4/16/2023 0 Comments Dhaka metro rail route mapIn the theoretical part, inductive thinking was used, whereby the empirical part was based on the TOPSIS technique and entropy method. The papers available on the Web of Science, Springer, Scopus, and Elsevier databases were reviewed. Secondly, it attempted to organize the techniques and main criteria in the field of urban transport and MCDM. Firstly, the study identified publications on urban transport and MCDM based on a literature review. The goal of this paper is to present the rankings of 44 smart cities around the world related to urban transport performance, based on the MCDM technique using seven criteria from the ISO 37120 standard. In empirical study, it is necessary to assess the solutions for traffic organisation and urban performance. There are a small number of decision-making study cases from the aspect of competitiveness and sustainability, related to urban transport. At the same time, it is expected that passenger transport will also increase by approximately 34% by 2030, and by more than 50% by 2050, in comparison to 2005. According to the European Commission forecasts, the intensity of freight transport in cities will increase by 40% by 2030, and rise by over 80% by 2050, when compared to 2005. In order to mitigate climate change, reducing greenhouse gas emissions from transport is key to keeping the liveability of cities. Many cities are implementing sustainable mobility measures to improve the flow of passenger and goods, for example, energy-efficient vehicles, biofuels, cycling, walking, public transport, carsharing, park-and-ride, travel reduction, and distance reduction. Urban transport causes many problems, such as traffic congestion, greenhouse gas emissions, air pollution and noise, biodiversity loss, fatalities and injuries, increased fuel consumption, low mobility, reduced quality of life, and delivery delays. Mobility affects the life quality of the inhabitants and the sustainability of the city. Urban transport should facilitate movement and access to public services. Finally, some suggestions for future research are discussed. The values of the relative closeness coefficient ranged from 0.03504 to 0.921402. Portland was found to be the best location for transport enterprises and projects Tbilisi was ranked last. The TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) was applied to calculate the assessment and ranking of transport performance for each smart city. The entropy weight method was used to compute the weight of each criterion. Seven criteria and forty-four objects were used as the input of the approach. The author highlights the importance of decision-making criteria and their weight, as well as techniques. This paper presents an overview of research works published between 19 concerning urban transport and MCDM (multi-criteria decision making). The goal of the paper is to analyse the smart cities selected, in terms of the urban transport. The rapid urbanization and motorization in smart cities have a huge impact on sustainability. The effects of urban transport are highly concerning.
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