利用基于模型的数字孪生和 MCDM 技术的 Dempster-Shafer 增强型城市道路规划框架

IF 2.8 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Zahra Maserrat, Ali Asghar Alesheikh, Ali Jafari, Neda Kaffash Charandabi, Javad Shahidinejad
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引用次数: 0

摘要

发展中国家的快速城市化带来了一个严峻的挑战,即需要广泛而适当地扩建道路,这反过来又加剧了交通拥堵和空气污染。城市是经济引擎,但其效率和宜居性有赖于精心设计的道路网络。本研究提出了一种新颖的城市道路规划方法,充分利用了几种创新技术的力量。这种方法的基石是城市环境的数字孪生模型。该数字孪生模型有助于对道路发展建议进行评估和比较。为了支持知情决策,我们采用了多标准决策(MCDM)框架,使规划人员能够考虑交通流量、环境影响和经济因素等各种因素。此外,还提供了空间数据和三维可视化,以丰富分析内容。最后,Dempster-Shafer 理论(DST)为解决加权过程中固有的不确定性提供了一个稳健的数学框架。所提出的方法既适用于新道路建设规划,也适用于现有道路扩建规划。通过结合这些要素,该模型为优化城市道路规划提供了一种可持续的、基于知识的方法。通过层次分析法(AHP)和贝叶斯最佳-最差法(B-BWM)这两种加权方法获得的权重综合结果显示,"破旧的城市肌理 "标准的权重非常高,而 "噪声污染 "标准的权重很低。最后,使用成本路径算法对所有三种方法(AHP、B-BWM 和 DST)的结果进行了评估。这些方法的结果具有高度相似性,表明所建议的方法结果稳定。对研究区域的分析表明,道路规划面临以下重大挑战:根据所选标准,35% 的区域被认为不适合,只有极少部分(4%)适合道路开发。这凸显了探索替代方法或大幅调整当前规划流程的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Dempster–Shafer Enhanced Framework for Urban Road Planning Using a Model-Based Digital Twin and MCDM Techniques
Rapid urbanization in developing countries presents a critical challenge in the need for extensive and appropriate road expansion, which in turn contributes to traffic congestion and air pollution. Urban areas are economic engines, but their efficiency and livability rely on well-designed road networks. This study proposes a novel approach to urban road planning that leverages the power of several innovative techniques. The cornerstone of this approach is a digital twin model of the urban environment. This digital twin model facilitates the evaluation and comparison of road development proposals. To support informed decision-making, a multi-criteria decision-making (MCDM) framework is used, enabling planners to consider various factors such as traffic flow, environmental impact, and economic considerations. Spatial data and 3D visualizations are also provided to enrich the analysis. Finally, the Dempster–Shafer theory (DST) provides a robust mathematical framework to address uncertainties inherent in the weighting process. The proposed approach was applied to planning for both new road constructions and existing road expansions. By combining these elements, the model offers a sustainable and knowledge-based approach to optimize urban road planning. Results from integrating weights obtained through two weighting methods, the Analytic Hierarchy Process (AHP) and the Bayesian best–worst Method (B-BWM), showed a very high weight for the “worn-out urban texture” criterion and a meager weight for “noise pollution”. Finally, the cost path algorithm was used to evaluate the results from all three methods (AHP, B-BWM, and DST). The high degree of similarity in the results from these methods suggests a stable outcome for the proposed approach. Analysis of the study area revealed the following significant challenge for road planning: 35% of the area was deemed unsuitable, with only a tiny portion (4%) being suitable for road development based on the selected criteria. This highlights the need to explore alternative approaches or significantly adjust the current planning process.
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来源期刊
ISPRS International Journal of Geo-Information
ISPRS International Journal of Geo-Information GEOGRAPHY, PHYSICALREMOTE SENSING&nb-REMOTE SENSING
CiteScore
6.90
自引率
11.80%
发文量
520
审稿时长
19.87 days
期刊介绍: ISPRS International Journal of Geo-Information (ISSN 2220-9964) provides an advanced forum for the science and technology of geographic information. ISPRS International Journal of Geo-Information publishes regular research papers, reviews and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. The 2018 IJGI Outstanding Reviewer Award has been launched! This award acknowledge those who have generously dedicated their time to review manuscripts submitted to IJGI. See full details at http://www.mdpi.com/journal/ijgi/awards.
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