Network-constrained spatial identification of high-risk roads for hit-parked-vehicle collisions in Brisbane, Australia
Material type: TextPublication details: Sage 2019.Description: Vol 51, Issue 2, 2019,(279-282 p.)Subject(s): Online resources: In: Environmental and planning A: Economy and spaceSummary: The severe loss of human life and material damage caused by traffic accidents is a growing concern faced by many countries across the world. In Australia, despite a decline in the total number of traffic collisions since 2001, the number of hit-parked-vehicle (HPV) collisions as a special type of road accident has increased over time. Utilizing the road collisions and roadway network data in Brisbane, Australia over a 10-year period from 2001 to 2010, we generated graphics illustrating the spatial patterning of high-risk road segments for HPV crashes identified using the local indicator of network-constrained clusters (LINCS) approach. These spatial patterns vary by days of the week and times of the day. Roads with high risk for HPV collision tend to occur in high-density road networks and cluster around road intersections. The methodology applied in this work is applicable to other network-constrained point-pattern analysis.Item type | Current library | Collection | Call number | Vol info | Status | Date due | Barcode | Item holds | |
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E-Journal | Library, SPAB | Reference Collection | Vol. 51, Issue 1-8, 2019 | Available |
The severe loss of human life and material damage caused by traffic accidents is a growing concern faced by many countries across the world. In Australia, despite a decline in the total number of traffic collisions since 2001, the number of hit-parked-vehicle (HPV) collisions as a special type of road accident has increased over time. Utilizing the road collisions and roadway network data in Brisbane, Australia over a 10-year period from 2001 to 2010, we generated graphics illustrating the spatial patterning of high-risk road segments for HPV crashes identified using the local indicator of network-constrained clusters (LINCS) approach. These spatial patterns vary by days of the week and times of the day. Roads with high risk for HPV collision tend to occur in high-density road networks and cluster around road intersections. The methodology applied in this work is applicable to other network-constrained point-pattern analysis.
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