Open AccessUsing BEAM Software to Simulate the Introduction of On-Demand, Automated, and Electric Shuttles for Last Mile Connectivity in Santa Clara County
Author(s) -
Gary Hsueh,
David Czerwinski,
Cristian Poliziani,
Terris Becker,
Alexandre Hughes,
Peter Chen,
Melissa Benn
Publication year - 2021
Language(s) - English
Resource type - Reports
DOI - 10.31979/mti.2021.1822
Subject(s) - software deployment , trips architecture , transport engineering , mile , downtown , software , sample (material) , transit (satellite) , public transport , computer science , engineering , aeronautics , geography , archaeology , chemistry , geodesy , chromatography , programming language , operating system
Despite growing interest in low-speed automated shuttles, pilot deployments have only just begun in a few places in the U.S., and there is a lack of studies that estimate the impacts of a widespread deployment of automated shuttles designed to supplement existing transit networks. This project estimated the potential impacts of automated shuttles based on a deployment scenario generated for a sample geographic area: Santa Clara County, California. The project identified sample deployment markets within Santa Clara County using a GIS screening exercise; tested the mode share changes of an automated shuttle deployment scenario using BEAM, an open-source beta software developed at the Lawrence Berkeley National Laboratory to run traffic simulations with MATSim; elaborated the model outputs within the R environment; and then estimated the related impacts. The main findings have been that the BEAM software, despite still being in its beta version, was able to model a scenario with the automated shuttle service: this report illustrates the potential of the software and the lessons learned. Regarding transportation aspects, the model estimated automated shuttle use throughout the county, with a higher rate of use in the downtown San José area. The shuttles would be preferred mainly by people who had been using gasoline-powered ride hail vehicles for A-to-B trips or going to the bus stop, as well as walking trips and a few car trips directed to public transport stops. As a result, the shuttles contributed to a small decrease in emissions of air pollutants, provided a competitive solution for short trips, and increased the overall use of the public transport system. The shuttles also presented a solution for short night trips—mainly between midnight and 2 am—when there are not many options for moving between points A and B. The conclusion is that the automated shuttle service is a good solution in certain contexts and can increase public transit ridership overall.