Evaluation Model for Equipping Urban Regions with Intelligent Transportation Based on the Combination of Euclidean and Manhattan Distances

Dorji, Yasamin; Rafsanjani, Ali Khaksari; AsadAmraji, Morteza · 2024 · Crossref

DOI: 10.21203/rs.3.rs-4593542/v1

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Summary

This study addresses the challenge of evaluating and prioritizing the deployment of Intelligent Transportation Systems (ITS) in urban regions, a process complicated by budget constraints and the need for efficient resource allocation. The authors propose a novel hybrid evaluation model to assess ITS development quality and quantity, aiming to support policymakers in strategic planning and budget distribution. The research focuses on five specific urban regions of Tehran (regions 3, 4, 10, 12, and 22), selected to represent diverse geographical and developmental characteristics. The methodology employs a mixed-method approach combining quantitative data with expert opinions through Multi-Criteria Decision-Making (MCDM). Thirteen indicators were identified to assess ITS development, ranging from intelligent traffic control systems and CCTV coverage to accessibility features for people with disabilities. To determine the weight of these criteria, the study utilized a hybrid weighting technique that averages results from the Shannon Entropy method (objective, data-driven) and the Best-Worst Method (subjective, expert-driven). Data for the subjective component were gathered via an online questionnaire administered to 70 experts in urban planning, transportation, and management, achieving a Cronbach’s alpha reliability of 0.817. The final ranking of the urban regions was performed using the Combinative Distance-based Assessment (CODAS) method, which utilizes both Euclidean and Manhattan distances to provide robust control and balanced rankings. The results identified "The number of intelligent central control systems for traffic lights at intersections" as the most critical indicator for ITS evaluation, with an average weight of 0.14015. This was followed by "The number of specialized cameras for bus routes" (0.094377) and "Index of BRT stations with adapted platforms for the use of people with disabilities" (0.084252). In terms of regional performance, Region 4 of Tehran ranked first with the highest assessment score (1.050716), indicating superior ITS development. Region 12 and Region 3 secured the second and third ranks, respectively, while Regions 10 and 22 scored lower. The study highlights that the hybrid weighting approach offers greater accuracy and acceptability than single-method alternatives by integrating both statistical entropy and expert judgment. The significance of this research lies in its contribution of a comprehensive, hybrid framework for ITS evaluation that moves beyond absolute criteria to relative, efficient assessments. By demonstrating the effectiveness of combining Shannon Entropy, Best-Worst, and CODAS methods, the study provides a strategic tool for urban managers to prioritize investments and ensure transportation equity. The findings offer actionable insights for enhancing smart city infrastructure, particularly by emphasizing the pivotal role of intelligent traffic control systems in urban transportation efficiency.

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