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

Author

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  • 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
    DOI: 10.1080/0042098032000094441
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    References listed on IDEAS

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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. Noland, Robert B. & Quddus, Mohammed A., 2005. "Congestion and safety: A spatial analysis of London," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 737-754.
    4. Ahlfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2019. "The economic effects of density: A synthesis," Journal of Urban Economics, Elsevier, vol. 111(C), pages 93-107.
    5. Nur Shaeza Darus & Muhamad Nazri Borhan & Siti Zaharah Ishak & Rozmi Ismail & Siti Fatin Mohd. Razali & Nor Aznirahani Mhd Yunin & Rizati Hamidun, 2022. "The Effect of Physical Environment Risk Factors on Vehicle Collisions Severity Involving Child-Pedestrians in Malaysia," SAGE Open, , vol. 12(1), pages 21582440211, January.
    6. 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.
    7. Nathaniel Bell & Nadine Schuurman, 2010. "GIS and Injury Prevention and Control: History, Challenges, and Opportunities," IJERPH, MDPI, vol. 7(3), pages 1-16, March.
    8. Robin Haynes & Andrew Jones & Victoria Kennedy & Ian Harvey & Tony Jewell, 2007. "District Variations in Road Curvature in England and Wales and their Association with Road-Traffic Crashes," Environment and Planning A, , vol. 39(5), pages 1222-1237, May.
    9. Dongkwan Lee & Jean-Michel Guldmann & Burkhard von Rabenau, 2023. "Impact of Driver’s Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach," IJERPH, MDPI, vol. 20(3), pages 1-22, January.
    10. Jesús López Baeza & José Carpio-Pinedo & Julia Sievert & André Landwehr & Philipp Preuner & Katharina Borgmann & Maša Avakumović & Aleksandra Weissbach & Jürgen Bruns-Berentelg & Jörg Rainer Noennig, 2021. "Modeling Pedestrian Flows: Agent-Based Simulations of Pedestrian Activity for Land Use Distributions in Urban Developments," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    11. Bajada, Thérèse & Attard, Maria, 2021. "A typological and spatial analysis of pedestrian fatalities and injuries in Malta," Research in Transportation Economics, Elsevier, vol. 86(C).
    12. Gabriel M. Ahfeldt & Elisabetta Pietrostefani, 2017. "The Compact City in Empirical Research: A Quantitative Literature Review," SERC Discussion Papers 0215, Centre for Economic Performance, LSE.
    13. 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.
    14. 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, vol. 11(17), pages 1-14, August.
    15. 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.
    16. 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.
    17. Dongkwan Lee & Jean-Michel Guldmann & Choongik Choi, 2019. "Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers," Sustainability, MDPI, vol. 11(23), pages 1-13, November.
    18. Hull, Angela, 2008. "Policy integration: What will it take to achieve more sustainable transport solutions in cities," Transport Policy, Elsevier, vol. 15(2), pages 94-103, March.
    19. Zhang, Yingheng & Li, Haojie & Ren, Gang, 2022. "Quantifying the social impacts of the London Night Tube with a double/debiased machine learning based difference-in-differences approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 288-303.
    20. Albalate, Daniel & Fageda, Xavier, 2021. "On the relationship between congestion and road safety in cities," Transport Policy, Elsevier, vol. 105(C), pages 145-152.
    21. 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.
    22. 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.
    23. Marshall, Wesley & Garrick, Norman, 2012. "Community design and how much we drive," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(2), pages 5-21.
    24. 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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