Solomon Kidane Zegeye

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In this paper we integrate the macroscopic traffic flow model METANET with the microscopic dynamic emission and fuel consumption model VT-Micro. We use the integrated models in the model predictive control (MPC) framework to reduce exhaust emissions, fuel consumption, and travel time using dynamic speed limit control. With simulation experiments we(More)
We present a freeway-traffic control strategy that continuously adapts traffic control measures to prevailing traffic conditions and features faster computation speed than conventional model-based predictive control (MPC). The control approach is based on the principles of state feedback control and MPC. Instead of computing the control input sequence, the(More)
This thesis has been completed in partial fulfillment of the requirements of the Dutch Institute of Systems and Control (DISC) and the Netherlands Research School on Transport, Infrastructure and Logistics (TRAIL) for graduate studies. It is allowed to copy and distribute this work if it is attributed to Solomon Kidane Zegeye, but only for noncommercial(More)
Although traffic congestion is a pressing problem that drivers face every day, improving the traffic flow does not always create a healthy environment to the people residing in the neighborhood of the freeway. Improved traffic flow neither means efficient fuel consumption of the vehicles. Moreover, reduction of total emissions or travel times in a traffic(More)
We present a framework to integrate macroscopic traffic flow models with microscopic emission and fuel consumption models. Since macroscopic traffic flow models do not provide the acceleration as an output, while microscopic emission and fuel consumption models require both the instantaneous speeds and accelerations as input, we describe how to generate(More)
In addition to the challenge to reduce traffic jams, reduction of traffic emissions in such a way that the dispersion of the emissions to residential areas, hospitals, schools, and other neighborhoods is decreased is a problem that requires state-of-the-art traffic control and management solutions. In this paper we model the dispersion of the emissions from(More)
This paper has two main contributions. First, it presents a simple area-wide emission (or dispersion) model for a freeway traffic networks. The model takes the variation of the wind speed and direction into account. Second, it presents a nonlinear parametrized MPC controller for freeway traffic systems. Next, the proposed model and control approach are(More)
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(More)
We propose a traffic control approach that can reduce both traffic emissions and travel times based on model predictive control (MPC). We approximate the traffic flow and emission models into a linear parameter varying (LPV) form, which leads to an LPV-MPC control approach. We consider two objective functions and formulate them as convex functions, so that(More)
In this paper we present a model-based traffic flow control approach to improve both traffic flow and emissions in a traffic network. A model predictive control (MPC) is implemented using a microscopic car-following traffic flow model and an average-speed-based emission model. We consider reduction of total time spent (TTS) and total emissions (TE) as(More)