Taxi Drivers AI Assistant
TaxiMize is an intelligent mobile application designed to help NYC taxi drivers maximize their earnings by minimizing idle time and optimizing ride selection. The app leverages machine learning to provide data-driven insights that transform how drivers approach their work.
Numerous studies show that taxi drivers often struggle with low earnings due to inefficient ride selection and excessive idle time. Our primary goal with TaxiMize is to help drivers maximize their profits.
To achieve this, we built 3 smart features:
Our machine learning models analyze passenger demand patterns across NYC's 264 zones, predicting passenger availability by hour, day, and month.
ML Algorithm: Analyzes historical pickup data to calculate passenger count predictions for strategic positioning.
Before accepting any ride, drivers receive a 1-5 star rating based on our machine learning model that evaluates ride profitability and drop-off zone quality.
Smart Evaluation: Drop-off zone "hotness" prevents dead-heading back to busy zones.
The app provides recommendations on when to start working, helping drivers avoid unprofitable periods and capitalize on high-demand times.
Development Note: Currently uses hardcoded hours, planned for future ML implementation.
TaxiMize was developed as the final project for my Computer Science Master's degree at University College Dublin (UCD). This project was supported by extensive literature review and represents a new approach to taxi driver optimization.