Adaptative Optimal Control of Nonlinear Systems Simulation to Support Hazardous Materials Traffic Management

Cooperative adaptative cruise controls and variable speed limit are gaining notoriety in recent years to fulfill the aim of reducing traffic congestions. Improvements in the management of hazardous materials, combined with these technologies, can reduce damages caused by congestions, mitigate risks...

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Bibliographic Details
Published inJournal of control, automation & electrical systems Vol. 32; no. 5; pp. 1143 - 1152
Main Authors Reis, Luiz Antonio, Pereira, Sergio Luiz, Dias, Eduardo Mario, Scoton, Maria Lídia Dias
Format Journal Article
LanguageEnglish
Published New York Springer US 2021
Springer Nature B.V
Subjects
Control
Control and Systems Theory
Control systems
Cooperative control
Cruise control
Decision making
Decision theory
Electrical Engineering
Engineering
Hazardous materials
Mechatronics
Nonlinear control
Nonlinear systems
Optimal control
Queuing theory
Robotics
Robotics and Automation
Shock waves
Systems simulation
Traffic capacity
Traffic congestion
Traffic control
Traffic engineering
Traffic flow
Traffic management
Traffic speed
Rippling traffic waves
Variable speed limit
Congestion phenomenon
Computer simulation
Closed-loop controller
Traffic engineering
Hazardous material transportation
Tracking control
Cooperative adaptative cruise controls
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Summary:Cooperative adaptative cruise controls and variable speed limit are gaining notoriety in recent years to fulfill the aim of reducing traffic congestions. Improvements in the management of hazardous materials, combined with these technologies, can reduce damages caused by congestions, mitigate risks to human health, and avoid environmental leakage. Drivers’ behaviors are directly influenced by human beings' different reactions. Therefore, the variance in traffic produces shockwaves, rippling traffic waves, and a reduction of the traffic flow capacity. This paper aims to present adaptative optimal control of nonlinear systems simulation as a tool to prove the effects of the predictions according to drivers’ behavior. Furthermore, it supports the decision making of hazardous material traffic management. Traffic engineering and queuing theory are also addressed.
ISSN:2195-3880
2195-3899
DOI:10.1007/s40313-021-00751-8