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  • برآورد میزان مصرف سوخت و آلودگی هوای ناشی از تردد سامانه اتوبوس‌های تندرو شهری با استفاده از مدل‌سازی عامل بنیان

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آدرس مقاله


کد مقاله : JEST-2303-5817 (R1) بازدید : 137 صفحه: 39 - 57

10.30495/jest.2023.72315.5817

نوع مقاله: پژوهشی

برآورد میزان مصرف سوخت و آلودگی هوای ناشی از تردد سامانه اتوبوس‌های تندرو شهری با استفاده از مدل‌سازی عامل بنیان

محورهای موضوعی : حمل و نقل شهری

رحمان نورمحمدی 1 , سید محمدعلی خاتمی فیروزآبادی 2 , اکبر عالم تبریز 3 , رضا احتشام راثی 4 , امیر دانشور 5

1 - دانشجوی دکتری، گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.
2 - استاد، گروه مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبایی، تهران، ایران و استاد مدعو، گروه مدیریت صنعتی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران. *(مسئول مکاتبات).
3 - استاد،گروه مدیریت صنعتی و فناوری اطلاعات، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران.
4 - استادیار، گروه مدیریت صنعتی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران.
5 - استادیار،گروه مدیریت فناوری اطلاعات، واحد الکترونیکی، دانشگاه آزاد اسلامی، تهران، ایران.

تاریخ دریافت : 1401/12/15 تاریخ پذیرش : 1402/02/13 تاریخ انتشار : 1402/06/01

کلید واژه: اتوبوس های تندرو, گازوئیل, نت لوگو, مدل سازی عامل بنیان, آلودگی هوا,

چکیده مقاله :

زمینه و هدف: افزایش ترافیک مشکلات زیادی را در کلان شهرها به همراه داشته که مهمترین آن آلودگی هوا و افزایش مصرف بی رویه سوخت است، از اقداماتی که می توان انجام داد، توجه به حمل و نقل عمومی به ویژه سامانه اتوبوس‌های تندرو است، زیرا علاوه بر کاهش هزینه‌های اجتماعی می‌تواند در کاهش آلودگی هوا نیز بسیار موثر باشد. هدف اصلی این تحقیق، مطالعه میزان مصرف سوخت و میزان انتشار انواع آلاینده‌های هوا شامل گازهـای CO2، CH4 ، N2O در سناریوهای مختلف سامانه اتوبوس های تندرو است. روش بررسی: از آنجـا کـه پدیده‌های ترافیکی و ازدحام دارای خصوصیاتی از جمله پیچیدگی و پویـایی هستند، مدل‌سازی آنها با مدل‎های ریاضی معمول بسیار دشوار و بعضاً غیرممکن است. به همین منظـور، مـی‌تـوان از تکنولوژی‌های مبتنی بر عامل‎ که دارای همخـوانی بـالایی بـا ایـن خصوصـیات هستند، بهـره گرفـت. در این تحقیق با استفاده از مدل‌سازی عامل‌‌بنیان سیستم عملکرد اتوبوس‌های تندرو شهری (BRT)، میزان مصرف سوخت و همچنین میزان تولید آلاینده‌های هوا برآورد شده است. تأکید این پژوهش بر این مطلب است که برای کنترل مصرف سوخت و بهبود عوامل آلاینده می‌بایست چه تغییراتی در پارامترهای موثر شامل سرعت اتوبوس‌ها، زمان توقف اتوبوس‌ها در ایستگاه‌ها و زمان‌بندی اعزام اتوبوس‌ها ایجاد شود. در این تحقیق، از نرم افزار پایۀ NetLogo برای کدنویسی مدل و اجرای شبیه سازی آن استفاده شده و سه سناریو متفاوت در خط یک اتوبوس های تندرو شهر تهران در نظر گرفته شده است. یافته ها: پس از تحلیل و مقایسۀ وضعیت‌های مختلف، پیشنهادهایی برای کاهش مصرف سوخت و آلاینده‌های هوا ارائه شده است، از جمله این که با تغییرات جزئی در پارامترهای زمان توقف اتوبوس‌ها در ایستگاه‌ها و همچنین تغییرات در زمان اعزام اتوبوس‌ها از پایانه می توان نسبت به بهبود وضعیت میزان مصرف سوخت و آلودگی هوا اقدام نمود. نتایج حاکی از آن است که یکی از وضعیت های بهبود یافته مربوط به وضعیت افزایش پارامتر زمان اعزام اتوبوس ها و در سناریو پل بوده که میزان انتشار گازهـای CO2، CH4، N2O به ترتیب برابر 6/1458 و 122/1 و 781/11 در یک ساعت زمان پیک مسافری می باشد. بحث و نتیجه گیری: نتایج حاصل شده حاکی از آن است که دستیابی به اهداف کاهش مصرف سوخت و آلودگی هوا در وضعیت سناریوی پل نسبت به دو سناریوی دیگر مناسب‌تر است. همچنین در صورت امکان در تقاطع‌های دارای ترافیک بالا نسبت به ایجاد پل اقدام گردد و یا ایجاد سامانه چراغ‌های راهنمایی هوشمند نیز در دستور کار باشد.

چکیده انگلیسی:

Background and Objective: The increased traffic has been followed by many problems in metropolitans, the key of which is air pollution and excessive fuel consumption. Paying attention to public transportation, particularly the bus rapid transit (BRT) system is one of the measures that may be taken, since besides reducing social expenses, it may be very effective in declining air pollution. The main objective of the present research is to study the fuel consumption rate and the emissions rate of various air pollutants including CO2, CH4, and N2O gases in various scenarios of BRT system. Material and Methodology: Since traffic and congestion phenomena are complex and dynamic, it is very difficult and sometimes impossible to model them with common mathematical models. To this end, agent-based technologies, highly compatible with these characteristics, can be utilized. In the current research, BRT system’s performance, the fuel consumption rate, and the amount of air pollutants production are estimated using agent-based modeling. This study emphasizes what changes should be made in effective parameters such as bus speed and bus stop time at stations, as well as bus dispatch timing in order to control fuel consumption and reduce pollution factors. This research uses NetLogo software to code the model and run its simulation and considers three different scenarios in line one of BRT system in Tehran (Iran). Findings: following the analysis and comparison of different scenarios, suggestions are made to decline fuel consumption and air pollutants, such as minor changes in the parameters of bus stop times at stations as well as changes in the dispatch time of buses from the terminal in order to reduce fuel consumption and air pollution rates. The results indicate that one of the improved situations was related to the situation of increasing the bus dispatch time parameter and in the bridge scenario, CO2, CH4, and N2O emissions are 1458.6, 1.122, and 11.781, respectively, in one hour of peak passenger time. Discussion and Conclusion: According to the results, achieving the goal of reducing fuel consumption and air pollution rates is more suitable in the bridge scenario compared to the other two scenarios. Furthermore, if possible, it is suggested to build bridges at intersections with high traffic, or put the smart traffic light system on the agenda.

منابع و مأخذ:


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_||_

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    2.
  2. Manisalidis, I.; Stavropoulou, E.; Stavropoulos, A.; Bezirtzoglou, E. Environmental and Health Impacts of Air Pollution: A Review. Front. Public Health 2020, 8, 14. [CrossRef] [PubMed]
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  3. Moya, Diego et al (2021), Agent-based scenarios comparison for assessing fuel-switching investment in long-term energy transitions of the India’s industry sector, Applied Energy, 274, 1-26.
    4.
  4. Asgari M. Potential to reduce pollutant emissions from personal rides In big cities with cars with new technologies Master’s (thesis). Iran. Faculty of Civil Engineering Sharif University; 2011. (In Persian)
    5.
  5. Ashrafi Kh., Shafipour M., Kamalan H. Estimating temporal and seasonal variation of ventilation coefficients, International Journal of Environmental Research,2009.
    6.
  6. USEPA (2009). Endangerment and Cause or Contribute Findings for Greenhouse Gases under Section 202(a) of the Clean Air Act. Available at: www.epa.gov/climatechange/index.html.
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  10. Etisam, Hadi, Rouhi, Amir (2014), investigating the causes of traffic congestion on rainy and snowy days and providing solutions to reduce it, 15th International Conference on Transportation and Traffic Engineering, Tehran, Traffic Transportation Organization. (In Persian)
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  11. Sachs J, Meng Y, Giarola S, Hawkes A. An agent-based model for energy investment decisions in the residential sector. Energy 2019;172: 752–68
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  23. Homayounfar, M., Bagher-Salimi, S., Nahavandi, B., Izadi Sheijani, K. (2018). Agentbased Simulation of National Oil Products Distribution Company’s Supply Network in the Framework of a Complex Adaptive System in Order to Achieve an Optimal Inventory Level. Industrial Management Journal, 10(4), 607-630.
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