@inproceedings{2e545683238f4cc09d7dcef4c959d4a9,
title = "Using data analytics to optimize public transportation on a college campus",
abstract = "Using a large volume of bus data in the form of GPS coordinates (over 100 million data points) and automated passenger count data (over 1 million data points) we have developed (1) a system of analysis and prediction of future public transportation demand (2) a new model that uses concepts specific to college campuses that maximizes passenger satisfaction. Using these concepts we improve service of a model college public transportation service and more specifically the Indiana University Campus Bus Service (IUCBS).",
keywords = "APC, Big data, Bus, GPS, Public transportation",
author = "Kurt Zimmer and Hasan Kurban and Mark Jenne and Logan Keating and Perry Maull and Mehmet Dalkilic",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 5th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2018 ; Conference date: 01-10-2018 Through 04-10-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/DSAA.2018.00059",
language = "English",
series = "Proceedings - 2018 IEEE 5th International Conference on Data Science and Advanced Analytics, DSAA 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "460--469",
editor = "Francesco Bonchi and Foster Provost and Tina Eliassi-Rad and Wei Wang and Ciro Cattuto and Rayid Ghani",
booktitle = "Proceedings - 2018 IEEE 5th International Conference on Data Science and Advanced Analytics, DSAA 2018",
address = "United States",
}