Browsing by Author "Liu, Xiao"

Now showing 1 - 6 of 6
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    Development and Application of On-Line Strategies for Optimal Intersection Control (Phase III)
    (Minnesota Department of Transportation, 1996-10) Kwon, Eil; Stephanedes, Yorgos J.; Liu, Xiao; Chidambaram, Sabhari; Antoniades, Charalambos
    The previous phases of this research reviewed and tested existing intersection control algorithms in a simulated environment. Further, a machine-vision detection system with four cameras was installed at the intersection of Franklin and Lyndale Avenues in Minneapolis, Minnesota, to develop a live intersection laboratory. Phase III enhanced the live laboratory with two additional cameras covering the intersection proper and the extended approach of southbound Lyndale Ave. A comprehensive operational plan for the laboratory was developed and a new microscopic simulator for the laboratory intersection was -also developed. Two types of new intersection control strategies, i.e., one with link-wide congestion measurements and the other based on neural-network approach, were developed and evaluated in the simulated environment. Further, using the data collected from the machine-vision detection system, an automatic procedure to estimate the intersection delay was also developed and applied to compare the performance of fixed-timing control with that of the actuated control strategy.
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    Development and Application of On-Line Strategies for Optimal Intersection Control Phase II: Off-Line Evaluation of Control Strategies and Development of a Live Laboratory
    (Minnesota Department of Transportation, 1994-10) Stephanedes, Yorgos J.; Kwon, Eil; Liu, Xiao
    This project evaluates various intersection control strategies in a simulated environment and also helped establish a live laboratory for use in future testing of new control strategies. The report reviews major intersection control strategies, including the state-of-the-art strategies with adaptive and on-line timing generation features. In addition, it details simulation results for the OPAC control strategy. The NETSIM simulator created the simulation environment for a test network that included part of downtown Minneapolis. Comparison results indicate that OPAC performs best with low-traffic demands, and pretimed control was the most effective during peak periods when traffic demand reached capacity. In conjunction with this project, Minneapolis city traffic engineers installed a machine-vision video detection system at a live intersection laboratory. Located at Franklin and Lyndale Avenues, the test site will help researchers evaluate new control strategies before full-scale implementation in later phases of this research.
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    Development of On-Line Control Strategies in Freeway Networks, Phase 2: Final Report
    (Minnesota Department of Transportation, 1998-05) Stephanedes, Yorgos J.; Liu, Xiao; Liu, Lu; Michel, Bernard R.
    Most traffic-responsive freeway ramp metering systems select metering rates from predetermined rate libraries. The efficiency of such systems is impaired by the lack of an efficient analysis tool that can evaluate and update the thresholds and rate libraries used by the meter controllers. In this project, a control-emulation method is developed to evaluate various automatic rateselection strategies; the new modeling features of this system are described in detail. Various rate selection strategies (based on neural network processing, exit ramp volume, and real time bottleneck/dynamic zone determination) are described and evaluated in comparison with the current Minneapolis-St. Paul strategy. An online traffic volume predictor based on Kalman filtering is developed, and integrated into the control-emulation module. A simulated annealing optimization algorithm, previously implemented on a supercomputer, is re-implemented on a personal computer and integrated into the simulation module.
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    Dynamics and Energy Scaling of Granular Explosion Cratering
    (2018) Liu, Xiao; Sun, Ting-Pi; Gao, Ming; Vanin, Luana Pasetti; Gordillo, Leonardo; Liu, Tianyu
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    Study of spontaneous bold fluctuation in animal and human brains
    (2010-09) Liu, Xiao
    Spontaneous blood-oxygen-level-dependent (BOLD) signals acquired at the resting state have recently been found to fluctuate coherently within many anatomically-connected and functionally-specific brain networks, and it may reflect an orderly organization of ongoing brain activity. Understanding this phenomenon may help us not only to understand some fundamental mechanisms of brain functions but also to find its applications in clinical field. However, the mechanisms underlying this phenomenon remains elusive, and even its neural origin is still controversial. This dissertation aimed to understand spontaneous BOLD fluctuation from its neurophysiological basis, its modulation under different brain states, and its role in brain functions. With five projects performed both on animals and humans, we have found that i) spontaneous BOLD fluctuation under deep burst-suppression anesthesia originates from underlying spontaneous neural activity, ii) spontaneous BOLD fluctuation is sensitive to changes in anesthesia depth, reflecting reorganization of ongoing brain activity at different consciousness level, iii) the resting-state visual network is spatially reorganized into activated and non-activated coherent network under continuous stimulation, and iv) the correlation strength within individuals' resting-state network can affect their evoked response to identical stimulations. These findings clearly support the functional significance of spontaneous BOLD fluctuation widely observed in animals and humans brain and provide new insights into its underlying mechanisms.