transit

What factors could strengthen or discourage a microtransit adopter to continue to use it? Who are these early adopters of microtransit? Guided by the theory of planned behavior, this study aims to fill the gap by conducting a large-scale survey focus on microtransit adopters and other means of transportation users in the Sacramento area of California in 2021 to address these research questions.

This is the dataset for the project "Fuel and Emissions Calculator (FEC) Version 4.0".

The dataset for this study was collected from various sources including Affordable Housing Communities Data, demographic information from the American Community Survey, OpenStreetMap road network, Points of Interest (POIs) data, General Transit Feed Specification (GTFS) data, and Longitudinal Employer-Household Dynamics (LEHD) data.

This is the replication data for a research project examines the link between job access and stop/station level transit ridership.

This is the dataset associated with the report "Simulating Bike-Transit Trips Using BikewaySim and TransitSim."

The dataset provided here is an anonymous version of the survey results of city planning directors in these regions, conducted between April and July, 2019.

This includes data used in the project, "All Aboard! Easier Transit Travel with Standardized Payments". The data was collected from California transit agencies in the fall of 2022 that gathered information about agency perceptions of open-loop payments and the challenges with adopting open fare collection systems, and whether assistance programs would benefit transit agencies interested in adopting open-loop payments.

The California Integrated Travel Project aims to allow transit users to pay for transit throughout the state of California with whichever card based, or electronic means of payment they prefer. However, for some passengers some of these options are not available. In this study the research team explores how these un and underbanked passengers will be able to access open payment systems.

Research performed in this supplemental NCST study improved model algorithms to increase analytical efficiency and to integrate ridership demographics, so that energy use impacts could be assessed across demographic groups for use in social sustainability analysis.

This policy brief summarizes research that tested whether or not rail transit developments cause an influx of high-income residents and an outflow of low-income residents near rail stations.