Attitudes Towards Emerging Mobility Options and Technologies

Attitudes Towards Emerging Mobility Options and Technologies – Phase 3: Survey Data Compilation and Analysis for Tampa, FL

Principal Investigator: Michael Maness, Assistant Professor, Department of Civil and Environmental Engineering
Project Duration: 12 months
​Project Budget (Federal UTC Funds): 
Project Budget (Cost-share): 
 University of South Florida

Emerging transportation technologies including electric and autonomous vehicles and emerging mobility services such as ride-hailing and vehicle sharing are bringing about transformative changes in the transportation landscape. With the emergence of new transportation technologies and services, it is critical that transportation forecasting models be enhanced to account for behavioral dynamics that will result from the increasing penetration of disruptive forces in the transportation marketplace. To enhance transportation forecasting models, people’s attitudes towards and perceptions of emerging technologies and services need to be measured and understood. Armed with such an understanding, it will be possible to specify and develop behavioral models that account for attitudes and perceptions, adoption cycles, and adaptation patterns. It is envisioned that such models will help decision-makers better plan transportation infrastructure systems and design marketing and policy strategies that maximize the benefits of these disruptive technologies. This project aims to collect survey data from a sample of 1000 residents in the Tampa Bay metro area to understand how the market perceives, adopts, and adapts to transformative transportation technologies. The third phase of this research project focuses on the compilation and analysis of survey data in order to better understand people’s preferences and choices for future mobility options and technologies in the Tampa Bay metropolitan area. A comprehensive description of all the steps taken to full deployment, data cleaning, and weighting is provided, in addition to a descriptive weighted univariate illustration of the findings from the Tampa Bay survey sample.

Research Products and Implementation

Scope of Work

​Final Report