Ranking of traffic congestion pricing schemes in tourist metropolises: Case study of Mashhad

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Kadkhodaei Masoud; shad rouzbeh

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Journal Paper

Paper Information

Journal: MOTALEATE SHAHRI Year:2020 | Volume:9 | Issue:33 Page(s): 27-38

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Information Journal Paper

Title

Ranking of traffic congestion pricing schemes in tourist metropolises: Case study of Mashhad

Author(s)

Kadkhodaei Masoud | shad rouzbeh | Issue Writer Certificate

Keywords

Traffic congestion controlQ1

Congestion pricingQ1

TourismQ2

Analytic Network ProcessQ2

Abstract

With the ever-increasing production of private cars, there has been far heavier traffic flowing through the streets of large cities, causing problems such as increased air pollution and increased travel time and latency in urban trips. Congestion pricing provides a way of managing traffic congestion and the consequent problems in large cities. In the implementation of the Congestion pricing policy in large cities, it is of great significance how toll rate varies by time, affecting the efficiency of the plan and citizens’ tendency to use private cars. Therefore, adoption of the most appropriate method of scheduling in Congestion pricing plans requires a precise analysis of different scheduling methods and their evaluation given the traffic and social characteristics of the city. Due to the presence of tourists in large tourist destinations, there are larger numbers of trips taken for entertainment and shopping purposes than in other cities. Furthermore, many drivers are not familiar with the directions, which makes urban travel patterns different in such cities, making it more important to adopt the appropriate Congestion pricing plan scheduling. In this research, three methods, including fixed tolls, scheduled tolls, and smart tolls, were adopted for scheduling Congestion pricing plans in large tourist destinations and ranked using the Analytic Network Process (ANP) method, where decision elements, including evaluation criteria and options, are weighted using pairwise comparison as well as their interdependence In the pairwise comparisons, the importance of or preference for each decision element is determined by experts opinions. Each option is scored with respect to each criterion through multiplication of the option weight by the criterion value, and the final score of the option is obtained through calculation of the sum of the above scores, on which basis the evaluation options are ranked. Since the final weights thus obtained by the ANP method are not normal, more accurate comparison could be made after their normalization. Based on the results, the method of scheduled tolls for Congestion pricing plans were ranked first with a normalized weight of 0. 49, and the methods of fixed tolls and smart tolls were ranked second and third with normalized weights of 0. 26 and 0. 25, respectively. The most effective indicators in the assessment included reduction of travel time, increase in the use of public transportation, reduction of the number of drivers traveling alone, increase in operating speed, and reduction of accidents with pedestrians, motorcyclists, and cyclists, in that order. Use of the results of this research in urban management policy-making will optimize Congestion pricing policies adopted in large tourist destinations such as the city of Mashhad, Iran and increase their effectiveness in reduction of traffic congestion and the consequent problems.

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APA: Copy

Kadkhodaei, Masoud, & shad, rouzbeh. (2020). Ranking of traffic congestion pricing schemes in tourist metropolises: Case study of Mashhad. MOTALEATE SHAHRI, 9(33 ), 27-38. SID. https://sid.ir/paper/407730/en

Vancouver: Copy

Kadkhodaei Masoud, shad rouzbeh. Ranking of traffic congestion pricing schemes in tourist metropolises: Case study of Mashhad. MOTALEATE SHAHRI[Internet]. 2020;9(33 ):27-38. Available from: https://sid.ir/paper/407730/en

IEEE: Copy

Masoud Kadkhodaei, and rouzbeh shad, “Ranking of traffic congestion pricing schemes in tourist metropolises: Case study of Mashhad,” MOTALEATE SHAHRI, vol. 9, no. 33 , pp. 27–38, 2020, [Online]. Available: https://sid.ir/paper/407730/en

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