The researchers used mobile crowd-sourced data to create an effective tool that evaluates the environmental impact of traffic congestion in an accurate, timely and economic way.
The purpose of this study is to develop an analytical framework for assignment of individual vehicular trips into viable carpooling pairs under a constrained set of reasonable restrictions, such as temporal and spatial bounds/limits and user preferences.
The research team will utilize the before/after “Smart Pedal” data to conduct a cost/benefit analysis of the top 2% of Caltrans Fleet vehicles which would benefit from “Smart Pedal” technology installation.
This study investigates the effect of different binder sources used in California pavement production, focusing on recycled asphalt materials in comparison to virgin binders.
This project focuses on safety, mobility, and environmental sustainability Measures of Effectiveness (MOEs) of Connected and Automated Vehicle (CAV) applications.
This project focuses on Connected and/or Automated Vehicle (CAV) applications. The researchers studied different types of CAV applications in terms of measures of effectiveness.
This project aims to understand the secondary pollutants that form when vehicle exhaust reacts with atmospheric oxidants. This project encompasses various studies related to the main objective.
This white paper develops a framework for combining urban (UM), material flow analysis (MFA) and elements of life cycle assessment (LCA) to measure and improve the efficiency of urban hardscape in large urbanized areas.
In this project, CSULB will develop a series of case studies designed to evaluate the impacts of freight-related environmental policies. The team will then produce brief videos to accompany the case studies research, in order to reach a wider audience.
In this project, the researchers will develop a methodology to reduce freight system inefficiencies by incorporating a centrally coordinated load balancing system.
