A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Origin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data
Identifying accurate origin-destination (O-D) travel demand is one of the most important and challenging tasks in the transportation planning field. Recently, a wide range of traffic data has been made available. This paper proposes an O-D estimation model using multiple field data. This study takes advantage of emerging technologies – car navigation systems, highway toll collecting systems and link traffic counts – to determine O-D demand. The proposed method is unique since these multiple data are combined to improve the accuracy of O-D estimation for an entire network. We tested our model on a sample network and found great potential for using multiple data as a means of O-D estimation. The errors of a single input data source do not critically affect the model’s overall accuracy, meaning that combining multiple data provides resilience to these errors. It is suggested that the model is a feasible means for more reliable O-D estimation.
Origin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data
Identifying accurate origin-destination (O-D) travel demand is one of the most important and challenging tasks in the transportation planning field. Recently, a wide range of traffic data has been made available. This paper proposes an O-D estimation model using multiple field data. This study takes advantage of emerging technologies – car navigation systems, highway toll collecting systems and link traffic counts – to determine O-D demand. The proposed method is unique since these multiple data are combined to improve the accuracy of O-D estimation for an entire network. We tested our model on a sample network and found great potential for using multiple data as a means of O-D estimation. The errors of a single input data source do not critically affect the model’s overall accuracy, meaning that combining multiple data provides resilience to these errors. It is suggested that the model is a feasible means for more reliable O-D estimation.
Origin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data
Kim, Hyunmyung (author) / Nam, Daisik (author) / Suh, Wonho (author) / Cheon, Seung Hoon (author)
Transportation Planning and Technology ; 41 ; 265-285
2018-04-03
21 pages
Article (Journal)
Electronic Resource
English
Dynamic Origin-Destination Trip Demand Estimation for Subarea Analysis
| British Library Online Contents | 2006
Method To Enhance Performance of Synthetic Origin-Destination Trip-Table Estimation Models
| British Library Online Contents | 1999
Improved Path Flow Estimator for Origin-Destination Trip Tables
| British Library Online Contents | 2005
Examining the Quality of Synthetic Origin-Destination Trip Table Estimated by Path Flow Estimator
| Online Contents | 2005
Maximum Entropy Method for Subnetwork Origin-Destination Trip Matrix Estimation
| British Library Online Contents | 2010