Developing a Hybrid Method for Weighted Distance-Based Prioritization (HWDP) to Prioritize the Implementation of Urban Intelligent Transportation Systems Projects

Asadamraji, Morteza; Mahmoudabadi, Mahdiye; Nadimi, Navid

doi:10.1007/s40996-023-01212-9

Cited by 2 publications

(2 citation statements)

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“…Other researchers have used different methods, but this study attempted a combined approach based on both the degree of deviation from the entropy of the criteria and the opinions of experts, using the best-worst method. The choice of ranking method has always been a topic of debate, and various studies have employed methods such as TOPSIS, DSM, (Khademi et al, 2010), GAHP (Krmac et al 2018), the balanced distance of options from the ideal option (Asadamraji et al 2024), and other methods (Hamurcu et al 2020). However, in this article, the CODAS method was used for ranking regions in the implementation of intelligent transportation systems, due to its dual control feature and the use of both Euclidean and Manhattan distances, which, according to the authors, result in more balanced and realistic rankings.…”

Section: Discussionmentioning

confidence: 99%

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

Dorji,

Rafsanjani,

AsadAmraji

2024

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Nowadays, the stratification of transportation has led to an enhancement of efficiency and a reduction in traffic and transportation issues. Intelligent transportation requires smart systems and equipment. This study presents a novel method for evaluating intelligent transportation systems (ITS) in urban regions. It emphasizes the necessity of assessing ITS quality and quantity in cities to determine the effectiveness in different urban regions. The research adopts a mixed-method approach to devise an evaluation model, focusing on five urban regions of Tehran (regions 3, 4, 12, 10, and 22). Thirteen indicators were selected to assess ITS development through multi-criteria decision-making methods, combining Shannon Entropy and best-worst methods to measure criteria effectively. Data were gathered via a questionnaire targeted at urban planning and transportation experts, producing 70 valid responses from an online survey. The evaluation employed the CODAS method, recognized for its robust control features. Results identified "The number of intelligent central control systems for traffic lights at intersections" as the pivotal indicator, with region 4 of Tehran scoring the highest. These findings provide crucial insights for scholars and policymakers, enhancing understanding of ITS evaluation and supporting budget allocations for such systems. The research's innovation lies in its unique approach to ITS assessment, integrating both quantitative data and expert opinions, which establishes a comprehensive framework for future evaluations in urban transportation planning. This contributes significantly to the academic and practical realms of transportation engineering, offering a strategic perspective on the deployment and enhancement of intelligent transportation frameworks in urban regions.

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Section: Discussionmentioning

confidence: 99%

“…As another example, in 2024, Asadamraji and colleagues prioritized smart transportation projects in the city of Isfahan, Iran, using the HWDP model, which is based on the balanced distance of options from an ideal option. This model was of a hybrid type (Asadamraji et al 2024).…”

Section: Introductionmentioning

confidence: 99%