Green Strategies in Mobility Planning Towards Climate Change Adaption of Urban Areas Using Fuzzy 2D Algorithm

Abstract

Urban mobility planning must urgently confront the challenges attendant to the low carbon transition and green transformation. The necessary paradigm shift from the traditional approaches to embracing environmental sustainability requires maintaining a firm and stable balancing act between opposing forces. The policy-making process in the transition period is complex and requires a detailed analysis that the academic literature lacks. This study analyzes the decision-making process for urban mobility planning to contribute the academic literature on sustainable transitions. In order to illustrate the complexities in the decision-making process, we design an original case scenario. In the case, the planners are supposed to choose the best project from among four recent green strategies. In the process, they need to take the conflicting requirements on the social, economic, environmental and technical issues into account. Sixteen constraints reflect the available physical and financial conditions. Because the decision-making process includes complexities, a novel two-stages model is introduced in the method that is used to solve the problem. In the first stage, the fuzzy D PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) algorithm is applied to determine the weights. In the second stage, the fuzzy D Dombi (fuzzy 2D) algorithm is proposed to evaluate the alternatives. The results show that societal dynamics are crucially important in choosing the best alternative. Among four alternatives, the one that is inclusive and makes the existing investments more efficient is highly prioritized. Our findings offer policy implications emphasizing the importance of green mobility projects that favors the social benefits as well as financial issues.

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