A network-constrained spatial identification of high-risk roads for hit-parked-vehicle collisions in Brisbane, Australia
Article
Article Title | A network-constrained spatial identification of high-risk roads for hit-parked-vehicle collisions in Brisbane, Australia |
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ERA Journal ID | 20858 |
Article Category | Article |
Authors | Liu, Yan, Wang, Siqin, Fu, Xuanming and Xie, Bin |
Journal Title | Environment and Planning A |
Journal Citation | 51 (2), pp. 279-282 |
Number of Pages | 4 |
Year | Mar 2019 |
Place of Publication | United Kingdom |
ISSN | 0308-518X |
1472-3409 | |
Digital Object Identifier (DOI) | https://doi.org/10.1177/0308518X18810531 |
Web Address (URL) | https://journals.sagepub.com/doi/full/10.1177/0308518X18810531 |
Abstract | 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. |
Keywords | Hit-parked-vehicle collision; network-constrained spatial statistics; local indicator of network-constrained clusters; Brisbane |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Queensland |
Library Services |
https://research.usq.edu.au/item/wq615/a-network-constrained-spatial-identification-of-high-risk-roads-for-hit-parked-vehicle-collisions-in-brisbane-australia
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