Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/11129
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMOONS, Elke-
dc.contributor.authorBRIJS, Tom-
dc.contributor.authorWETS, Geert-
dc.date.accessioned2010-09-06T12:36:03Z-
dc.date.availableNO_RESTRICTION-
dc.date.available2010-09-06T12:36:03Z-
dc.date.issued2009-
dc.identifier.citationGavrilova, ML; Tan, CJK (Ed.) TRANSACTIONS ON COMPUTATIONAL SCIENCE VI. p. 288-300.-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/1942/11129-
dc.description.abstractTraffic safety has become top priority for policy makers in most European countries. The first step is to identify hazardous locations. This can be carried out in many different ways, via (Bayesian) statistical models or by incorporating the spatial configuration by means of a. local indicator of spatial association. In this paper, the structure of the underlying road network is taken into account by applying Moran's I to identify hot spots. One step further than the pure identification of hazardous locations is a deeper investigation of these hot spots in a hot zone analysis. This extended analysis is important both theoretically in enriching the way of conceptualizing and identifying hazardous locations and practically in providing useful information for addressing traffic safety problems. The results are presented on highways in a province in Belgium and in an urban environment. They indicate that incorporating the hot zone methodology in a hot spot analysis reveals a clearer picture of the underlying hazardous road locations and, consequently, this may have an important impact on policy makers.-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.relation.ispartofseriesLecture Notes in Computer Science-
dc.subject.otherHot spot analysis; Moran index; hot zone; traffic safety-
dc.titleIdentifying Hazardous Road Locations: Hot Spots versus Hot Zones-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsGavrilova, ML; Tan, CJK-
local.bibliographicCitation.conferencenameInternational Joint Conference on Computer Vision and Computer Graphics Theory and Applications-
local.bibliographicCitation.conferenceplaceFunchal, PORTUGAL, JAN 22-25, 2008-
dc.identifier.epage300-
dc.identifier.spage288-
dc.identifier.volume5730-
local.format.pages13-
local.bibliographicCitation.jcatC1-
dc.description.notes[Moons, Elke; Brijs, Tom; Wets, Geert] Hasselt Univ, Transportat Res Inst, B-3590 Diepenbeek, Belgium.-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.relation.ispartofseriesnr5730-
dc.bibliographicCitation.oldjcatC1-
dc.identifier.isi000280705300017-
local.bibliographicCitation.btitleTRANSACTIONS ON COMPUTATIONAL SCIENCE VI-
item.fulltextNo Fulltext-
item.fullcitationMOONS, Elke; BRIJS, Tom & WETS, Geert (2009) Identifying Hazardous Road Locations: Hot Spots versus Hot Zones. In: Gavrilova, ML; Tan, CJK (Ed.) TRANSACTIONS ON COMPUTATIONAL SCIENCE VI. p. 288-300..-
item.accessRightsClosed Access-
item.validationecoom 2011-
item.contributorMOONS, Elke-
item.contributorBRIJS, Tom-
item.contributorWETS, Geert-
Appears in Collections:Research publications
Show simple item record

WEB OF SCIENCETM
Citations

19
checked on May 10, 2024

Page view(s)

112
checked on Nov 7, 2023

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.