Model for planning emergency response services in road safety

Kepaptsoglou, K; Karlaftis, MG; Mintsis, G

dc.contributor.author	Kepaptsoglou, K	en
dc.contributor.author	Karlaftis, MG	en
dc.contributor.author	Mintsis, G	en
dc.date.accessioned	2014-03-01T02:11:26Z
dc.date.available	2014-03-01T02:11:26Z
dc.date.issued	2012	en
dc.identifier.issn	07339488	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/29899
dc.subject	Accidents	en
dc.subject	Emergency Services	en
dc.subject	Networks	en
dc.subject	Optimization	en
dc.subject.other	Accident frequency	en
dc.subject.other	Emergency response	en
dc.subject.other	Emergency response plans	en
dc.subject.other	Emergency service	en
dc.subject.other	Human lives	en
dc.subject.other	Location decisions	en
dc.subject.other	Location models	en
dc.subject.other	Road safety	en
dc.subject.other	Social concerns	en
dc.subject.other	Thessaloniki , Greece	en
dc.subject.other	Urban transportation networks	en
dc.subject.other	Networks (circuits)	en
dc.subject.other	Optimization	en
dc.subject.other	Transportation	en
dc.subject.other	Accidents	en
dc.subject.other	accident	en
dc.subject.other	action plan	en
dc.subject.other	genetic algorithm	en
dc.subject.other	optimization	en
dc.subject.other	road	en
dc.subject.other	safety	en
dc.subject.other	urban transport	en
dc.subject.other	Central Macedonia	en
dc.subject.other	Greece	en
dc.subject.other	Thessaloniki [Central Macedonia]	en
dc.subject.other	Thessaloniki	en
dc.title	Model for planning emergency response services in road safety	en
heal.type	journalArticle	en
heal.identifier.primary	10.1061/(ASCE)UP.1943-5444.0000097	en
heal.identifier.secondary	http://dx.doi.org/10.1061/(ASCE)UP.1943-5444.0000097	en
heal.publicationDate	2012	en
heal.abstract	In an era of continuous growth in mobility and demand for transportation, safety is an issue of major social concern and an area of extensive research and work by practitioners and academics. Emergency response services are very important in handling and minimizing the impacts of traffic accidents and for saving human lives. In this paper, we develop an efficient emergency response plan for responding to traffic accidents; the objective is to strategically deploy emergency response vehicles in a large urban transportation network. We combine a location model with a genetic algorithm and guide location decisions through accident metrics such as accident frequencies and severities at different parts of the network. We demonstrate the usefulness and applicability of this approach by planning for a real-world case study in the city of Thessaloniki, Greece. © 2012 American Society of Civil Engineers.	en
heal.journalName	Journal of Urban Planning and Development	en
dc.identifier.doi	10.1061/(ASCE)UP.1943-5444.0000097	en
dc.identifier.volume	138	en
dc.identifier.issue	1	en
dc.identifier.spage	18	en
dc.identifier.epage	25	en