When cities look alike but move differently: comparing urban regions using micromobility trip patterns

Regulating free-floating micromobility services, such as e-scooters, presents a unique challenge for cities. This work aims to support cities in developing regulations by assessing similarities between and within urban regions based on micromobility trip patterns, built environment characteristics, and socioeconomic and demographic profiles. We develop three random forest classification models across these dimensions for five U.S. cities – Baltimore, Denver, Detroit, Portland, and Washington DC. We demonstrate that cities with similar built environment characteristics or socioeconomic and demographic profiles do not always exhibit comparable micromobility characteristics. Similarly, we find that cities exhibit more generalizable micromobility patterns than they do through built environment or socioeconomic and demographics. Our regional similarity models offer a means to compare micromobility across regions, while contrasting how regions differ in their built environment or socioeconomic and demographic characteristics. By enabling micromobility focused comparisons, cities with similar built environment characteristics or socioeconomic and demographic profiles may draw conclusions as to which policies may be most effective.