The purpose of this project is to apply computational tools from topological data analysis (TDA) to study the logistics systems in the state of California and the USA, with an emphasis on freight networks.
The main objective of this project is to develop a centralized truck parking system that will balance parking utilization in time and space by using full information about supply and demand.
The purpose of this project is to develop a CENtrally COordinated Shuttle system (CENCOS) which can effectively coordinate airport shuttle schedules and routes in order to minimize curb congestion at the pick-up and drop-off points, reduce operational cost, improve quality of service with considerable benefits to mobility and environment.
The researchers created a model to solve the "Empty Container Problem" of freight operations. They tested the model using data from the Port of Los Angeles and the Port of Long Beach.
The purpose of this research is to develop real-time algorithms to reduce traffic congestion and improve routing efficiency via offering personalized incentives to drivers.
This project will investigate how connectivity provided by vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) technologies can be used to develop traffic flow control systems that will enhance mobility and safety, and reduce queues at ramps with positive benefits to transportation efficiency and environment.
This project examines the potential for zero-emission and near-zero emission truck technologies from both economic and environmental perspectives, focusing on their use in short-haul drayage service.
This report evaluates the market status and potential freight market penetration of zero emission vehicles (ZEVs) and near-ZEVs in the medium and heavy duty class within the California market. It focuses on intra-urban rather than long-haul deployment scenarios.
