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Using detection of vehicular presence to estimate shockwave speed and upstream traffics for a signalized intersection

dc.citation.epage1165en_US
dc.citation.issueen_US
dc.citation.spage1151en_US
dc.citation.volume232en_US
dc.citation.woscount0
dc.contributor.authorCho, Hsun-Jungen_US
dc.contributor.authorTseng, Ming-Teen_US
dc.contributor.authorHwang, Ming-Chorngen_US
dc.contributor.department運輸與物流管理系 註:原交通所+運管所zh_TW
dc.contributor.department友訊交大聯合研發中心zh_TW
dc.contributor.departmentDepartment of Transportation and Logistics Managementen_US
dc.contributor.departmentD Link NCTU Joint Res Ctren_US
dc.date.accessioned2014-12-08T15:35:52Z
dc.date.available2014-12-08T15:35:52Z
dc.date.issued2014-04-01en_US
dc.description.abstractBased on the Lighthill-Whitham-Richards (LWR) traffic flow theory, this paper provides alternative methods to compute shockwave speed mainly by using detection data that reflects three states of vehicular presences: vehicles in moving, vehicles stopped, and void of vehicles. As the duration of a state is firmly identified within a cycle, the proposed methods compute shockwave speeds directly by means of Euclidian geometrics on time-space trajectory of shockwaves. This approach is also applicable to congested signal links with a long queue (but a residual queue) beyond detection zone. In addition, given signal timing and the shockwave speeds calculated by the methods, characteristics of arrival traffics, i.e. upstream flow rate and speed, can be predicted before the end of current cycle. It justifies that the methods are capable of whether to extend green phase before next cycle or not and will be a promising tool for real-time operations of signal control. Finally, the predicted shockwave speeds, upstream flow rate, and space mean speed by the proposed method are testified using simulated data from CORSIM. The mean absolute percentage errors of the estimated speeds of forward recovery shockwave and backward forming shockwave are 4.0% and 12.4% respectively. For the predicted flow rate and space mean speed of downstream arrival traffics, the mean absolute percentage errors are 18% and 4%, respectively. The results demonstrate the effectiveness of the presented approach. (C) 2014 Elsevier Inc. All rights reserved.en_US
dc.identifier.doi10.1016/j.amc.2013.12.180en_US
dc.identifier.issn0096-3003en_US
dc.identifier.journalAPPLIED MATHEMATICS AND COMPUTATIONen_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.amc.2013.12.180en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/24247
dc.identifier.wosnumberWOS:000335201700109
dc.language.isoen_USen_US
dc.subjectShockwaye speeden_US
dc.subjectLWR traffic flow theoryen_US
dc.subjectSignal controlen_US
dc.subjectVehicle detectionen_US
dc.titleUsing detection of vehicular presence to estimate shockwave speed and upstream traffics for a signalized intersectionen_US
dc.typeArticleen_US

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