کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4942603 1437413 2017 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A group-based traffic signal control with adaptive learning ability
ترجمه فارسی عنوان
کنترل سیگنال مبتنی بر گروه با قابلیت یادگیری تطبیقی
کلمات کلیدی
سیستم ترافیک تطبیقی کنترل بهینه تصادفی، مرحله بندی مبتنی بر گروه، تقویت یادگیری، پشتیبان گیری چند مرحله ای،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Group-based control is an advanced traffic signal strategy capable of dynamically generating phase sequences at intersections. Combined with the phasing scheme, vehicle actuated timing is often adopted to respond to the detected traffic. However, the parameters of a signal controller are often predetermined in practice, and the control performance may suffer from deterioration when dealing with highly fluctuating traffic demand. This study proposes a group-based signal control approach capable of making decisions based on its understanding of traffic conditions at the intersection level. In particular, the control problem is formulated using a framework of stochastic optimal control for multi-agent system in which each signal group is modeled as an intelligent agent. The agents learn how to react to traffic environment and make optimal timing decisions according to the perceived system states. Reinforcement learning, enhanced by multiple-step backups, is employed as the kernel of the intelligent control algorithm, where each agent updates its knowledge on-line based on a sequence of states during the process. In addition, the proposed system is designated to be compatible with the prevailing signal system. A case study was carried out in a simulation environment to compare the proposed control approach with a benchmark controller used in practice, group-based vehicle actuated (GBVA) controller, whose parameters were off-line optimized using a genetic algorithm. Simulation results show that the proposed adaptive group-based control system outperforms the optimized GBVA control system mainly because of its real-time adaptive learning capacity in response to the changes in traffic demand.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 65, October 2017, Pages 282-293
نویسندگان
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