CLC number: U491.2
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2013-09-12
Cited: 4
Clicked: 8939
Peng Chen, Huan Liu, Hong-sheng Qi, Fu-jian Wang. Analysis of delay variability at isolated signalized intersections[J]. Journal of Zhejiang University Science A, 2013, 14(10): 691-704.
@article{title="Analysis of delay variability at isolated signalized intersections",
author="Peng Chen, Huan Liu, Hong-sheng Qi, Fu-jian Wang",
journal="Journal of Zhejiang University Science A",
volume="14",
number="10",
pages="691-704",
year="2013",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1300208"
}
%0 Journal Article
%T Analysis of delay variability at isolated signalized intersections
%A Peng Chen
%A Huan Liu
%A Hong-sheng Qi
%A Fu-jian Wang
%J Journal of Zhejiang University SCIENCE A
%V 14
%N 10
%P 691-704
%@ 1673-565X
%D 2013
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1300208
TY - JOUR
T1 - Analysis of delay variability at isolated signalized intersections
A1 - Peng Chen
A1 - Huan Liu
A1 - Hong-sheng Qi
A1 - Fu-jian Wang
J0 - Journal of Zhejiang University Science A
VL - 14
IS - 10
SP - 691
EP - 704
%@ 1673-565X
Y1 - 2013
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1300208
Abstract: On urban arterials, travel time variability is largely dependent on the variability in the delays vehicles experience at signalized intersections. The interpretation of delay evolvement at intersections will give a comprehensive insight into arterial travel time variability and provide more possibilities for travel time estimation. Accordingly, an analytical model is proposed to study delay variability at isolated, fixed-time controlled intersections. Classic cumulative curves are utilized to derive average delay (per cycle) formulas by assuming a deterministic overflow queue. Then, an analogy with the markov chain process is made to clarify the mechanism of stochastic delays and overflow queues at signalized intersections. It was found that, in undersaturated cases, the shape of the delay distribution changes very little over time, whereas for saturated and oversaturated cases the delay distribution is time-dependent and becomes flatter with an increasing number of cycles. The analysis of arrival distributions, e.g., Poisson and binomial, produces the conclusion that the variability of arrivals has a significant effect on delay estimates in both undersaturated and oversaturated conditions. A larger variance of arrival flow results in a larger variance of delay distribution. All of these analyses can help road authorities to gain insights into arterial travel time variability.
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