What Makes the Route More Traveled? Optimizing U.S. Suburban Microtransit for Sustainable Mobility

Alexandra Q. Pan and Susan Shaheen ()
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Alexandra Q. Pan: Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA 94720, USA
Susan Shaheen: Transportation Sustainability Research Center, University of California, Berkeley, Berkeley, CA 94704, USA

Sustainability, 2025, vol. 17, issue 3, 1-19

Abstract: Microtransit services that provide pooled on-demand transportation with dynamic routing have been used in low-density areas since the 1970s, but improvements to routing technology have led to a resurgence of interest in the past decade. Questions remain about the effectiveness of microtransit to serve riders in low-density, car-dependent suburban areas. Better understanding of the factors underlying microtransit ridership can improve usage of these services and shift travelers to more sustainable modes in suburban areas. We compile a database of suburban microtransit programs from 32 public transit agencies in the U.S. to study internal factors (e.g., operating hours, service area) and external factors (e.g., population density, vehicle ownership) impacting ridership using a random effects model. We find that internal agency factors have a greater effect on microtransit ridership than external factors. The most impactful factor is operating a point deviation service, where vehicles have scheduled stops at one or more checkpoints within the service area (e.g., transit center or shopping center), rather than zone-based services, where vehicles pick up and drop off passengers at any time within a service area. There is high potential to convert some zone-based services to point deviation services; 52% of zone-based service areas contain a transit center that could be used as a checkpoint. For the remaining zone-based service areas, maximizing ridership may not be feasible, and using ridership as an evaluation metric can be misleading. Instead, metrics that capture the accessibility, safety, or customer satisfaction impacts of microtransit may be more appropriate for these services.

Keywords: microtransit; on-demand transportation; microtransit ridership (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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