Suggested Citation:
Kazemzadeh, Khashayar, Prateek Bansal, Dillon T. Fitch-Polse (2025)

Developing an E-scooter Level of Service Model for Shared Spaces: Insights From Davis, California

The rapid integration of e-scooters into transport systems has outpaced proper planning, impacting the experiences of users across all modes of transport. This underscores the urgent need to evaluate the experiences of e-scooter riders, particularly in their interactions with other road users. To address this need, we conducted a dedicated video-based experiment as part of the annual UC Davis Campus Travel Survey (CTS), involving 1142 e-scooter users and non-users. The aim was to analyse comfort levels when e-scooter riders interact with pedestrians and cyclists, laying the groundwork for developing an e-scooter level-of-service (LOS) assessment framework. We categorised interactions into passing (same-direction encounters), meeting (opposite-direction encounters), and mixed scenarios involving both interaction types. Building on this, we proposed a framework that integrates encounter direction with users’ demographic characteristics and attitudes to better understand perceived comfort. Subsequently, we estimated a Bayesian multilevel cumulative logistic regression model to quantify e-scooter riders’ comfort across different interaction types. Findings from the statistical model reveal that meeting or mixed interactions generally induce more discomfort than passing interactions among e-scooter riders. This contrasts with traditional findings in the bicycle literature, where meeting scenarios are often deemed more comfortable due to opportunities for nonverbal communication. Additionally, comfort levels of e-scooter riders in different interactions with pedestrians varied across gender groups and were significantly influenced by individuals’ general comfort with walking near e-scooters. The model results were translated into heterogeneous measures related to LOS for e-scooter riders, which are crucial for planners and policymakers to improve navigation in shared spaces, particularly for emerging transport modes and underrepresented groups.