Designing streets for people: a multicriteria decision-making study

Designing streets for people: a multicriteria decision-making study

Designing Streets for People involves selecting appropriate materials, determining the optimal configuration, and finding the best solution based on technical criteria for urban structures. This paper aims to identify the best solution by comparing two multicriteria decision-making methods: the WISP...

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Bibliographic Details
Main Authors: Luiz Fernando Kowalski, Érico Masiero, António Manuel Saraiva Lopes, Marcos dos Santos, Carlos Francisco Simões Gomes, Dragiša Stanujkić
Format: Article
Language:English
Published: University in Belgrade 2024-11-01
Series:Serbian Journal of Management
Subjects:
street for people
ahp-gaussian
wisp method
urban pavement
multicriterial decision-making
case study
Online Access:https://aseestant.ceon.rs/index.php/sjm/article/view/48257/26449
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Summary:Designing Streets for People involves selecting appropriate materials, determining the optimal configuration, and finding the best solution based on technical criteria for urban structures. This paper aims to identify the best solution by comparing two multicriteria decision-making methods: the WISP (Weighted Sum-Product) and AHP-Gaussian, which represents a recent algorithm for the Analytical Hierarchy Process (AHP) decision- making. We created a matrix with eight factors (cost, braking distance, lifetime, sidewalk width, carbon footprint, electricity consumption, and pavement temperature) to choose between four pavement options (concrete and asphalt with different sidewalk widths). The WISP recommended a concrete pavement and 2.0-meter sidewalk. The least viable option was asphalt pavement with a 1.2-meter sidewalk, due to its higher carbon footprint (12%), increased air temperatures (10%), and greater public lighting expenses (11%). WISP allows for assigning weights to criteria with robustness, computational effectiveness, and transparency. Conversely, AHP-Gaussian incorporates a sensitivity feature that lets decision-makers assign weights based on statistical analysis. Despite each method's limitations, both are suitable for urban projects, estimating decisions based on multiple technical aspects, thereby promoting more integrated and efficient choices.
ISSN:1452-4864
2217-7159

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