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Characterizing the dynamics and uncertainty of queues at signalized intersections with left-turn bay.
- Source :
-
Physica A . Aug2022, Vol. 599, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
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Abstract
- In most signalized intersections, in order to solve the problem of insufficient road space, left-turn bays are commonly set up at intersections with a shared through and left-turn lane. However, this design tends to result in the potential queue overflow and blockage problems, which further make the discharge process of either left-turn vehicles or through vehicles at the intersections to be interrupted unexpectedly during their respective green phase. As a result, the queueing processes of vehicles present high nonlinearity and uncertainty during a signal cycle. In this paper, a stochastic queueing model is proposed to characterize the dynamics and uncertainty of queues at signalized intersections with a left-turn bay. The proposed model takes full account of the random interaction between the through movement and the left-turn movement under the influence of overflow and blockage of queues. We obtain some average performance indicators as well as the signal-state-dependent dynamic performance measure of queues and its variance at any given time point within a signal cycle. The proposed analytical model is validated against the VISSIM simulation model under different scenarios; the results show a good degree of agreement. In addition, in order to systematically determine the queue dynamics and uncertainty, we also conduct a series of numerical simulations to quantitatively capture the queue characteristics of vehicles at signalized intersections with left-turn bay by considering possible factors. • Develop a stochastic model to describe the queues at signals with left-turn bay. • Random interactions between the different movements are focused. • Signal-state-dependent dynamic performance measures of queues are obtained. • Factors that can affect the queue dynamics are examined. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03784371
- Volume :
- 599
- Database :
- Academic Search Index
- Journal :
- Physica A
- Publication Type :
- Academic Journal
- Accession number :
- 157120269
- Full Text :
- https://doi.org/10.1016/j.physa.2022.127439