Projects

This white paper will evaluate revenue-neutral mechanisms to  encourage zero emission vehicle (ZEV) sales in the US, with no net cost to taxpayers.

This research will develop a total cost of ownership (TCO) model and online vehicle cost calculator (VCC) for transport network company (TNC) drivers. Many VCCs have been developed to support consumers in calculating the relative costs of electric and gas vehicles, but their design and the TCO models that underlie them are geared toward traditional vehicle ownership.

The electrification of privately owned vehicles is a necessary step to eliminating transportation greenhouse gas emissions. The adoption of electric vehicles so far has been heavily focused among high-income commuters who live in major metropolitan areas.

Given the increase in demand and incentives for e-bicycling; this project seeks to evaluate the behavioral effects (change in bicycling, driving, use of transit) of these incentives to help guide future policy interventions for e-bicycling. The researchers will examine these changes based on survey data, and will propose future study designs for more in-depth analyses and evaluations of e-bike incentives.

This project will develop a practical tool for policymakers to infer the effects of alternative strategies for reducing traffic congestion in Los Angeles. 

This research aims to develop an Artificial Neural Network (ANN) to forecast EVs’ trip destinations and charging behavior–information that is essential for electricity load aggregators to effectively manage charging loads.

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.

This research will examine four consequences of freeway construction on minority neighborhoods.

This research will focus on reconstructing fundamental diagrams of heterogeneous traffic from trajectory data.

This research will develop plausible scenarios for land-based passenger mobility over a ten-year horizon leading to 2030, and evaluate potential outcomes and impacts.

The research team will investigate how accessibility of city blocks is quantified through the transport systems utilizing real traffic flow data from the Los Angeles Metropolitan Area.

The research team will create a quantitative spatial equilibrium model of on-site and remote worker location choice and transport demand in the contiguous United States in order to examine how the distribution of jobs and residents within and across U.S. cities would change if the 2020 surge in working from home becomes permanent, and what the effect on demand for commuting and freight transport would be.

The objective of this work is to develop a last-mile delivery optimization model based on Continuous Approximation (CA) techniques and cost-based sustainability assessments, capable of testing various last-mile strategies.

This research incorporates the traffic dynamics when considering the sensor location problem, which makes use of the valuable flow-time relation.

This project analyzes the prospects of hydrogen as a clean energy carrier for the transportation sector.