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. 2014 by IGI Global. All rights reserved.
| Original language | English (US) |
|---|---|
| Title of host publication | Mobile Technologies for Activity-Travel Data Collection and Analysis |
| Publisher | IGI Global |
| Pages | 239-257 |
| Number of pages | 19 |
| ISBN (Electronic) | 9781466661714 |
| ISBN (Print) | 1466661704, 9781466661707 |
| DOIs | |
| State | Published - Jun 30 2014 |
All Science Journal Classification (ASJC) codes
- Social Sciences(all)
- Economics, Econometrics and Finance(all)
- Business, Management and Accounting(all)