Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/17AEB497-A1A2-43A9-A666-695E242B59A7 | ||
| Year | 2016 | ||
| Type of Item | Master Thesis | ||
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| Bibliographic Citation | Georgia Perraki, "Evaluation of a model predictive control strategy on a calibrated multilane microscopic model", Master Thesis, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2016 https://doi.org/10.26233/heallink.tuc.66973 | ||
| Appears in Collections |
This master thesis investigates the effectiveness of a Model Predictive Control (MPC) scheme applied on a calibrated and validated microscopic multilane model. Microscopic traffic models have become increasingly popular in order to solve design and analysis problems difficult to be studied by other means. Although the simulation models can be useful for engineers, they have to be firstly calibrated and validated in order to ensure that they can lead to meaningful results. A stretch of the freeway A20 which connects Rotterdam to Gouda in the Netherlands is modeled in a microscopic simulator. Speed and flow measurements, collected from the field, are used in order to tune the simulation parameters with the purpose of replicating realistic traffic conditions. Different datasets are used in order to verify that the model reproduces reality under different conditions. An MPC scheme is then applied in the calibrated model aiming at the mitigation of traffic congestion in the case study network. The control strategy is based on the assumption that the vehicles are equipped with Vehicle Automation and Communication Systems (VACS), which offer numerous advantages concerning the actuation possibilities and availability of information.
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