Collaborative real-time traffic information generation and sharing framework for the intelligent transportation system

  • Authors:

  • Wei-Hsun Lee;Shian-Shyong Tseng;Wern-Yarng Shieh

  • Affiliations:

  • Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan, ROC and Telecommunication Laboratories of Chung-hwa Telecom, 12, Lane 551, Min-Tsu Road, Se ...;Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan, ROC and Department of Information Science and Applications, Asia University, 500 Liufeng Ro ...;Department of Computer and Communication Engineering, St. John's University, 499, Sec. 4, Tam King Road, Tamsui, Taipei 251, Taiwan, ROC

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2010

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Abstract

Real-time traffic information collection and data fusion is one of the most important tasks in the advanced traffic management system (ATMS), and sharing traffic information to users is an essential part of the advance traveler information system (ATIS) among the intelligent transportation systems (ITS). Traditionally, sensor-based schemes or probing-vehicle based schemes have been used for collecting traffic information, but the coverage, cost, and real-time issues have remained unsolved. In this paper, a wiki-like collaborative real-time traffic information collection, fusion and sharing framework is proposed, which includes user-centric traffic event reacting mechanism, and automatic agent-centric traffic information aggregating scheme. Smart traffic agents (STA) developed for various front-end devices have the location-aware two-way real-time traffic exchange capability, and built-in event-reporting mechanism to allow users to report the real-time traffic events around their locations. In addition to collecting traffic information, the framework also integrates heterogeneous external real-time traffic information data sources and internal historical traffic information database to predict real-time traffic status by knowledge base system technique.