Fuzzy Rules to Improve Traffic Light Decisions in Urban Roads

• 作者: D. Uribe Agundis J. A. Castá J. D. Terá J. Laria Menchaca J. Pé M. G. Treviñ n Rocha n Villanueva nez o Berrones rez Cobos S. Ibarra Martí
• 来源期刊: 智能学习系统与应用(英文)
• 学科: 医学
• 关键词: Fuzzy INFERENCE SYSTEM URBAN TRAFFIC Control Vehicular MOBILITY Intelligent Transport SYSTEM
• 年，卷（期）: 2018,（2）
• 页码范围: 36-45
• 页数: 10页
• 分类号: R73

摘要

Many researchers around the world are looking for developing techniques or technologies that cover traditional and recent constraints in urban traffic con-trol. Normally, such traffic devices are facing with a large scale of input data when they must to response in a reliable, suitable and fast way. Because of such statement, the paper is devoted to introduce a proposal for enhancing the traffic light decisions. The principal goal is that a semaphore can provide a correct and fluent vehicular mobility. However, the traditional semaphore operative ways are outdated. We present in a previous contribution the development of a methodology capable of improving the vehicular mobility by proposing a new green light interval based on road conditions with a CBR approach. However, this proposal should include whether it is needed to modify such light duration. To do this, the paper proposes the adaptation of a fuzzy inference system helping to decide when the semaphore should try to fix the green light interval according to specific road requirements. Some experiments are conducted in a simulated environment to evaluate the pertinence of implementing a decision-making before the CBR methodology. For example, using a fuzzy inference approach the decisions of the system improve almost 18% in a set of 10,000 experiments. Finally, some conclusions are drawn to emphasize the benefits of including this technique in a methodology to implement intelligent semaphores.