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Articles 1 - 17 of 17
Full-Text Articles in Controls and Control Theory
Understanding Vehicular Traffic Behavior From Video: A Survey Of Unsupervised Approaches, Brendan Tran Morris, Mohan Manubhai Trivedi
Understanding Vehicular Traffic Behavior From Video: A Survey Of Unsupervised Approaches, Brendan Tran Morris, Mohan Manubhai Trivedi
Electrical & Computer Engineering Faculty Research
Recent emerging trends for automatic behavior analysis and understanding from infrastructure video are reviewed. Research has shifted from high-resolution estimation of vehicle state and instead, pushed machine learning approaches to extract meaningful patterns in aggregates in an unsupervised fashion. These patterns represent priors on observable motion, which can be utilized to describe a scene, answer behavior questions such as where is a vehicle going, how many vehicles are performing the same action, and to detect an abnormal event. The review focuses on two main methods for scene description, trajectory clustering and topic modeling. Example applications that utilize the behavioral modeling …
Tunable Fano Resonances Based On Two-Beam Interference In Microring Resonator, Ting Hu, Ping Yu, Chen Qui, Huiye Qui, Fan Wang, Mei Yang, Xiaoqing Jiang, Hui Yu, Jianyi Yang
Tunable Fano Resonances Based On Two-Beam Interference In Microring Resonator, Ting Hu, Ping Yu, Chen Qui, Huiye Qui, Fan Wang, Mei Yang, Xiaoqing Jiang, Hui Yu, Jianyi Yang
Electrical & Computer Engineering Faculty Research
In this paper, a resonant system is demonstrated on silicon-on-insulator wafer to achieve tunable Fano resonances. In this system, the Fano resonance originates from the interference of two beams resonant in the microring resonator. The shapes of the Fano resonances are tunable through controlling the phase difference of the two beams. Both large slope and high extinctionratio (ER) are obtained when the phase difference is 0.5π or 1.5π. Experimental results show that Fano resonances with steep slope and ER over 20 dB are achieved in the whole free spectral range by controlling the microheaters to meet the phase condition.
Estimation Of Performance Indices For The Planning Of Sustainable Transportation Systems, Alexander Paz, Pankaj Maheshwari
Estimation Of Performance Indices For The Planning Of Sustainable Transportation Systems, Alexander Paz, Pankaj Maheshwari
Electrical & Computer Engineering Faculty Research
In the context of sustainable transportation systems, previous studies have either focused only on the transportation systemor have not used a methodology that enables the treatment of incomplete, vague, and qualitative information associated with the available data. This study proposes a system of systems (SOS) and a fuzzy logic modeling approach. The SOS includes the Transportation, Activity, and Environment systems. The fuzzy logic modeling approach enables the treatment of the vagueness associated with some of the relevant data. Performance Indices (PIs) are computed for each system using a number of performance measures. The PIs illustrate the aggregated performance of each …
Real-Time On-Board Object Tracking For Cooperative Flight Control, Ajay Kumar Mandava, Emma Regentova, Henry Selvaraj
Real-Time On-Board Object Tracking For Cooperative Flight Control, Ajay Kumar Mandava, Emma Regentova, Henry Selvaraj
Electrical & Computer Engineering Faculty Research
One of possible cooperative Situations for flights could be a scenario when the decision on a new path is taken by A Certain fleet member, who is called the leader. The update on the new path is Transmitted to the fleet members via communication That can be noisy. An optical sensor can be used as a back-up for re-estimating the path parameters based on visual information. For A Certain topology, the issue can be solved by continuous tracking of the leader of the fleet in the video sequence and re-adjusting parameters of the flight, accordingly. To solve such a problem …
Scheduling Architectures For Diffserv Networks With Input Queuing Switches, Mei Yang, Henry Selvaraj, Enyue Lu, Jianping Wang, S. Q. Zheng, Yingtao Jiang
Scheduling Architectures For Diffserv Networks With Input Queuing Switches, Mei Yang, Henry Selvaraj, Enyue Lu, Jianping Wang, S. Q. Zheng, Yingtao Jiang
Electrical & Computer Engineering Faculty Research
ue to its simplicity and scalability, the differentiated services (DiffServ) model is expected to be widely deployed across wired and wireless networks. Though supporting DiffServ scheduling algorithms for output-queuing (OQ) switches have been widely studied, there are few DiffServ scheduling algorithms for input-queuing (IQ) switches in the literaure. In this paper, we propose two algorithms for scheduling DiffServ DiffServ networks with IQ switches: the dynamic DiffServ scheduling (DDS) algorithm and the hierarchical DiffServ scheduling (HDS) algorithm. The basic idea of DDS and HDS is to schedule EF and AF traffic According to Their minimum service rates with the reserved bandwidth …
Free Regions Of Sensor Nodes, Laxmi P. Gewali, Navin Rongatana, Henry Selvaraj, Jan B. Pedersen
Free Regions Of Sensor Nodes, Laxmi P. Gewali, Navin Rongatana, Henry Selvaraj, Jan B. Pedersen
Electrical & Computer Engineering Faculty Research
We introduce the notion of free region of a node in a sensor network. Intuitively, a free region of a node is the connected set of points R in its neighborhood such that the connectivity of the network remains the same when the node is moved to any point in R. We characterize several properties of free regions and develop an efficient algorithm for computing them. We capture free region in terms of related notions called in-free region and out-free region. We present an O(n2) algorithm for constructing the free region of a node, where n is the number of …
Implementation Of Large Neural Networks Using Decomposition, Henry Selvaraj, H. Niewiadomski, P. Buciak, M. Pleban, Piotr Sapiecha, Tadeusz Luba, Venkatesan Muthukumar
Implementation Of Large Neural Networks Using Decomposition, Henry Selvaraj, H. Niewiadomski, P. Buciak, M. Pleban, Piotr Sapiecha, Tadeusz Luba, Venkatesan Muthukumar
Electrical & Computer Engineering Faculty Research
The article presents methods of dealing with huge data in the domain of neural networks. The decomposition of neural networks is introduced and its efficiency is proved by the authors’ experiments. The examinations of the effectiveness of argument reduction in the above filed, are presented. Authors indicate, that decomposition is capable of reducing the size and the complexity of the learned data, and thus it makes the learning process faster or, while dealing with large data, possible. According to the authors experiments, in some cases, argument reduction, makes the learning process harder.
Isolated Ramp Metering Feedback Control Utilizing Mixed Sensitivity For Desired Mainline Density And The Ramp Queues, Pushkin Kachroo, Kaan Ozbay, Donald E. Grove
Isolated Ramp Metering Feedback Control Utilizing Mixed Sensitivity For Desired Mainline Density And The Ramp Queues, Pushkin Kachroo, Kaan Ozbay, Donald E. Grove
Electrical & Computer Engineering Faculty Research
This paper presents a feedback control design for isolated ramp metering control. This feedback control design, unlike the existing isolated feedback ramp controllers, also takes into account the ramp queue length. Using a nonlinear H∞ control design methodology, we formulate the problem in the desired setting to be able to utilize the results of the methodology.
Sliding Mode Measurement Feedback Control For Antilock Braking Systems, Cem Unsal, Pushkin Kachroo
Sliding Mode Measurement Feedback Control For Antilock Braking Systems, Cem Unsal, Pushkin Kachroo
Electrical & Computer Engineering Faculty Research
We describe a nonlinear observer-based design for control of vehicle traction that is important in providing safety and obtaining desired longitudinal vehicle motion. First, a robust sliding mode controller is designed to maintain the wheel slip at any given value. Simulations show that longitudinal traction controller is capable of controlling the vehicle with parameter deviations and disturbances. The direct state feedback is then replaced with nonlinear observers to estimate the vehicle velocity from the output of the system (i.e., wheel velocity). The nonlinear model of the system is shown locally observable. The effects and drawbacks of the extended Kalman filters …
Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay
Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay
Electrical & Computer Engineering Faculty Research
This paper suggests an intelligent controller for an automated vehicle planning its own trajectory based on sensor and communication data. The intelligent controller is designed using the learning stochastic automata theory. Using the data received from on-board sensors, two automata (one for lateral actions, one for longitudinal actions) can learn the best possible action to avoid collisions. The system has the advantage of being able to work in unmodeled stochastic environments, unlike adaptive control methods or expert systems. Simulations for simultaneous lateral and longitudinal control of a vehicle provide encouraging results
Feedback Control Theory For Dynamic Traffic Assignment, Pushkin Kachroo, Kaan Ozbay
Feedback Control Theory For Dynamic Traffic Assignment, Pushkin Kachroo, Kaan Ozbay
Electrical & Computer Engineering Faculty Research
Traditionally, traffic assignment and traffic control in general have mostly been performed using optimisation techniques which do not lend themselves to real-time control. This volume presents feedback control techniques for performing traffic assignment in real-time, where traffic diversion control variables are instantaneous functions of sensed traffic variables. The authors outline the whole theory behind Intelligent Transportation Systems (ITS) which allows traffic variables to be sensed in real time and microprocessors to use the sensed traffic variable input to perform the traffic actuation tasks. They show h ow to design feedback controllers to perform dynamic traffic routing and assignment, and present …
Incident Management In Intelligent Transportation Systems, Kaan Ozbay, Pushkin Kachroo
Incident Management In Intelligent Transportation Systems, Kaan Ozbay, Pushkin Kachroo
Electrical & Computer Engineering Faculty Research
Since the conception of Intelligent Transportation Systems (ITS) in the 1980s, many transportation researchers have also worked on the development of incident management models and integrated systems for real-time operations. ITS created the required infrastructure for collecting, processing, and managing real-time traffic data that can be used to develop on-line incident management strategies. This book provides the reader with a broad picture of the overall incident management process in the context of ITS along with a quick review of the models and systems developed by numerous researchers worldwide. This book is a direct result of the long-term incident management research …
Validation Of Waimss Incident Duration Estimation Model, Wei Wu, Pushkin Kachroo, Kaan Ozbay
Validation Of Waimss Incident Duration Estimation Model, Wei Wu, Pushkin Kachroo, Kaan Ozbay
Electrical & Computer Engineering Faculty Research
This paper presents an effort to validate the traffic incident duration estimation model of WAIMSS (wide area incident management support system). Duration estimation model of WAIMSS predicts the incident duration based on an estimation tree which was calibrated using incident data collected in Northern Virginia. Due to the limited sample size, a full scale test of the distribution, mean and variance of incident duration was performed only for the root node of the estimation tree, white only mean tests were executed at all other nodes whenever a data subset was available. Further studies were also conducted on the model error …
Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay
Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay
Electrical & Computer Engineering Faculty Research
One of the most important issues in Automated Highway System (AHS) deployment is intelligent vehicle control. While the technology to safely maneuver vehicles exists, the problem of making intelligent decisions to improve a single vehicle’s travel time and safety while optimizing the overall traffic flow is still a stumbling block. We propose an artificial intelligence technique called stochastic learning automata to design an intelligent vehicle path controller. Using the information obtained by on-board sensors and local communication modules, two automata are capable of learning the best possible (lateral and longitudinal) actions to avoid collisions. This learning method is capable of …
Sliding Mode For User Equilibrium Dynamic Traffic Routing Control, Pushkin Kachroo, Kaan Ozbay
Sliding Mode For User Equilibrium Dynamic Traffic Routing Control, Pushkin Kachroo, Kaan Ozbay
Electrical & Computer Engineering Faculty Research
Presents a solution to the user equilibrium dynamic traffic routing (DTR) problem for a point diversion case using feedback control methodology. The sliding mode control technique which is a robust control methodology applicable to nonlinear systems in canonical form is employed to solve the user equilibrium DTR problem. The canonical form for this problem is obtained by using a feedback linearization technique, and the uncertainties of the system are countered by using the sliding mode principle. Simulation results show promising results.
Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay
Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay
Electrical & Computer Engineering Faculty Research
A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting.
Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo
Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo
Electrical & Computer Engineering Faculty Research
We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results.