SYSTEM ANALYSIS OF MAJOR TRENDS IN DEVELOPMENT OF ADAPTIVE TRAFFIC FLOW MANAGEMENT METHODS
https://doi.org/10.21122/2309-4923-2017-3-28-32
Abstract
Adaptive algorithms, which current traffic systems are based on, exist for many decades. Information technologies have developed significantly over this period and it makes more relevant their application in the field of transport. This paper analyses modern trends in the development of adaptive traffic flow control methods. Reviewed the most perspective directions in the field of intelligent transport systems, such as high-speed wireless communication between vehicles and road infrastructure based on such technologies as DSRC and WAVE, traffic jams prediction having such features as traffic flow information, congestion, velocity of vehicles using machine learning, fuzzy logic rules and genetic algorithms, application of driver assistance systems to increase vehicle’s autonomy. Advantages of such technologies in safety, efficiency and usability of transport are shown. Described multi-agent approach, which uses V2I-communication between vehicles and intersection controller to improve efficiency of control due to more complete traffic flow information and possibility to give orders to separate vehicles. Presented number of algorithms which use such approach to create new generation of adaptive transport systems.
About the Authors
A. N. Klimovich
Brest State Technical University
Russian Federation
limovich Andrei graduated
Russian Federation
limovich Andrei graduated
V. N. Shuts
Brest State Technical University
Belarus
Shuts Vasilii – Candidate of Technical Sciences, Associate Professor of the Department of Intellectual Information
Belarus
Shuts Vasilii – Candidate of Technical Sciences, Associate Professor of the Department of Intellectual Information
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Review
For citations:
Klimovich A.N., Shuts V.N. SYSTEM ANALYSIS OF MAJOR TRENDS IN DEVELOPMENT OF ADAPTIVE TRAFFIC FLOW MANAGEMENT METHODS. «System analysis and applied information science». 2017;(3):28-32. (In Russ.) https://doi.org/10.21122/2309-4923-2017-3-28-32
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