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

Alain J F Chiaradia,Ian Harvey,Scott Orford,Crispin H V Cooper

doi:10.1007/s11116-019-10072-0

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.

Highlights

Predicting how changes to the urban environment layout will affect the spatial distribution of pedestrian flows is important for numerous reasons
This study has tested the forecasting ability of Multiple Hybrid Spatial Design Network Analysis, which in contrast to traditional spatial network analysis attempts to explicitly capture a diverse array of behaviour
We have shown Multiple Hybrid Spatial Design Network Analysis (MH-sDNA) to be capable of predicting the effect of major changes in city centre street layout, including re-alignment and urban block size changes and re-allocation of street space, on pedestrian flow counts, by extrapolating from measured pedestrian flow data both across space and across time

Summary

Introduction

Predicting how changes to the urban environment layout will affect the spatial distribution of pedestrian flows is important for numerous reasons. UK policy (Department for Communities and Local Government 2009) stresses the importance of ‘linked trips’. Vitality on the other hand relates to the intensity of activities at various times of the day, and is usually measured by pedestrian flows (Department for Communities and Local Government 2014 paragraph 5). To this end, town centres have audited pedestrian volumes and their changes over time. All of the above aims in public policy relate to complex phenomena in which spatial distribution of pedestrian flows constitutes only part of the picture, but an essential part

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Conclusion