Abstract

Developing methodologies to facilitate the planning of sustainable transport systems for decision makers (DMs) is becoming more critical. This study proposed a methodological framework for sustainable urban transportation to make decisions during urban transportation’s design and planning stages. Urban transportation alternatives were evaluated by sustainability indicators that considered a triple bottom line approach’s environmental, economic, and social aspects. To choose the best alternative sustainable transportation scenarios, two multicriteria decision-making (MCDM) methods, for example, a hesitant fuzzy analytical hierarchy process (HF–AHP) and multiple attribute utility model (MAUT), were integrated. First, eight sustainable transportation indicators that considered data availability from the transport sector were selected. The weights of the selected indicators were calculated using an HF–AHP. These indicators included carbon dioxide (CO2) emissions, energy consumption, depletion of nonrenewable resources, operational and maintenance costs, fuel and taxes, the number of fatalities or injuries, and motor vehicles for public transport per 10,000 population. Finally, sensitivity analysis was applied to validate the robustness. Based on HF–AHP results, the number of fatalities or injuries was the most significant among the eight indicators, with a 0.158 normalized weight (Ni). The results of this integrated methodology highlighted that Alternative 11, which was dominated by low-motorized vehicles (low-MVs), was the best sustainable alternative and Alternative 1 was the worst sustainable alternative, which was dominated by high-MVs with 0.69 and 0.27 total utility values, respectively. Low-motorized urban transportation alternatives showed higher sustainable performances than the motorized and high-motorized alternatives. This study proposed a novel and robust methodology for decisions on sustainable urban transportation projects and renovating current urban transportation systems.

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