Multiple Concentric Gating Traffic Control in Large-Scale Urban Networks

Keyvan‐Ekbatani, Mehdi; Yildirimoḡlu, Mehmet; Geroliminis, Nikolas; Papageorgiou, Markos

doi:10.1109/tits.2015.2399303

Cited by 149 publications

(42 citation statements)

References 31 publications

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“…This is important for modeling purposes, as details in individual links are not necessary to describe congestion in cities. It can also be utilized to introduce simple control strategies to improve mobility in multi-region city centers building on the concept of an MFD, like in Ramezani et al (2015) , Keyvan-Ekbatani et al (2015) , Haddad and Shraiber (2014) , and others. A detailed literature review of network modeling and control can be found for instance in Haddad et al (2013) or Mahmassani et al (2013) .…”

Section: Introductionmentioning

confidence: 99%

Clustering of heterogeneous networks with directional flows based on “Snake” similarities

Saeedmanesh

Geroliminis

2016

Transportation Research Part B: Methodological

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196

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a b s t r a c tAggregated network level modeling and control of traffic in urban networks have recently gained a lot of interest due to unpredictability of travel behaviors and high complexity of physical modeling in microscopic level. Recent research has shown the existence of well-defined Macroscopic Fundamental Diagrams (MFDs) relating average flow and density in homogeneous networks. The concept of MFD allows to design real-time traffic control schemes specifically hierarchical perimeter control approaches to alleviate or postpone congestion. Considering the fact that congestion is spatially correlated in adjacent roads and it propagates spatiotemporaly with finite speed, describing the main pockets of congestion in a heterogeneous city with small number of clusters is conceivable. In this paper, we propose a three-step clustering algorithm to partition heterogeneous networks into connected homogeneous regions, which makes the application of perimeter control feasible. The advantages of the proposed method compared to the existing ones are the ability of finding directional congestion within a cluster, robustness with respect to parameters calibration, and its good performance for networks with low connectivity and missing data. Firstly, we start to find a connected homogeneous area around each road of the network in an iterative way (i.e. it forms a sequence of roads). Each sequence of roads, defined as 'snake', is built by starting from a single road and iteratively adding one adjacent road based on its similarity to join previously added roads in that sequence. Secondly, based on the obtained sequences from the first step, a similarity measure is defined between each pair of the roads in the network. The similarities are computed in a way that put more weight on neighboring roads and facilitate connectivity of the clusters. Finally, Symmetric Non-negative Matrix Factorization (SNMF) framework is utilized to assign roads to proper clusters with high intra-similarity and low inter-similarity. SNMF partitions the data by providing a lower rank approximation of the similarity matrix. The proposed clustering framework is applied in medium and large-size networks based on micro-simulation and empirical data from probe vehicles. In addition, the extension of the algorithm is proposed to deal with the networks with sparse measurements where information of some links is missing. The results show the effectiveness and robustness of the extended algorithm applied to simulated network under different penetration rates (percentage of links with data).

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Section: Introductionmentioning

confidence: 99%

Clustering of heterogeneous networks with directional flows based on “Snake” similarities

Saeedmanesh

Geroliminis

2016

Transportation Research Part B: Methodological

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196

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“…Research effort has been made by many researchers, e.g. perimeter flow control for single-mode networks (Aboudolas and Geroliminis, 2013;Keyvan-Ekbatani et al, 2015;Haddad, 2015), and multimodal networks . In addition to online traffic control, studies have shown promising results on demand management with the MFD, as well.…”

Section: Introductionmentioning

confidence: 99%

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

Zheng

Rérat

Geroliminis

2016

Transportation Research Part C: Emerging Technologies

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121

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a b s t r a c tIn this paper, we investigate an area-based pricing scheme for congested multimodal urban networks with the consideration of user heterogeneity. We propose a time-dependent pricing scheme where the tolls are iteratively adjusted through a Proportional-Integral type feedback controller, based on the level of vehicular traffic congestion and traveler's behavioral adaptation to the cost of pricing. The level of congestion is described at the network level by a Macroscopic Fundamental Diagram, which has been recently applied to develop network-level traffic management strategies. Within this dynamic congestion pricing scheme, we differentiate two groups of users with respect to their value-of-time (which related to income levels). We then integrate incentives, such as improving public transport services or return part of the toll to some users, to motivate mode shift and increase the efficiency of pricing and to attain equitable savings for all users. A case study of a medium size network is carried out using an agent-based simulator. The developed pricing scheme demonstrates high efficiency in congestion reduction. Comparing to pricing schemes that utilize similar control mechanisms in literature which do not treat the adaptivity of users, the proposed pricing scheme shows higher flexibility in toll adjustment and a smooth behavioral stabilization in long-term operation. Significant differences in behavioral responses are found between the two user groups, highlighting the importance of equity treatment in the design of congestion pricing schemes. By integrating incentive programs for public transport using the collected toll revenue, more efficient pricing strategies can be developed where savings in travel time outweigh the cost of pricing, achieving substantial welfare gain.

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“…Other studies, such as Aboudolas and Geroliminis (2013); Keyvan-Ekbatani et al (2015); Kouvelas et al (2016) optimize traffic signals at perimeter or boundaries between regions, utilizing micro-simulations where it is possible to change the signal control plan for each individual intersection. Nevertheless, no detailed methodology has been reported nor formulated on the optimization of signal timing allocations at the local level.…”

Section: General Frameworkmentioning

confidence: 99%

Multi-scale perimeter control approach in a connected-vehicle environment

Yang

Zheng

Menéndez

2018

Transportation Research Part C: Emerging Technologies

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This paper proposes a novel approach to integrate optimal control of perimeter intersections (i.e. to minimize local delay) into the perimeter control scheme (i.e. to optimize traffic performance at the network level). This is a complex control problem rarely explored in the literature. In particular, modeling the interaction between the network level control and the local level control has not been fully considered. Utilizing the Macroscopic Fundamental Diagram (MFD) as the traffic performance indicator, we formulate a dynamic system model, and design a Model Predictive Control (MPC) based controller coupling two competing control objectives and optimizing the performance at the local and the network level as a whole. To solve this highly non-linear optimization problem, we employ an approximation framework, enabling the optimal solution of this large-scale problem to be feasible and efficient. Numerical analysis shows that by applying the proposed controller, the protected network can operate around the desired state as expressed by the MFD, while the total delay at the perimeter is minimized as well. Moreover, the paper sheds light on the robustness of the proposed controller. This multi-scale hybrid controller is further extended to a stochastic MPC scheme, where connected vehicles (CV) serve as the only data source. Hence, low penetration rates of CVs lead to strong noises in the controller. This is a first attempt to develop a network-level traffic control methodology by using the emerging CV technology. We consider the stochasticity in traffic state estimation and the shape of the MFD. Simulation analysis demonstrates the robustness of the proposed stochastic controller, showing that efficient controllers can indeed be designed with this newly-spread vehicle technology even in the absence of other data collection schemes (e.g. loop detectors).

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Multiple Concentric Gating Traffic Control in Large-Scale Urban Networks

Cited by 149 publications

References 31 publications

Clustering of heterogeneous networks with directional flows based on “Snake” similarities

Clustering of heterogeneous networks with directional flows based on “Snake” similarities

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

Multi-scale perimeter control approach in a connected-vehicle environment

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