A knowledge based real-time travel time prediction system for urban network

ASIA unversity > 資訊學院 > 行動商務與多媒體應用學系 > 期刊論文 > Item 310904400/8725

Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8725

Title:	A knowledge based real-time travel time prediction system for urban network
Authors:	Lee, Wei-Hsun;Tseng, Shian-Shyong;Tsai, Sheng-Han
Contributors:	Department of Information Science and Applications
Keywords:	Computer networks;Data mining;Dynamic response;Forecasting;Information management;Intelligent vehicle highway systems;Knowledge management;Mathematical models;Mine transportation;Sensor networks;Time varying control systems;Traffic surveys;Vehicle locating systems;Arterial networks;Data mining techniques;Dynamic weights;Intelligent transportation system (ITS);Knowledge-based;Location-Based services;Path routing;Raw datums;Real times;Real-time traffics;Sensor datums;Spatiotemporal data mining;Spatiotemporal datums;Time travels;Traffic patterns;Travel time prediction;Travel times;Urban networks
Date:	2009
Issue Date:	2010-04-07 21:34:13 (UTC+8)
Publisher:	Asia University
Abstract:	Many approaches had been proposed for travel time prediction in these decades; most of them focus on the predicting the travel time on freeway or simple arterial network. Travel time prediction for urban network in real time is hard to achieve for several reasons: complexity and path routing problem in urban network, unavailability of real-time sensor data, spatiotemporal data coverage problem, and lacking real-time events consideration. In this paper, we propose a knowledge based real-time travel time prediction model which contains real-time and historical travel time predictors to discover traffic patterns from the raw data of location based services by data mining technique and transform them to travel time prediction rules. Besides, dynamic weight combination of the two predictors by meta-rules is proposed to provide a real-time traffic event response mechanism to enhance the precision of the travel time prediction. © 2008 Elsevier Ltd. All rights reserved.
Relation:	Expert Systems with Applications 36:4239-4247
Appears in Collections:	[行動商務與多媒體應用學系] 期刊論文

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