Utilizing data from the Uber platform, this project aims to identify and implement strategies for reducing the time between a customer booking a ride and cab/driver reaching the customer.
To optimize the time between a customer booking a ride and a cab/driver reaching the customer, my approach included cleaning and preprocessing the dataset, performing extensive exploratory data analysis to identify trends and patterns, and applying cluster analysis techniques such as k-means to group similar data points. The cluster centroids, represented by their latitude and longitude, were then used to establish the new bases. The implementation of 8 clusters allowed for efficient dispatch of vehicles to multiple customers at once. This will provide a strong foundation for implementing strategies to reduce the waiting time for customers.