The Experts below are selected from a list of 258 Experts worldwide ranked by ideXlab platform
Sherif Ishak - One of the best experts on this subject based on the ideXlab platform.
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Genetic Algorithm–Based Approach for Optimal Deployment of Roadside Units in Connected and Automated Vehicle Environments
Transportation Research Record: Journal of the Transportation Research Board, 2016Co-Authors: Osama A. Osman, Sherif IshakAbstract:Traffic management strategies play a critical role in connected and auto-mated vehicle (CV/AV) environments in which vehicles will be the pri-mary source of traffic information. In CV/AV environments, traffic data are collected from vehicles, and decisions are made at the transportation management centers (TMCs) and communicated back to vehicles via deployed roadside units (RSUs). This process poses a challenge at the early deployment stages of the technology because of the anticipated low market penetration. Under such conditions, RSUs must be optimally located throughout the network to provide continuity and expand the coverage of vehicle-to-vehicle communication systems. This study pre-sents a genetic algorithm–based approach for determining the optimal locations of RSUs by maximizing the connectivity Robustness Measure, by taking into consideration vehicle clustering (groups of vehicles in transmission range of each other), network size, and other factors. Traf-fic simulation data were generated from a microscopic simulation plat-form (VISSIM) and used to test the proposed approach for different penetration rates. The results show that the proposed approach identi-fied locations where more vehicles can communicate. The optimized RSU locations enabled communication between more vehicles in the network, which was identified by the increased Robustness of connectivity. This aspect can maximize the amount of exchanged information between vehicles and the RSUs. Consequently, better traffic monitoring can be achieved by collecting more representative data of the traffic conditions in the network. Thus, optimal decisions, such as vehicle rerouting, are made at the TMCs and disseminated to as many vehicles as possible, which helps in achieving better management. Connected and automated vehicle (CV/AV) technology is a rapidly emerging, promising, challenging, and self-organized technology that will take place in the very near future. It aims at using safety and operation information from moving vehicles in the network to have a highly operable and safe transportation environment. In environ-ments with this technology, the information transmission takes place between vehicles with high mobility and limited degrees of freedom, as determined by the transportation network and surrounding vehicles. Therefore, a highly efficient and dynamic broadcasting protocol that guarantees a high connectivity is required. In that context, many studies were conducted to develo…
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a network level connectivity Robustness Measure for connected vehicle environments
Transportation Research Part C-emerging Technologies, 2015Co-Authors: Osama A. Osman, Sherif IshakAbstract:This study introduces a new CONnectivity Robustness model (CONROB) to assess vehicle-to-vehicle communication in connected vehicle (CV) environments. CONROB is based on Newton’s universal law of gravitation and accounts for multiple factors affecting the connectivity in CV environments such as market penetration, wireless transmission range, spatial distribution of vehicles relative to each other, the spatial propagation of the wireless signal, and traffic density. The proposed methodology for the connectivity Robustness calculation in CONROB accounts for the Link Expiration Time (LET) and the Route Expiration Time (RET) that are reflected in the stability of links between each two adjacent vehicles and the expiration time of communication routes between vehicles. Using a 117 sq-km (45-square mile) network in Washington County, located west of Portland city, Oregon, a microscopic simulation model (VISSIM) was built to verify CONROB model. A total of 45 scenarios were simulated for different traffic densities generated from five different traffic demand levels, three levels of market penetration (5%, 15%, and 25%), and three transmission range values [76 (250), 152 (500), and 305 (1000) m (ft)]. The simulation results show that the overall Robustness increases as the market penetration increases, given the same transmission range, and relative traffic density. Similarly, the overall connectivity Robustness increases as the relative traffic density increases for the same market penetration. More so, the connectivity Robustness becomes more sensitive to the relative traffic density at higher values of transmission range and market penetration. Multiple regression analysis was conducted to show the significant effect of relative traffic density, transmission range, and market penetration on the Robustness Measure. The results of the study provide an evidence of the ability of the model to capture the effect of the different factors on the connectivity between vehicles, which provides a viable tool for assessing CV environments.
Osama A. Osman - One of the best experts on this subject based on the ideXlab platform.
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Genetic Algorithm–Based Approach for Optimal Deployment of Roadside Units in Connected and Automated Vehicle Environments
Transportation Research Record: Journal of the Transportation Research Board, 2016Co-Authors: Osama A. Osman, Sherif IshakAbstract:Traffic management strategies play a critical role in connected and auto-mated vehicle (CV/AV) environments in which vehicles will be the pri-mary source of traffic information. In CV/AV environments, traffic data are collected from vehicles, and decisions are made at the transportation management centers (TMCs) and communicated back to vehicles via deployed roadside units (RSUs). This process poses a challenge at the early deployment stages of the technology because of the anticipated low market penetration. Under such conditions, RSUs must be optimally located throughout the network to provide continuity and expand the coverage of vehicle-to-vehicle communication systems. This study pre-sents a genetic algorithm–based approach for determining the optimal locations of RSUs by maximizing the connectivity Robustness Measure, by taking into consideration vehicle clustering (groups of vehicles in transmission range of each other), network size, and other factors. Traf-fic simulation data were generated from a microscopic simulation plat-form (VISSIM) and used to test the proposed approach for different penetration rates. The results show that the proposed approach identi-fied locations where more vehicles can communicate. The optimized RSU locations enabled communication between more vehicles in the network, which was identified by the increased Robustness of connectivity. This aspect can maximize the amount of exchanged information between vehicles and the RSUs. Consequently, better traffic monitoring can be achieved by collecting more representative data of the traffic conditions in the network. Thus, optimal decisions, such as vehicle rerouting, are made at the TMCs and disseminated to as many vehicles as possible, which helps in achieving better management. Connected and automated vehicle (CV/AV) technology is a rapidly emerging, promising, challenging, and self-organized technology that will take place in the very near future. It aims at using safety and operation information from moving vehicles in the network to have a highly operable and safe transportation environment. In environ-ments with this technology, the information transmission takes place between vehicles with high mobility and limited degrees of freedom, as determined by the transportation network and surrounding vehicles. Therefore, a highly efficient and dynamic broadcasting protocol that guarantees a high connectivity is required. In that context, many studies were conducted to develo…
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a network level connectivity Robustness Measure for connected vehicle environments
Transportation Research Part C-emerging Technologies, 2015Co-Authors: Osama A. Osman, Sherif IshakAbstract:This study introduces a new CONnectivity Robustness model (CONROB) to assess vehicle-to-vehicle communication in connected vehicle (CV) environments. CONROB is based on Newton’s universal law of gravitation and accounts for multiple factors affecting the connectivity in CV environments such as market penetration, wireless transmission range, spatial distribution of vehicles relative to each other, the spatial propagation of the wireless signal, and traffic density. The proposed methodology for the connectivity Robustness calculation in CONROB accounts for the Link Expiration Time (LET) and the Route Expiration Time (RET) that are reflected in the stability of links between each two adjacent vehicles and the expiration time of communication routes between vehicles. Using a 117 sq-km (45-square mile) network in Washington County, located west of Portland city, Oregon, a microscopic simulation model (VISSIM) was built to verify CONROB model. A total of 45 scenarios were simulated for different traffic densities generated from five different traffic demand levels, three levels of market penetration (5%, 15%, and 25%), and three transmission range values [76 (250), 152 (500), and 305 (1000) m (ft)]. The simulation results show that the overall Robustness increases as the market penetration increases, given the same transmission range, and relative traffic density. Similarly, the overall connectivity Robustness increases as the relative traffic density increases for the same market penetration. More so, the connectivity Robustness becomes more sensitive to the relative traffic density at higher values of transmission range and market penetration. Multiple regression analysis was conducted to show the significant effect of relative traffic density, transmission range, and market penetration on the Robustness Measure. The results of the study provide an evidence of the ability of the model to capture the effect of the different factors on the connectivity between vehicles, which provides a viable tool for assessing CV environments.
Konstantin Turitsyn - One of the best experts on this subject based on the ideXlab platform.
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a Robustness Measure of transient stability under operational constraints in power systems
IEEE Control Systems Letters, 2018Co-Authors: Liviu Aolaritei, Thanh Long Vu, Konstantin TuritsynAbstract:The aggressive integration of distributed renewable sources is changing the dynamics of the electric power grid in an unexpected manner. As a result, maintaining conventional performance specifications, such as transient stability, may not be sufficient to ensure its reliable operation in stressed conditions. In this letter, we introduce a novel criteria in transient stability with consideration of operational constraints over frequency deviation and angular separation. In addition, we provide a Robustness Measure of the region of attraction, which can quantify the ability of the post-fault system to remain synchronized even under disturbances. To assess this new stability specification, we adopt the notion of input-to-state stability to the context of power systems and introduce a new class of convex Lyapunov functions, which will result in tractable convex-optimization-based stability certificates. As a result, we are able to quantify the level of disturbance a power system can withstand while maintaining its safe operation. We illustrate the introduced stability specification and certificate on the IEEE 9 bus system.
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a Robustness Measure of transient stability under operational constraints in power systems
arXiv: Optimization and Control, 2018Co-Authors: Liviu Aolaritei, Thanh Long Vu, Konstantin TuritsynAbstract:The aggressive integration of distributed renewable sources is changing the dynamics of the electric power grid in an unexpected manner. As a result, maintaining normal performance specifications, such as transient stability, may not be sufficient to ensure its reliable operation in stressed conditions. In this paper, we introduce a stability criteria in transient stability with consideration of operational constraints over frequency deviation and angular separation. In addition, we provide a Robustness Measure of the region of attraction, which can quantify the ability of the post-fault system to remain synchronized even under disturbances. To assess this new stability specification, we adopt the Input-to-State Stability (ISS) to the context of power system and introduce a new class of convex Lyapunov functions. This class of Lyapunov functions will result in tractable convex-optimization-based stability certificates. As a result, we are able to quantify the level of disturbance a power system can withstand while maintaining its safe operation. We illustrate the introduced stability specification and certificate on a IEEE 9 bus test case.
Imme Ebert-uphoff - One of the best experts on this subject based on the ideXlab platform.
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ICRA - Disturbance Robustness Measures for underconstrained cable-driven robots
Proceedings 2006 IEEE International Conference on Robotics and Automation 2006. ICRA 2006., 2006Co-Authors: P. Bosscher, Imme Ebert-uphoffAbstract:This paper investigates the Robustness of underconstrained cable-driven robots to external disturbance wrenches (force/moment combinations). Two cases are considered: impulsive disturbance wrenches and static (constant) disturbance wrenches. In the analysis of these cases a mapping to an intermediate space is introduced, which allows a restatement of Gauss' principle of least constraint in a simpler form. Two Measures are developed: the impulsive disturbance Robustness Measure and the static disturbance Robustness Measure. It is then shown that these two Measures can be expressed as a single disturbance Robustness Measure, R. This single Measure enables underconstrained cable robots to be designed for maximum Robustness to both impulsive and static disturbances
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Disturbance Robustness Measures and wrench-feasible workspace generation techniques for cable-driven robots
2004Co-Authors: P. Bosscher, Imme Ebert-uphoffAbstract:Cable robots are a type of robotic manipulator that has recently attracted interest for large workspace manipulation tasks. Cable robots are relatively simple in form, with multiple cables attached to a mobile platform or end-effector. The end-effector is manipulated by motors that can extend or retract the cables. Cable robots have many desirable characteristics, including low inertial properties, high payload-to-weight ratios, potentially vast workspaces, transportability, ease of disassembly/reassembly, reconfigurability and economical construction and maintenance. However, relatively few analytical tools are available for analyzing and designing these manipulators. This thesis focuses on expanding the existing theoretical framework for the design and analysis of cable robots in two areas: disturbance Robustness and workspace generation. Underconstrained cable robots cannot resist arbitrary external disturbances acting on the end-effector. Thus a disturbance Robustness Measure for general underconstrained single-body and multi-body cable robots is presented. This Measure captures the Robustness of the manipulator to both static and impulsive disturbances. Additionally, a wrench-based method of analyzing cable robots has been developed and is used to formulate a method of generating the Wrench-Feasible Workspace of cable robots. This workspace consists of the set of all poses of the manipulator where a specified set of wrenches (force/moment combinations) can be exerted. For many applications the Wrench-Feasible Workspace constitutes the set of all usable poses. The concepts of Robustness and workspace generation are then combined to introduce a new workspace: the Specified Robustness Workspace. This workspace consists of the set of all poses of the manipulator that meet or exceed a specified Robustness value.
Bo An - One of the best experts on this subject based on the ideXlab platform.
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A simulation framework for measuring Robustness of incentive mechanisms and its implementation in reputation systems
Autonomous Agents and Multi-Agent Systems, 2016Co-Authors: Jie Zhang, Bo AnAbstract:In game theoretical analysis of incentive mechanisms, all players are assumed to be rational. Since it is likely that mechanism participants in the real world may not be fully rational, such mechanisms may not work as effectively as in the idealized settings for which they were designed. Therefore, it is important to evaluate the Robustness of incentive mechanisms against various types of agents with bounded rational behaviors. Such evaluations would provide us with the information needed to choose mechanisms with desired properties in real environments. In this article, we first propose a general Robustness Measure, inspired by research in evolutionary game theory, as the maximal percentage of invaders taking non-equilibrium strategies such that the agents sustain the desired equilibrium strategy. We then propose a simulation framework based on evolutionary dynamics to empirically evaluate the equilibrium Robustness. The proposed simulation framework is validated by comparing the simulated results with the analytical predictions based on a modified simplex analysis approach. Finally, we implement the proposed simulation framework for evaluating the Robustness of incentive mechanisms in reputation systems for electronic marketplaces. The results from the implementation show that the evaluated mechanisms have high Robustness against a certain non-equilibrium strategy, but is vulnerable to another strategy, indicating the need for designing more robust incentive mechanisms for reputation management in e-marketplaces.
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a practical Robustness Measure of incentive mechanisms
Adaptive Agents and Multi-Agents Systems, 2014Co-Authors: Jie Zhang, Bo AnAbstract:In this abstract, we propose a general Robustness definition for a desired equilibrium and a practical Robustness Measure against a non-equilibrium strategy, inspired by the studies of evolutionary game theory. We also propose a framework to quantitatively evaluate the Robustness and provide theoretical analysis of the framework.
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AAMAS - A practical Robustness Measure of incentive mechanisms
2014Co-Authors: Jie Zhang, Bo AnAbstract:In this abstract, we propose a general Robustness definition for a desired equilibrium and a practical Robustness Measure against a non-equilibrium strategy, inspired by the studies of evolutionary game theory. We also propose a framework to quantitatively evaluate the Robustness and provide theoretical analysis of the framework.
