Kiss Gabor, Bakucz Peter
Institute of Safety Science and Cybersecurity, Obuda University, 1034 Budapest, Hungary.
Sensors (Basel). 2024 Sep 30;24(19):6337. doi: 10.3390/s24196337.
Self-driving cars are one of the main areas of research today, but it has to be acknowledged that the information from the sensors (the perceptron) is a huge amount of data, which is now unmanageable even when projected onto a single traffic junction. In the case of self-driving, the nodes have to be sequenced and organized according to the planned route. A self-driving car in Hungary would have to be able to interpret more than 70,000 traffic junctions to be able to drive all over the country. Besides the huge amount of data, another problem is the issue of validation and verification. For self-driving cars, this implies a level of complexity using traditional methods that calls into question the economics of the already existing system. Fuzzy Petri nets provide an alternative solution to both problems. They allow us to obtain a model that accurately describes the reliability of a node through its dynamics, which is essential in perception since the more reliable a node is, the smaller the deep learning mesh required. In this paper, we outline the analysis of a traffic node's safety using Petri nets and fuzzy analysis to gain information on the reliability of the node, which is essential for the modeling of self-driving cars, due to the deep learning model of perception. The reliability of the dynamics of the node is determined by using the modified fuzzy Petri net procedure. The need for a fuzzy extension of the Petri net was developed by knowledge of real traffic databases.
自动驾驶汽车是当今主要的研究领域之一，但必须承认，来自传感器（感知器）的信息是海量数据，即使投影到单个交通路口，目前也难以管理。在自动驾驶的情况下，节点必须根据规划路线进行排序和组织。在匈牙利，一辆自动驾驶汽车必须能够解读7万多个交通路口，才能在全国行驶。除了海量数据，另一个问题是验证和核实问题。对于自动驾驶汽车而言，这意味着使用传统方法会产生一定程度的复杂性，这对现有系统的经济性提出了质疑。模糊Petri网为这两个问题提供了一种替代解决方案。它们使我们能够通过其动态特性获得一个准确描述节点可靠性的模型，这在感知中至关重要，因为节点越可靠，所需的深度学习网格就越小。在本文中，我们概述了使用Petri网和模糊分析对交通节点安全性进行分析，以获取有关节点可靠性的信息，由于感知的深度学习模型，这对于自动驾驶汽车的建模至关重要。通过使用改进的模糊Petri网程序来确定节点动态特性的可靠性。对Petri网进行模糊扩展的需求是根据实际交通数据库的知识发展而来的。
