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 locationbased 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.
|Original language||English (US)|
|Number of pages||11|
|Journal||Transportation Research Record|
|State||Published - 2016|
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Mechanical Engineering