Carrel, Andre

Biography

Dr. Andre L. Carrel is an assistant professor of transportation and the director of the Ohio State Travel Behavior Research Group. His expertise is in travel demand modeling and public transportation, and his research focuses on the dynamics of travel behavior, travelers’ adaptation to experienced service quality, and the impact of emerging mobility technologies on travel behavior. His research contributes to the forecasting of long-term trends in travel behavior and has practical implications for designing policies to promote more sustainable travel choices and to strengthen public transportation. His principal methods involve complex, survey-based studies, discrete choice models, and the integration of automatically collected data from mobile phones with survey data. Dr. Carrel is jointly appointed in Civil Engineering and City and Regional Planning and is a core faculty member of the Ohio State Translational Data Analytics Institute. He is the recipient of a 2021 NSF CAREER award. Dr. Carrel graduated from UC Berkeley, MIT, and ETH Zurich, and was a postdoctoral associate at the MIT Center for Transportation and Logistics. His academic experience spans both passenger transportation and logistics.

Expertise

Dr. Carrel's research interests include:

  • Understanding the influence of autonomous, shared, and alternative-fuel transportation technologies on travel behavior
  • Incorporating the effect of past experiences and habits into travel behavior and demand models
  • Leveraging new data collection technologies to improve the collection of travel behavior data
  • Understanding and mitigating the effect of unreliability on public transportation passengers and operations
  • Designing new operating models for public transportation, shared mobility systems and freight systems that make use of connected vehicle and automation technologies
  • Understanding the interaction between supply chain management strategies, shopping behavior, and travel demand
  • Acquisition and statistical analysis of large-scale data sets from emerging data sources to understand and influence traveler choices and facilitate the design, operations and monitoring of transportation and logistics systems.