پژوهشنامه حمل و نقل

پژوهشنامه حمل و نقل

توسعه و ارزیابی نمودارهای کنترل آماری برای پایش وضعیت ترافیک (ارائه یک الگوریتم فراابتکاری خوشه‌بندی جدید)

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشجوی دکترا، گروه مهندسی صنایع، دانشگاه آزاد اسلامی، واحد تهران شمال، تهران، ایران
2 دانشیار، گروه فنی و مهندسی، دانشگاه آزاد اسلامی، واحد تهران شمال، تهران، ایران
3 دانش آموخته دکترا، گروه مهندسی صنایع، دانشگاه آزاد اسلامی، واحد تهران شمال، تهران، ایران
چکیده
پایش و تعیین لحظه‌ای وضعیت ترافیک در بزرگراه‌های شهری و برون‌شهری نقش مؤثری در افزایش بهره‌وری منابع و زیرساخت‌ها و همچنین افزایش رضایت ذینفعان سیستم‌های حمل‌ونقل دارد. تجزیه‌وتحلیل متغیرهای تصادفی ترافیکی مانند تردد و سرعت به تشخیص و پیش‌بینی وضعیت‌‌های غیرعادی ترافیک در یک مسیر با کمترین استفاده از منابع انسانی که عموماً نشان از وجود بحران‌های ترافیکی دارند، کمک می‌کند. در این مقاله، نمودارهای کنترل آماری تک و چندمتغیره برای پایش متغیرهای ترافیکی و شتاسایی وضعیت‌های غیرعادی پیشنهاد شده است. جهت ارتقا, عملکرد نمودارهای کنترل، الگوریتمی فراابتکاری مبتنی بر روش بهینه‌سازی ازدحام ذرات برای خوشه‌بندی بازه‌های زمانی ترافیک بر پایه‌ی داده‌های متغیرهای ترافیکی در یکی از معابر برون‌شهری تهران ارائه شده است. به ازای هر خوشه، نمودارهای کنترل مختلف توسعه داده شده و عملکرد آنها در هر خوشه ارزیابی شده است. استخراج قواعد تشخیص وضعیت‌های غیرعادی و اجرای نمودارهای کنترلی نشان می‌دهد که رویکرد پیشنهادی دقت قابل قبولی برای تعیین وضعیت ترافیک در یک مسیر دارد.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

A Meta-Heuristic Algorithm for Clustering and Monitoring Traffic Streams Using the Integrated Approach of Particle Swarm Optimization Algorithm and Shuhart Control Charts

نویسندگان English

Seyed Mohammad-Mahdi BaniHosseini 1
Vahid Baradaran 2
Mohammad Hadi Doroudian 3
1 Ph.D., Student, Industrial Engineering Department, Islamic Azad University, Tehran North Branch, Tehran, Iran.
2 Associate Professor, Engineering Faculty, Islamic Azad University, Hakimieh, Babaee Highway, Tehran, Iran.
3 Ph.D.,Grad., Industrial Engineering Department, Islamic Azad University, Tehran North Branch, Tehran, Iran.
چکیده English

Traffic monitoring and control in urban and intercity highways plays an effective role in increasing the efficiency of resources and infrastructure, as well as increasing the satisfaction of the stakeholders of transportation systems. Analyzing random traffic variables such as traffic and speed and diagnosing and predicting their unusual situations, which generally indicate the existence of traffic crises, is one of the approaches to monitoring traffic flow and solving traffic problems in metropolises. In this article, by using the data collected by traffic sensors, the data related to traffic variables have been grouped using an innovative algorithm based on the particle swarm optimization method in terms of the traffic situation. The grouped data were used to calculate suitable control limits for time intervals, and the results indicate the high performance of this method. For this purpose, in the first step, using an innovative method based on particle swarm optimization, the training data is grouped based on the values of traffic variables, including density, traffic and speed, and then the appropriate group is identified for each variable value. In the next step, the traffic situation is calculated for the clusters and hours of the day, and based on that, superior and standard control charts are drawn. The obtained results indicate the appropriate accuracy of the proposed system in traffic monitoring.

کلیدواژه‌ها English

Particle Swarm Optimization
Clustering
Intelligent Traffic Control
Shohart Control Chart
Traffic Situation
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