Optimizing distribution of metered traffic flow in perimeter control: Queue and delay balancing approaches

Abstract

Perimeter traffic flow control based on the macroscopic or network fundamental diagram provides the opportunity of operating an urban traffic network at its capacity. Because perimeter control operates on the basis of restricting inflow via reduced green times at selected entry (gated) links, vehicles on those links may be subject to queuing and delay. The experienced delay or resulting queue lengths depend on the adopted policy for the distribution of the inflows and corresponding green times at the gated links. The chosen policy may have a significant impact on the traffic system under control. For example, managing queue lengths may reduce the interference with upstream traffic whereas the management of delays may improve users' perception with respect to equity and fairness. In this paper, an approach has been proposed to distribute the gated flow based on the queue lengths or experienced delay at the gated signalized junctions. This is in contrast to standard practice that distributes inflows proportionally to the gated links' saturation flows. Perimeter control is then evaluated in a microscopic simulator for a realistic traffic network and compared in three configurations against fixed-time: perimeter control without queue or delay management; perimeter control with relative queue balancing; and perimeter control with delay balancing. It has been found that managing the queues at the gated links not only improves the overall network performance but also reduces the possibility of queue propagation to the upstream junctions. This improves traffic flow outside the protected network by managing the queue propagation at the gated links and reducing the possibility of queue spillback to upstream intersections. In addition, the results indicate that perimeter control with delay balancing has a similar performance as the case without queue or delay management being a suitable approach for flow distribution among the gated links. In the scenarios with perimeter control with either queue or delay balancing the gap between the ordered flow by the controller and the actual flow crossing the stop-line at the gated links reduced remarkably.

Partitioning of urban networks with polycentric congestion pattern for traffic management policies: Identifying protected networks

“…Future potential research directions include the following: Applying the approach using real‐world data and investigating the practical way to determine the partitioning parameters. Studying the influence of correlations and independence of different types of data when using the framework. Investigating the maximal number of partitions under different real‐world cases. Utilizing more data types and higher dimension structured data. Investigating the interaction between real‐time traffic management, for example, perimeter control with metered queue/delay balancing policies (Keyvan‐Ekbatani et al., 2021), and partitioning behaviors. Analyzing the quality of partitioning results when network simplification algorithms are applied. …”

“…5. Investigating the interaction between real-time traffic management, for example, perimeter control with metered queue/delay balancing policies (Keyvan-Ekbatani et al, 2021), and partitioning behaviors. 6.…”

“…Some region-based management strategies rely on static partitioning, similar to the counterpart for modeling purposes, while dynamic strategies may require time-varying partitioning. The performance of policies such as perimeter control with static PN(s) may deteriorate over time since large queuing and unbalanced delays may occur in the vicinity of the RZ (or PN; Keyvan-Ekbatani et al, 2021). Recent studies (Li et al, 2021;S.…”

“…Some region‐based management strategies rely on static partitioning, similar to the counterpart for modeling purposes, while dynamic strategies may require time‐varying partitioning. The performance of policies such as perimeter control with static PN(s) may deteriorate over time since large queuing and unbalanced delays may occur in the vicinity of the RZ (or PN; Keyvan‐Ekbatani et al., 2021). Recent studies (Li et al., 2021; S. Jiang et al., 2021) have shown that perimeter control with dynamic partitioning can in fact be remarkably effective in mitigating congestion and distributing the traffic flow homogeneously across a large‐scale urban network.…”

Improving Deep Reinforcement Learning-Based Perimeter Metering Control Methods With Domain Control Knowledge

“…The boundary capacity constraints can be omitted as well, since they have been shown to be inconsequential ( 30 , 35 , 49 , 50 ) and such omission leads to significant computational advantage. Moreover, the effects of perimeter control on boundary queue dynamics are assumed to be marginal in this paper; see Haddad ( 25 ), Ni and Cassidy ( 42 ), Li et al ( 51 ), and Keyvan-Ekbatani et al ( 52 ) for more details on the relaxation of this assumption.…”