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Necessary code and data to reproduce results contain in "Modeling curbside parking as a network of finite capacity queues" submitted to IEEE Transactions on Intelligent Transportation Systems.

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"Modeling Curbside Parking as a Network of Finite Capacity Queues" (2019), IEEE Transactions on ITS

Neccessariy code and data to reproduce results contain in "Modeling curbside parking as a network of finite capacity queues" by Chase Dowling, Lillian Ratliff, and Baosen Zhang, published in IEEE Transactions on Intelligent Transportation Systems, 2019.

This repository contains two main directories:   -./congestion: code and data neccessary to reproduce congestion and time delay estimation results   -./spatial-data-analysis: a git submodule (owned by Tanner Fiez, https://github.com/fiezt/spatial-data-analysis) containing code and data neccessary to reproduce GMM model results

Instructions for re-executing code can be found in each respective directory.

Note ./congestion/data contains all essential data for both experiment directories, as well as a data manifest (data_notes.txt) with detailed descriptions of the contents of each data file and subdirectory.

basic dependencies

All code was written and tested in unix environments.

-Python 2.7+

pandas==0.20.3

seaborn==0.8.1

scipy==0.19.1

gmplot==1.1.1

matplotlib==2.0.2

numpy==1.13.1

scikit_learn==0.19.0

support

Questions can be sent directly to cdowling@uw.edu

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Necessary code and data to reproduce results contain in "Modeling curbside parking as a network of finite capacity queues" submitted to IEEE Transactions on Intelligent Transportation Systems.

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