Traffic Swarm Behaviour: Machine Learning and Game Theory in Behaviour Analysis

被引:2
|
作者
Hollosi, Gergely [1 ]
Lukovszki, Csaba [1 ]
Bancsics, Mate [1 ]
Magyar, Gabor [1 ]
机构
[1] Budapest Univ Technol & Econ, Dept Telecommun & Media Informat, Budapest, Hungary
来源
INFOCOMMUNICATIONS JOURNAL | 2021年 / 13卷 / 04期
关键词
traffic swarm; traffic behaviour; behaviour analysis; game theory; machine learning; deep learning; MODEL; FRAMEWORK; EVOLUTION; STATES;
D O I
10.36244/ICJ.2021.4.3
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
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 the 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.
引用
收藏
页码:19 / 27
页数:9
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