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

Wei Hsun Lee, Shian Shyong Tseng, Sheng Han Tsai

Research output: Contribution to journalArticlepeer-review

79 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)4239-4247
Number of pages9
JournalExpert Systems With Applications
Volume36
Issue number3 PART 1
DOIs
Publication statusPublished - 2009 Apr

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'A knowledge based real-time travel time prediction system for urban network'. Together they form a unique fingerprint.

Cite this