travel demand

This study develops a model that estimates how the built environment affects the decision to choose ridehailing for making non-work trips.

Microtransit can potentially offer greater efficiency and more equitable service than ride-hailing services, and it may fill gaps in traditional transit services. Aiming to fill this gap, in 2021, researchers at the University of California, Davis conducted focus groups and an online survey of SmaRT Ride adopters and users of other means of transportation in the Sacramento area.

This policy brief aims to answer the following questions: what is the best way to measure individuals’ long-distance travel in order to inform planning and policy, and what factors are associated with long-distance travel and do they suggest inequitable access to intercity and more distant destinations?

This dissertation proposes an inclusive framework to analyze ride-pool services, assuming they implement the mechanism of spatial bipartite matching. An agent-based simulator is developed to validate and calibrate the models.

The goal of this project was to assess the capabilities of the travel demand forecasting models (TDMs) used by California’s metropolitan planning organizations (MPOs) with respect to forecasting the increase in vehicle miles of travel induced by highway capacity expansion.

This study explored potential system-level travel effects of vehicle automation in the San Francisco Bay Area.

Researchers explored what a future with automated vehicles in the San Francisco Bay Area might look like by simulating effects on travel and emissions.

In this project, the researchers consider the issue of coordinating the parking decisions of a large number of long-haul trucks. More specifically, how to model the behavior of a region’s driver population and how it could be influenced.