Understanding and Predicting the Usage of Shared Electric Scooter Services on University Campuses

Abstract

Electric vehicles (EVs) have been progressing rapidly in urban transport systems given their potential in reducing emissions and energy consumptions. The Shared Free-Floating Electric Scooter (SFFES) is an emerging EV publicized to address the first-/last-mile problem in travel. It also offers alternatives for short-distance journeys using cars or ride-hailing services. However, very few SFFES studies have been carried out in developing countries and for university populations. Currently, many universities are facing an increased number of short-distance private car travels on campus. The study is designed to explore the attitudes and perceptions of students and staff towards SFFES usage on campus and the corresponding influencing factors. Three machine learning models were used to predict SFFES usage. Eleven important factors for using SFFESs on campus were identified via the supervised and unsupervised feature selection techniques, with the top three factors being daily travel mode, road features (e.g., green spaces) and age. The random forest model showed the highest accuracy in predicting the usage frequency of SFFESs (93.5%) using the selected 11 variables. A simulation-based optimization analysis was further conducted to discover the characterization of SFFES users, barriers/benefits of using SFFESs and safety concerns.

Shared E-scooter Usage Analysis considering the Effect of Weather Conditions and Land Use: Qatar Case Study

“…The study's findings highlighted the model's superior predictive ability, with factors like time of day and the density of Points of Interest (POIs) being highly significant. [79] conducted a study focusing on the use of e-scooters among students and staff on campus. They also employed the Random Forest model, achieving high accuracy in predicting e-scooter usage frequency.…”

Üni̇versi̇te öğrenci̇leri̇ni̇n mi̇kromobi̇li̇teye bakış açıları: E-scooterlar açısından bi̇r değerlendi̇rme

“…In addition to the above-mentioned study by Zhang et al (2021), there are some studies that focused on university students' use of micromobility, particularly e-scooters. One of them is carried out by Moosavi et al (2022), who identified eleven factors that can affect the e-scooter use of university students' and staff. The factors are daily travel patterns on campus, availability of green space and water, age, road surface quality, daily travel time and cost on campus, monthly income, private vehicle ownership, connected roads, transportation to and from campus, and gender.…”

“…Safety is one of the most important factors that prevents students from riding e-scooters. Those who think e-scooters are unsafe would never ride e-scooters (Moosavi et al, 2022). E-scooters have even been banned on some university campuses, claiming they are unsafe and cause too many accidents (Abdulahi, 2022).…”

“…E-scooters have even been banned on some university campuses, claiming they are unsafe and cause too many accidents (Abdulahi, 2022). Moosavi et al (2022) found that 85 percent of the participants in the research that they conducted on a university campus underlined that safety was the most important issue. Depending on these studies, the second hypothesis was formulated as follows:…”