Projects

Principal Investigator:

Jiaqi Ma

Funding Source:

Statewide Transportation Research Program

Program Area(s):

Environment, New Mobility

The project aims to present an in-depth understanding of the public EV charging infrastructure in the present and future transportation electrification for public agencies, such as SCAG. One contribution is to provide an integrated eTranSym tool, which can simulate the travel and charging behaviors of every EV user, assess disparities in charging infrastructure distribution among communities, and predict the future demand for public charging facilities. The eTranSym tool helps prioritize underserved communities and assists the spatial-varying investment of the public charging infrastructure.

Principal Investigator:

Teo Wickland

Funding Source:

USDOT FHWA Talent Development

Program Area(s):

New Mobility, Transportation & Communities

The United States’ transportation workforce is currently at a skills deficit in key areas. New and innovative transportation technologies and approaches threaten to exacerbate this situation. Yet, transportation workers need more than skills to implement new technologies: they need the skills to critically determine which technologies are likely to support a thriving nation and under what conditions. Additionally, transportation workers need the skills to support non-technology-focused solutions to the nation’s transportation challenges, including cultural, political, and social change.

Principal Investigator:

Jacob L. Wasserman

Funding Source:

Statewide Transportation Research Program & Resilient and Innovative Mobility Initiative

Program Area(s):

Access to Opportunities, New Mobility

This project synthesizes three primary data sources—credit data, unemployment claims data, and small business loan and grant data—to explore the financial conditions of those who drive for a living before and during the COVID-19 pandemic in California. Automobile debt was high among groups likely to contain professional drivers. The occupational categories in which many drivers fall had high absolute and relative levels of automobile debt compared to other workers. After the onset of the pandemic, unemployment rose dramatically in the transportation industry and in transportation occupations, peaking at rates higher than the national average. However, state unemployment claims data, among transportation employee claimants only, show less of a spike. Contractor drivers lived in areas with more Pandemic Unemployment Assistance claims, a special program for self-employed workers like gig drivers. Finally, contractor drivers received unprecedented but uneven federal small business loans and grants. Drivers in many areas, however, did not receive much or any of these funds, though those areas that did tended to have more residents of color. Assessing the full effect of the pandemic on professional drivers’ debt and finances will require additional and better data, particularly workforce data from gig economy firms that contract with drivers.

Principal Investigator:

Jiaqi Ma

Funding Source:

Statewide Transportation Research Program

Program Area(s):

New Mobility

Transportation agencies use travel demand models (e.g., four-step models, activity-based models, dynamic traffic assignment models) to evaluate transportation improvement projects. However, existing travel demand models are unable to account for capacity changes of the network and mode shifts associated with connected and automated vehicle (CAV) technologies and services. This project aims to lay a foundational framework for the development of planning-level analysis capability that includes CAVs and engage in a small scale case study, toward a vision where practitioners have CAV-aware tools available. The research team will work with stakeholders in the Southern California Association of Governments (SCAG) to identify current needs in modeling CAVs and new mobility services in demand models. The project will develop methodologies to enhance the existing SCAG activity-based demand model, and the areas of enhancements include, but not limited to, capacity adjustments and new scenarios of travel behavior/choice modeling.

Principal Investigator:

Izhak Rubin

Funding Source:

Statewide Transportation Research Program

Program Area(s):

New Mobility

Researchers have been developing innovative methods for integrated traffic management and communications networking systems for autonomous transportation systems. These models provide for optimal on-ramp merging and adaptive formation of vehicular flows across highway lanes, with the goal of achieving high vehicular flow rates while reducing queueing delays. To effectively control vehicular flows and formations across the highway, researchers have developed new data communications protocols and algorithms.The research team proposes to translate its models and techniques to the design of autonomous transportation systems when aided by interconnected roadside unit (RSU) stations that form a backbone network infrastructure. The research team’s methods will be used to determine the best configuration of joint traffic management and data networking mechanisms, described by the locations and interconnection features of the RSU stations and the backbone network infrastructure that they form.

Principal Investigator:

Anne Brown

Funding Source:

Statewide Transportation Research Program

Program Area(s):

Access to Opportunities, New Mobility