Data-driven analysis of rideshare spatial travel patterns and ride metrics

Rideshare services offer an alternative transportation mode that has the potential to minimize transportation inequity, specifically in areas with limited transportation coverage. Previous studies have explored the spatial distribution of rideshare demand in high density areas with fixed-route public transportation; however, they lack comprehensive information about spatial variations in rideshare travel patterns in suburban areas without extensive public transit access. Thus, this study provides an in-depth analysis of spatial rideshare demand in Arlington, Texas over a two-year period through the assessment of origin-destination patterns and various ride metrics. The results revealed that ride demand is route specific and dependent on time of day and day of the week. Certain routes were also indicative of commuter patterns, demonstrating increased demand during peak hours. Other trip characteristics, such as wheelchair accessible vehicle requests, did not appear to be impacted by spatial variability. In addition to rideshare service providers, the findings of this study may also benefit urban planners and policymakers who can utilize these insights to improve transportation equity.