Exploiting the fundamental diagram of urban networks for feedback-based gating

Keyvan‐Ekbatani, Mehdi; Kouvelas, Anastasios; Papamichail, Ioannis; Papageorgiou, Markos

doi:10.1016/j.trb.2012.06.008

Cited by 415 publications

(241 citation statements)

References 18 publications

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“…The outcome of this optimization does not provide the exact phase settings for traffic signals in the boundary between the two regions. Nevertheless, recent work for single (Keyvan-Ekbatani et al, 2012) and multiple regions (Aboudolas and Geroliminis, 2013) provide the necessary tools to dynamically change the signal settings to meet the controllers' inputs u 12 and u 21 from the aggregated optimization. In case that local queues are developed in the proximity of the controllers (ramps and boundaries between urban regions), analysis of Geroliminis and Boyacı (2012) can identify signal parameters in the individual regions of a city in such a way to move traffic smoothly at the desired flows, without concentrating a large number of vehicles at the boundaries of the regions.…”

Section: Discussionmentioning

confidence: 99%

“…one can apply the proposed scheme on Yokohama network that experiences a well-defined MFD (as was found in Geroliminis and Daganzo (2008)) or Buisson and Ladier (2009), (II) simulation-based plant, e.g. using micro-simulations of the San-Francisco business district center presented in Geroliminis and Daganzo (2007), Ji et al (2010) or Keyvan-Ekbatani et al (2012), and (III) model-based plant, e.g. Geroliminis et al (2013) and Daganzo (2007).…”

Section: Solution Approach -An Mpc Controllermentioning

confidence: 99%

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Cooperative traffic control of a mixed network with two urban regions and a freeway

Haddad

Ramezani

Geroliminis

2013

Transportation Research Part B: Methodological

235

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a b s t r a c tCurrently most optimization methods for urban transport networks (i) are suited for networks with simplified dynamics that are far from real-sized networks or (ii) apply decentralized control, which is not appropriate for heterogeneously loaded networks or (iii) investigate good-quality solutions through micro-simulation models and scenario analysis, which make the problem intractable in real time. In principle, traffic management decisions for different sub-systems of a transport network (urban, freeway) are controlled by operational rules that are network specific and independent from one traffic authority to another. In this paper, the macroscopic traffic modeling and control of a large-scale mixed transportation network consisting of a freeway and an urban network is tackled. The urban network is partitioned into two regions, each one with a well-defined Macroscopic Fundamental Diagram (MFD), i.e. a unimodal and low-scatter relationship between region density and outflow. The freeway is regarded as one alternative commuting route which has one on-ramp and one off-ramp within each urban region. The urban and freeway flow dynamics are formulated with the tool of MFD and asymmetric cell transmission model, respectively. Perimeter controllers on the border of the urban regions operating to manipulate the perimeter interflow between the two regions, and controllers at the on-ramps for ramp metering are considered to control the flow distribution in the mixed network. The optimal traffic control problem is solved by a Model Predictive Control (MPC) approach in order to minimize total delay in the entire network. Several control policies with different levels of urban-freeway control coordination are introduced and tested to scrutinize the characteristics of the proposed controllers. Numerical results demonstrate how different levels of coordination improve the performance once compared with independent control for freeway and urban network. The approach presented in this paper can be extended to implement efficient real-world control strategies for large-scale mixed traffic networks.

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Section: Discussionmentioning

confidence: 99%

Section: Solution Approach -An Mpc Controllermentioning

confidence: 99%

Cooperative traffic control of a mixed network with two urban regions and a freeway

Haddad

Ramezani

Geroliminis

2013

Transportation Research Part B: Methodological

235

View full text Add to dashboard Cite

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“…The most classic method was developed by Ji and Geroliminis [19] that divided the entire network according to the congestion feature [20,21], and then the dynamic division problem was also studied. Keyvan-Ekbatani et al [22] studied the feedback gate control method using the simulation network with perimeter gate control and obtained satisfying results with lower total travel time. Aboudolas and Geroliminis [23] used multireservoir networks with well-defined MFDs to design the perimeter and boundary flow control schemes that aimed at distributing the accumulation of vehicles in each reservoir as homogeneously as possible.…”

Section: Introductionmentioning

confidence: 99%

A Two-Layer Network Dynamic Congestion Pricing Based on Macroscopic Fundamental Diagram

Wei

Sun

2018

Journal of Advanced Transportation

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Dynamic congestion pricing has attracted increasing attentions during the recent years. Nevertheless, limited research has been conducted to address the dynamic tolling scheme at the network level, such as to cooperatively manage two alternative networks with heterogeneous properties, e.g., the two-layer network consisting of both expressway and arterial network in the urban areas. Recently, the macroscopic fundamental diagram (MFD) developed by both field experiments and simulation tests illustrates a unimodal low-scatter relationship between the mean flow and density network widely, providing the network traffic state is roughly homogeneous. It reveals traffic flow properties at an aggregated level and sheds light on dynamic traffic management of a large network. This paper proposes a bilevel programming toll model, incorporating MFD to solve the unbalanced flow distribution problem within the two-layer transportation networks. The upper level model aims at minimizing the total travel time, while the lower level focuses on the MFD-based traffic assignment, which extends the link-based traffic assignment to network wide level. Genetic algorithm (GA) and the method of successive average were adopted for solving the proposed model, on which an online experimental platform was established using VISSIM, MATLAB, and Visual Studio software packages. The results of numerical studies demonstrate that the total travel time is decreased by imposing the dynamic toll, while the total travel time savings significantly outweigh the toll paid. Consequently, the proposed dynamic toll scheme is believed to be effective from both traffic and economic points of view.

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“…For alleviating this problem, a Proportional-Integral (PI) controller is proposed by Keyvan-Ekbatani et al (2012) for real-time gating, with an application to the network of Chania, Greece. By modeling the dynamics of the external queues, a perimeter problem is solved via a Nonlinear MPC formulation in Csikós et al (2015).…”

Section: Introductionmentioning

confidence: 99%

Network traffic flow optimization under performance constraints

Csikós

Charalambous

Farhadi

et al. 2017

Transportation Research Part C: Emerging Technologies

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In this paper, a model-based perimeter control policy for large-scale urban vehicular networks is proposed. Assuming a homogeneously loaded vehicle network and the existence of a well-posed Network Fundamental Diagram (NFD), we describe a protected network throughout its aggregated dynamics including nonlinear exit ow characteristics. Within this framework of constrained optimal boundary ow gating, two main performance metrics are considered: (a) rst, connected to the NFD, the concept of average network travel time and delay as a performance metric is de ned;(b) second, at boundaries, we take into account additional external network queue dynamics governed by uncontrolled in ow demands. External queue capacities in terms of nite-link lengths are used as the second performance metric. Hence, the corresponding performance requirement is an upper bound of external queues. While external queues represent vehicles waiting to enter the protected network, internal queue describes the protected network's aggregated behaviour.By controlling the number of vehicles joining the internal queue from the external ones, herewith a network tra c ow maximization solution subject to the internal and external dynamics and their performance constraints is developed. The originally non-convex optimization problem is transformed to a numerically e ciently convex one by relaxing the performance constraints into time-dependent state boundaries. The control solution can be 1 interpreted as a mechanism which transforms the unknown arrival process governing the number of vehicles entering the network to a regulated process, such that prescribed performance requirements on travel time in the network and upper bound on the external queue are satis ed. Comparative numerical simulation studies on a microscopic tra c simulator are carried out to show the bene ts of the proposed method.

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Exploiting the fundamental diagram of urban networks for feedback-based gating

Cited by 415 publications

References 18 publications

Cooperative traffic control of a mixed network with two urban regions and a freeway

Cooperative traffic control of a mixed network with two urban regions and a freeway

A Two-Layer Network Dynamic Congestion Pricing Based on Macroscopic Fundamental Diagram

Network traffic flow optimization under performance constraints

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