Solomon Kidane Zegeye

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Model-based traffic control for balanced reduction of fuel consumption, emissions, and travel time, " Pro-Abstract: 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(More)
Reduction of travel times and traffic emissions using model predictive control, " Abstract— 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(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)
In this paper a model-based traffic control is used to design variable speed limits and on-ramp metering rates in order to reduce road traffic generated area-wide emissions near freeways. First an area-wide emission model is proposed and next a nonlinear model predictive control (MPC) approach is applied. The objectives of the MPC controller considered are(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)
based traffic control for the reduction of fuel consumption, emissions, and travel time, " Proceedings of mobil. Abstract In this paper we use a model-based traffic control approach to determine dynamic speed limits with the aim of reducing fuel consumption and emissions, while still guaranteeing small travel times. The approach we propose is based on model(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)
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)