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Modeling the Spatial Effects of Land-Use Patterns on Traffic Safety Using Geographically Weighted Poisson Regression

Author

Listed:
  • Chengcheng Xu

    (Southeast University
    Southeast University
    Southeast University)

  • Yuxuan Wang

    (Southeast University
    Southeast University
    Southeast University)

  • Wei Ding

    (Southeast University
    Southeast University
    Southeast University)

  • Pan Liu

    (Southeast University
    Southeast University
    Southeast University)

Abstract

This study aimed to investigate how land-use pattern affects crash frequency at traffic analysis zone (TAZ) level. Traffic, road network, land use, population and crash data were collected from Los Angeles County, California in 2014. K-means clustering analysis was first conducted to divide land use at each TAZ into five different patterns. Geographically weighted Poisson regression (GWPR) models were then developed to investigate the associations between crash counts and land-use patterns. The elasticity was calculated to compare the safety effect of each explanatory factor across different patterns. The results of this study indicated that land use combinations at TAZs can be divided into different patterns using land-use mix and proportions of different land use types, and that each land use combination can be assigned with a certain safety level. The effects of contributing factors on crash frequency are different across different land-use patterns. The results suggest that proper combinations of different land uses can improve safety performance at the urban and road network planning stage.

Suggested Citation

  • Chengcheng Xu & Yuxuan Wang & Wei Ding & Pan Liu, 2020. "Modeling the Spatial Effects of Land-Use Patterns on Traffic Safety Using Geographically Weighted Poisson Regression," Networks and Spatial Economics, Springer, vol. 20(4), pages 1015-1028, December.
  • Handle: RePEc:kap:netspa:v:20:y:2020:i:4:d:10.1007_s11067-020-09509-2
    DOI: 10.1007/s11067-020-09509-2
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    References listed on IDEAS

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    1. David Novak & Christopher Hodgdon & Feng Guo & Lisa Aultman-Hall, 2011. "Nationwide Freight Generation Models: A Spatial Regression Approach," Networks and Spatial Economics, Springer, vol. 11(1), pages 23-41, March.
    2. Luis Miranda-Moreno & Liping Fu, 2006. "A Comparative Study of Alternative Model Structures and Criteria for Ranking Locations for Safety Improvements," Networks and Spatial Economics, Springer, vol. 6(2), pages 97-110, June.
    3. Pirdavani, Ali & Bellemans, Tom & Brijs, Tom & Kochan, Bruno & Wets, Geert, 2014. "Assessing the road safety impacts of a teleworking policy by means of geographically weighted regression method," Journal of Transport Geography, Elsevier, vol. 39(C), pages 96-110.
    4. Daniel Griffith & Yongwan Chun, 2015. "Spatial Autocorrelation in Spatial Interactions Models: Geographic Scale and Resolution Implications for Network Resilience and Vulnerability," Networks and Spatial Economics, Springer, vol. 15(2), pages 337-365, June.
    5. Daniel P. McMillen, 2004. "Geographically Weighted Regression: The Analysis of Spatially Varying Relationships," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 554-556.
    6. Judith Y. T. Wang & Richard D. Connors, 2018. "Urban Growth, Transport Planning, Air Quality and Health: A Multi-Objective Spatial Analysis Framework for a Linear Monocentric City," Networks and Spatial Economics, Springer, vol. 18(4), pages 839-874, December.
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