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.

翻译：美国四个城市(波特兰、奥斯汀、芝加哥和纽约市)估算了电子摩托车旅行模式:波特兰、奥斯汀、芝加哥和纽约市。根据用户年龄、人口、陆地面积和摩托车数量,对电子摩托车旅行估计了一个记录回归模型。模型预测曼哈顿每天有75K次电子摩托车旅行,部署2000辆摩托车,相当于每年收入7 700万美元。我们提议了一个新的非线性、多要素模型,以根据统计相似性,他们可能替代的替代交通方式,打破每日旅行次数。模型参数显示与自行车、步行、汽车、汽车和出租车的直接旅行以及与曼哈顿公共交通的进出/出行之间的关系。我们的模型估计,电子摩托车可以取代32 %的汽车;13 %的自行车;7.2%的出租车旅行。访问/出行收入的距离结构与其他替代旅行不同。