Assessing Impact Factors That Affect School Mobility Utilizing a Machine Learning Approach

The analysis and modeling of parameters influencing parents’ decisions regarding school travel mode choice have perennially been a subject of interest. Concurrently, the evolution of artificial intelligence (AI) can effectively contribute to generating reliable predictions across various topics. Thi...

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Bibliographic Details
Published in:Sustainability 2024-01, Vol.16 (2), p.588
Main Authors: Kolidakis, Stylianos, Kotoula, Kornilia Maria, Botzoris, George, Kamberi, Petros Fotios, Skoutas, Dimitrios
Format: Article
Language:English
Subjects:
Artificial intelligence
Classification
Data collection
Decision making
Forecasting
Literature reviews
Machine learning
Parenting
Preferences
Questionnaires
School districts
Students
Surveys
Traffic congestion
Citations: Items that this one cites
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Summary:The analysis and modeling of parameters influencing parents’ decisions regarding school travel mode choice have perennially been a subject of interest. Concurrently, the evolution of artificial intelligence (AI) can effectively contribute to generating reliable predictions across various topics. This paper begins with a comprehensive literature review on classical models for predicting school travel mode choice, as well as the diverse applications of AI methods, with a particular focus on transportation. Building upon a published questionnaire survey in the city of Thessaloniki (Greece) and the conducted analysis and exploration of factors shaping the parental framework for school travel mode choice, this study takes a step further: the authors evaluate and propose a machine learning (ML) classification model, utilizing the pre-recorded parental perceptions, beliefs, and attitudes as inputs to predict the choice between motorized or non-motorized school travel. The impact of potential changes in the input values of the ML classification model is also assessed. Therefore, the enhancement of the sense of safety and security in the school route, the adoption of a more active lifestyle by parents, the widening of acceptance of public transportation, etc., are simulated and the impact on the parental choice ratio between non-motorized and motorized school commuting is quantified.
ISSN:2071-1050
2071-1050
DOI:10.3390/su16020588