01593374

Component

https://doi.org/10.3141/2564-05

With many of today’s metropolitan areas experiencing changes in population and land development faster than the traditional transportation planning efforts can be undertaken, new methods for transportation planning are constantly being explored. This paper presents a novel approach to the transportation planning problem through the use of location-based social networking data and the many-to-many modeling structure of peer-to-peer modeling. With smartphone and tablet use increasing in the United States, many popular social networking sites have begun to include geospatial location in their platforms, and location-based social networking data sources have become attractive data sets for the transportation community because of their ability to be representative of populations and to provide detailed spatial–temporal data. The novel origin–destination estimation method through peer-to-peer modeling is presented, and a case study example of Austin, Texas, provides initial findings through a comparison against a doubly constrained gravity model and an existing origin–destination matrix for the study area. This first look at peer-to-peer modeling for origin–destination estimation revealed the method’s strengths with respect to intrazonal trip estimations and production and attraction estimations and was found to be more computationally efficient than the doubly constrained gravity model.

01624690

16-4531

English

pp 41–51

2016

Transportation Research Record: Journal of the Transportation Research Board

9780309441452

Print

Figures (4) ; Maps; References (52) ; Tables (2)

Case studies; Metropolitan areas; Mobile applications; Origin and destination; Population density; Smartphones; Transportation planning

Austin (Texas)

Data and Information Technology; Planning and Forecasting; Transportation (General)

TRIS, TRB, ATRI

Jan 12 2016 6:00PM

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