Estimating spatio-temporal variations of taxi ridership caused by hurricanes in New York City

Taxi is an indispensable component of the public transportation system in New York City (NYC). In estimating taxi ridership past studies, days with extreme weather were usually removed as outliers. However, taxi plays an important role during extreme weather events, especially for evacuation purposes or as a substitute for suspended regular public transportation service. Thus, estimating spatio-temporal variations of taxi ridership during extreme weather conditions can provide valuable information on heretofore relatively unknown taxi rider behavior and help identify zones with unusual taxi demand. In this study, NYC taxi ridership shortly before landfall of Hurricanes Irene and Sandy was analyzed. It was found that the total taxi ridership began to drop about 24 hours before hurricane landfall. Three multisource regression models were estimated to explain the variation of taxi ridership in the last 24 hours. Characteristics of an approaching hurricane, local weather conditions, and household 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 of taxi riders decrease as the storm approaches; a storm has the greatest impact on taxi ridership during weekend nighttime and the least impact on weekday daytime; and taxi users travel less during heavy rain conditions.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ABR30 Standing Committee on Emergency Evacuations. Alternate title: Estimating Spatiotemporal Variations of Taxi Ridership Caused by Hurricanes in New York City
  • Authors:
  • Conference:
  • Date: 2018

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 7p

Subject/Index Terms

Filing Info

  • Accession Number: 01659946
  • Record Type: Publication
  • Report/Paper Numbers: 18-01422
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 13 2018 9:53AM