University of Chicago | Spring 2018
Repository for CMSC 12300 (Computer Science with Applications-3) Group Project
Traffic Pattern Detection Based on New York Yellow Taxi Dataset
This project looks at causal relationship between several factors and traffic time by using big data technique mapreduce and mpi. Factors include weather, time and location. Different algorithms are also used to predict traffic time by using those variables. The project looks at single trip and pair of trips.
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report: project proposal, final presentation and final report can be found here. -
code: all the code we wrote can be found here.- index - generates index on weather, location, and time over traffic time and tip rate
- single trip - predicts traffic time on single trip
- matching pair - looks at causality between pair differences and predicts traffic time by matching pair
- passenger privacy - deanonymizing interesting trips
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data: sample data used or generated can be found here.
- http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml
- http://toddwschneider.com/posts/analyzing-1-1-billion-nyc-taxi-and-uber-trips-with-a-vengeance/
Hyun Ki Kim coreanokim
Andi Liao liaoandi
Winston Zunda Xu zundaxu
Weiwei Zheng ZhengErWei
We would like to express our wholehearted gratitude to Dr. Matthew Wachs for his support for our project.