1355853 - Data-Driven Methods for Estimating Dockless Electric Scooter Service Areas

Dockless electric scooters (e-scooters) have been lauded as a solution to first-mile, last-mile (FMLM) public transit access. In the United States, the number of E-scooters trips more than doubled in a year, increasing from 38 million trips in 2018 to 88 million in 2019. Improving public transit access is one of the benefits of FMLM improvement, which can affect mobility patterns, transportation behaviors, and dependence on private vehicles in the cities. With the surging usage of e-scooters worldwide, there is a growing interest in understanding different aspects of e-scooters trips and their impact on urban mobility. In addition, the emergence of this new mode of transportation has risen social concerns such as lack of equity in low-income communities access to e-scooter, the inequitable societal impacts of e-scooters on disadvantaged populations, and disproportionately longer wait times for minority populations. In this study, we developed a data-driven approach to estimate the spatial boundary or service area for e-scooter users with OD data and will use the service area to measure the accessibility to public transit via e-scooter in Louisville, Kentucky. To estimate the e-scooter service area and public transit accessibility, a multi-stage data-driven methodological framework is proposed. In the first stage, OD data is used to construct the service areas (SA) for the e-scooter trips in each traffic analysis zone. In the second stage, accessibility is estimated by capturing the public transit stops and routes within specific e-scooter SAs of each traffic analysis zones (TAZ). It is anticipated that the finding of this research could help the Department of Transportation and Metropolitan Planning Organization to better relocate the e-scooter vehicles to serve the community better in terms of accessibility. In addition, additional e-scooter vehicles could be added to locations where users suffer from lower accessibility to public transit. Similarly, transportation authorities can look into other types of accessibility (e.g., accessibility to hospitals, and shopping centers) using the e-scooter service area and tackle the equity challenges by relocating and/or adding new e-scooter vehicles to underrepresented areas.