Performance evaluation of an adaptive travel time prediction model

Shamas Ul Islam Bajwa; Edward Chung; Masao Kuwahara

doi:10.1109/ITSC.2005.1520187

Performance evaluation of an adaptive travel time prediction model

Shamas Ul Islam Bajwa, Edward Chung, Masao Kuwahara

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

42 Citations (Scopus)

Abstract

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 language	English
Title of host publication	ITSC`05
Subtitle of host publication	2005 IEEE Intelligent Conference on Transportation Systems, Proceedings
Pages	1000-1005
Number of pages	6
DOIs	https://doi.org/10.1109/ITSC.2005.1520187
Publication status	Published - 1 Dec 2005
Externally published	Yes
Event	8th International IEEE Conference on Intelligent Transportation Systems - Vienna, Austria Duration: 13 Sept 2005 → 16 Sept 2005

Publication series

Name	IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume	2005

Conference

Conference	8th International IEEE Conference on Intelligent Transportation Systems
Country/Territory	Austria
City	Vienna
Period	13/09/05 → 16/09/05

Keywords

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

ASJC Scopus subject areas

Automotive Engineering
Mechanical Engineering
Computer Science Applications

More information

10.1109/ITSC.2005.1520187

Cite this

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title = "Performance evaluation of an adaptive travel time prediction model",

abstract = "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 na{\"i}ve model.",

keywords = "Adaptive Parameters, Intelligent Transportation Systems (ITS), Pattern Matching Technique, Travel Time Prediction",

author = "Bajwa, {Shamas Ul Islam} and Edward Chung and Masao Kuwahara",

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series = "IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC",

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Bajwa, SUI, Chung, E & Kuwahara, M 2005, Performance evaluation of an adaptive travel time prediction model. in ITSC`05: 2005 IEEE Intelligent Conference on Transportation Systems, Proceedings., 1520187, IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, vol. 2005, pp. 1000-1005, 8th International IEEE Conference on Intelligent Transportation Systems, Vienna, Austria, 13/09/05. https://doi.org/10.1109/ITSC.2005.1520187

Performance evaluation of an adaptive travel time prediction model. / Bajwa, Shamas Ul Islam; Chung, Edward; Kuwahara, Masao.
ITSC`05: 2005 IEEE Intelligent Conference on Transportation Systems, Proceedings. 2005. p. 1000-1005 1520187 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC; Vol. 2005).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AB - 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.

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Performance evaluation of an adaptive travel time prediction model

Abstract

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Conference

Keywords

ASJC Scopus subject areas

More information

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