Application of a Multi-Agent System with the Large-Scale Agent-Based Model for Freight Demand Modeling [Research Brief]

Lee, EunSu; Taleqani, Ali Rahim; Park, Yong Shin

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Application of a Multi-Agent System with the Large-Scale Agent-Based Model for Freight Demand Modeling [Research Brief]

2018-11-01
By Lee, EunSu ; Taleqani, Ali Rahim ; Park, Yong Shin

File Language:

English

Details

Creators:

Lee, EunSu ; Taleqani, Ali Rahim ; Park, Yong Shin
Corporate Creators:

New Jersey City University ; North Dakota State University ; Upper Great Plains Transportation Institute ; Mountain-Plains Consortium
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Publication/ Report Number:

MPC-18-370
Resource Type:

Brief
Geographical Coverage:

North Dakota ; United States
Edition:

Research Brief
Corporate Publisher:

Mountain-Plains Consortium
Abstract:

In this study, researchers used the agent-based simulation (ABS) for modeling agricultural transportation demand. With the simulation model, geographic information systems (GIS) was utilized to collect and analyze remote sensing of agricultural crops. The researchers reviewed agent-based modeling in freight and public transportation planning to fill the gap between traditional modeling efforts and emerging needs of adopting behavioral modeling for an agricultural transportation model. The study then investigated adoption of an agent-based model for a large-scale travel demand model. The objective of the proposed model was to provide a platform to analyze grain transportation movement at the micro-level, since most industry reports lack such micro-level freight analysis while supporting regional and statewide planning.
Format:

PDF
Funding:

MPC-458
Download URL:

https://rosap.ntl.bts.gov/view/dot/68721/dot_68721_DS1.pdf
File Type:

[PDF - 556.83 KB]
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha256:894c0fffee109d31cdfb0af541abf14964075af65286fa0012ca5abe8f36518a

File Language:

English

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