Planning for Equitable Outcomes During Periods of Disruption in the Transportation Sector

 Disruptions to transportation tend to disproportionately impact the most vulnerable groups, making equity an important consideration when studying disruptions. In this dissertation, we investigate the equity impact of external changes in transportation (e.g., COVID-19 and dependence on public transportation) and the impact of internal disruptions to transportation (e.g., technology innovations, such as vehicle electrification and automation). We investigated COVID-19 because it created unprecedented upheaval in transportation patterns and revealed vulnerabilities in the transportation system that were not discernible pre-pandemic. Looking forward, the transition to electric vehicles (EVs) will present a lower-emissions alternative to internal combustion engines. This is significant because light-duty vehicles are the largest sector source of carbon emissions in the US. However, vehicle electrification will change how people re-fuel their vehicles and will impact grid operations. We investigate EV adoption and infrastructure to discern who will be left behind and how the EV movement will impact the state of the grid. 

In the second chapter, we investigate the role that public transportation potentially played as a vector for spreading COVID-19 and assess the trade-offs of potential alternatives to crowding on public transit. We find that some trips have demands that exceed their COVID-19 passenger limit, where the driver must decide: 1) leaving a passenger without a ride or 2) allowing them on the bus and increasing COVID-19 risk. We consider five alternatives for alleviating overcapacity and compare the trade-offs of each. We use transit ridership and COVID-19 data from the spring of 2020 by combining transportation data and a stochastic epidemiological model of COVID-19 in a Monte Carlo Analysis. Our results show that 4% of county cases were contracted on the bus or from a bus rider, and a disproportionate amount (52%) were from overcapacity trips. The risk of contracting COVID-19 on the bus was low but worth mitigating. 

In the third chapter, we use the COVID-19 stay-at-home order to study the dependence on Transportation Network Companies (TNC) by income of the trip origin. TNCs such as Uber and Lyft set out to provide transportation that was not fulfilled by private vehicles or public transit. The social value of TNCs for essential trips is difficult to discern in normal conditions. The COVID-19 stay-at-home order is used as a natural experiment to investigate the heterogeneous ability to avoid TNCs by income areas of trip origins. We measure the sensitivity of different populations’ ability to respond to policies and to avoid TNC trips (e.g., early stay-at-home orders) using a difference-in-difference style regression. We fill a gap in the literature by evaluating the role TNCs play in serving unavoidable and essential trips. We find that high-income community areas showed greater sensitivity to the stay-at-home order with a 56% greater decrease in TNC ridership during the stay-at-home order compared to low-income community areas.

 In the fourth chapter, we investigate the impact of federal investments in public charging station access for Electric vehicles (EVs) to find where coverage is lacking and which parts of the country are left behind by federal spending. EV charging stations need EVs to be profitable, while consumers hesitate to purchase EVs if there is a lack of charging infrastructure. The federal government has committed to investing up to $7.5 billion into publicly accessible EV charging infrastructure through the Bipartisan Infrastructure Law. Several highway corridors are designated as alternative fuel corridors (AFC) and are prioritized for fast charging station development. We develop a novel metric, ‘consecutive coverage’, to compute the percent of roads (weighted by traffic) that are consecutively accessible, with?out large gaps in charging stations, within 500 miles of each starting county. We use our metric to answer several questions: What is the state of consecutive EV charging coverage from each county? What is the increase in coverage per state when the federally designated corridors have fast charging stations? The output of our model is the percent of national coverage reached for each county in the US. In 2023, only 10% of counties have minimum viable coverage, with at least 75% of highways consecutively covered for long-distance travel. If all AFCs have fast charging stations, 94% of counties will have consecutive coverage of fast chargers for at least 75% of travel. 

In the fifth chapter, we look at the impact of EVs on grid capacity expansion, generation mix, and emissions. There are several EV policies and federal goals aimed at reducing carbon emissions; however, to understand the impact of EV adoption on carbon emissions, we investigate the impact of high EV penetration on the grid needs by endogenously modeling dispatch and capacity expansion. We find that high EV penetration scenarios (the Biden Administration 2021 EV sales goal, the U.S. Environmental Protection Agency 2024 fuel standards, and net zero by 2050) have higher consequential emissions compared to the Inflation Reduction Act (IRA) (inducing a higher carbon intensity of the grid). However, the consequential per-vehicle emissions fall over time to nearly reach zero per-vehicle consequential emissions by 2050 compared to the IRA reference. The grid’s carbon intensity is anticipated to decrease significantly over the next decade leading to a reduction in consequential EV emissions of high EV policies; this widens the gap between per vehicle EV grid emissions and displaced tailpipe emission out through 2032, at which point the consequential per vehicle emissions stays consistent across high EV scenarios. We model the lowest EV scenario (no policy intervention) as reaching emissions low enough to trigger the phase-out of IRA renewable tax credits. The higher EV policies maintain positive grid emissions beyond the IRA but have significantly lower displaced tailpipe emissions for 2026 onward.