Hesham A. Rakha

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The research presented in this paper develops a framework to enhance vehicle fuel consumption efficiency while approaching a signalized intersection through the provision of signal phase and timing information that may be available through vehicle-to-infrastructure communication. While past research uses simplified objective functions to optimize fuel(More)
Driver route choice is typically modeled using mathematical programming approaches that assume that drivers choose their routes to minimize some objective function, and assume that drivers have perfect, or close to perfect, knowledge of their choice set, as well as the travel characteristics associated with each of the choice elements. It is, however, well(More)
The paper develops a heuristic optimization algorithm for automated vehicles (equipped with cooperative adaptive cruise control CACC systems) at uncontrolled intersections using a game theory framework. The proposed system models the automated vehicles as reactive agents interacting and collaborating with the intersection controller (manager agent) to(More)
Recently several artificial intelligence labs have suggested the use of fully equipped vehicles with the capability of sensing the surrounding environment to enhance roadway safety. As a result, it is anticipated in the future that many vehicles will be autonomous and thus there is a need to optimize the movement of these vehicles. This paper presents a new(More)
The research presented in this paper develops a multi-step traffic state prediction algorithm using spot speed measurements. The traditional Lighthill-Whitham-Richards (LWR) flow continuity equation is combined with the Van Aerde traffic stream model to generate a new partial differential equation (PDE) named the Van Aerde flow continuity model. The(More)
This paper adopts different supervised learning methods from the field of machine learning to develop multiclass classifiers that identify the transportation mode, including driving a car, riding a bicycle, riding a bus, walking, and running. Methods that were considered include K-nearest neighbor, support vector machines (SVMs), and tree-based models that(More)
Researchers have attempted to compute a fuel-optimal vehicle trajectory by receiving traffic signal phasing and timing information. This problem, however, is complex when microscopic models are used to compute the objective function. This paper suggests use of a multi-stage dynamic programming tool that not only provides outputs that are closer to optimum,(More)
The study estimates the energy and air quality impacts of route choice decisions using various fuel consumption and emission models with second-by-second floating-car GPS data. The study investigates two routes: a faster and longer highway route and a slower and shorter arterial route. The study demonstrates that the faster highway route choice is not(More)
Notice This document is disseminated under the sponsorship of the Department of Transportation in the interest of information exchange. The United States Government assumes no liability for its contents or use thereof. Abstract This report concentrates on a velocity advisory tool, or decision support system, for vehicles approaching an intersection using(More)