A Traffic Information Estimation Model Using Periodic Location Update Events from Cellular Network

Bon-Yeh Lin*, Chi-Hua Chen, Chi-Chun Lo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

In recent years considerable concerns have arisen over building Intelligent Transportation System (ITS) which focuses on efficiently managing the road network. One of the important purposes of ITS is to improve the usability of transportation resources so as extend the durability of vehicle, reduce the fuel consumption and transportation times. Before this goal can be achieved, it is vital to obtain correct and real-time traffic information, so that traffic information services can be provided in a timely and effective manner. Using Mobile Stations (MS) as probe to tracking the vehicle movement is a low cost and immediately solution to obtain the real-time traffic information. In this paper, we propose a model to analyze the relation between the amount of Periodic Location Update (PLU) events and traffic density. Finally, the numerical analysis shows that this model is feasible to estimate the traffic density.
Original languageEnglish
Title of host publicationINTELLIGENT COMPUTING AND INFORMATION SCIENCE, PT II
Pages72-77
DOIs
StatePublished - 2011
EventInternational Conference on Intelligent Computing and Information Science - Chongqing, China
Duration: 8 Jan 20119 Jan 2011

Publication series

NameINTELLIGENT COMPUTING AND INFORMATION SCIENCE, PT II
ISSN (Print)1865-0929

Conference

ConferenceInternational Conference on Intelligent Computing and Information Science
CountryChina
CityChongqing
Period8/01/119/01/11

Keywords

  • Periodic Location Update; Intelligent Transportation System; Cellular Network; Traffic Density Estimation

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  • Cite this

    Lin, B-Y., Chen, C-H., & Lo, C-C. (2011). A Traffic Information Estimation Model Using Periodic Location Update Events from Cellular Network. In INTELLIGENT COMPUTING AND INFORMATION SCIENCE, PT II (pp. 72-77). (INTELLIGENT COMPUTING AND INFORMATION SCIENCE, PT II). https://doi.org/10.1007/978-3-642-18134-4_12, https://doi.org/10.1007/978-3-642-18134-4_12