A Few Quantitative Thoughts on Parking in Marburg - RC3 - 2020

Explore quantitative insights on parking patterns in Marburg through a 28-minute conference talk. Analyze scraped parking deck data over a 7-month period to uncover usage trends, time series patterns, and day-time utilization of parking spots. Discover periodicities in parking signals using autocorrelations and learn how Gaussian Process predictions can estimate parking demand at locations without parking decks, such as the university Mensa. Gain valuable knowledge on data scraping, time series analysis, and machine learning applications in urban planning and parking management.

Intro
Welcome
Data source
Scraper
Data format
Joint data
Separate data
Prediction
Bonus