Research Project

This project seeks to unpack the political opposition to gasoline taxes, by examining how precinct-level support for California Proposition 6, which would have immediately reduced state gasoline taxes, covaries with the political ideology of voters and the economic burden of gasoline taxes.

The objectives of this project are to expand the previous work to evaluate the potential benefits of dockless systems to improve accessibility to disadvantaged communities, and to compare them with dock‐based systems. Specifically, the project will analyze the difference in service levels among dock‐based and dockless systems.

This project examines the potential for single-occupancy drivers to use public transit in their morning commutes. (For the final project, the researchers switched the study location from the Sacramento area to the San Francisco Bay area.)

The objective of this research is to develop dynamic routing algorithms to support ridesharing.

This work studies the optimization of scheduling of chassis and container movements at the operational level for individual trucking companies when Chassis Processing Facilities (CPFs) are available for use in the vicinity of a container port within a major metropolitan area.

This project evaluates benefits from transit vehicle eco-driving.

The research team will build on past research to develop new cooperative traffic operation methods, methods that take advantage of not only infrastructure-to-vehicle communications, but also vehicle-to-infrastructure communications.

The researchers use Eco-Friendly Intelligent Transportation Systems (ECO-ITS) to log real-time vehicle and engine/after treatment data to accurately establish truck baseline fuel consumption and emissions and quantify fuel and emission savings.

In this project, the researchers present an agent-based online adaptive signal control strategy based on real-time traffic information available from vehicles equipped with Connected Vehicle technology, with the goal of making freight operations more sustainable.

This project examines intelligent traffic control strategies, which will have positive impact on the environment by reducing fuel consumption and pollution levels in areas where the truck volume is relatively high.