attitudes

This tabular dataset describes the travel behavior and travel mode related attitudes of residents and bike-share users in the greater Sacramento region.

This dataset is from a usability survey with vehicle cost calculators (VCC) users who tested three VCCs and provide feedback on their usability.

This study explores the impacts of latent attitudes, socio-demographic characteristics, and neighborhood effects on consumers’ current vehicle fuel type choice and their interest in purchasing or leasing an alternative fuel vehicles in the future.

Long-distance travel research is limited due to the lack of robust data and the complexity of defining a long-distance trip. This study contributes to filling that gap by investigating the factors that affect the frequency of long-distance trips of Californian millennials and members of the preceding Generation X.

This study employs a novel approach combining spatial analysis and Factor Analysis of Mixed Data (FAMD) to delve into bikeshare users’ perceptions and expectations based on bikeshare systems' online platforms for user feedback.

This study uses data from bike-share user surveys in the Sacramento region to perform market segmentation based on perceptions of the bike-share service, mode use patterns, and bike-share use.

Bike-share systems are proliferating across the US and could expand opportunities for those most underserved by the transportation system. A deeper understanding of current bike-share users could enable the expansion of these services and their benefits to a larger population.

Researchers at the University of California, Davis surveyed residents and employees of the West Village area of the UC Davis campus during the three-month pilot deployment of a self-driving, electric shuttle to understand attitudes toward self-driving technology. This policy brief summarizes findings from that research and provides policy implications of self-driving shuttles.