Urban network gridlock: Theory, characteristics, and dynamics

“…They observed that the average network flow is consistently higher when link density variance is low for the same network density, but higher densities can create points below an MFD when they are heterogeneously distributed. Other investigations of empirical and simulated studies for network level traffic patterns can be found in Buisson and Ladier (2009), Aboudolas et al (2010), Ji et al (2010), Gayah and Daganzo (2011a), Wu et al (2011), Mahmassani et al (2013a), Mahmassani et al (2013), Zhang et al (2013) and elsewhere.…”

Section: Introductionmentioning

confidence: 99%

Perimeter and boundary flow control in multi-reservoir heterogeneous networks

Aboudolas

Geroliminis

2013

Transportation Research Part B: Methodological

325

176

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a b s t r a c tIn this paper, we macroscopically describe the traffic dynamics in heterogeneous transportation urban networks by utilizing the Macroscopic Fundamental Diagram (MFD), a widely observed relation between network-wide space-mean flow and density of vehicles. A generic mathematical model for multi-reservoir networks with well-defined MFDs for each reservoir is presented first. Then, two modeling variations lead to two alternative optimal control methodologies for the design of perimeter and boundary flow control strategies that aim at distributing the accumulation in each reservoir as homogeneously as possible, and maintaining the rate of vehicles that are allowed to enter each reservoir around a desired point, while the system's throughput is maximized. Based on the two control methodologies, perimeter and boundary control actions may be computed in real-time through a linear multivariable feedback regulator or a linear multivariable integral feedback regulator. Perimeter control occurs at the periphery of the network while boundary control occurs at the inter-transfers between neighborhood reservoirs. To this end, the heterogeneous network of San Francisco is partitioned into three homogeneous reservoirs and the proposed feedback regulators are compared with a pre-timed signal plan and a singlereservoir perimeter control strategy. Finally, the impact of the perimeter and boundary control actions is demonstrated via simulation by the use of the corresponding MFDs and other performance measures. A key advantage of the proposed approach is that it does not require high computational effort and future demand data if the current state of each reservoir can be observed with loop detector data.

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“…Thus, the sequence of regions for specific ODs is considered known priori. Yildirimoglu and Geroliminis (2014) and Mahmassani et al (2013) showed that route choice adaptation is more important under congested conditions. While the pricing strategies that are presented here, are able to avoid such conditions, not integrating an assignment framework is not expected to significantly alter the result, with an important computational benefit in parallel.…”

Section: System Dynamics With Mfd Representation and Parkingmentioning

confidence: 99%

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

Zheng

Geroliminis

2016

Transportation Research Part B: Methodological

158

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a b s t r a c tCruising-for-parking constraints mobility in urban networks. Car-users may have to cruise for on-street parking before reaching their destinations. The accessibility and the cost of parking significantly influence people's travel behavior (such as mode choice, or parking facility choice between on-street and garage). The cruising flow causes delays eventually to everyone, even users with destinations outside limited parking areas. It is therefore important to understand the impact of parking limitation on mobility, and to identify efficient parking policies for travel cost reduction. Most existing studies on parking fall short in reproducing the dynamic spatiotemporal features of traffic congestion in general, lack the treatment of dynamics of the cruising-for-parking phenomenon, or require detailed input data that are typically costly and difficult to collect. In this paper, we propose an aggregated and dynamic approach for modeling multimodal traffic with the treatment on parking, and utilize the approach to design dynamic parking pricing strategies. The proposed approach is based on the Macroscopic Fundamental Diagram (MFD), which can capture congestion dynamics at network-level for single-mode and bi-modal (car and bus) systems. A parsimonious parking model is integrated into the MFD-based multimodal modeling framework, where the dynamics of vehicular and passenger flows are considered with a change in the aggregated behavior (e.g. mode choice and parking facility choice) caused by cruising and congestion. Pricing strategies are developed with the objective of reducing congestion, as well as lowering the total travel cost of all users. A case study is carried out for a bi-modal city network with a congested downtown region. An elegant feedback dynamic parking pricing strategy can effectively reduce travel delay of cruising and the generic congestion. Remarkably, such strategy, which is applicable in real-time management with limited available data, is fairly as efficient as a dynamic pricing scheme obtained from system optimum conditions and a global optimization with full information about the future states of the system. Stackelberg equilibrium is also investigated in a competitive behavior between different parking facility operators. Policy indications on on-street storage capacity management and pricing are provided.

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Urban network gridlock: Theory, characteristics, and dynamics

Cited by 175 publications

References 19 publications

A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks

A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks

Perimeter and boundary flow control in multi-reservoir heterogeneous networks

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

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