Contents lists available at ScienceDirect Transportation Research Part D journal homepage: www.elsevier.com/locate/trd Estimating spatio-temporal variations of taxi ridership caused by Hurricanes Irene and Sandy: A case study of New York City Ruijie (Rebecca) Bian a, ⁎ , Chester G. Wilmot b , Ling Wang c a The Glenn Department of Civil Engineering, Clemson University, 125 Lowry Hall, Clemson, SC 29634, United States b 3240R Patrick F. Taylor Hall, Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, United States c Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China ARTICLE INFO Keywords: Taxi ridership Extreme weather Hurricane New York City ABSTRACT Extreme weather days were usually removed as outliers in past studies of taxi ridership. However, taxis play an important role during extreme weather events when other public trans- portation service is suspended. Thus, estimating spatio-temporal variations of taxi ridership during extreme weather conditions can provide valuable information on heretofore relatively unknown behavior of taxi riders and help identify areas with unusual taxi demands. In this study, New York City (NYC) taxi ridership shortly before the landfall of Hurricanes Irene and Sandy was analyzed. It was found that taxi ridership began to drop about 24 h before each hurricane made landfall. Six multisource regression models were estimated to explain the variation of taxi ri- dership in the last 24 h. Characteristics of the approaching hurricane, local weather conditions, and zonal socio-demographic variables were entered as explanatory variables. It was found that taxi ridership during hurricane-affected periods has a strong linear association with the ridership in unaffected periods but the proportion decreases as the storm approaches; a storm has the greatest impact on taxi ridership during weekend and at night, and the least impact on a weekday during the day; and taxi users make fewer trips during conditions of heavy rain or strong wind. 1. Introduction Taxi is an indispensable component of public transportation system in dense metropolitan areas such as New York City (NYC). According to data in the Census Transportation Planning Package (CTPP), commuting trips by taxi account for 2% of all commuting trips by public transportation within NYC. According to a report published by the Taxi and Limousine Commission (TLC) in 2006, NYC taxi cabs carry 11% of passengers who travel in modes of public transportation (Schaller Consulting, 2006). The most recent TLC report of 2016 states that yellow and green taxis together carry about 474,000 trips per day (NYCTLC, 2016). This statistic can be roughly validated based on data from other sources: the population of NYC is about 8.5 million, the daily person trip rate is about 2.5 trips/person for NYC residents, and about 3% of all-purpose trips use taxi or other similar shared-ride service, which gives 0.64 million taxi trips per day (PSB, 2017; U.S. Census Bureau, 2018). The significance of taxi for NYC is also revealed by the number of active taxi drivers (over 50,000) and the millions of taxi passengers they serve per year (NYCTLC, 2016). According to rules of the TLC, all licensed taxis must install the Taxicab Technology System and taxi owners must ensure this system is constantly maintained (NYCTLC, 2017). The Taxicab Technology System automatically records, collects, and transmits trip https://doi.org/10.1016/j.trd.2019.10.009 ⁎ Corresponding author. E-mail addresses: rbian@clemson.edu (R.R. Bian), cecgw@lsu.edu (C.G. Wilmot), wang_ling@tongji.edu.cn (L. Wang). Transportation Research Part D xxx (xxxx) xxx–xxx 1361-9209/ © 2019 Elsevier Ltd. All rights reserved. Please cite this article as: Ruijie (Rebecca) Bian, Chester G. Wilmot and Ling Wang, Transportation Research Part D, https://doi.org/10.1016/j.trd.2019.10.009