Research

 

Research Interests

Research Highlights

Planning and Policy: Technology Adoption Behavior

This line of research explores humans' reaction to advances in transportation systems by analyzing human behavior, decision-making, sentiment, attitudes, and preferences. This is accomplished through both: (i) empirical studies by collecting data on human subjects who respond to questionnaires such as travel diary survey; and (ii) experimental studies by collecting data on human subjects exposed to a field or a simulated environment. The collected databases are then analyzed in the modeling frameworks built on economics (e.g., theory of choice behavior), statistics, and psychology (e.g., theory of planned behavior and technology acceptance model). By recognizing heterogeneous cohorts of individuals behaving differently regarding technology acceptance and adoption behavior, the findings can provide policy makers and stakeholders with incentivizing policy recommendations effectively geared towards appropriate population groups.

Planning and Policy: Dynamics of Household (Electric) Vehicle Ownership

Electric vehicles (EVs) promise for positive impacts on energy security, climate change, and public health which are yet to be entirely manifested (especially in the U.S.) through widespread EV adoption. To increase EV market penetration, this line of research explores EV adoption behavior by designing empirical studies including: (i) data collection (such as first-of-a-kind national household retrospective vehicle survey conducted by our group); and (ii) developing novel modeling frameworks on dynamics of household vehicle ownership decisions such as vehicle transaction, fuel type, use, and ownership level. By mapping the households' decisions to their demographic attributes, travel patterns, and attitudes, the research outcome is useful to inform policy makers, for instance, about the impacts of EV charging infrastructure on EV adoption behavior and efficiency of national- and state-level policy incentives (e.g., tax exemption, free parking, and access to exclusive lanes for high occupancy vehicles).

Designing Smart Moving Infrastructure: Human-Technology Interaction

This research path aims at comprehending how users of smart transportation systems interact in real-time with the transportation technologies through an in-depth analysis of human feeling, emotion, and affect, which leads to designing technological infrastructures enabled to “partner” with users, for instance, automated vehicles (AVs) endowed to “empathize” with users. The outcome contributes to the flourishing area of human-technology interaction and is further fed into the above research directions (i.e., planning and policy for smart transportation infrastructure) to enrich the analysis, as a vital step in better understanding users’ response to the technologies is understanding their interaction.

Smart Infrastructure Management: Health Monitoring and Maintenance

In the research path on the management/operation of smart transportation infrastructure, the focus is on lifecycle asset management of fixed (e.g., roadways) and rolling (e.g., trains) infrastructure by considering the role of technologies such as embedded sensors or unmanned aerial vehicles (e.g., drones) for collecting data on the infrastructure condition. This is accomplished by employing and extending methods from various disciplines such as mathematical science (e.g., operations research), computer science (e.g., 3D convolutional neural network), and statistics.