Estimating vehicle trajectories on a motorway by data fusion of probe and detector data

Masao Kuwahara; Takeshi Ohata; Tsubasa Takigawa; Koichi Abe; Satoshi Watanabe; Hiroshi Warita; Kiichiro Nakamura; Takeshi Imai; Hiroyuki Tsuda

Estimating vehicle trajectories on a motorway by data fusion of probe and detector data

Masao Kuwahara, Takeshi Ohata, Tsubasa Takigawa, Koichi Abe, Satoshi Watanabe, Hiroshi Warita, Kiichiro Nakamura, Takeshi Imai, Hiroyuki Tsuda

INF - Human-Social Information Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In this study, we propose a data fusion technique to estimate trajectories of all running vehicles on an intercity motorway based on probe vehicle data and conventional traffic detector data. Although probe vehicle data are getting popular, their rich information on vehicle trajectories have not been fully utilized but mostly reduced travel time information have been used. The objective of this research is therefore to examine a data fusion framework to reconstruct vehicle trajectories by combining traffic data with conventional traffic detectors and probe vehicle data based on the kinematic wave theory and implements the solution by the variational theory proposed by Daganzo. And we utilize trajectories and examine how to get the useful information for drivers, which is travel time.

Original language	English
Title of host publication	20th ITS World Congress Tokyo 2013
Publisher	Intelligent Transportation Society of America
Publication status	Published - 2013
Event	20th Intelligent Transport Systems World Congress, ITS 2013 - Tokyo, Japan Duration: 2013 Oct 14 → 2013 Oct 18

Other

Other	20th Intelligent Transport Systems World Congress, ITS 2013
Country	Japan
City	Tokyo
Period	13/10/14 → 13/10/18

Keywords

Data fusion
Trajectory
Variational theory

ASJC Scopus subject areas

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

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Estimating vehicle trajectories on a motorway by data fusion of probe and detector data. / Kuwahara, Masao; Ohata, Takeshi; Takigawa, Tsubasa; Abe, Koichi; Watanabe, Satoshi; Warita, Hiroshi; Nakamura, Kiichiro; Imai, Takeshi; Tsuda, Hiroyuki.

20th ITS World Congress Tokyo 2013. Intelligent Transportation Society of America, 2013.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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title = "Estimating vehicle trajectories on a motorway by data fusion of probe and detector data",

abstract = "In this study, we propose a data fusion technique to estimate trajectories of all running vehicles on an intercity motorway based on probe vehicle data and conventional traffic detector data. Although probe vehicle data are getting popular, their rich information on vehicle trajectories have not been fully utilized but mostly reduced travel time information have been used. The objective of this research is therefore to examine a data fusion framework to reconstruct vehicle trajectories by combining traffic data with conventional traffic detectors and probe vehicle data based on the kinematic wave theory and implements the solution by the variational theory proposed by Daganzo. And we utilize trajectories and examine how to get the useful information for drivers, which is travel time.",

keywords = "Data fusion, Trajectory, Variational theory",

author = "Masao Kuwahara and Takeshi Ohata and Tsubasa Takigawa and Koichi Abe and Satoshi Watanabe and Hiroshi Warita and Kiichiro Nakamura and Takeshi Imai and Hiroyuki Tsuda",

year = "2013",

language = "English",

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T1 - Estimating vehicle trajectories on a motorway by data fusion of probe and detector data

AU - Kuwahara, Masao

AU - Ohata, Takeshi

AU - Takigawa, Tsubasa

AU - Abe, Koichi

AU - Watanabe, Satoshi

AU - Warita, Hiroshi

AU - Nakamura, Kiichiro

AU - Imai, Takeshi

AU - Tsuda, Hiroyuki

PY - 2013

Y1 - 2013

N2 - In this study, we propose a data fusion technique to estimate trajectories of all running vehicles on an intercity motorway based on probe vehicle data and conventional traffic detector data. Although probe vehicle data are getting popular, their rich information on vehicle trajectories have not been fully utilized but mostly reduced travel time information have been used. The objective of this research is therefore to examine a data fusion framework to reconstruct vehicle trajectories by combining traffic data with conventional traffic detectors and probe vehicle data based on the kinematic wave theory and implements the solution by the variational theory proposed by Daganzo. And we utilize trajectories and examine how to get the useful information for drivers, which is travel time.

AB - In this study, we propose a data fusion technique to estimate trajectories of all running vehicles on an intercity motorway based on probe vehicle data and conventional traffic detector data. Although probe vehicle data are getting popular, their rich information on vehicle trajectories have not been fully utilized but mostly reduced travel time information have been used. The objective of this research is therefore to examine a data fusion framework to reconstruct vehicle trajectories by combining traffic data with conventional traffic detectors and probe vehicle data based on the kinematic wave theory and implements the solution by the variational theory proposed by Daganzo. And we utilize trajectories and examine how to get the useful information for drivers, which is travel time.

KW - Data fusion

KW - Trajectory

KW - Variational theory

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