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Integrated control of road networks with model predictive control

Project members:  hhellendoorn, prof. B. De Schutter, A. Hegyi
 
Keywords:  Model predictive control, Identification and estimation, Transportation and infrastructure, Model-based control, Old - project will be removed
 
Sponsored by:  BSIK-TRANSUMO
 
This project is part of the BSIK-TRANSUMO ATMA (Advanced Traffic Management) project and aims at further developing and applying advanced model-based predictive traffic control techniques with practical implementation and assessment in a real-life case study or field test as the ultimate goal.

The theoretical basis of the contribution is the work of Papageorgiou on optimal traffic control and the work of Hegyi, De Schutter and Hellendoorn on model predictive traffic control. More specifically, in the PhD work of Hegyi a generic on-line, real-time traffic control approach has been developed that uses a traffic flow model in combination with numerical optimization to determine optimal traffic control signal settings, which are then applied to the traffic network using a receding or rolling horizon approach. The approach proposed by Hegyi allows integrated and coordinated network-wide control of various traffic control measures (such as ramp metering, traffic signals, variable speed limits, dynamic route guidance, etc.). Moreover, the approach allows to include various hard constraint s (maximal queue lengths, maximal and minimal metering rates, maximum cycle times, ...), and allows a balanced trade-off between the urban and freeway parts of a network.

The main aim of the proposed research is to further extended this approach so as to make it ready for implementation in practice, and then to really implement and assess this model-based traffic control approach in one of the three test regions of ATMA. In this context some theoretical issues will also have to be addressed, such as stability, robustness, efficient implementation, trade-off issues, adaptive re-estimation and re-identification, and scalability.

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Last modified: 5 July 2013, 15:30 UTC
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