@article{ref1,
title="A network-constrained spatial identification of high-risk roads for hit-parked-vehicle collisions in Brisbane, Australia",
journal="Environment and planning A",
year="2019",
author="Liu, Yan and Wang, Siqin and Fu, Xuanming and Xie, Bin",
volume="51",
number="2",
pages="279-282",
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.<p /> <p>Language: en</p>",
language="en",
issn="0308-518X",
doi="10.1177/0308518X18810531",
url="http://dx.doi.org/10.1177/0308518X18810531"
}