This paper studies the effect of bicycles on intersection operations for those intersections where bicycle traffic causes the most disturbances to vehicular traffic. By studying different states of bicycles crossing a...
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This paper studies the effect of bicycles on intersection operations for those intersections where bicycle traffic causes the most disturbances to vehicular traffic. By studying different states of bicycles crossing a signalized intersection, this paper divides the conflicts between bicycles and turning vehicles into multiple stages and models the saturation flow rate of turning vehicles under the bicycles' influence for each stage. For right-turn vehicles, in the first stage, previously queued turning vehicles and bicycles are released at the onset of green, and right-turn vehicles are blocked by through bicycles;in the second stage, bicycles arriving at the intersection randomly after initial queues are discharged, and gap acceptance consideration is used to analyze the conflict between the right-turn vehicles and bicycles to obtain the saturation flow reduction factor for right-turn vehicles. In the first stage, left-turn vehicles wait while the opposing through vehicles discharge from the queue;in the second-stage, the left-turn vehicles cross opposing randomly arriving vehicular flow and may be blocked by the bicycles in queue discharge mode and in the third stage, left-turn vehicles cross randomly arriving opposing through bicycles. The saturation flow rates of right-turn and left-turn vehicles under the bicycles' influence are modeled considering differences in these stages. The model results are compared with real-world observations and show a better match than those from the Highway Capacity Manual (hcm) model. The results of this study can supplement the content of the signalized intersection capacity analysis method in the hcm and provide the basis for design of intersection signal timing and capacity calculation under mixed traffic conditions at signalized intersections. DOI: 10.1061/(ASCE)TE.1943-5436.0000317. (C) 2012 American Society of Civil Engineers.
The method of the investigation of information web system users' activity using a clustering method is presented in the paper. On the basis of a web server log, anonymous sessions are determined in the form of a 6...
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ISBN:
(纸本)9781424420957
The method of the investigation of information web system users' activity using a clustering method is presented in the paper. On the basis of a web server log, anonymous sessions are determined in the form of a 65 dimensional vector, where dimensions represent individual web system pages. Each dimension comprises the value of a measure of user interest in a page during a given session. This value is calculated as a ratio of time user spent visiting a given page to the total time of a session. Then the whole set of sessions is clustered using hcm (Hard C-Means) algorithm. The resulting clusters are assumed as the user activity patterns and among them clusters dominated by a page are selected as those where the user interest value exceeds a given threshold value e.g. 50 per cent. The sessions of named users, registered in the system, are determined using an application log of user activity. The frequencies of named user sessions, comprised by individual clusters, are calculated for a given period of time e.g. one month. The user activity can be assessed by analyzing frequencies obtained. For example, the user behavior can be regarded as deviated front normal pattern when the frequency of a session in a cluster dominated by a page is below a determined threshold value e.g. 10 per cent. The method was evaluated using data front a cadastral web system exploited in an extranet.
Based on the defect of rival checked fuzzy c-means clustering algorithm, a new algorithm: suppressed fuzzy c-means clustering algorithm is proposed. The new algorithm overcomes the shortcomings of the original algorit...
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Based on the defect of rival checked fuzzy c-means clustering algorithm, a new algorithm: suppressed fuzzy c-means clustering algorithm is proposed. The new algorithm overcomes the shortcomings of the original algorithm, establishes more natural and more reasonable relationships between hard c-means clustering algorithm and fuzzy c-means clustering algorithm. (C) 2002 Elsevier Science B.V. All rights reserved.
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