Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sheu, JB | en_US |
dc.date.accessioned | 2014-12-08T15:40:56Z | - |
dc.date.available | 2014-12-08T15:40:56Z | - |
dc.date.issued | 2003-05-01 | en_US |
dc.identifier.issn | 0041-1655 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1287/trsc.37.2.230.15244 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/27900 | - |
dc.description.abstract | Queue overflow is a critical issue in developing queue prediction technologies for applications in Advanced Transportation Management System (ATMS). Conventional queue prediction methods, however are limited to incident-free queue length prediction where traffic arrivals can be readily obtained using detectors. Despite the problems posed by queue overflow, studies addressing queue-overflow issues, or for predicting queue overflows beyond detectors, appear inadequate. This paper describes an advanced methodology which uses a stochastic system modeling approach and random processes for predicting queue lengths beyond detectors in real time. Lane changing is taken into account in developing the queue-overflow prediction model because lane changing accompanies queue overflow in most cases. A discrete-time, nonlinear stochastic system is specified for modeling the queues and lane changes beyond detectors during queue-overflow occurrence. The noise terms of the recursive equations of the model account for the effects of queues and a variety of arriving volumes on vehicular lane-changing maneuvers during queue-overflow occurrence. The unknown traffic arrivals beyond detectors a-re predicted employing random processes. In addition, a recursive estimation algorithm for predicting real-time queue overflows is developed utilizing the extended Kalman filtering technique. Preliminary test results indicate that the proposed methodology is promising for real-time prediction of queue overflows. The predicted queue overflows can be used not only in understanding the phenomenon of lane traffic patterns during queue-overflow occurrence, but also in developing related advanced technologies such as real-time road traffic congestion control and management systems. | en_US |
dc.language.iso | en_US | en_US |
dc.title | A stochastic modeling approach to real-time prediction of queue overflows (vol 37, pg 97, 2003) | en_US |
dc.type | Correction | en_US |
dc.identifier.doi | 10.1287/trsc.37.2.230.15244 | en_US |
dc.identifier.journal | TRANSPORTATION SCIENCE | en_US |
dc.citation.volume | 37 | en_US |
dc.citation.issue | 2 | en_US |
dc.citation.spage | 230 | en_US |
dc.citation.epage | 252 | en_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 | Department of Transportation and Logistics Management | en_US |
dc.identifier.wosnumber | WOS:000183114300008 | - |
dc.citation.woscount | 2 | - |
Appears in Collections: | Articles |