Research Brief

This research brief summarizes the associated project, which developed a methodology that combines urban metabolism and life cycle assessment to examine the life cycle impacts of hardscapes at the urban scale rather than at the product or project scale.

Researchers at the University of Southern California developed a truck routing model that minimizes fuel consumption and reduces emissions while explicitly accounting for parking availability and hours-of-service constraints. The researchers used the model to test various scenarios that reflect the practical constraints faced by drivers.

This brief summarizes research findings from the University of California, Riverside, on a prediction-based, adaptive connected eco-driving strategy to account for real-world uncertainties.

The University of California, Davis and the California Energy Commission held a series of three Emerging Technologies Workshops to identify environmentally and economically promising alternative fuel and vehicle emerging technologies.

In this study, researchers from the University of Southern California investigated the adoption of battery electric heavy-duty trucks (BEHDTs) in the short-haul freight movement sector and the drayage industry.

Researchers at the Georgia Institute of Technology created a semi-automated process for developing an all-streets network to be used in TDM applications to more accurately model bicycle travel.

Researchers at the University of Southern California developed a real-time, distributed algorithm for offering personalized incentives to individual drivers to make socially optimal routing decisions.

Researchers examined the possibility of ride-sharing being able to mitigate traffic congestion by developing a two-stage algorithm to solve the routing problem with ride-share in real-time within a context where ride-sharing drivers are traveling toward their own destinations while making detours to serve passengers with flexible pickup and drop-off locations.

This brief summarizes findings from researchers at the University of Southern California who developed an optimization-based vehicle scheduling model that allows for a “street exchange” in which empty containers can go directly from importers to exporters without returning to the port.

This research brief presents a new model for predicting heavy-duty vehicle fuel savings from using low rolling resistance tires.