Abstract
Substantial development in Dynamic traffic assignment (DTA) methods has resulted in a new generation of applicable DTA-based tools for operational planning and evaluation of ITS deployment. However, the computational intensiveness of simulation-based DTA methodologies places limitations on the application of such tools to large-scale networks. To allow the consideration and rapid evaluation of large number of scenarios, a subarea analysis capability is critically needed to support transportation network planning and operations decisions for situations that may not require analysis on a complete network representation. This paper describes a two-stage subarea network extraction and zonal aggregation procedure using a simulation-based DTA model. The first stage extracts a subarea network from the original network and generates an induced OD demand matrix. Based on an iterative bi-level subarea OD estimation method, the second stage finds a consistent network flow pattern by utilizing the induced OD demand information in combination with network assignment results and archived traffic measurements in the subarea network. The proposed procedure was applied to the Southern California Association of Governments (SCAG) regional transportation planning network.
Original language | English (US) |
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Title of host publication | Intelligent Transportation Society of America - 12th World Congress on Intelligent Transport Systems 2005 |
Pages | 4972-4990 |
Number of pages | 19 |
Volume | 8 |
State | Published - Dec 1 2009 |
Event | 12th World Congress on Intelligent Transport Systems 2005 - San Francisco, CA, United States Duration: Nov 6 2005 → Nov 10 2005 |
Other
Other | 12th World Congress on Intelligent Transport Systems 2005 |
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Country/Territory | United States |
City | San Francisco, CA |
Period | 11/6/05 → 11/10/05 |
Keywords
- Dynamic traffic assignment
- Network aggregation
- Origin-destination demand estimation
- Subarea analysis
- Zonal aggregation
ASJC Scopus subject areas
- Mechanical Engineering
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Transportation
- Automotive Engineering
- Computer Networks and Communications
- Artificial Intelligence
- Computer Science Applications