Title :
Transportation Mode Split with Mobile Phone Data
Author :
Yingchun Qu;Hang Gong;Pu Wang
Author_Institution :
Sch. of Traffic &
Abstract :
Mode split is an important step in the estimation of travel demand. Beside traditional costly surveys, many mode split methods, which employ the new emerging large-scale social signal data, are recently proposed. In this paper, we develop a mode split model based on the widely available mobile phone data and transportation networks´ geographical data. The shares of three transportation modes (car, public transportation, walking) in each census tract are estimated for Boston central and suburb area. Finally, the proposed model is validated with real mode share data obtained from the U.S. census.
Keywords :
"Mobile handsets","Public transportation","Global Positioning System","Legged locomotion","Data models","Roads"
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on
Electronic_ISBN :
2153-0017
DOI :
10.1109/ITSC.2015.56