01519378

Component

https://doi.org/10.3141/2430-08

http://scholar.google.com...+Ran&publication_year=2014

Trip distribution is an invaluable portion of the transportation planning process; this distribution leads to the creation of origin–destination (O-D) matrices. Location-based social networking (LBSN) has increased in popularity and sophistication and has emerged as a new travel demand data source. Users of LBSN provide location-sensitive data interactively with mobile devices, including smartphones and tablets. These data can provide O-D estimates with significantly higher temporal resolution at a much lower cost in comparison with traditional methods. An LBSN O-D estimation model based on the doubly constrained gravity model was proposed to improve a previously proposed model based on the singly constrained gravity model. The proposed methodology was calibrated and comparatively evaluated against the O-D matrix generated by the method based on the singly constrained gravity model as well as a reference matrix from the local metropolitan planning organization. The results of this method illustrate significant improvement in reducing the O-D estimation errors caused by the sampling bias from the method based on the singly constrained gravity model.

01543148

14-5314

English

pp 72–82

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295185

Print

Figures (5) ; References (36) ; Tables (2)

Gravity models; Origin and destination; Transportation planning; Travel demand; Trip distribution; Trip matrices

Social networking

Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 27 2014 3:51PM

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