GPS data based urban guidance

Yao-Hua Ho*, Yao Chuan Wu, Meng Chang Chen, Tsun Jui Wen, Yeali S. Sun

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

1 引文 斯高帕斯(Scopus)

摘要

In many metropolitan areas, traffic congestion is an escalating problem which causes a significant waste of money and time. Nowadays, cars equipped with GPS devices become widespread. The location information of those cars is very useful for estimate traffic condition in the complex city road network. Using the accurate and real time traffic condition, we can provide dynamic route guidance to ease traffic congestion. In this paper, we proposed a speed pattern model, called two phase piecewise linear speed model (2PEED), to estimate traffic condition and represent speed pattern in a road network using GPS data collected vehicles. With the estimated traffic condition and speed pattern, a proposed classification-based route guidance approach using machine learning technique provides dynamic routing for drivers. Using both current traffic data and the experience learned from history data, our route guidance approach is able to accurately predict the future traffic condition and selects a best route. We give simulation results to show that the proposed approach is able to select and dynamically update a route to prove drivers a best (e.g., less traffic and shortest travel time) route to their destination.

原文英語
主出版物標題Proceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011
頁面703-708
頁數6
DOIs
出版狀態已發佈 - 2011 九月 19
事件2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011 - Kaohsiung, 臺灣
持續時間: 2011 七月 252011 七月 27

其他

其他2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011
國家/地區臺灣
城市Kaohsiung
期間2011/07/252011/07/27

ASJC Scopus subject areas

  • 電腦網路與通信
  • 電氣與電子工程

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