Browsing by Author "Hsu, Chih-Cheng"

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A Modified Cellular Automaton Model for Accounting for Traffic Behaviors during Signal Change Intervals
(2018-01-01)
Hsu, Chih-Cheng
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Chiou, Yu-Chiun
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Previous cellular automata (CA) models have been developed for simulating driver behaviors in response to traffic signal control. However, driver behaviors during traffic signal change intervals, including cross/stop decision and speed adjustment, have not yet been studied. Based on this, this paper aims to propose a change interval CA model for replicating driver's perception and response to amber light based on stopping probability and speed adjusting functions. The proposed model has been validated by exemplified and field cases. To investigate the applicability of the proposed model, macroscopic and microscopic analyses are conducted. Although the macroscopic fundamental diagram analysis reveals only a small decrease in maximum traffic flow rates with considering driver behaviors in change intervals, in the microscopic analysis, the proposed model can present reasonable vehicular trajectories and deceleration rates during slowdown process.
A refined cellular automaton model to rectify impractical vehicular movement behavior
(2009-09-15)
Lan, Lawrence W.
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Chiou, Yu-Chiun
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Lin, Zih-Shin
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Hsu, Chih-Cheng
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運輸與物流管理系註：原交通所+運管所
When implementing cellular automata (CA) into a traffic simulation, one common defect yet to be rectified is the abrupt deceleration when vehicles encounter stationary obstacles or traffic jams. To be more in line with real world vehicular movement, this paper proposes a piecewise-linear movement to replace the conventional particle-hopping movement adopted in most previous CA models. Upon this adjustment and coupled with refined cell system, a new CA model is developed using the rationale of Forbes' et al. car-following concept. The proposed CA model is validated on a two-lane freeway mainline context. It shows that this model can fix the unrealistic deceleration behaviors, and thus call reflect genuine driver behavior in the real world. The model is also capable of revealing Kerner's three-phase traffic patterns and phase transitions among them. Furthermore, the proposed CA model is applied to simulate a highway work zone wherein traffic efficiency (maximum flow rates) and safety (speed deviations) impacted by various control schemes are tested. (C) 2009 Elsevier B.V. All rights reserved.
Cellular automaton simulations for mixed traffic with erratic motorcycles' behaviours
(2010-05-15)
Lan, Lawrence W.
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Chiou, Yu-Chiun
;
Lin, Zih-Shin
;
Hsu, Chih-Cheng
;
運輸與物流管理系註：原交通所+運管所
Modeling mixed traffic composed of motorcycles can be a challenging issue because many erratic motorcyclists may not follow the lane disciplines, particularly when traffic is congested. Based upon the refined cellular automaton (CA) model recently developed by the authors [LW. Lan, Y C Chiou. Z.S. Lin, C.C. Hsu, Physica A 388 (2009) 3917-3930], this paper further proposed a sophisticated CA model to elucidate the erratic motorcycle behaviours in mixed traffic contexts. In addition to the conventional moving forward and lane-change rules, the sophisticated CA model also explicated the lateral drift behaviour for cars moving in the same lane, the lateral drift behaviour for motorcycles breaking into two moving cars. and the transverse crossing behaviour for motorcycles through the gap between two stationary cars in the same lane. Fundamental diagrams and space-time trajectories for vehicles with various car-motorcycle mixed ratios are demonstrated (C) 2010 Elsevier B.V. All rights reserved
Glucocorticoids may compromise the effect of gefitinib in non-small cell lung cancer
(2016-12-27)
Wang, Hsian-Yu
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Chang, Yu-Ling
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Cheng, Chun-Chun
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Chao, Min-Wu
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Lin, Su-I
The epidermal growth factor receptor (EGFR)-targeting tyrosine kinase inhibitors (TKIs) have shown remarkable benefits in non-small cell lung cancer (NSCLC) patients with drug-sensitive mutations in the EGFR gene. Responsive patients are usually continuously prescribed with TKIs until disease progression. Glucocorticoids (GCs) are potent homeostasis maintaining drugs and are frequently used in cancer patients to alleviate discomforts caused by anti-cancer therapies. Several previous studies reported that concomitant use of GCs may compromise the efficacy of chemo-therapeutics in patients with solid tumors. Little is known in the concomitant use of target therapy with GCs in treating NSCLC. In this study, we hypothesized that concomitant use of GCs in EGFR-TKI therapy may be detrimental and addressed this issue using cell cultures and xenograft studies followed by a retrospective population study based on data from the Taiwan national health insurance system. In cell cultures and xenograft studies, GCs were shown to unequally compromise the anti-cancer efficacy of TKIs in both PC9 and NCI-H1975 NSCLC cells models. In the retrospective population study, patients with similar disease status that were co-medicated with GCs had a significantly higher risk of disease progression.
Multiparametric graph theoretical analysis reveals altered structural and functional network topology in Alzheimer's disease
(2019-01-01)
Lin, Shih-Yen
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Lin, Chen-Pei
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Hsieh, Tsung-Jen
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Lin, Chung-Fen
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Chen, Sih-Huei
Alzheimer's disease (AD), an irreversible neurodegenerative disease, is the most common type of dementia in elderly people. This present study incorporated multiple structural and functional connectivity metrics into a graph theoretical analysis framework and investigated alterations in brain network topology in patients with mild cognitive impairment (MCI) and AD. By using this multiparametric analysis, we expected different connectivity metrics may reflect additional or complementary information regarding the topological changes in brain networks in MCI or AD. In our study, a total of 73 subjects participated in this study and underwent the magnetic resonance imaging scans. For the structural network, we compared commonly used connectivity metrics, including fractional anisotropy and normalized streamline count, with multiple diffusivity-based metrics. We compared Pearson correlation and covariance by investigating their sensitivities to functional network topology. Significant disruption of structural network topology in MCI and AD was found predominantly in regions within the limbic system, prefrontal and occipital regions, in addition to widespread alterations of local efficiency. At a global scale, our results showed that the disruption of the structural network was consistent across different edge definitions and global network metrics from the MCI to AD stages. Significant changes in connectivity and tract-specific diffusivity were also found in several limbic connections. Our findings suggest that tract-specific metrics (e.g., fractional anisotropy and diffusivity) provide more sensitive and interpretable measurements than does metrics based on streamline count. Besides, the use of inversed radial diffusivity provided additional information for understanding alterations in network topology caused by AD progression and its possible origins. Use of this proposed multiparametric network analysis framework may facilitate early MCI diagnosis and AD prevention.
USING CELLULAR AUTOMATA TO EXPLORE SPATIOTEMPORAL TRAFFIC PATTERNS
(2005)
Lan, Lawrence W.
;
Hsu, Chih-Cheng
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This paper respectively simulates the emergence of traffic flow patterns for light and heavy vehicles on a two-lane freeway mainline by setting up different cellular automata (CA) rules to govern their moving forward and changing lane behaviors. Vehicular trajectories, flow-occupancy, speed-occupancy and speed-flow diagrams, and spatiotemporal traffic features under deterministic and stochastic conditions are displayed. The simulation results have revealed noticeable traffic flow patterns with free flow, wide moving jam and synchronized flow phases, which support Kerner's recent three-phase traffic theory.