Forecasting e-scooter substitution of direct and access trips by mode and distance

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Tác giả: Joseph Y. J Chow, Brian Yueshuai He, Mina Lee, Gyugeun Yoon

Ngôn ngữ: eng

Ký hiệu phân loại: 725.3 *Transportation and storage buildings

Thông tin xuất bản: 2019

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 163255

 An e-scooter trip model is estimated from four U.S. cities: Portland, Austin, Chicago and New York City. A log-log regression model is estimated for e-scooter trips based on user age, population, land area, and the number of scooters. The model predicts 75K daily e-scooter trips in Manhattan for a deployment of 2000 scooters, which translates to 77 million USD in annual revenue. We propose a novel nonlinear, multifactor model to break down the number of daily trips by the alternative modes of transportation that they would likely substitute based on statistical similarity. The model parameters reveal a relationship with direct trips of bike, walk, carpool, automobile and taxi as well as access/egress trips with public transit in Manhattan. Our model estimates that e-scooters could replace 32% of carpool
  13% of bike
  and 7.2% of taxi trips. The distance structure of revenue from access/egress trips is found to differ from that of other substituted trips.Comment: 30 pages, 9 figures
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