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| Type | Bachelor's Thesis |
| Scope | Discipline-based scholarship |
| Title | Using Artificial Intelligence for the Reduction of Emissions in Cities – Creating sustainable transportation with AI |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Date | 2022 |
| Abstract Text | This bachelor thesis investigates different use cases of using artificial intelligence to reduce city transport emissions with a focus on using machine learning to forecast passenger demand. We first conducted a literature review to gather the different uses of artificial intelligence in city transport emission reduction. Then we developed a prototype that uses artificial intelligence to predict the public transport passenger demand for the city of Zurich using the design science research method. Last we presented and evaluated the usability of the prototype in a workshop. Our results highlight applications of artificial intelligence that can be used in city transport emission reduction. Our prototype shows how artificial intelligence can be used to predict public transport passenger demand in the city of Zurich. The findings from the evaluation show how transport decision makers can use our prototype to reduce city transport emissions, We conclude that artificial intelligence methods can be used to support measures that reduce transport emissions in cities, by providing citiesí decision makers with information about traffic, passenger demand, mobility patterns, transport network design, electrification, and emissions. Passenger demand predictions made by artificial intelligence can be used by transport companies to reduce transport emissions through better public transport planning. |
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