@article{ref1,
title="Estimating driver response rates to variable message signage at Seattle-Tacoma International Airport",
journal="Transport findings",
year="2022",
author="Vasisht, Soumya and Choudhury, Shushman and Nazir, Nawaf and Zoepf, Stephen and Dowling, Chase P.",
volume="2022",
number="",
pages="-",
abstract="We apply Bayesian Linear Regression to estimate the response rate of drivers to variable message signs at Seattle-Tacoma International Airport, or SEA. Our approach uses vehicle speed and flow data measured at the entrances of the arrival and departure-ways of the airport terminal, and sign message data. Depending on the time of day, we estimate that between 5.5 and 9.1% of drivers divert from departures to arrivals when the sign reads &quot;departures full, use arrivals&quot;, and conversely, between 1.9 and 4.2% of drivers divert from arrivals to departures. Though we lack counterfactual data (i.e., what would have happened had the diversionary treatment not been active), adopting a causal model that encodes time dependency with prior distributions rate can yield a measurable effect.<p /> <p>Language: en</p>",
language="en",
issn="2652-8800",
doi="10.32866/001c.38134",
url="http://dx.doi.org/10.32866/001c.38134"
}