A traffic control model on VANET environment for minimum road risk in a shortest way

Saeid Ghahremani, M. Sattari, S. Khorsandroo, Mohamed Ahmed, R. M. Noor
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引用次数: 3

Abstract

Global warming and its related phenomena such as iceberg melting and sea level rising, is the result of human's penchant to industrial living which leads to increase of greenhouse gas emission. Increase of greenhouse gas inside the atmosphere gets result in Greenhouse effect phenomenon. This problem has received increasing attention from scholars and industries in recent years under name of green. Controlling or decreasing of Green House Gas emissions is possible by green programs and technologies in future. These programs are considered as an effective solution of global warming prevention. The main reason of greenhouse gas emissions in urban environment is unnecessary deceleration and acceleration of moving vehicles as well as drivers' risky actions such as reverse moves, fast speed zigzag moves. Therefore, a traffic management system is needed for providing smooth trips for drivers. By a periodic central abnormal and normal vehicles clustering, at each moment we can suggest less risk roads to vehicles for reaching to their destination with less risk. In addition potential hazards can be avoided. In this paper, we propose a model to calculate mobile vehicles risk by monitoring them and calculate the shortest path with minimum risk based on updated collected data in each moment. This model can use in both case of general and emergency vehicle.
基于最短路径最小道路风险的VANET环境交通控制模型
全球变暖及其相关现象,如冰山融化和海平面上升,是人类倾向于工业化生活导致温室气体排放增加的结果。大气中温室气体的增加导致温室效应现象。近年来,在绿色的名义下,这一问题越来越受到学者和业界的关注。在未来,通过绿色项目和技术控制或减少温室气体排放是可能的。这些项目被认为是防止全球变暖的有效解决方案。城市环境中温室气体排放的主要原因是行驶车辆不必要的减速和加速以及驾驶员的危险行为,如倒车、快速之字形行驶。因此,需要一个交通管理系统来为司机提供顺畅的出行。通过周期性的中心异常车辆和正常车辆聚类,我们可以在每个时刻为车辆提供风险较小的到达目的地的道路。此外,可以避免潜在的危险。本文提出了一种通过对移动车辆进行监测来计算其风险的模型,并根据每一时刻更新的采集数据计算出风险最小的最短路径。该型号可用于普通车辆和应急车辆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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