A novel ML-MCDM-based decision support system for evaluating autonomous vehicle integration scenarios in Geneva’s public transportation
Shervin Zakeri,
Dimitri Konstantas,
Shahryar Sorooshian
et al.
Abstract:This paper proposes a novel decision-support system (DSS) to assist decision-makers in the ULTIMO project with integrating Autonomous Vehicles (AVs) in Geneva, Switzerland. Specifically, it aids in selecting the best scenario for incorporating AVs into Geneva’s public transportation system. The proposed DSS is architected on a combined integrated framework that includes a machine learning (ML) algorithm, random forest (RF) algorithm, and three novel multi-criteria decision-making (MCDM) algorithms: (1) Modifie… Show more
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