Developing Mesoscopic Models for the Before and After Study of the Inter-county Connector: Phase-One [Research Summary]

Zhang, Lei; Chang, Gang-Len

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Developing Mesoscopic Models for the Before and After Study of the Inter-county Connector: Phase-One [Research Summary]

2013-03-01
By Zhang, Lei ; Chang, Gang-Len

File Language:

English

Details

Creators:

Zhang, Lei ; Chang, Gang-Len
Corporate Creators:

University of Maryland (College Park, Md.). Department of Civil and Environmental Engineering
Subject/TRT Terms:
Publication/ Report Number:

SP109B4P
Resource Type:

Brief
Geographical Coverage:

Maryland
Corporate Publisher:

Maryland. State Highway Administration
Description:

It has become apparent in recent years that significant benefits will be obtained if the Maryland State Highway Administration (SHA) can combine its data products and modeling tools for integrated transportation operations and planning. Examples of integrating operations and planning at SHA include: archiving ITS/operations/count data for planning applications and performance monitoring; applying travel demand models to evaluate operations projects; and combining travel demand and microscopic traffic simulation models for more efficient congestion management at the corridor level. In addition to these general benefits, integrating microscopic operations and macroscopic planning models is also necessary for a variety of scenarios and policy analyses that are important to SHA. For instance, it is desirable to develop mesoscopic models that link microscopic traffic simulation, dynamic traffic assignment, and travel demand models to analyze both the local congestion effects and the regional demand effects.
Format:

PDF
Download URL:

https://rosap.ntl.bts.gov/view/dot/25776/dot_25776_DS1.pdf
File Type:

[PDF - 100.93 KB]
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha-512:cdc8d59311c238b4266c42fd6ec656d6a00bff4bce0ce2b6a46f4a88f768505b71e8a5b9fb7a660bf23bd1dc17943bf194aac83ae44b2e6554aaee4294fa1e6f

File Language:

English

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