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This project was done as part of the University of Pennsylvania’s Master of Urban Spatial Analytics (MUSA) Spring 2023 Practicum. We’d like to thank several people who supported and advised us throughout the duration of this project:

  • Andrew Simpson at the Office of Transportation, Infrastructure and Sustainability, for helping us understand the severity of bus bunching in Philadelphia and its impacts on residents, answering all our questions, and providing us with the necessary data sets to build our predictive models

  • Steve Labedz at SEPTA, for all his expertise and advice about the operational aspects of bus bunching

  • Our instructors, Matt Harris and Michael Fichman, for organizing this project, steering us in the right direction, and for their valuable feedback throughout the semester

Our githubs:

Jie’s github
Mia’s github
Yihong’s github

1 Introduction

1.1 Background

As the negative consequences of automobile dependence and climate change are becoming increasingly apparent, it is crucial that city governments prioritize the provision of safe, efficient, equitable, and reliable transit to their residents. In Philadelphia specifically, over half of all transit trips are taken on buses. Additionally, among all income levels, low income residents rely on buses the most. In an ideal scenario, residents are confident that a given bus route will arrive at their bus stop at regular intervals, there is sufficient space on the bus for them to sit or stand comfortably, and they are able to plan their trip without much stress.

Ideal situation (source: https://setosa.io/bus/):