Proc Natl Acad Sci U S A
September 2025
We model the effect of plug-in electric vehicle (EV) adoption on U.S. power system generator capacity investment, operations, and emissions through 2050 by estimating power systems outcomes under a range of EV adoption trajectory scenarios.
View Article and Find Full Text PDFThe United States federal government has invested $7.5 billion into charging infrastructure, including the National Electric Vehicle Infrastructure Program, to build fast charging stations along designated highways for long-distance car travel. We develop a consecutive coverage metric to compute the percent of United States roads (traffic-weighted) that are consecutively accessible within 500 miles of each county.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
October 2024
We assess racial disparities in the service quality of app-based ride-hailing services, like Uber and Lyft, by simulating their operations in the city of Chicago using empirical data. To generate driver cancellation rate disparities consistent with controlled experiments (up to twice as large for Black riders as for White riders), we estimate that more than 3% of drivers discriminate by race. We find that the capabilities of ride-hailing technology to rapidly rematch after a cancellation and prioritize long-waiting customers heavily mitigates the effects of driver discrimination on rider wait times, reducing average discrimination-induced disparities to less than 1 min-an order of magnitude less than traditional taxis.
View Article and Find Full Text PDFTransp Res Interdiscip Perspect
March 2023
Public transit has received scrutiny as a vector for spreading COVID-19 with much of the literature finding correlations between transit ridership and COVID-19 rates by assessing the role that transportation plays as a vector for human mobility in COVID-19 spread. However, most studies do not directly measure the risk of contracting COVID-19 inside the public transit vehicle. We fill a gap in the literature by comparing the risk and social costs across several modes of transportation.
View Article and Find Full Text PDFMost light-duty vehicle crashes occur due to human error. Many of these crashes could be avoided or made less severe with the aid of crash avoidance technologies. These technologies can assist the driver in maintaining control of the vehicle when a possibly dangerous situation arises by issuing alerts to the driver and in a few cases, responding to the situation itself.
View Article and Find Full Text PDFAccid Anal Prev
October 2016
Many light-duty vehicle crashes occur due to human error and distracted driving. Partially-automated crash avoidance features offer the potential to reduce the frequency and severity of vehicle crashes that occur due to distracted driving and/or human error by assisting in maintaining control of the vehicle or issuing alerts if a potentially dangerous situation is detected. This paper evaluates the benefits and costs of fleet-wide deployment of blind spot monitoring, lane departure warning, and forward collision warning crash avoidance systems within the US light-duty vehicle fleet.
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