Unveiling Urban Mobility Patterns: A Comprehensive Analysis of Uber

Abstract

This research paper conducts an extensive analysis of Uber ride-sharing data to uncover valuable insights into urban mobility patterns. Leveraging a vast dataset spanning various cities and time periods, our study explores ride frequency, duration, and pricing trends. We also investigate the impact of external factors, such as weather conditions and local events, on Uber usage. Furthermore, we analyze the geographic distribution of ride requests and the implications for urban transportation infrastructure. Our findings shed light on the dynamics of modern urban mobility and offer valuable information for policymakers and transportation stakeholders.

Keywords: frequency dynamics, uber, artificial intelligence, machine learning

JEL Classification: O3