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Hotzone identification with GIS-based post-network screening analysis

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  • Young, Jason
  • Park, Peter Y.

Abstract

This paper proposes a two-step method called post-network screening analysis for identifying collision hotzones (i.e., groups of neighboring hotspots) on a road network. The first step is the familiar safety network screening that uses AASHTO’s Highway Safety Manual (HSM) to identify and rank individual locations (i.e., hotspots) according to their potential for safety improvement. The second step is new and involves network-constrained kernel density estimation (KDE), a type of spatial analysis. KDE uses expected collision counts to estimate collision density, and outputs a graphical display that shows areas with a high density of expected collision counts. These are the hotzones. A particularly interesting area of application is the identification of high-collision corridors that may benefit from a program of systemic safety improvements. The proposed method was tested using five years of collision data (2005–2009) for the City of Regina, Saskatchewan. Three different network screening measures were compared: (1) observed collision counts, (2) observed severity-weighted collision counts, and (3) expected severity-weighted collision counts. The study found that observed severity-weighted collision counts produced a dramatic picture of the city’s hotzones, but this picture could be misleading as it could be heavily influenced by a small number of severe collisions. The results obtained from the expected severity-weighted collision counts smoothed the effects of the severity-weighting and successfully reduced regression-to-the-mean bias. A comparison is made between the proposed approach and the results of the HSM’s existing network screening method. As the proposed approach takes the spatial association of roadway segments into account, and is not limited to single roadway segments, the hotzones identified capture a higher number of expected equivalent-property-damage-only (EPDO) collisions than the existing HSM methodology. The study concludes that the proposed two-step method can help transportation safety professionals to prioritize hotzones within high-collision corridors more efficiently and scientifically.

Suggested Citation

  • Young, Jason & Park, Peter Y., 2014. "Hotzone identification with GIS-based post-network screening analysis," Journal of Transport Geography, Elsevier, vol. 34(C), pages 106-120.
  • Handle: RePEc:eee:jotrge:v:34:y:2014:i:c:p:106-120
    DOI: 10.1016/j.jtrangeo.2013.11.007
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    2. Delso, Javier & Martín, Belén & Ortega, Emilio, 2018. "A new procedure using network analysis and kernel density estimations to evaluate the effect of urban configurations on pedestrian mobility. The case study of Vitoria –Gasteiz," Journal of Transport Geography, Elsevier, vol. 67(C), pages 61-72.
    3. Khondoker Billah & Qasim Adegbite & Hatim O. Sharif & Samer Dessouky & Lauren Simcic, 2021. "Analysis of Intersection Traffic Safety in the City of San Antonio, 2013–2017," Sustainability, MDPI, vol. 13(9), pages 1-18, May.
    4. Ke Nie & Zhensheng Wang & Qingyun Du & Fu Ren & Qin Tian, 2015. "A Network-Constrained Integrated Method for Detecting Spatial Cluster and Risk Location of Traffic Crash: A Case Study from Wuhan, China," Sustainability, MDPI, vol. 7(3), pages 1-16, March.
    5. Khondoker Billah & Hatim O. Sharif & Samer Dessouky, 2022. "How Gender Affects Motor Vehicle Crashes: A Case Study from San Antonio, Texas," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    6. Matthias Eckardt & Jorge Mateu, 2021. "Second-order and local characteristics of network intensity functions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 318-340, June.
    7. Costa, Isabella & Rochedo, Pedro & Costa, Daniele & Ferreira, Paula & Araújo, Madalena & Schaeffer, Roberto & Szklo, Alexandre, 2019. "Placing hubs in CO2 pipelines: An application to industrial CO2 emissions in the Iberian Peninsula," Applied Energy, Elsevier, vol. 236(C), pages 22-31.
    8. Khondoker Billah & Hatim O. Sharif & Samer Dessouky, 2023. "Bivariate-Logit-Based Severity Analysis for Motorcycle Crashes in Texas, 2017–2021," Sustainability, MDPI, vol. 15(13), pages 1-26, June.
    9. Rodrigues, Daniel Souto & Ribeiro, Paulo Jorge Gomes & da Silva Nogueira, Isabel Cristina, 2015. "Safety classification using GIS in decision-making process to define priority road interventions," Journal of Transport Geography, Elsevier, vol. 43(C), pages 101-110.
    10. Khondoker Billah & Hatim O. Sharif & Samer Dessouky, 2021. "Analysis of Bicycle-Motor Vehicle Crashes in San Antonio, Texas," IJERPH, MDPI, vol. 18(17), pages 1-19, September.

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