Funding amount: $100,000

Contract number: 65A0674 TO 014

Project period: 8/1/2019 to 12/31/2020

Link to dataset: https://doi.org/10.7910/DVN/B2LJSB

This research builds a land use regression model to explain dockless scooter trip generations. We use publicly available scooter trip generation data for Louisville, KY and Minneapolis, MN and publicly available data on land use characteristics. The model shows that scooter trip generations are associated with higher employment densities, higher densities of entertainment land uses (bars and clubs), and in some specifications higher densities of eating establishments and university buildings. We establish that using the regression results to predict out of sample gives predictions that correspond well to observed scooter trip generations in Austin, TX. Because scooter trip data are not available for research in California, we use the Minneapolis model to predict scooter trips as a function of land use characteristics in California census tracts. The results yield a promising screening method that can highlight census tracts with land use characteristics that are potentially supportive of micromobility and non-automobile short-trip travel. We recommend that such a screening method can be a first step in more detailed analyses of planning programs or infrastructure that could support non-automobile short-trip travel.