Understanding and Predicting the Usage of Shared Electric Scooter Services on University Campuses
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Transportation Planning and Optimization · Vehicle emissions and performance · Urban Transport and Accessibility
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Civil Engineering, Faculty of Engineering, Universiti of Malaya, Kuala Lumpur 50603, Malaysia
Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
Department of Urban Planning, Engineering Networks and Systems, Institute of Architecture and Construction, South Ural State University, 76 Lenin Prospect, 454080 Chelyabinsk, Russia
Transportation Institute, Chulalongkorn University, Bangkok 10330, Thailand
Malaysia School of Business, Monash University, Subang Jaya 47500, Selangor, Malaysia
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