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 |
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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 |
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Country/Territory | 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