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Spatial Variation in Road Pedestrian Casualties: The Role of Urban Scale, Density and Land-use Mix

Author

Listed:
  • Daniel J. Graham

    (Centre for Transport Studies, Imperial College London, London SW7 2AZ, UK. d.j.graham@imperial.ac.uk)

  • Stephen Glaister

    (Centre for Transport Studies, Imperial College London, London SW7 2AZ, UK. s.glaister@imperial.ac.uk)

Abstract

This paper examines the role of urban scale, density and land-use mix on the incidence of road pedestrian casualties. It develops a spatial model at a disaggregate level that attempts to understand how the nature of the urban environment, with its associated traffic generation characteristics, affects the incidence of road pedestrian casualties. The results show that the characteristics of the local environment have a powerful influence on pedestrian casualties. The incidence of pedestrian casualties and KSIs is higher in residential than in economic zones and a quadratic relationship is found between urban density and pedestrian casualties with incidents diminishing for the most extremely dense wards. Distinguishing broad land-use effects, the paper explores the ways in which population and employment density influence pedestrian casualties.

Suggested Citation

  • Daniel J. Graham & Stephen Glaister, 2003. "Spatial Variation in Road Pedestrian Casualties: The Role of Urban Scale, Density and Land-use Mix," Urban Studies, Urban Studies Journal Limited, vol. 40(8), pages 1591-1607, July.
  • Handle: RePEc:sae:urbstu:v:40:y:2003:i:8:p:1591-1607
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    Cited by:

    1. Jones, Peter & Lucas, Karen, 2012. "The social consequences of transport decision-making: clarifying concepts, synthesising knowledge and assessing implications," Journal of Transport Geography, Elsevier, vol. 21(C), pages 4-16.
    2. Ahfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2017. "The compact city in empirical research: A quantitative literature review," LSE Research Online Documents on Economics 83638, London School of Economics and Political Science, LSE Library.
    3. Ahlfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2019. "The economic effects of density: A synthesis," Journal of Urban Economics, Elsevier, vol. 111(C), pages 93-107.
    4. Chi, Guangqing & Porter, Jeremy R. & Cosby, Arthur G. & Levinson, David, 2013. "The impact of gasoline price changes on traffic safety: a time geography explanation," Journal of Transport Geography, Elsevier, vol. 28(C), pages 1-11.
    5. Gabriel M. Ahfeldt & Elisabetta Pietrostefani, 2017. "The Compact City in Empirical Research: A Quantitative Literature Review," SERC Discussion Papers 0215, Spatial Economics Research Centre, LSE.
    6. Daniel J. Graham & Emma J. McCoy & David A. Stephens, 2013. "Quantifying the effect of area deprivation on child pedestrian casualties by using longitudinal mixed models to adjust for confounding, interference and spatial dependence," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(4), pages 931-950, October.
    7. Ningcheng Wang & Yufan Liu & Jinzi Wang & Xingjian Qian & Xizhi Zhao & Jianping Wu & Bin Wu & Shenjun Yao & Lei Fang, 2019. "Investigating the Potential of Using POI and Nighttime Light Data to Map Urban Road Safety at the Micro-Level: A Case in Shanghai, China," Sustainability, MDPI, Open Access Journal, vol. 11(17), pages 1-14, August.
    8. Hanson, Christopher S. & Noland, Robert B. & Brown, Charles, 2013. "The severity of pedestrian crashes: an analysis using Google Street View imagery," Journal of Transport Geography, Elsevier, vol. 33(C), pages 42-53.
    9. Wang, Chao & Quddus, Mohammed & Ison, Stephen, 2009. "The effects of area-wide road speed and curvature on traffic casualties in England," Journal of Transport Geography, Elsevier, vol. 17(5), pages 385-395.
    10. Dongkwan Lee & Jean-Michel Guldmann & Choongik Choi, 2019. "Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers," Sustainability, MDPI, Open Access Journal, vol. 11(23), pages 1-13, November.
    11. Areti Boulieri & Silvia Liverani & Kees Hoogh & Marta Blangiardo, 2017. "A space–time multivariate Bayesian model to analyse road traffic accidents by severity," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 119-139, January.
    12. Dai, Dajun, 2012. "Identifying clusters and risk factors of injuries in pedestrian–vehicle crashes in a GIS environment," Journal of Transport Geography, Elsevier, vol. 24(C), pages 206-214.
    13. Dongkwan Lee & Jean-Michel Guldmann & Burkhard von Rabenau, 2018. "Interactions between the built and socio-economic environment and driver demographics: spatial econometric models of car crashes in the Columbus Metropolitan Area," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 22(1), pages 17-37, January.

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