کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
524848 868866 2016 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Hierarchical model predictive control for multi-lane motorways in presence of Vehicle Automation and Communication Systems
ترجمه فارسی عنوان
کنترل مدل پیش بینی شده سلسله مراتبی برای بزرگراه های چند لاین در حضور سیستم های اتوماسیون و ارتباطات خودرو
کلمات کلیدی
کنترل ترافیک بزرگراه؛ سیستم های اتوماسیون و ارتباطات خودرو؛ کنترل مدل پیش بینی شده
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• A hierarchical MPC problem for traffic management in presence of VACS is proposed.
• The problem considers ramp metering, mainstream traffic flow control, and lane-changing control.
• The exploitation of VACS as actuators is envisaged.
• The effectiveness of this methodology is demonstrated using microscopic simulations.

A widespread deployment of vehicle automation and communication systems (VACS) is expected in the next years. This may lead to improvements in traffic management efficiency because of the novel possibilities of using VACS both as sensors and as actuators, as well as of a variety of new communications channels (vehicle-to-vehicles, vehicle-to-infrastructure) and related opportunities. To achieve this traffic flow efficiency, appropriate studies, developing potential control strategies to exploit the VACS availability, are essential. This paper describes a hierarchical model predictive control framework that can be used for the coordinated and integrated control of a motorway system, considering that an amount of vehicles are equipped with specific VACS. The concept employs and exploits the synergistic (integrated) action of a number of old and new control measures, including ramp metering, vehicle speed control, and lane changing control at a macroscopic level. The effectiveness and the computational feasibility of the proposed approach are demonstrated via microscopic simulation for a variety of penetration rates of equipped vehicles.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transportation Research Part C: Emerging Technologies - Volume 62, January 2016, Pages 117–132
نویسندگان
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