Petri nets, FCCS, and synchronous languages to specify discrete events systems: a comparative synthesis on validation power

Author(s):  
A. El Rhalibi ◽  
D. Crestani ◽  
F. Prunet ◽  
C. Durante
Author(s):  
Juan L. G. Guirao ◽  
Fernando L. Pelayo

This paper provides an overview over the relationship between Petri Nets and Discrete Event Systems as they have been proved as key factors in the cognitive processes of perception and memorization. In this sense, different aspects of encoding Petri Nets as Discrete Dynamical Systems that try to advance not only in the problem of reachability but also in the one of describing the periodicity of markings and their similarity, are revised. It is also provided a metric for the case of Non-bounded Petri Nets.


Author(s):  
Juan L. G. Guirao ◽  
Fernando L. Pelayo

This paper provides an overview over the relationship between Petri Nets and Discrete Event Systems as they have been proved as key factors in the cognitive processes of perception and memorization. In this sense, different aspects of encoding Petri Nets as Discrete Dynamical Systems that try to advance not only in the problem of reachability but also in the one of describing the periodicity of markings and their similarity, are revised. It is also provided a metric for the case of Non-bounded Petri Nets.


2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Hannes Weinreuter ◽  
Balázs Szigeti ◽  
Nadine-Rebecca Strelau ◽  
Barbara Deml ◽  
Michael Heizmann

Abstract Autonomous driving is a promising technology to, among many aspects, improve road safety. There are however several scenarios that are challenging for autonomous vehicles. One of these are unsignalized junctions. There exist scenarios in which there is no clear regulation as to is allowed to drive first. Instead, communication and cooperation are necessary to solve such scenarios. This is especially challenging when interacting with human drivers. In this work we focus on unsignalized T-intersections. For that scenario we propose a discrete event system (DES) that is able to solve the cooperation with human drivers at a T-intersection with limited visibility and no direct communication. The algorithm is validated in a simulation environment, and the parameters for the algorithm are based on an analysis of typical human behavior at intersections using real-world data.


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