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The Application of Venue-Side Location-Based Social Networking (VS-LBSN) Data in Dynamic Origin-Destination Estimation

The Application of Venue-Side Location-Based Social Networking (VS-LBSN) Data in Dynamic Origin-Destination Estimation
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Author(s): Fan Yang (University of Wisconsin – Madison, USA), Peter J. Jin (Rutgers University, USA), Meredith Cebelak (University of Texas – Austin, USA), Bin Ran (Southeast University, China & University of Wisconsin – Madison, USA)and C. Michael Walton (University of Texas – Austin, USA)
 Copyright: 2018
 Pages: 21
 Source title: Intelligent Transportation and Planning: Breakthroughs in Research and Practice
Source Author(s)/Editor(s): Information Resources Management Association (USA)
 DOI: 10.4018/978-1-5225-5210-9.ch016

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Abstract

Location-Based Social Networking (LBSN) allows users to confirm their current locations and trip purposes by “checking in” with places of interests (“venues”) registered at the LBSN Websites. Such individual activity data provides the potential to collect dynamic travel demand data in a temporal and spatial resolution that cannot be achieved using traditional survey-based methods. In this chapter, the authors investigate and propose LBSN data-based urban travel demand estimation methods—specifically, the dynamic Origin-Destination (OD) demand estimation. This chapter investigates the feasibility of using VS-LBSN data to estimate dynamic Origin-Destination (OD) travel demand for general trips. A combined non-parametric cluster and regression model is used to establish the relationship between VS-LBSN data and the trip production and attraction. A modified gravity model-based trip distribution method with three friction function variations is proposed to estimate the OD matrix. The proposed methods are calibrated and evaluated against the ground truth OD data from CMAP (Chicago Metropolitan Agency for Planning). The results demonstrate the promising potential of using VS-LBSN data for dynamic OD estimation.

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