Social and Behavioral Sciences Commons^™

Transportation Mode Choice Behavior In The Era Of Autonomous Vehicles: The Application Of Discrete Choice Modeling And Machine Learning, Sangwan Lee

Dissertations and Theses

New mobility technologies, such as shared mobility services (e.g., car-sharing) and, more importantly, autonomous vehicles (AVs), continue to evolve. The supply-side advancement will likely disrupt and transform transportation mode choice behaviors, and create a new paradigm since they are emerging and becoming increasingly feasible alternatives to the existing modes of transportation. Accordingly, this dissertation employs discrete choice modeling (DCM) and machine learning (ML) using a U.S. nationwide stated choice experiment to understand how travelers adopt new transportation modes or continue to use conventional modes of transportation.

This dissertation consists of three papers. The first examines future market shares of each …

Recent Advances In Activity-Based Travel Demand Models For Greater Flexibility, Kihong Kim

Dissertations and Theses

Most existing activity-based travel demand models are implemented in a tour-based microsimulation framework. Due to the significant computational and data storage benefits, the demand microsimulation allows a greater amount of flexibility in terms of demographic market segmentation, temporal scale, and spatial resolution, and thus the models can represent a wider range of travel behavior aspects associated with various policies and scenarios. This dissertation proposes three innovative methodologies, one for each of the three key dimensions, to fulfill the greater level of details toward a more mature state of activity-based travel demand models.

Travel Mode Choice Framework Incorporating Realistic Bike And Walk Routes, Joseph Broach

Dissertations and Theses

For a number of reasons--congestion, public health, greenhouse gas emissions, energy use, demographic shifts, and community livability to name a few--the importance of walking and bicycling as transportation options will only continue to increase. Currently, policy interest and infrastructure funding for nonmotorized modes far outstrip our ability to model bike and walk travel. To ensure scarce resources are used most effectively, accurate models sensitive to key policy variables are needed to support long-range planning and project evaluation, and to continue adding to our growing understanding of key factors driving walk and bike behavior. This research attempts to synthesize and advance …