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100			_a Liu, Yan _944143
245			_aNetwork-constrained spatial identification of high-risk roads for hit-parked-vehicle collisions in Brisbane, Australia
260			_bSage _c2019.
300			_aVol 51, Issue 2, 2019,(279-282 p.)
520			_aThe 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.
650			_aHit-parked-vehicle collision, _944144
650			_a network-constrained spatial statistics, _944145
650			_a local indicator of network-constrained clusters, _944146
650			_a Brisbane _944147
700			_aWang, Siqin _930414
700			_a Fu, Xuanming _944148
700			_aXie, Bin _940774
773	0		_011325 _915507 _dSage, 2019. _tEnvironmental and planning A: Economy and space
856			_uhttps://doi.org/10.1177/0308518X18810531
942			_2ddc _cART