Asservissement Linéaire d'Entrée Autoroutière (ALINEA), a local feedback ramp-metering strategy, has had multiple field applications, and more applications are planned in several European countries. The main features of ALINEA are presented and the field results achieved to date at both single and multiple ramps of the Boulevard Périphérique in Paris and at the A10 West motorway in Amsterdam are summarized. The reported results indicate easy application, flexibility, and high efficiency of ALINEA. Planned implementations are outlined.

(2002) 'Trac ow modeling of large-scale motorway networks using the macroscopic modeling tool METANET.', IEEE transactions on intelligent transportation systems., 3 (4). pp. 282-292. Further information on publisher's website: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract-This paper employs previously developed modeling, validation, and stimulation tools to address, for the first time, the realistic macroscopic simulation of a real large-scale motorway network. More specifically, the macroscopic simulator METANET, involving a second-order traffic flow model as well as network-relevant extensions, is utilized. A rigorous quantitative validation procedure is applied to individual network links, and subsequently a heuristic qualitative validation procedure is employed at a network level. The large-scale motorway network around Amsterdam, The Netherlands, is considered in this investigation. The main goal of the paper is to describe the application approach and procedures and to demonstrate the accuracy and usefulness of macroscopic modeling tools for large-scale motorway networks.

A generic approach to the problem of optimal coordinated ramp metering control in large-scale motorway networks is described that is implemented in the software tool Advanced Motorway Optimal Control. In this approach, the traffic flow process is modeled by use of a secondorder macroscopic traffic flow model. The overall problem of coordinated ramp metering is formulated as a constrained discrete-time nonlinear optimal control problem, and a feasible-direction nonlinear optimization algorithm is employed for its numerical solution. The control strategy’s efficiency is demonstrated through its application to the 32-km long Amsterdam ring road. A number of different scenarios with regard to the number of controlled ramps and the available storage space are discussed in some detail. The results of the presented approach are very promising and demonstrate the high efficiency and general applicability of the optimal control methodology for motorway traffic control problems.

No abstract

In this article a nonlinear model predictive control approach to the problem of coordinated ramp metering is presented. The previously designed optimal control tool Advanced Motorway Optimal Control (AMOC) is used within the framework of a hierarchical control structure which consists of three basic layers: the estimation/prediction layer, the optimization layer, and the direct control layer. More emphasis is given to the last two layers where the control actions on a network-wide and on a local level, respectively, are decided. The hierarchical control strategy combines AMOC's coordinated ramp metering control with local feedback Asservissement LInéaire d'Entré Autoroutière (ALINEA) control in an efficient way. Simulation investigations for the Amsterdam ring-road are reported whereby the results are compared with those obtained by applying ALINEA as a stand-alone strategy. It is shown that the proposed control scheme is efficient, fair, and real-time feasible.