An In-Depth Analysis of Ride-Hailing Travel Using a Large-scale Trip-Based Dataset

TL;DR

This study analyzes a large-scale dataset of over 104 million ride-hailing trips in Chicago over a year to understand trip patterns, usage trends, and implications for regulation.

Contribution

It provides a comprehensive analysis of ride-hailing trip patterns using a large dataset, offering insights into usage trends and temporal variations.

Findings

Trip rates remained stable over the year.

Weekend trips are approximately 20% higher than weekday trips.

Pooled trips decreased from 20% to 9% over the year.

Abstract

With the rapid increase in ride-hailing (RH) use, a need to better understand and regulate the industry arises. This paper analyzes a year's worth of RH trip data from the Greater Chicago Area to study RH trip patterns. More than 104 million trips were analyzed. For trip rates, the results show that the total number of trips remained stable over the year, with pooled trips steadily decreasing from 20 to 9 percent. People tend to use RH more on weekends compared to weekdays. Specifically, weekend RH trip counts (per day) are, on average, 20 percent higher than weekday trip counts. The results of this work will help policy makers and transportation administrators better understand the nature of RH trips, which in turn allows for the design of a better regulation and guidance system for the ride-hailing industry.