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The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: This study presents a thorough microscopic simulation investigation of a recently developed model-based approach for per-lane density estimation, as well as on-ramp and off-ramp flow estimation, for highways in the presence of connected vehicles. The estimation methodology is mainly based on the assumption that a certain percentage of vehicles is equipped with Vehicle Automation and Communication Systems (VACS), which provide the necessary measurements used by the estimator, namely vehicle speed and position measurements. In addition, a minimum number of conventional flow detectors is needed. In the investigation, a calibrated and validated, with real data, microscopic multi-lane model is employed, which concerns a stretch of motorway A20 from Rotterdam to Gouda in the Netherlands. It is demonstrated that the proposed methodology provides satisfactory estimation performance even for low penetration rates of connected vehicles. Παρουσιάστηκε στο: IEEE 20th International Conference on Intelligent Transportation Systems

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: We propose a feedback control strategy for lane assignment at bottleneck locations, assuming that a percentage of vehicles, equipped with Vehicle Automation and Communication Systems (VACS), are capable of receiving and executing specific lane-changing orders or recommendations. Starting from a previously proposed optimal control strategy, based on a simplified multi-lane motorway traffic flow model and formulated as a linear quadratic regulator, we design a feedback control problem aiming at maximising the throughput at bottleneck locations while distributing, according to a given policy, the total density at the bottleneck area among the different lanes, via optimal lane assignment of vehicles upstream of the bottleneck. The feedback control decisions are based on real-time measurements of the traffic state and inflow. The proposed strategy is tested on a nonlinear first-order macroscopic multi-lane traffic flow model, which also accounts for the capacity drop phenomenon. Παρουσιάστηκε στο: 96th Annual Meeting of the Transportation Research Board

The development and deployment of simple, yet efficient, coordinated and integrated control tools for motorway traffic control remains a challenge. A generic integrated feedback-based motorway traffic flow control concept has been proposed recently by the authors of this paper. It is based on the combination and suitable extension of control algorithms and tools proposed or deployed in other studies, such as ramp metering or VSL (Variable Speed Limit)-enabled cascade-feedback mainstream traffic flow control, and allows for consideration of multiple bottlenecks. The new controller enables coordination of ramp metering actions at a series of on-ramps, as well as integration with VSL control actions towards a common control goal, which is bottleneck throughput maximization. While doing this, the approach considers a pre-specified (desired) balancing of the incurred delays upstream of the employed actuators, via a suitably designed knapsack problem. Despite the multitude of the offered configurations, options andpossibilities, the generic control algorithm remains simple, efficient and suitable for field implementation. The control algorithm is demonstrated and evaluated using validated macroscopic traffic flow models for two case studies and for a number of different scenarios.

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: This paper proposes a freeway traffic controller with the objective of minimizing, at the same time, congestion phenomena and traffic emissions. A multi-class framework is considered in the paper, i.e two classes of vehicles (cars and trucks) are explicitly modelled and specific control actions for each vehicle class are computed. The controller is based on the formulation and solution of a constrained discretetime nonlinear optimal control problem for which a specific solution algorithm, the feasible direction algorithm, is used. The effectiveness of the proposed approach is shown and discussed in the paper by means of some simulation results. Παρουσιάστηκε στο: 14th Annual European Control Conference

openaire: EC/H2020/856602/EU//FINEST TWINS Evaluating potential of shifting to low-carbon transport modes requires considering limited travel-time budget of travelers. Despite previous studies focusing on time-relevant modal shift, there is a lack of integrated and transferable computational frameworks, which would use emerging smartphone-based high-resolution longitudinal travel datasets. This research explains and illustrates a computational framework for this purpose. The proposed framework compares observed trips with computed alternative trips and estimates the extent to which alternatives could reduce carbon emission without a significant increase in travel time. The framework estimates potential of substituting observed car and public-transport trips with lower-carbon modes, evaluating parameters per individual traveler as well as for the whole city, from a set of temporal and spatial viewpoints. The illustrated parameters include the size and distribution of modal shifts, emission savings, and increased active-travel growth, as clustered by target mode, departure time, trip distance, and spatial coverage throughout the city. Parameters are also evaluated based on the frequently repeated trips. We evaluate usefulness of the method by analyzing door-to-door trips of a few hundred travelers, collected from smartphone traces in the Helsinki metropolitan area, Finland, during several months. The experiment's preliminary results show that, for instance, on average, 20% of frequent car trips of each traveler have a low-carbon alternative, and if the preferred alternatives are chosen, about 8% of the carbon emissions could be saved. In addition, it is seen that the spatial potential of bike as an alternative is much more sporadic throughout the city compared to that of bus, which has relatively more trips from/to city center. With few changes, the method would be applicable to other cities, bringing possibly different quantitative results. In particular, having more thorough data from large number of participants could provide implications for transportation researchers and planners to identify groups or areas for promoting mode shift. Finally, we discuss the limitations and lessons learned, highlighting future research directions.

Nikolaos Bekiaris-Liberis was supported by the funding from the European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 747898, project PADECOT. Claudio Roncoli and Markos Papageorgiou were supported by the funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007- 2013) / ERC Grant Agreement n. [321132], project TRAMAN21. Summarization: We develop a predictor-based adaptive cruise control design with integral action (based on a nominal constant time-headway policy) for compensation of long actuator and sensor delays in vehicular systems utilizing measurements of the relative spacing as well as of the speed and the short-term history of the desired acceleration of the ego vehicle. Employing an input-output approach we show that the predictor-based adaptive cruise control law with integral action guarantees all of the four typical performance specifications of adaptive cruise control designs, namely, (1) stability, (2) zero steady-state spacing error, (3) string stability, and (4) non-negative impulse response, despite the long input delay. The effectiveness of the developed control design is illustrated in simulation considering various performance metrics. Παρουσιάστηκε στο: 15th IFAC Symposium on Control in Transportation Systems CTS 2018

Nikolaos Bekiaris-Liberis was supported by the funding from the European Commission’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747898, project PADECOT. Summarization: Considering the target of an operating effectively transportation system, we propose here a novel methodology for integrated lane-changing and ramp metering control that exploits the presence of connected and partly automated vehicles. In particular, we assume that a percentage of vehicles can receive and implement specific control tasks (e.g., lane-changing commands). A novel approach is designed to robustly maximise the throughput at motorway bottlenecks employing a Linear Quadratic Integral (LQI) regulator in combination with an antiwindup scheme, based on a simple Linear Time Invariant (LTI) model. The method is evaluated via simulation experiments, performed on a first-order, multi-lane, macroscopic traffic flow model, also featuring the capacity drop phenomenon, which allows to demonstrate the effectiveness of the developed methodology and to highlight the improvement in terms of traffic efficiency. Presented on

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: The development and deployment of simple, yet efficient, coordinated and integrated control tools for motorway traffic control remains a challenge. A generic integrated feedback-based motorway traffic flow control concept has been proposed recently by the authors of this paper. It is based on the combination and suitable extension of control algorithms and tools proposed or deployed in other studies, such as ramp metering or VSL (Variable Speed Limit)-enabled cascade-feedback mainstream traffic flow control, and allows for consideration of multiple bottlenecks. The new controller enables coordination of ramp metering actions at a series of on-ramps, as well as integration with VSL control actions towards a common control goal, which is bottleneck throughput maximization. While doing this, the approach considers a pre-specified (desired) balancing of the incurred delays upstream of the employed actuators, via a suitably designed knapsack problem. Despite the multitude of the offered configurations, options and possibilities, the generic control algorithm remains simple, efficient and suitable for field implementation. The control algorithm is demonstrated and evaluated using validated macroscopic traffic flow models for two case studies and for a number of different scenarios. Παρουσιάστηκε στο: 8th International Congress on Transportation Research in Greece

This work was supported by the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Advanced Grant Agreement n. 321132, project TRAMAN21. Nikolaos Bekiaris-Liberis was also supported by the European Commission’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement n. 747898, project PADECOT. Summarization: Traffic congestion on motorways is a serious threat for the economic and social life of modern society as well as for the environment, which calls for drastic and radical solutions. Conventional traffic management measures, currently applied, are valuable, but face limitations. During the last decades, a variety of vehicle automation and communication systems (VACS) have been developed and deployed, and many more are expected to appear in the near future. These systems provide a novel basis for a new generation of traffic management, which exploits emerging vehicle automation functions and connectivity channels to enable sensible traffic flow improvements in terms of efficiency and safety. A number of innovative concepts, tools and results that open up new horizons for traffic management research and practice in presence of VACS have been produced recently in the frame of TRAMAN21, an ERC Advanced Grant. This paper presents a collection of novel problems as well as of related traffic flow modelling, estimation and control developments for motorway traffic that can be used in the evolving traffic environment with VACS. Presented on: Annual Reviews in Control

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: A widespread deployment of vehicle automation and communication systems (VACS) is expected in the next years. This may lead to improvements in traffic management efficiency because of the novel possibilities of using VACS both as sensors and as actuators, as well as of a variety of new communications channels (vehicle-to-vehicles, vehicle-to infrastructure) and related opportunities. To achieve this traffic flow efficiency, appropriate studies, developing potential control strategies to exploit the VACS availability, are essential. This paper describes a hierarchical model predictive control framework that can be used for the coordinated and integrated control of a motorway system, considering that an amount of vehicles are equipped with specific VACS. The concept employs and exploits the synergistic (integrated) action of a number of old and new control measures, including ramp metering, vehicle speed control, and lane changing control at a macroscopic level. The effectiveness and the computational feasibility of the proposed approach are demonstrated via microscopic simulation for a variety of penetration rates of equipped vehicles. Presented on

Summarization: Mainstream traffic flow control (MTFC) enabled via variable speed limits (VSLs) has been investigated in previous studies, utilizing various control strategies. In this paper, an extended feedback control strategy is proposed for MTFC enabled via VSLs, considering multiple-bottleneck locations. Feedback-based results are compared with optimal control results for the evaluation of the controller using a validated macroscopic model. The performance of the feedback controller is shown to approach the optimal control results, despite the fact that many practical and safety restrictions are additionally considered by the feedback controller. Presented on: IEEE Transactions on Intelligent Transportation Systems

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: Emerging vehicle automation and communication systems (VACS) may contribute to the mitigation of motorway traffic congestion on the basis of appropriate traffic control strategies. Based on appropriate VACS-based actuators, future traffic control may incorporate vehicle speed control and lane-assignment or lane-changing recommendations. To this end, an appropriate traffic flow model is needed, both for control strategy design and as a no-control base case for comparative evaluation studies. In this context, this paper presents a novel first-order multi-lane macroscopic traffic flow model for motorways which is mainly intended for use within a related optimal control problem formulation. The starting point is close to the well-known cell-transmission model (CTM), which is modified and extended to consider additional aspects of the traffic dynamics, such as lane changing and the capacity drop. The model has been derived with a view to combine realistic traffic flow description with a simple (piecewise linear) mathematical form, which can be exploited for efficient optimal control problem formulations. Although the model has been primarily derived for use in future traffic conditions including VACS, it may also be used for conventional traffic flow representation. In fact, the accuracy of the proposed modelling approach is demonstrated through calibration and validation procedures using conventional real data from an urban motorway located in Melbourne, Australia. Presented on

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: This paper describes a novel approach for defining optimal strategies in motorway traffic flow control, considering that a portion of vehicles are equipped with vehicle automation and communication systems. An optimisation problem, formulated as a Quadratic Programming (QP) problem, is developed with the purpose of minimising traffic congestion. The proposed problem is based on a first-order macroscopic traffic flow model able to capture the lane changing and the capacity drop phenomena. An application example demonstrates the achievable improvements in terms of the Total Time Spent if the vehicles travelling on the motorway are influenced by the control actions computed as a solution of the optimisation problem. Παρουσιάστηκε στο: International Conference on Engineering and Applied Sciences Optimization

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: We present a macroscopic model-based approach for estimation of the total density and flow of vehicles, for the case of “mixed” traffic, i.e., traffic comprising both ordinary and connected vehicles, utilizing only average speed measurements reported by connected vehicles and a minimum number (sufficient to guarantee observability) of spot sensor-based total flow measurements. The approach is based on the realistic assumption that the average speed of conventional vehicles is roughly equal to the average speed of connected vehicles, and consequently, it can be obtained at the (local or central) traffic monitoring and control unit from connected vehicles’ reports. Thus, complete traffic state estimation (for arbitrarily selected segments in the network) may be achieved by estimating the total density of vehicles. Recasting the dynamics of the total density of vehicles, which are described by the well-known conservation law equation, as a linear time-varying system, we employ a Kalman filter for the estimation of the total density. We demonstrate the fact that the developed approach allows a variety of different measurement configurations, by also considering the case in which additional mainstream total flow measurements are employed to replace a corresponding number of total flow measurements at on-ramps or off-ramps. We validate the performance of the developed estimation scheme through simulations using a well-known second-order traffic flow model as ground truth for the traffic state. Παρουσιάστηκε στο: 18th International IEEE Conference on Intelligent Transportation Systems

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: A model-based traffic state estimation approach is developed for per-lane density estimation as well as on-ramp and off-ramp flows estimation for highways in presence of connected vehicles, namely, vehicles that are capable of reporting information to an infrastructure-based system. Three are the basic ingredients of the developed estimation scheme: (1) a data-driven version of the conservation-of-vehicles equation (in its time- and space-discretized form); (2) the utilization of position and speed information from connected vehicles’ reports, as well as total flow measurements obtained from a minimum number (sufficient for the observability of the model) of fixed detectors, such as, for example, at the main entry and exit of a given highway stretch; and (3) the employment of a standard Kalman filter. The performance of the estimation scheme is evaluated for various penetration rates of connected vehicles utilizing real microscopic traffic data collected within the Next Generation SIMulation (NGSIM) program. It is shown that the estimation performance is satisfactory, in terms of a suitable metric, even for low penetration rates of connected vehicles. The sensitivity of the estimation performance to variations of the model parameters (two in total) is also quantified, and it is shown that, overall, the estimation scheme is little sensitive to the model parameters. Παρουσιάστηκε στο: 20th EURO Working Group on Transportation Meeting

Summarization: In this paper we develop a fast model predictive control (MPC) approach for variable speed limit coordination to resolve freeway jam waves. Existing MPC approaches that are based on the second-order traffic flow models suffer from high computation load due to the non-linear and non-convex optimization formulation. In recent years, simplified MPC approaches which are based on discrete first-order traffic flow models have attracted more and more attention because they are beneficial for real-time applications. In literature, the type of traffic jam resolved by these approaches is limited to the standing queue in which the jam head is fixed at the bottleneck. Another type of traffic jam known as the jam wave, has been neglected by the discrete first-order model-based MPC approaches. To fill this gap, we develop a fast MPC approach based on a more accurate discrete first-order model. The model keeps the linear property of the classical discrete first-order model, meanwhile takes traffic flow features of jam waves propagation into consideration. A classical non-linear MPC and a recently proposed linear MPC are compared with the proposed MPC in terms of computation speed and jam wave resolution by a benchmark problem. Simulation results show that the proposed MPC resolves the jam wave with a real-time feasible computation speed. Παρουσιάστηκε στο: Transportation Research Part C: Emerging Technologie

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: A widespread use of vehicle automation and communication systems (VACS) is expected in the next years. This may lead to improvements in traffic management because of the augmented possibilities of using VACS both as sensors and as actuators. To achieve this, appropriate studies, developing potential control strategies to exploit the VACS availability, are essential. This paper describes a model predictive control framework that can be used for the integrated and coordinated control of a motorway system, considering that vehicles are equipped with specific VACS. Microscopic simulation testing demonstrates the effectiveness and the computational feasibility of the proposed approach. Παρουσιάστηκε στο: 17th International IEEE Conference on Intelligent Transportation Systems

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: We propose an optimal feedback control strategy for lane-changing control at bottleneck locations, assuming that a percentage of vehicles, equipped with vehicle automation and communication systems, are capable of receiving and executing specific lane-changing orders or recommendations. Based on a simplified multi-lane motorway traffic flow model, we formulate an optimal feedback control problem, cast as a linear quadratic regulator problem, aiming at maximising the throughput at bottleneck locations, via optimal lane assignment of vehicles upstream of the bottleneck. The feedback control decisions are based on appropriate choice of set-points for traffic densities and real-time measurements of the state of the system. We also present an extremum seeking algorithm to seek the optimal set-points using only the measurement of a cost that is representative of the achieved traffic conditions. The proposed strategy is tested on a nonlinear first-order macroscopic multilane traffic flow model, which accounts also for the capacity drop phenomenon. Παρουσιάστηκε στο: 2016 IEEE 19th International Conference on Intelligent Transportation Systems

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: Vehicle automation and communication systems (VACS) are expected to appear in an increasing amount of vehicles within the next years. Among the wide range of proposed VACS, the ones that include vehicle-to-infrastructure communication capabilities may be exploited both as sensors and as actuators. This enables traffic control centres to obtain more accurate information on the current traffic state and to assign to each vehicle appropriate control tasks, so as to achieve a global traffic flow target. The concept employs and exploits the synergistic (integrated) action of a number of old and new control measures, including ramp metering, vehicle speed control, and lane changing control, at a macroscopic level. The problem is tackled through a Quadratic Programming optimisation problem used as the core of a model predictive control framework. The optimal control actions may be sent directly to vehicles equipped with adaptive cruise control (ACC), affecting directly their cruise speed and, in addition, their lane-changing behaviour. The effectiveness and the computational feasibility of the proposed approach are demonstrated via microscopic simulation for a variety of ACC settings and penetration rates of equipped vehicles. Παρουσιάστηκε στο: 18th meeting of the EURO Working Group on Transportation

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: This paper presents two case studies in which a macroscopic model-based approach for the estimation of traffic conditions, which the authors have recently developed, is employed and tested. The estimation method is developed for a mixed traffic scenario, in which traffic is composed of both ordinary and connected vehicles. Only average speed measurements, which may be obtained from connected vehicle reports, and a minimal number (sufficient to guarantee observability) of spot sensor–based total flow measurements are utilized. In the first case study, NGSIM microscopic data are used to test the capability of estimating traffic conditions on the basis of aggregated information retrieved from moving vehicles and considering various penetration rates of connected vehicles. In the second case study, a longer highway stretch with internal congestion is utilized to test the capability of the proposed estimation scheme to produce appropriate estimates for varying traffic conditions on long stretches. In both cases, the performances are satisfactory and the obtained results demonstrate the effectiveness of the method in both qualitative and quantitative terms. Παρουσιάστηκε στο: Transportation Research Record: Journal of the Transportation Research Board

Μη διαθέσιμη περίληψη Not available summarization Παρουσιάστηκε στο: 20th Conference of the International Federation of Operational Research Societies

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: This study presents an ACC (Adaptive Cruise Control)-based traffic control strategy which aims to adapt in real time the driving behavior of ACC-equipped vehicles to the prevailing traffic conditions so that the motorway traffic flow efficiency is improved. The potential benefits obtained by applying the proposed control concept are demonstrated for different ACC penetration rates by use of validated microscopic simulation applied to a real motorway stretch where recurrent traffic congestion is created due to an on-ramp bottleneck. The simulation results demonstrate that, even for low penetration rates of ACC vehicles, the proposed control concept improves the average vehicle delay and fuel consumption by reducing the space-time extent of congestion compared to the case of only manually driven or regular ACC vehicles. Παρουσιάστηκε στο: 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: We establish sufficient and necessary conditions for the (weak) structural observability as well as the strong structural observability of lane-based highway traffic. Based on these results, we characterize the fixed detector configurations that guarantee the proper operation of a proposed traffic state estimation scheme. The structural observability analyses are based on a data-driven model, which is introduced for the per-lane traffic density dynamics. The proposed model is derived from the well-known conservation law equation via utilization of position and speed information from connected vehicle reports. Παρουσιάστηκε στο: IEEE 20th International Conference on Intelligent Transportation Systems

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: This paper presents two case studies where a macroscopic model-based approach for traffic state estimation, which we have recently developed, is employed and tested. The estimation methodology is developed for a “mixed” traffic scenario, where traffic is composed of both ordinary and connected vehicles. Only average speed measurements, which may be obtained from connected vehicles reports, and a minimum number (sufficient to guarantee observability) of spot sensor-based total flow measurements are utilised. In the first case study, we use NGSIM microscopic data in order to test the capability of estimating the traffic state on the basis of aggregated information retrieved from moving vehicles and considering various penetration rates of connected vehicles. In the second case study, a longer highway stretch with internal congestion is utilised, in order to test the capability of the proposed estimation scheme to produce appropriate estimates for varying traffic conditions on long stretches. In both cases the performances are satisfactory, and the obtained results demonstrate the effectiveness of the methodology, both in qualitative and quantitative terms. Παρουσιάστηκε στο: 95th Annual Meeting of the Transportation Research Board

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: First-order traffic flow models are known for their simplicity and computational efficiency and have, for this reason, been widely used for various traffic engineering tasks. However, first-order models are not able to reproduce significant traffic phenomena of great interest such as the capacity-drop and stop-and-go waves. This paper presents an overview of the, so far, proposed modelling approaches which aim to introduce the capacity-drop phenomenon into first-order traffic flow models. The background and main characteristics of each approach are analyzed with a particular emphasis on the practical applicability of such models for traffic management and control. The presented modelling approaches are calibrated and tested using real data from a motorway network in U.K. Παρουσιάστηκε στο: 95th Annual Meeting of the Transportation Research Board

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: This paper investigates the effectiveness of a Model Predictive Control (MPC) scheme for motorway traffic involving vehicles equipped with Vehicle Automation and Communication Systems (VACS). A stretch of the motorway A20, which connects Rotterdam to Gouda in the Netherlands, is modeled in a microscopic traffic simulation environment. In order to ensure the reliability of the microscopic simulation outcome, the simulation parameters are tuned with the purpose of replicating realistic traffic conditions. The MPC framework is then applied to the calibrated microscopic simulation model aiming at the mitigation of traffic congestion in the case study motorway. The synergistic control measures for coordinated and integrated traffic control are ramp metering, with the use of conventional traffic lights, vehicle speed control, and lane changing control actions that are enabled with the aid of VACS. Παρουσιάστηκε στο: IEEE 20th International Conference on Intelligent Transportation Systems