Transport network traffic management and urban travel demand to reduce air pollution (Case study: Shiraz)
- سال انتشار: 1402
- محل انتشار: مجله آنالیز غیر خطی و کاربردها، دوره: 14، شماره: 11
- کد COI اختصاصی: JR_IJNAA-14-11_028
- زبان مقاله: انگلیسی
- تعداد مشاهده: 80
نویسندگان
Department of Environmental Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
Department of Environmental Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
Department of Environmental Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
Department of Environmental Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
Department of Environmental Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
چکیده
Today, air pollution and energy consumption are metropolitans’ main transportation issues. In these cities, most people consider their mode of transportation based on the appropriate means, including passenger, travel characteristics, population growth, urban space, and transportation. Therefore, the systematic optimization of travel demand in the actual road network in urban areas is necessary. Travel Demand Management (TDM) is one of the well-known methods to solve these problems in congested areas. TDM is a strategy to reduce the efficiency of the urban transportation system by granting special concessions to public transportation methods, implementing the ban on private cars in certain places or times, and increasing the cost of using some facilities such as parking in busy areas pricing network. Transportation demand management is one of the most effective methods to reduce traffic and control air pollution, especially in crowded areas of the city center. A few studies have optimized urban transportation in congested cities by combining Markov decision processes based on decision processes with reward and evolution-based algorithms and simultaneously considering customers and travel characteristics. Therefore, this study provided a new network traffic management for urban cities with multiple objective functions related to the expected reward value of the Markov decision system using a genetic algorithm. Shiraz is considered as a benchmark to evaluate the performance of the proposed approach. Then, the impact of toll levels was evaluated on changes in user and operator cost components.کلیدواژه ها
Traffic management, Transportation Network, Travel demand, Decrease air pollutionاطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.