Ride-Sharing Analysis

Ride-Sharing Analysis examines the usage patterns, demand dynamics, and transportation system impacts of shared mobility services including ride-hailing platforms (Uber, Lyft), traditional carpooling, and vanpooling. Using trip-level data that includes pickup and dropoff locations, timestamps, and trip distances, analysts map demand patterns, identify peak usage areas, and evaluate how ride-sharing interacts with public transit, private vehicles, and active transportation. GISGISGeographic Information Systems (GIS) enable users to analyze and visualize spatial data to uncover patterns, relation...-based analysis of ride-hailing data reveals spatial and temporal demand patterns that inform infrastructure and policy decisions. Hotspot mapping identifies pickup and dropoff concentrations at airports, entertainment districts, and transit stations. Mode substitution analysis evaluates whether ride-hailing complements transit by providing first/last-mile connections or competes by diverting riders from buses and trains. Vehicle-miles-traveled analysis measures whether ride-hailing increases or decreases total driving in a region. Applications include curb managementCurb ManagementCurb Management is the strategic allocation and regulation of curbside space for competing uses including parking, tr... at high-demand pickup locations, transit integration planning that coordinates ride-hailing with fixed-route service, congestion analysis in corridors heavily used by ride-hailing vehicles, and equity evaluation that examines whether ride-sharing services are accessible across income levels and neighborhoods. Regulators use analysis results to set licensing fees, define operating boundaries, and develop data-sharing requirements that ensure ride-hailing contributes to rather than detracts from broader transportation goals.