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Spatial Analysis of Characteristics and Influencing Factors of Killed or Seriously Injured Persons from Motor Vehicle Collisions within the City of Toronto

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posted on 2024-02-07, 20:21 authored by Andrew Thompson

This research is intended to support policy makers, infrastructure designers, road safety planners, and law enforcement in the identification of the underlying characteristics of Killed or Seriously Injured (KSI) between 2006 and 2019, as a result of Motor Vehicle Collisions (MVCs) within the City of Toronto. A combination of global & local spatial autocorrelation testing approaches with Moran’s I and Getis-Ord followed by statistical modelling were leveraged. Results determined KSIs within the City of Toronto were not random in nature and spatial interaction was driven by underlying factors. Global autocorrelation was only present in the Downtown Toronto Area. Stepwise Regression Modelling (SRM) revealed a multitude of explanatory factors including: land use, infrastructure density, and demographics to explain the variation within the rate of KSI occurrences with statistical significance. Data for this research was acquired through open data and academic repositories from Toronto Police Service, City of Toronto, and Statistics Canada.

History

Language

English

Degree

  • Spatial Analysis

Program

  • Spatial Analysis

Granting Institution

Ryerson University

LAC Thesis Type

  • MRP

Thesis Advisor

Dr. Eric Vaz

Year

2021

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