transportation systems

In rural areas, cost-effective transit service is challenging due to greater travel distances, lower population densities, and longer travel times than in cities. UC Davis partnered with the eight San Joaquin Valley Metropolitan Planning Organizations to identify and support development of three innovative mobility pilot concepts for the region.

To validate their approach, the authors construct test cases based on the New York City taxicab dataset.

Dataset used in the project "Tools and Best Practices for Land Use Efficiency and Equity in Cities" by Peter Nguyen and Jesus M. Barajas.

This study develops a low-cost and easily extendable data-driven framework for crash modification factor predictions.

This report describes the scope and scale of car access in rural areas, identifies barriers that rural zero-car and car-deficit households face in their mobility and access, and proposes personal and policy-level adaptations that would help these households achieve their mobility and access needs using descriptive analysis from US census microdata and interviews with 22 residents of California’s Central Valley.

A robust rideshare system needs to take uncertainties such as traffic congestion and passenger cancellations into account. In this report, the authors propose a data-driven stochastic rideshare system that integrates those sources of uncertainties.