Performance evaluation of an adaptive travel time prediction model

Shamas Ul Islam Bajwa, Edward Chung, Masao Kuwahara

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

42 Citations (Scopus)


This paper presents a travel time prediction model and evaluates its performance and transferability. Advanced Travelers Information Systems (ATIS) are gaining more and more importance, increasing the need for accurate, timely and useful information to the travelers. Travel time information quantifies the traffic condition in an easy to understand way for the users. The proposed travel time prediction model is based on an efficient use of nearest neighbor search. The model is calibrated for optimal performance using Genetic Algorithms. Results indicate better performance by using the proposed model than the presently used naïve model.

Original languageEnglish
Title of host publicationITSC`05
Subtitle of host publication2005 IEEE Intelligent Conference on Transportation Systems, Proceedings
Number of pages6
Publication statusPublished - 1 Dec 2005
Externally publishedYes
Event8th International IEEE Conference on Intelligent Transportation Systems - Vienna, Austria
Duration: 13 Sept 200516 Sept 2005

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC


Conference8th International IEEE Conference on Intelligent Transportation Systems


  • Adaptive Parameters
  • Intelligent Transportation Systems (ITS)
  • Pattern Matching Technique
  • Travel Time Prediction

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


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