{"id":{"repo_id":"uwo","oai_identifier":"oai:uwo.scholaris.ca:20.500.14721/32541"},"canonical_url":"https://search.dev.ndltd.org/etd/uwo/oai:uwo.scholaris.ca:20.500.14721/32541","repository":{"repo_id":"uwo","name":"Western University","base_url":"https://uwo.scholaris.ca/server/oai/request"},"display":{"title":"Motor Vehicle Collisions in London, Ontario: Estimating the influence of the built environment and children’s potential exposure","abstract":"Motor vehicle collisions are the leading cause of death for children and youth worldwide. To effectively target interventions to improve child safety, it is necessary to identify where motor vehicle collisions occur most often and what factors make these areas more hazardous. Study #1 maps collisions in London, Ontario (2010-2019) and identifies hotspots using a network kernel density estimation method within a GIS. Logistic regression analysis revealed that bike lanes were negatively associated with hotspots, while sidewalks were positively associated. Study #2 estimated children’s risk of being exposed to a motor vehicle collision while commuting to and from school, by combining collision risk data from study #1 with modelled student pedestrian volumes. Results suggest current crossing guard locations in London are not optimally deployed and should be relocated to the riskiest areas for student pedestrians. The findings of this thesis suggest that certain built environment characteristics have a significant influence on collision hotspots and should be considered in future road safety policy.","abstract_html":"Motor vehicle collisions are the leading cause of death for children and youth worldwide. To effectively target interventions to improve child safety, it is necessary to identify where motor vehicle collisions occur most often and what factors make these areas more hazardous. Study #1 maps collisions in London, Ontario (2010-2019) and identifies hotspots using a network kernel density estimation method within a GIS. Logistic regression analysis revealed that bike lanes were negatively associated with hotspots, while sidewalks were positively associated. Study #2 estimated children’s risk of being exposed to a motor vehicle collision while commuting to and from school, by combining collision risk data from study #1 with modelled student pedestrian volumes. Results suggest current crossing guard locations in London are not optimally deployed and should be relocated to the riskiest areas for student pedestrians. The findings of this thesis suggest that certain built environment characteristics have a significant influence on collision hotspots and should be considered in future road safety policy.","abstract_has_math":false,"creators":["Lui, David"],"institution":"The University of Western Ontario","degree_name":"M Sc","degree_level":null,"degree_discipline":"Geography and Environment","degree_department":null,"school":null,"contributors":[],"advisors":["Gilliland, Jason","Long, Jed"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-10-04","date_published":"2022-10-04","updated_at":"2026-07-27T21:56:03Z","subjects":["Motor vehicle collisions","Geographic information systems","Built environment","Kernel density estimation","Hotspots","Child pedestrians"],"languages":["en_ca"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/20.500.14721/32541","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Gilliland, Jason","Long, Jed"]},{"key":"dc:creator","label":"Author","values":["Lui, David"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-07-10T19:32:01Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-07-10T19:32:01Z"]},{"key":"dc:date.issued","label":"Date","values":["2022-10-04"]},{"key":"dc:publisher","label":"Institution","values":["The University of Western Ontario"]},{"key":"dc:type","label":"Dc Type","values":["thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geography and Environment"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M Sc"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Motor vehicle collisions","Geographic information systems","Built environment","Kernel density estimation","Hotspots","Child pedestrians"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_ca"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.14721/32541"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The thesis cover page in the PDF document includes references to Western University’s previous institutional repository platform, known as Scholarship@Western, and links to that platform (beginning with ir.lib.uwo.ca). In citing or referring to this thesis, use the DOI or handle from this page instead. Sample citation: Author name, \"Thesis title.\" (Year). Western University Open Repository. https://doi.org/10.71858/123456."]},{"key":"dc:description.abstract","label":"Abstract","values":["Motor vehicle collisions are the leading cause of death for children and youth worldwide. To effectively target interventions to improve child safety, it is necessary to identify where motor vehicle collisions occur most often and what factors make these areas more hazardous. Study #1 maps collisions in London, Ontario (2010-2019) and identifies hotspots using a network kernel density estimation method within a GIS. Logistic regression analysis revealed that bike lanes were negatively associated with hotspots, while sidewalks were positively associated. Study #2 estimated children’s risk of being exposed to a motor vehicle collision while commuting to and from school, by combining collision risk data from study #1 with modelled student pedestrian volumes. Results suggest current crossing guard locations in London are not optimally deployed and should be relocated to the riskiest areas for student pedestrians. The findings of this thesis suggest that certain built environment characteristics have a significant influence on collision hotspots and should be considered in future road safety policy."]},{"key":"dc:title","label":"Title","values":["Motor Vehicle Collisions in London, Ontario: Estimating the influence of the built environment and children’s potential exposure"]}]}],"canonical_facts":{"dc:contributor.advisor":["Gilliland, Jason","Long, Jed"],"dc:creator":["Lui, David"],"dc:date.accessioned":["2025-07-10T19:32:01Z"],"dc:date.available":["2025-07-10T19:32:01Z"],"dc:date.issued":["2022-10-04"],"dc:description":["The thesis cover page in the PDF document includes references to Western University’s previous institutional repository platform, known as Scholarship@Western, and links to that platform (beginning with ir.lib.uwo.ca). In citing or referring to this thesis, use the DOI or handle from this page instead. Sample citation: Author name, \"Thesis title.\" (Year). Western University Open Repository. https://doi.org/10.71858/123456."],"dc:description.abstract":["Motor vehicle collisions are the leading cause of death for children and youth worldwide. To effectively target interventions to improve child safety, it is necessary to identify where motor vehicle collisions occur most often and what factors make these areas more hazardous. Study #1 maps collisions in London, Ontario (2010-2019) and identifies hotspots using a network kernel density estimation method within a GIS. Logistic regression analysis revealed that bike lanes were negatively associated with hotspots, while sidewalks were positively associated. Study #2 estimated children’s risk of being exposed to a motor vehicle collision while commuting to and from school, by combining collision risk data from study #1 with modelled student pedestrian volumes. 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