تعیین تأثیر نفوذ خودروهای خودران بر روی ظرفیت در معابر شریانی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد، دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران، تهران، ایران

2 دانشیار، دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران، تهران، ایران

3 دانشجوی کارشناسی ارشد، دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران، تهران، ایران

چکیده

افزایش ظرفیت شبکه ترافیک با ساخت معابر و زیرساخت‌های آن پرهزینه است. روش‌های مختلف مدیریت ترافیک برای رسیدگی به رشد سریع تقاضای سفر به روش‌های گوناگون ارائه شده است که از بین آن‌ها می‌توان اظهار نمود که وسایل نقلیه خودران نویدبخش خوبی برای پاسخگویی به تقاضای سفر می‌باشند. خودروهای خودران با توجه به کاهش خطاهای انسانی می‌تواند با کاهش فضا بین خودروها ظرفیت را افزایش دهند. ازاین‌رو در این تحقیق با اعمال ویژگی‌های مدل‌های وسایل نقلیه خودران و غیرخودران در شبکه معابر بخشی از تهران، با روش‌های گوناگون شبیه‌سازی شده است. در این شبیه‌سازی‌ها با استفاده از مدل‌ها، دنبال کردن خودرو، تغییر خط و دسته‌بندی خودروهای خودران در زمانی که با مقادیر سهم مختلف در شبکه مشارکت می‌کنند، در نظر گرفته شده است. پارامترهایی که در این تحقیق به عنوان خروجی در نظر گرفته شده عبارتند از میزان خودروهای عبوری از شبکه، سرعت میانگین کل شبکه و میانگین کل زمان سفر که مورد بررسی قرار گرفتند. همچنین تقاضای ترافیکی مختلفی بر روی شبکه اعمال شده است تا عملکرد خودروهای خودران در شرایط مختلف مورد بررسی قرار گیرد. نتایج نشان می‌دهد که نفوذ کامل خودروهای خودران می‌توانند حتی تا بیش از 50 درصد در ظرفیت شبکه تأثیر بگذاردو نیز تغییرات مقدار سرفاصله زمانی خودروهای خودران می‌تواند در تعامل خودروهای خودران در نفوذ مختلف، با خودروهای عادی تأثیر مثبتی داشته باشد و این نوید را می‌دهد که در واقعیت نیز تأثیرات آن را در شبکه‌های واقعی مشاهده شوند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Determining the Effect of Self-Driving Vehicles on Capacity in Arterial Passages

نویسندگان [English]

  • Shahriar Afandizadeh 1
  • Mahmoud Ahmadinejad 2
  • Arian Akbari 3
1 Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
2 Associated Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
3 M.Sc., Student, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
چکیده [English]

The solution to congestion is the balance of demand and supply side. Increasing network capacity with road construction and more infrastructure is expensive and environmentally damaging. With better utilization of existing infrastructure, road capacity can be increased. Different traffic management methods have been proposed to address the rapid growth of travel demand, which seem to be promising. Due to the reduction of human error due to faster reaction, Autonomous adopt less distance between vehicles, which can eventually increase capacity by reducing the space between vehicles. The ability of connecting to each other can also further contribute to the formation of Platooning. Increasing the number of AVs on roads around the world causes uncertainty about their impact on the capacity of roads with AV and non-AV vehicles and mostly faces many challenges. Therefore, in this study, by applying the characteristics of AV and non-AV vehicle models in the road network of west Tehran, related southern arterial routes by various methods, total of 825 simulations were performed. These simulations take into account the models of car following, lane change and Platooning, when they participate in the network with different share values with %10 intervals that normal vehicles constitute the entire traffic flow and in Each stage of the simulation contributes to AV cars, showing the Autonomous Vehicles effects that have on the capacity of the network passages, The results of the thesis show that the full penetration of Autonomous vehicles in Platoon can contribute more than %50 in the capacity of the network as well as increasing the amount of time headway for the free driving and Leader of the platoon vehicles, which will have a positive effect on the interaction of AVs in low penetration, and these promise to experts to observe its effects in reality.

کلیدواژه‌ها [English]

  • Penetration impact
  • Autonomous Vehicles
  • Capacity
  • Car following Model
  • Lane changing
  • Platooning

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