نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری مهندسی عمران، دانشکده مهندسی، دانشگاه فردوسی مشهد، مشهد، ایران

2 استادیار گروه عمران، دانشکده مهندسی، دانشگاه فردوسی مشهد، مشهد، ایران.

چکیده

در اجرای سیاست قیمت­گذاری تراکم ترافیک در کلانشهرها، نحوه تغییرات نرخ عوارض نسبت به زمان اهمیت زیادی دارد و در میزان کارایی طرح قیمت­گذاری تراکم ترافیک و بازدارندگی آن در میزان استفاده از خودروهای شخصی مؤثر است. بنابراین انتخاب مناسب­ترین شیوه برای زمان­بندی طرح­های قیمت­گذاری تراکم ترافیک نیازمند تحلیل و بررسی دقیق شیوه­های مختلف زمان­بندی و ارزیابی آنها با توجه به ویژگی­های ترافیکی و اجتماعی شهر مورد نظر است. در کلانشهرهای توریستی به دلیل حضور گردشگران، حجم سفرهای با اهداف تفریحی و خرید در این کلانشهرها بیشتر از سایر شهرهاست. از طرفی بخش زیادی از رانندگان نیز با مسیر آشنایی نداشته و موجب متفاوت شدن الگوی سفرهای درون­شهری در این کلانشهرها با سایر شهرها می­شوند. به همین دلیل، انتخاب شیوه مناسب زمان­بندی طرح­های قیمت­گذاری تراکم ترافیک در کلانشهرهای توریستی اهمیت بیشتری می­یابد. در این تحقیق، سه شیوه زمان­بندی عوارض ثابت، عوارض زمان­بندی شده و عوارض هوشمند برای زمان­بندی طرح­های قیمت­گذاری تراکم ترافیک در کلانشهرهای توریستی انتخاب شده و با استفاده از روش تحلیل شبکه­ای (ANP) و براساس مقایسات زوجی و نظرات کارشناسان رتبه­بندی شدند. براساس نتایج، شیوه عوارض زمان­بندی شده برای طرح­های قیمت­گذاری تراکم ترافیک با وزن نرمال 49/0 در رتبه نخست و شیوه­های عوارض ثابت و عوارض هوشمند به ترتیب با وزن­های نرمال 26/0 و 25/0 در رتبه­های دوم و سوم قرار گرفتند. مؤثرترین شاخص­های این ارزیابی به ترتیب شاخص­های کاهش زمان سفر، افزایش استفاده از حمل­ونقل عمومی، کاهش تردد خودروهای تک­سرنشین، افزایش سرعت عملکردی و کاهش تصادفات با عابرپیاده، موتور و دوچرخه سواران شناخته شدند. استفاده از نتایج این تحقیق در سیاست­گذاری­های مدیریت شهری موجب بهینه­سازی سیاست قیمت­گذاری تراکم ترافیک در کلانشهرهای توریستی مانند شهر مشهد شده و اثرگذاری این سیاست در کاهش تراکم ترافیک و مشکلات ناشی از آن را افزایش می­دهد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

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

نویسندگان [English]

  • masoud kadkhodaei 1
  • rouzbeh shad 2

1 Ph.D Student od Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad,Mashhad, Iran

2 Assistant Professor, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

چکیده [English]

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.

کلیدواژه‌ها [English]

  • Traffic congestion control
  • Congestion pricing
  • Tourism
  • Analytic Network Process

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