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Valuing Autonomy in Micro Mobility

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Four members of the Rollo senior project team pose for a photo

Team Members
Evgeny Moshkovich, Justin Kaull, Justin Kahl, Skyler Mclean

Faculty Mentor
Markus Pelger

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The Client: Rollo

Rollo is a micro mobility company based in Los Angeles. They are developing scooters with autonomous driving technology.

The Problem to Solve

As an autonomous redistribution and smartphone-based ride hailing business, the team sought to help Rollo answer the following questions:

  • What is the economic benefit of autonomy for a scooter company?
  • How many fewer autonomous scooters would Rollo need to satisfy the same rider demand compared to a traditional scooter fleet?

Engineering a Solution

Tools and Methodologies

The team used a Gaussian mixture model to analyze competitor data and access ride demand by cluster points. This model helped them:

  • Quantify how many scooters can be taken off the streets while still allowing Rollo to satisfy current demand and forecasted demand through linear optimization modeling.
  • Determine how much money Rollo can save by using autonomous driving technology through unit economics modeling.
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