Authors: Jingyi Xiao*, University of California, Santa Barbara
Topics: Transportation Geography, Behavioral Geography
Keywords: mode choices, travel behavior, mobility pattern
Session Type: Paper
Start / End Time: 11:10 AM / 12:25 PM
Room: Spruce, Sheraton, IM Pei Tower, Majestic Level
Presentation File: No File Uploaded
A significant number of individuals in U.S. depends on automobile as their primary travel mode. Understand why people prefer a particular travel mode is very important in constructing more efficient and effective transportation system and to promote greener cities. This paper examines over 25,000 household individuals’ travel behavior from the 2017 National Household Travel Survey data by US residents in all 50 States and the District of Columbia. Whether a person commute by car, public transit or active mode is estimated using multinomial regression and machine learning algorithms based off the commuter’s demographic information, the trip attributes and the regional variation. The results suggest some variables do affect individual’s travel behavior, which informs the governors and city planners in decision-making process.