Temporal and spatial variations of real-time traffic data in urban areas

Stathopoulos, A; Karlaftis, M

dc.contributor.author	Stathopoulos, A	en
dc.contributor.author	Karlaftis, M	en
dc.date.accessioned	2014-03-01T02:42:02Z
dc.date.available	2014-03-01T02:42:02Z
dc.date.issued	2001	en
dc.identifier.issn	0361-1981	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30731
dc.subject	Real-time Traffic	en
dc.subject	Spatial Variation	en
dc.subject	Urban Area	en
dc.subject.classification	Engineering, Civil	en
dc.subject.classification	Transportation	en
dc.subject.classification	Transportation Science & Technology	en
dc.subject.other	Computer simulation	en
dc.subject.other	Data reduction	en
dc.subject.other	Environmental impact	en
dc.subject.other	Intelligent vehicle highway systems	en
dc.subject.other	Mathematical models	en
dc.subject.other	Motor transportation	en
dc.subject.other	Urban planning	en
dc.subject.other	Intelligent transportation systems (ITS)	en
dc.subject.other	Highway traffic control	en
dc.title	Temporal and spatial variations of real-time traffic data in urban areas	en
heal.type	conferenceItem	en
heal.identifier.primary	10.3141/1768-16	en
heal.identifier.secondary	http://dx.doi.org/10.3141/1768-16	en
heal.language	English	en
heal.publicationDate	2001	en
heal.abstract	Variations in traffic flow patterns can be very useful in helping intelligent transportation systems (ITS) provide drivers with useful and accurate route and travel-time information, in examining the potential benefits of flexible work hours, and in assessing the environmental effects of traffic congestion. Much of the work done toward examining temporal and spatial variations in traffic flow has concentrated on freeways, largely ignoring urban areas, where ITS strategies can have the most important effects. Addressed are the issues of temporal and spatial distributions and variations in real-time traffic flow by using data from 140 loop detectors from the greater Athens, Greece, urban area. The results indicate that the temporal distributions of traffic flows are nonnormal, and they vary by direction (toward, in, or away from the central business district) and time of day. This result has important implications in correctly calibrating the real-time simulation models used for volume and travel-time predictions. The results also indicate that traffic in Athens exhibits low seasonality, with lower traffic during the summer months, although traffic conditions are very similar for all weekdays but vary relative to the weekends and by time of day.	en
heal.publisher	TRANSPORTATION RESEARCH BOARD NATL RESEARCH COUNCIL	en
heal.journalName	Transportation Research Record	en
heal.bookName	TRANSPORTATION RESEARCH RECORD	en
dc.identifier.doi	10.3141/1768-16	en
dc.identifier.isi	ISI:000176595000016	en
dc.identifier.issue	1768	en
dc.identifier.spage	135	en
dc.identifier.epage	140	en