A Neuro-fuzzy Based Approach to Cooperative Ramp Metering

To solve today's road traffic congestion problems new solutions in the form of advanced control approaches of existing road infrastructure. Such solutions are from the domain of intelligent transportation systems and include various services. Technologies such as advanced driver assistant syste...

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Bibliographic Details
Main Authors: Greguric, Martin, Ivanjko, Edouard, Mandzuka, Sadko
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Automatic control
Control systems
Delays
Highways
Infrastructure
Mathematical model
Metering
Prediction algorithms
Predictive models
Ramps
Road transportation
Roads
Vehicles
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Summary:To solve today's road traffic congestion problems new solutions in the form of advanced control approaches of existing road infrastructure. Such solutions are from the domain of intelligent transportation systems and include various services. Technologies such as advanced driver assistant systems, and communication between vehicles and the road infrastructure are enabling new possibilities in traffic control. Vehicles can obtain a control input from the traffic management system and become an actuator ensuring that the driver complies to the traffic control system. In this paper, a concept of possible automatic vehicle control in cooperation with neuro-fuzzy based urban highway control systems (ramp metering and variable speed limit control) is described. Implemented urban highway control systems are tested using the CTMSIM simulator assuming that all vehicles support automatic vehicle control.
ISSN:2153-0009
2153-0017
DOI:10.1109/ITSC.2015.17