efficiency | National Center for Sustainable Transportation

Costs, Reliability, Vehicle Characteristics, and Incentives are the Top Factors Influencing Freight Vehicle Technology Choices

Research Product Type

Policy Brief

California has set goals for transitioning the freight sector to near-zero-emission and zero-emission vehicles (ZEVs). California offers several incentive programs to encourage adoption of ZEVs, but purchase decisions are driven by complex factors beyond simple purchase price. Researchers at UC Davis deployed a stated-preference survey of fleet and carrier companies to collect information about vehicle purchase preferences and how they might be influenced by various incentive programs.

Data from: Congestion reduction through efficient container movement under stochastic demand

Research Product Type

Data

The data from this project is primarily randomly generated data sets and demand data for containers near the San Pedro Ports.

Dataset: Compilation of California and US Zero Emission Vehicle Programs, Laws, and Incentives

Research Product Type

Data

These appendices serve as a compilation of California and US Zero Emission Vehicle (ZEV) programs, laws, and incentives.

Dataset: Congestion reduction via personalized incentives

Research Product Type

Data

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.

Dataset: Fostering the use of zero and near zero emission vehicles in freight operations

Research Product Type

Data

This study explored different incentives programs in California and reviewed the literature to identify other potential types of incentives to foster a change.

Dataset: NCST Caltrans project on sensor data error estimation

Research Product Type

Data

The aim of this script is to automate the process of directed network graph formation, i.e., creation of incidence matrix, node adjacency matrix, and map the sensors to appropriate links.

Developing Statistical Models Using Dynamic Network Modeling, Spatiotemporal Analysis, and Theories of AI to Optimize of Transportation System Management

Principal Investigator Yanlin Qi
University of California, Davis

This research is focused on the optimization of transportation system management by developing statistical models involving dynamic network modeling, spatiotemporal analysis, and theories of AI.

Project Status

In Progress

Development of a Freight System Conceptualization and Impact Assessment (Fre‐SCANDIA) Framework

Principal Investigator Miguel Jaller, Ph.D.
University of California, Davis

This project applies life cycle analysis to develop a framework for understanding the impacts of California freight operations.

Project Status

Complete

Development of Eco-Friendly Ramp Control Based on Connected and Automated Vehicle Technology

Principal Investigator Guoyuan Wu
University of California, Riverside

This project uses connected and automated vehicle technology to streamline freeway ramp traffic.

Project Status

Complete

Development of Eco-Friendly Ramp Control for Connected and Automated Electric Vehicles

Research Product Type

Research Report

This project proposed a hierarchical ramp merging system that not only allowed microscopic cooperative maneuvers for connected and automated electric vehicles on the ramp to merge into mainline traffic flow, but also had controllability of ramp inflow rate, which enabled macroscopic traffic flow control.