Joint route guidance and demand management for multi-region traffic networks

Menelaou, C.; Timotheou, Stelios; Kolios, Panayiotis; Panayiotou, Christos G.

doi:10.23919/ecc.2019.8795819

Cited by 9 publications

(9 citation statements)

References 18 publications

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“…The problem definition in this work differs from other papers, such as, [8], [21], in which they also take into consideration the origin and destination of vehicles. In this paper, the total aggregated demands and accumulation of vehicles are considered, information which is lower-level and easier to obtain and to work with in the macroscopic model.…”

Section: Problem Formulationmentioning

confidence: 99%

“…In order to maintain each region at an equilibrium point, previous work tried to develop strategies to control (i) the incoming traffic from outside of the network, and (ii) the transfer flows between regions (inter-transfers). Very recently, [8] proposed a demand management strategy restricting the amount of vehicles allowed to enter the network, combined with route guidance using MPC. In the literature of traffic control, nonlinear control algorithms based on MPC are widely used (see, for example, [9]) and applied to appropriate cost functions optimizing the states of the network [10] [11].…”

Section: Introductionmentioning

confidence: 99%

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Centralized and Distributed Multi-Region Traffic Flow Control

Boufous¹,

Roncoli²,

Charalambous³

2020

2020 European Control Conference (ECC)

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In this paper, centralized and distributed multiregion perimeter flow control approaches are proposed for congestion avoidance in urban networks. First, multi-region network dynamics are modeled with Macroscopic Fundamental Diagrams (MFDs) and necessary stability conditions are derived using Lyapunov stability theory for a centralized perimeter controller. Later, an optimization problem is formulated, solved and the desired optimal states are reached by means of an algorithm based on Model Predictive Control (MPC). Finally, the paper combines the centralized controller for perimeter control as a first layer controller and a distributed controller managing the inter-transfers between regions, thus optimizing the overall state of the network. Simulations show that the distributed control scheme leads to good results maximizing the output of the traffic network, similar to the MPC controller.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Centralized and Distributed Multi-Region Traffic Flow Control

Boufous¹,

Roncoli²,

Charalambous³

2020

2020 European Control Conference (ECC)

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“…To relieve the network from congestion, the density of each region should be maintained below the critical value [8]. Motivated by this insight, the work presented in [4] introduces route guidance with demand management to ensure a congestion-free operation.…”

Section: Background and Related Workmentioning

confidence: 99%

“…In this paper, demand management occurs through the regulation of traffic inflow inside a network, e.g., through a route reservation scheme [2], [3], to significantly reduce traffic congestion. Our recent work in [4] investigates a novel regional-level MPC scheme that jointly integrates route guidance with demand management and formulates a Mixed Integer Linear Program (MILP) problem in order to schedule vehicle flows through multi-region networks. The resulting formulation assumes that all routes for each origindestination pair have a constant length.…”

Section: Introductionmentioning

confidence: 99%

Path-based joint demand management and route guidance for multi-region traffic networks

Menelaou

Timotheou

Kolios

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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This work investigates the joint optimization problem of demand management and route guidance to minimize the total travel time of vehicles in traffic networks characterized by well-defined regional fundamental diagrams. To account for variable route length, a path-based regional traffic flow model is introduced which enables the routing of vehicles through multiple paths. Within this modeling framework, route guidance aims to reduce the density imbalances observed within each region by splitting the demand flows of arbitrary origin-destination pairs among a set of preselected paths. At the same time, demand management regulates access to the network by delaying the journey starting time of individual vehicles. For the solution of the considered problem, a Model Predictive Approach (MPC) is proposed which aims towards minimizing the total time that vehicles spend in the network while maintaining noncongested conditions at all times through demand management. A relaxed linear programming formulation of the original non-convex, non-linear problem is also proposed which provides tight lower bound to the optimal solution. Extensive simulation results show the importance of demand management in minimizing the total travel time and demonstrate the effectiveness of the proposed MPC approach, as it provides fast and very-close to optimal results for all considered scenarios.

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“…Many clustering algorithms have been developed in order to determine small regions where there is small variance in density and an NFD can be generated [9][10][11][12][13][14][15]. With the determination of multi-region networks, researchers developed multi-region controllers [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Network Perimeter Control

Bichiou

Elouni

Abdelghaffar

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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Urban traffic congestion is a chronic problem faced by many cities in the US and worldwide. It results in inefficient infrastructure use as well as increased vehicle fuel consumption and emission levels. Congestion is intertwined with delay, as road users waste precious hours on the road, which in turn reduces productivity. Researchers have developed, and continue to develop, tools and systems to alleviate this problem. Network perimeter control is one such tool that has been studied extensively. It attempts to control the flow of vehicles entering a protected area to ensure that the congested regime predetermined by the Network Fundamental Diagram (NFD) is not reached. In this paper, an approach derived from sliding mode control theory is presented. Its main advantages over proportional-integral controllers include (1) minimal tuning, (2) no linearization of the governing equations, (3) no assumptions with regard to the shape of the NFD, and (4) ability to handle various demand profiles without the need to retune the controller. A sliding mode controller was implemented and tested on a congested grid network. The results show that the proposed controller produces network-wide delay savings and disperses congestion effectively.Index Terms-Network fundamental diagram, network perimeter control, sliding mode control, traffic signal control

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Joint route guidance and demand management for multi-region traffic networks

Cited by 9 publications

References 18 publications

Centralized and Distributed Multi-Region Traffic Flow Control

Centralized and Distributed Multi-Region Traffic Flow Control

Path-based joint demand management and route guidance for multi-region traffic networks

Sliding Mode Network Perimeter Control

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