@misc{046d54b556ab418fb6c337f61dd231be,
title = "Optimizing Fleet Operations in Automated Mobility Districts: Serving On-Demand Mobility with Automated Electric Shuttles",
abstract = "On-demand transportation services have seen a dramatic rise in the past decade, thanks to technology. Connected and automated vehicle (CAV) technology holds potential for a major transformation in the on-demand mobility services landscape.The timeline for fully automated vehicles (AVs) to reach the critical market share is still uncertain. In the short term, many cities in the United States and abroad are testing low-speed automated electric shuttles (AES) as a shared on-demand mobility service in geo-fenced regions. An automated mobility district (AMD) is a campus-sized implementation of connected/automated vehicle technology to realize the full benefits of a fully electric automated mobility service within a confined region or district. Building on this concept, an AMD toolkit is under development at the National Renewable Energy Laboratory (NREL) to inform a campus-or district-sized implementation in which automated electric shuttles (AES). This research extends the functionality of the AMD toolkit by developing a mathematical program to optimize the operations of an AES fleet in an on-demand service configuration.",
keywords = "AES, AMD, automated electric shuttle, automated mobility district, automated vehicles, AV, CAV, connected and automated vehicles, fleet operations, on-demand transportation services",
author = "Venu Garikapati",
year = "2019",
language = "American English",
series = "Presented at the International Conference on Demand Responsive and Innovative Transportation Services, 15-17 April 2019, Baltimore, Maryland",
type = "Other",
}