Nonlinear optimization for freeway control using variable-speed signaling

Alessandri, A.; Febbraro, Angela Di; Ferrara, Antonella; Punta, Elisabetta

doi:10.1109/25.806796

Cited by 79 publications

(45 citation statements)

References 16 publications

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“…Overviews of ramp metering methods and results are given in [41,50]. The use of variable speed limits on freeways is described in [2,21,32,49], and the use of route guidance in [11,13,26]. Several authors have described methods for coordinated control of freeways using different traffic control measures [6,19,28,29].…”

Section: The Need For Intelligent Dynamic Traffic Managementmentioning

confidence: 99%

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Model-based Control of Intelligent Traffic Networks

Schutter

Hellendoorn

Hegyi

et al. 2009

Intelligent Infrastructures

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Road traffic networks are increasingly being equipped and enhanced with various sensing, communication, and control units, resulting in an increased intelligence in the network and offering additional handles for control. In this chapter we discuss some advanced model-based control methods for intelligent traffic networks. In particular, we consider model predictive control (MPC) of integrated freeway and urban traffic networks. We present the basic principles of MPC for traffic control including prediction models, control objectives, and constraints. The proposed MPC control approach is modular, allowing the easy substitution of prediction models and the addition of extra control measures or the extension of the network. Moreover, it can be used to obtain a balanced trade-off between various objectives such as throughput, emissions, noise, fuel consumption, etc. Moreover, MPC also allows the integration and network-wide coordination of various traffic control measures such as traffic signals, speed limits, ramp metering, lane closures, etc. We illustrate the MPC approach for traffic control with two case studies. The first case study involves control of a freeway stretch with a balanced trade-off between total time spent, fuel consumption, and emissions as control objective. The second case study has a more complex layout and involves control of a mixed urban-freeway network with total time spent as control objective.

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Section: The Need For Intelligent Dynamic Traffic Managementmentioning

confidence: 99%

“…The outflow of the origin depends on the traffic conditions on the mainstream and, for the metered on-ramp, on the ramp metering rate 2 …”

Section: Freeway Traffic Flow Modelmentioning

confidence: 99%

Model-based Control of Intelligent Traffic Networks

Schutter

Hellendoorn

Hegyi

et al. 2009

Intelligent Infrastructures

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“…Congestion can be dissipated by raising the outflow [17], by limiting the inflow to a traffic jam or shock wave [18,19] or by homogenising the general traffic flow [20,21]. All studies are based on the use of variable speed limit signs and static speed assistance [22,23].…”

Section: Further Perspectivesmentioning

confidence: 99%

Technical Feasibility of Advanced Driver Assistance Systems (ADAS) for Road Traffic Safety

Wevers²,

Heijden³

2005

Transportation Planning and Technology

122

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Technical feasibility of advanced driver assistance systems (ADAS) for road traffic safety.Lu, Meng; Wevers, Kees; Heijden, Rob Van Der General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal

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“…The first emphasizes the homogenization effect [1], [2], [5], [16], [15], whereas the second is more focused on the prevention of traffic breakdown [9], [10], [4]. The idea of homogenization is that speed limits reduce the speed differences between vehicles by which a higher (and safer) flow can be achieved.…”

Section: Introductionmentioning

confidence: 99%

“…Several control methodologies are used in literature to find a control law for speed control, such as multi-layer control [12], sliding-mode control [9], [10], or optimal control [1], [2]. In [5] the optimal control is approximated by a neural network (NN) in a rolling horizon framework.…”

Section: Introductionmentioning

confidence: 99%

Shock wave elimination/reduction by optimal coordination of variable speed limits

Breton

Hegyi

Schutter

et al.

Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems

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Abstract-We present a model predictive control (MPC) approach to optimally coordinate variable speed limits for highway traffic. The basic idea is that dynamic speed limits can create traffic conditions where shock waves can damp out faster. The control objective is to minimize the total time that vehicles spend in the network. For the prediction of the evolution of the traffic flows in the network we use an adapted version of the METANET model that takes the variable speed limits into account. The coordinated control results in a network with less congestion, a higher outflow, and a lower total time spent. In addition, the receding horizon approach of MPC results in an adaptive, on-line control strategy that automatically takes changes in the system parameters into account.

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Nonlinear optimization for freeway control using variable-speed signaling

Cited by 79 publications

References 16 publications

Model-based Control of Intelligent Traffic Networks

Model-based Control of Intelligent Traffic Networks

Technical Feasibility of Advanced Driver Assistance Systems (ADAS) for Road Traffic Safety

Shock wave elimination/reduction by optimal coordination of variable speed limits

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