  • Ian Harvey

    (Cardiff University
    Cardiff University)

  • Scott Orford

    (Cardiff University)

  • Alain J. F. Chiaradia

    (University of Hong Kong
    Belt and Road Urban Observatory (OBORobs))

Abstract

Predicting how changes to the urban environment layout will affect the spatial distribution of pedestrian flows is important for environmental, social and economic sustainability. We present longitudinal evaluation of a model of the effect of urban environmental layout change in a city centre (Cardiff 2007–2010), on pedestrian flows. Our model can be classed as regression based direct demand using Multiple Hybrid Spatial Design Network Analysis (MH-sDNA) assignment, which bridges the gap between direct demand models, facility-based activity estimation and spatial network analysis (which can also be conceived as a pedestrian route assignment based direct demand model). Multiple theoretical flows are computed based on retail floor area: everywhere to shops, shop to shop, railway stations to shops and parking to shops. Route assignment, in contrast to the usual approach of shortest path only, is based on a hybrid of shortest path and least directional change (most direct) with a degree of randomization. The calibration process determines a suitable balance of theoretical flows to best match observed pedestrian flows, using generalized cross-validation to prevent overfit. Validation shows that the model successfully predicts the effect of layout change on flows of up to approx. 8000 pedestrians per hour based on counts spanning a 1 km2 city centre, calibrated on 2007 data and validated to 2010 and 2011. This is the first time, to our knowledge, that a pedestrian flow model with assignment has been evaluated for its ability to forecast the effect of urban layout changes over time.

Suggested Citation

  • Crispin H. V. Cooper & Ian Harvey & Scott Orford & Alain J. F. Chiaradia, 2021. "Using multiple hybrid spatial design network analysis to predict longitudinal effect of a major city centre redevelopment on pedestrian flows," Transportation, Springer, vol. 48(2), pages 643-672, April.
    • Handle: RePEc:kap:transp:v:48:y:2021:i:2:d:10.1007_s11116-019-10072-0
    DOI: 10.1007/s11116-019-10072-0
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    References listed on IDEAS

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    Cited by:

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    2. Sevtsuk, Andres & Basu, Rounaq, 2022. "The role of turns in pedestrian route choice: A clarification," Journal of Transport Geography, Elsevier, vol. 102(C).
    3. An, Zihao & Xie, Bo & Liu, Qiyang, 2023. "No street is an Island: Street network morphologies and traffic safety," Transport Policy, Elsevier, vol. 141(C), pages 167-181.
    4. Tianyang Ge & Wenjun Hou & Yang Xiao, 2023. "Study on the Regeneration of City Centre Spatial Structure Pedestrianisation Based on Space Syntax: Case Study on 21 City Centres in the UK," Land, MDPI, vol. 12(6), pages 1-26, June.
    5. Pei Yin & Miaojuan Peng, 2023. "Station Layout Optimization and Route Selection of Urban Rail Transit Planning: A Case Study of Shanghai Pudong International Airport," Mathematics, MDPI, vol. 11(6), pages 1-29, March.
    6. Zhou, You & Zhang, Lingzhu & JF Chiaradia, Alain, 2022. "Estimating wider economic impacts of transport infrastructure Investment: Evidence from accessibility disparity in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 220-235.
    7. Zaouche, Mounia & Bode, Nikolai W.F., 2023. "Bayesian spatio-temporal models for mapping urban pedestrian traffic," Journal of Transport Geography, Elsevier, vol. 111(C).

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