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Agent Based Simulation of ITS for Urban Traffic Control Using GPS | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 11، Special Issue، بهمن 2020، صفحه 249-263 اصل مقاله (449.9 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2020.4598 | ||
| نویسندگان | ||
| Mohammad Akhondi* 1؛ Mohammad Saadi Mesgari2 | ||
| 1Department of Civil and Architectural Engineering, Faculty of Shahid mohajer, Isfahan Branch, Technical and Vocational University (TVU), Isfahan, Iran | ||
| 2Associate Prof. of Geospatial Information System, Geodesy and Geomatics Engineering Faculty, K.N. Toosi University of Technology, Tehran, Iran | ||
| تاریخ دریافت: 18 بهمن 1398، تاریخ بازنگری: 11 مرداد 1399، تاریخ پذیرش: 19 مرداد 1399 | ||
| چکیده | ||
| Intelligent transportation systems (ITS), especially in metropolitan areas, can play a crucial role in reducing traffic and its flow and finally reducing the average travel time of vehicles. Due to the high capabilities of intelligent agents in modeling and simulation, they have been used significantly to model complex urban environments and traffic control systems in recent years. In fact, base operating systems are appropriate for modeling intelligent transportation systems, especially in changing urban spaces, and simulating related facilities and equipment. However, most researches in this area have not been comprehensive. As it was mentioned, in this research, a comprehensive agent-based modeling of intelligent urban transportation system is used to control and manage urban traffic using instantaneous traffic information of streets and finally various scenarios have been proposed and implemented. Also, all vehicles have been equipped with GPS and communication devices are simulated. In this study, more emphasis has been placed on intelligent traffic lights using traffic information than routing methods using traffic information and the results have shown high effect of the smartization of traffic lights compared to the change in vehicles routing methods in management and reduction of urban traffic in implemented scenarios. | ||
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