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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication20th ITS World Congress Tokyo 2013
PublisherIntelligent Transportation Society of America
Publication statusPublished - 2013
Event20th Intelligent Transport Systems World Congress, ITS 2013 - Tokyo, Japan
Duration: 2013 Oct 142013 Oct 18

Other

Other20th Intelligent Transport Systems World Congress, ITS 2013
CountryJapan
CityTokyo
Period13/10/1413/10/18

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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