交通群行为:行为分析中的机器学习和博弈论

IF 0.9 Q4 TELECOMMUNICATIONS
Gergely Hollósi, Csaba Lukovszki, Máté Bancsics, G. Magyar
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引用次数: 0

摘要

高速公路和城市街道上的高密度交通包括参与者之间无休止的互动。这些相互作用和相应的行为不仅对交通吞吐量有很大的影响,而且对安全性、舒适性和经济性也有很大的影响。正因为如此,人们对更深入地了解这些相互作用并总结对交通参与者的影响非常感兴趣。本文探索和描绘了交通行为分析的世界,特别是关注被称为交通群的车辆群体的研究,同时介绍了最先进的方法和算法。本文的结论指出,在不久的将来,交通行为分析的特殊领域有很大的研究潜力,可以比现有的方法更详细地描述交通行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic Swarm Behaviour: Machine Learning and Game Theory in Behaviour Analysis
High density traffic on highways and city streets consists of endless interactions among participants. These interactions and the corresponding behaviours have great impact not only on throughput of traffic but also on safety, comfort and economy. Because of this, there is a great interest in deeper understanding of these interactions and concluding the impacts on traffic participants. This paper explores and maps the world of traffic behaviour analysis, especially researches focusing on groups of vehicles called traffic swarm, while presents the state-of-the-art methods and algorithms. The conclusion of this paper states that there are special areas of traffic behaviour analysis which have great research potential in the near future to describe traffic behaviour in more detail than present methods.
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来源期刊
Infocommunications Journal
Infocommunications Journal TELECOMMUNICATIONS-
CiteScore
1.90
自引率
27.30%
发文量
0
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