Arefeh Nasri
University of Maryland, College Park
27 Papers
80 Citations
Arefeh Nasri is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Travel behavior & Metropolitan area. The author has an hindex of 12, co-authored 26 publications. Previous affiliations of Arefeh Nasri include Rutgers University.
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Papers
The analysis of transit-oriented development (TOD) in Washington, D.C. and Baltimore metropolitan areas
Arefeh Nasri,Lei Zhang +1 more
TL;DR: In this paper, the authors tried to understand how travel behavior is different for transit-oriented development (TOD) residents in the two metropolitan areas of Washington, D.C. and Baltimore.
252
How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities
TL;DR: In this article, the authors examined the effects of built environment factors on travel behavior, in particular VMT in five U.S. metropolitan areas grouped into four case study areas, and found that promoting compact, mixed-use, small-block and infill developments can be effective in reducing VMT per person.
Analysis of Washington, DC taxi demand using GPS and land-use data
TL;DR: In this paper, the authors investigated the correlation between demand for taxi, land use patterns, and accessibility to other modes using detailed GPS and GIS information collected from the Washington D.C. metropolitan area.
102
How transit service closures influence bikesharing demand; lessons learned from SafeTrack project in Washington, D.C. metropolitan area
TL;DR: In this paper, the authors examined changes in bikeshare ridership due to rail transit closures in the Washington, D.C. area and investigated how promoting bikshare systems in large metropolitan areas could be beneficial in cases of transit disruptions regardless of the type, cause, and duration.
48
Impact of Metropolitan-Level Built Environment on Travel Behavior
Arefeh Nasri,Lei Zhang +1 more
TL;DR: In this article, an extensive database is used for six major metropolitan areas in the United States to employ a multilevel mixed-effect model that highlights the impact of built environment characteristics on travel behavior at different scales.