Travel time prediction using probe-car data

Takashi Fujita; Enjian Yao; Yasuhiro Sugisaki; Jun Ichi Takeuchi; Kozue Hirabayashi; Takayuki Nakata

Travel time prediction using probe-car data

Takashi Fujita, Enjian Yao, Yasuhiro Sugisaki, Jun Ichi Takeuchi, Kozue Hirabayashi, Takayuki Nakata

Mathematical Informatics

Research output: Contribution to conference › Paper › peer-review

4 Citations (Scopus)

Abstract

Travel time prediction is very important to the development of Advanced Traveler Information System (ATIS) and other ITS applications such as route guidance system and traffic flow management. In this paper, a comprehensive approach including short-term, medium-term, and long-term travel time predictions based on the link travel time data collected by probe vehicle system is proposed. The suitable models for these three types of prediction and the conditions for the models' application are also identified respectively. Finally, the performance of the proposed approach is examined with the Automated Vehicle Identification (AVI) data, and the accuracy and the practicability are identified successfully. .

Original language	English
Publication status	Published - 2006
Event	13th World Congress on Intelligent Transport Systems and Services, ITS 2006 - London, United Kingdom Duration: Oct 8 2006 → Oct 12 2006

Other

Other	13th World Congress on Intelligent Transport Systems and Services, ITS 2006
Country/Territory	United Kingdom
City	London
Period	10/8/06 → 10/12/06

All Science Journal Classification (ASJC) codes

Mechanical Engineering
Transportation
Electrical and Electronic Engineering
Computer Science Applications
Automotive Engineering
Artificial Intelligence
Control and Systems Engineering
Computer Networks and Communications

Cite this

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title = "Travel time prediction using probe-car data",

abstract = "Travel time prediction is very important to the development of Advanced Traveler Information System (ATIS) and other ITS applications such as route guidance system and traffic flow management. In this paper, a comprehensive approach including short-term, medium-term, and long-term travel time predictions based on the link travel time data collected by probe vehicle system is proposed. The suitable models for these three types of prediction and the conditions for the models' application are also identified respectively. Finally, the performance of the proposed approach is examined with the Automated Vehicle Identification (AVI) data, and the accuracy and the practicability are identified successfully. .",

author = "Takashi Fujita and Enjian Yao and Yasuhiro Sugisaki and Takeuchi, {Jun Ichi} and Kozue Hirabayashi and Takayuki Nakata",

year = "2006",

language = "English",

note = "13th World Congress on Intelligent Transport Systems and Services, ITS 2006 ; Conference date: 08-10-2006 Through 12-10-2006",

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TY - CONF

T1 - Travel time prediction using probe-car data

AU - Fujita, Takashi

AU - Yao, Enjian

AU - Sugisaki, Yasuhiro

AU - Takeuchi, Jun Ichi

AU - Hirabayashi, Kozue

AU - Nakata, Takayuki

PY - 2006

Y1 - 2006

N2 - Travel time prediction is very important to the development of Advanced Traveler Information System (ATIS) and other ITS applications such as route guidance system and traffic flow management. In this paper, a comprehensive approach including short-term, medium-term, and long-term travel time predictions based on the link travel time data collected by probe vehicle system is proposed. The suitable models for these three types of prediction and the conditions for the models' application are also identified respectively. Finally, the performance of the proposed approach is examined with the Automated Vehicle Identification (AVI) data, and the accuracy and the practicability are identified successfully. .

AB - Travel time prediction is very important to the development of Advanced Traveler Information System (ATIS) and other ITS applications such as route guidance system and traffic flow management. In this paper, a comprehensive approach including short-term, medium-term, and long-term travel time predictions based on the link travel time data collected by probe vehicle system is proposed. The suitable models for these three types of prediction and the conditions for the models' application are also identified respectively. Finally, the performance of the proposed approach is examined with the Automated Vehicle Identification (AVI) data, and the accuracy and the practicability are identified successfully. .

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M3 - Paper

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T2 - 13th World Congress on Intelligent Transport Systems and Services, ITS 2006

Y2 - 8 October 2006 through 12 October 2006

ER -

Travel time prediction using probe-car data

Abstract

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All Science Journal Classification (ASJC) codes

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