Impact of stop-and-go waves and lane changes on discharge rate in recovery flow

Oh, Simon; Yeo, Hwasoo

doi:10.1016/j.trb.2015.03.017

Cited by 36 publications

(35 citation statements)

References 28 publications

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“…Empirical data show that the queue discharge rate varies considerably at the same location (Chung et al 2007, Yuan et al 2016. This is shown to correlate well with congestion states (Yuan et al 2015, Oh andYeo 2015). Yuan et al (2015) reveal a linear relation between the speed in congestion and the queue discharge rate (see Figure 1).…”

Section: Introductionmentioning

confidence: 83%

“…Road design and control measures can contribute to varying queue discharge rates (Srivastava andGeroliminis 2013, Oh andYeo 2015). These findings show that there might be promising strategies that can increase the queue discharge rate to reduce delays.…”

Section: Introductionmentioning

confidence: 88%

“…However, a reduction of capacity does not only occur at bottlenecks. In fact, some research (Kerner 1998, Yuan et al 2016, Oh and Yeo 2015 report on queue discharge rates out of stop-and-go waves on homogeneous freeway sections, which are also lower than the capacity. In this paper, we also call that a capacity drop.…”

Section: Introductionmentioning

confidence: 99%

“…By empirically analyzing NGSIM trajectory datasets, Oh and Yeo (2015) firstly shows that the contribution of traffic passing stop-and-go waves to discharge rates outperforms the contribution of lane change related traffic to discharge rates. Secondly, it is found that the queue discharge rate could be related to the severity of congestion in the absence of lane changing.…”

Section: Introductionmentioning

confidence: 99%

“…Secondly, it is found that the queue discharge rate could be related to the severity of congestion in the absence of lane changing. Our work can hence be seen in the perspective shaped by Oh and Yeo (2015), and we therefore focus on the study on the drivers longitudinal behavior mechanism behind the capacity drop.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Microscopic Investigation Into the Capacity Drop: Impacts of Longitudinal Behavior on the Queue Discharge Rate

Yuan¹,

Knoop²,

Hoogendoorn³

2017

Transportation Science

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The capacity drop indicates that the queue discharge rate is lower than the free-flow capacity. Studies show that the queue discharge rate varies under different traffic conditions. Empirical data show that the queue discharge rate increases as the speed in congestion increases. Insights into the underlying behavioral mechanisms that cause these variable queue discharge rates can help minimize traffic delays and eliminate congestion. However, to the best of the authors knowledge, few efforts have been devoted to testing impacts of traffic behaviors on the queue discharge rate. This paper tries to fill this gap. We investigate to what extent the acceleration spread and reaction time can influence the queue discharge rate. It is found that the (inter-driver) acceleration spread does not reduce the queue discharge rates as much as found empirically.Modelling reaction time might be more important than modeling acceleration for capacity drop in carfollowing models. A speed-dependent reaction time mechanism for giving variable queue discharge rates is proposed. That is, decreasing reaction time as the speed in congestion increases can give the same queue discharge rate as found empirically. This research suggests that motivating drivers to speed up earlier could increase the queue discharge rate and thereby minimize delays.

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Section: Introductionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 88%