Digital technologies of transportation-related communication: Review and the state-of-the-art

Yigitcanlar, Tan; Downie, Adam T.; Mathews, Shane; Fatima, Samar; MacPherson, John; Behara, Krishna N.S.; Paz, Alexander

doi:10.1016/j.trip.2023.100987

Cited by 2 publications

(1 citation statement)

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“…The deployment of intelligent transportation systems is an approach that leads to smart development and enhanced efficiency in cities (Elassy et al 2024). Intelligent transportation systems provide a framework and order that offer a range of optimal solutions for improving traffic flow smoothness and safety (Oladimeji et al 2023), and meeting transportation needs through the application of new technologies in information processing (Yigitcanlar et al 2024), communications, control, and electronics globally (Bazzan et al 2013). The use of intelligent transportation systems is among the measures that have attracted considerable attention from urban transport and traffic managers (Jain et al 2021) and experts in major cities around the world in recent decades (Ikpe et al 2024).…”

Section: Introductionmentioning

confidence: 99%

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

Dorji,

Rafsanjani,

AsadAmraji

2024

Preprint

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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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