Forecasting e-scooter substitution of direct and access trips by mode and distance
| Autor: | Joseph Y.J. Chow, Mina Lee, Brian Yueshuai He, Gyugeun Yoon |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
General Economics (econ.GN) 020209 energy Population Transportation 02 engineering and technology Statistics - Applications FOS: Economics and business Carpool Transport engineering 0502 economics and business 0202 electrical engineering electronic engineering information engineering Revenue Applications (stat.AP) education General Environmental Science Civil and Structural Engineering Economics - General Economics 050210 logistics & transportation education.field_of_study business.industry 05 social sciences Mode (statistics) Regression analysis Geography Public transport TRIPS architecture business Trip generation |
| Popis: | 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. 30 pages, 9 figures |
| Databáze: | OpenAIRE |
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