132,908 research outputs found
Doctor of Philosophy
dissertationThe Active Traffic and Demand Management (ATDM) initiative aims to integrate various management strategies and control measures so as to achieve the mobility, environment and sustainability goals. To support the active monitoring and management of real-world complex traffic conditions, the first objective of this dissertation is to develop a travel time reliability estimation and prediction methodology that can provide informed decisions for the management and operation agencies and travelers. A systematic modeling framework was developed to consider a corridor with multiple bottlenecks, and a series of close-form formulas was derived to quantify the travel time distribution under both stochastic demand and capacity, with possible on-ramp and off-ramp flow changes. Traffic state estimation techniques are often used to guide operational management decisions, and accurate traffic estimates are critically needed in ATDM applications designed for reducing instability, volatility and emissions in the transportation system. By capturing the essential forward and backward wave propagation characteristics under possible random measurement errors, this dissertation proposes a unified representation with a simple but theoretically sound explanation for traffic observations under free-flow, congested and dynamic transient conditions. This study also presents a linear programming model to quantify the value of traffic measurements, in a heterogeneous data environment with fixed sensors, Bluetooth readers and GPS sensors. It is important to design comprehensive traffic control measures that can systematically address deteriorating congestion and environmental issues. To better evaluate and assess the mobility and environmental benefits of the transportation improvement plans, this dissertation also discusses a cross-resolution modeling framework for integrating a microscopic emission model with the existing mesoscopic traffic simulation model. A simplified car-following model-based vehicle trajectory construction method is used to generate the high-resolution vehicle trajectory profiles and resulting emission output. In addition, this dissertation discusses a number of important issues for a cloud computing-based software system implementation. A prototype of a reliability-based traveler information provision and dissemination system is developed to offer a rich set of travel reliability information for the general public and traffic management and planning organizations
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The uses of process modeling : a framework for understanding modeling formalisms
There is wide-spread recognition of the urgent need to improve software processes in order to improve the performance of software organizations. Process models are essential in achieving understanding and visibility of processes and are important for other uses including the analysis of processes for improvement. It has been increasingly difficult to compare and evaluate the variety of process modeling formalisms that have appeared in recent years without a clear understanding of precisely for what they will be used. The contribution of this paper is to provide an understanding and a fairly comprehensive catalog of the applications of process modeling for which formalisms may be used. The primary mechanism for doing this is a guided tour of the literature on process modeling supplemented by recent industrial experience. In the paper, basic definitions concerning processes, process descriptions and process modeling are reviewed and then uses of process modeling are surveyed under the following headings: communication among process participants, construction of new processes, control of processes, process· analysis, and process support by automation. Comments are offered on paradigms for process modeling formalisms and directions for future work to permit evolution of a discipline of process engineering are given
The 1990 progress report and future plans
This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers
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Requirements for building information modeling based lean production management systems for construction
Smooth flow of production in construction is hampered by disparity between individual trade teams' goals and the goals of stable production flow for the project as a whole. This is exacerbated by the difficulty of visualizing the flow of work in a construction project. While the addresses some of the issues in Building information modeling provides a powerful platform for visualizing work flow in control systems that also enable pull flow and deeper collaboration between teams on and off site. The requirements for implementation of a BIM-enabled pull flow construction management software system based on the Last
Planner System™, called ‘KanBIM’, have been specified, and a set of functional mock-ups of the proposed system has been implemented and evaluated in a series of three focus group workshops. The requirements cover the areas of maintenance of work flow stability, enabling negotiation and commitment between teams, lean production planning with sophisticated pull flow control, and effective communication and visualization of flow. The evaluation results show that the system holds the potential to improve work flow and reduce waste by providing both process and product visualization at the work face
Measuring the Economic Impact of High Speed Rail Construction for California and the Central Valley Region
The nation’s first high-speed rail project is under construction in California’s Central Valley as of the date of this report. This research analyzes the immediate economic impacts, focused on employment and spending generated by California High-Speed Rail (HSR) Construction Package 1 (CP1) in the Central Valley and the rest of California. The authors use a two-pronged approach that combines original economic analysis and modeling with case study vignettes that explore the economic impacts through the lens of a sample of businesses and individuals directly impacted by this phase of HSR development. Overall, the economic analysis suggests that CP1-related spending (forecasted through to 2019) will lead to more than 31,500 additional jobs (both part-time and full-time) by the year 2029. Growth is concentrated in Fresno County, with the number of additional jobs estimated at more than 15,500. The analysis considers job growth across a number of alternative scenarios, converting the raw jobs estimates to full-time equivalent job-years. Under the most conservative HSR spending scenario considered, over the 15-year period evaluated, more than 25,000 full-time equivalent job-years are created. This amount to 14,900 jobs per billion (real) dollars of spending, or a cost of approximately $67,200 per job-year
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An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
This paper describes an approach to the design of a population of cooperative
robots based on concepts borrowed from Systems Theory and Artificial
Intelligence. The research has been developed under the SocRob project, carried
out by the Intelligent Systems Laboratory at the Institute for Systems and
Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the
project stands both for "Society of Robots" and "Soccer Robots", the case study
where we are testing our population of robots. Designing soccer robots is a
very challenging problem, where the robots must act not only to shoot a ball
towards the goal, but also to detect and avoid static (walls, stopped robots)
and dynamic (moving robots) obstacles. Furthermore, they must cooperate to
defeat an opposing team. Our past and current research in soccer robotics
includes cooperative sensor fusion for world modeling, object recognition and
tracking, robot navigation, multi-robot distributed task planning and
coordination, including cooperative reinforcement learning in cooperative and
adversarial environments, and behavior-based architectures for real time task
execution of cooperating robot teams
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