This project’s objective was to study the truck parking problem and generate useful information and parking assist algorithms that could assist truck drivers in better planning their trips.
This project explores the probability of developing a centrally coordinated routing system for trucks. The project develops a method for estimating the utility functions of truck drivers based on their response to a centrally coordinated routing system that they are participating, and it also evaluates the impact of assumed wrong utility functions that could be viewed as non-compliance on the system optimum cost.
This project developed a set of traffic simulation models for the Los Angeles/Long Beach region that allowed the researchers to evaluate impacts on transportation system efficiency and on the environment.
This study will examine how transit system characteristics –including frequencies, routes, and travel times –are associated with ridership, with a focus on buses.
The purpose of this project is to integrate solutions for eco-routing and practical constraints, and develop a more practical model for eco-routing in the trucking industry.
This project will develop a framework that will, in real-time, match drivers to passengers and route rideshare drivers that incorporates traffic data to provide improved solutions. The resulting solution framework will use commercial traffic simulation software to achieve this goal.
The objective of this project is to demonstrate an aftermarket “retrofit kit” for small (10-30kW) diesel generators, capable of capturing particulate matter (PM) emissions (i.e., soot) to levels be
This project proposes using intelligent transportation system (ITS) technologies that take into account the presence of trucks in the traffic flow. The researchers anticipate that this will improve impact on the environment by reducing fuel consumption and pollution levels in areas where the truck volume is relatively high.
