Cloud traffic monitoring and control

Hahanov, Vladimir; Gharibi, Wajeb; Abbas, Baghdadi Ammar Awni; Chumachenko, Svetlana; Guz, Olesya; Litvinova, Eugenia

doi:10.1109/idaacs.2013.6662681

Cited by 9 publications

(3 citation statements)

References 3 publications

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“…[1] propose a cloud based traffic signal control system based on camera detection. [2] introduces another cloud based system that gathers data through RFID from vehicles and generates 'green wave traffic'. These studies focus on utilization of the computation power in the cloud and assume ideal network connections; hence, network latency could potentially degrade the performance of these systems.…”

Section: Related Workmentioning

confidence: 99%

Using AI for Mitigating the Impact of Network Delay in Cloud-based Intelligent Traffic Signal Control

Zhang,

Zhou,

Tonguz

2020

Preprint

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Section: Related Workmentioning

confidence: 99%

Using AI for Mitigating the Impact of Network Delay in Cloud-based Intelligent Traffic Signal Control

Zhang,

Zhou,

Tonguz

2020

Preprint

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“…Stochastic traffic models are used by specialist but very exceptional. Two most normal stochastic versatility prototypes incorporate Random Walk and Random Direction Mobility Model, 40,41 where the portable hubs are allowed to travel in any irregular ways.…”

Section: Associated Workmentioning

confidence: 99%

An optimal Internet of Things–based smart cities using vehicular cloud for smart driving

Devi

Krishnan

Lokesh

2018

Concurrency and Computation

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Empowering vehicular cloud can be done by having certain snapshot of the quantity of vehicles and their accessibility in a given lane through a model, and in addition, some additional framework, including movement of vehicles. The quantity of vehicles determines the calculation abilities accessible in this area and the traveling time shows the time of validity for a particular lane. Accordingly, in this paper, we do research using stochastic investigation of a few traffic attributes identified with the usage of cloud computing in a street portion to embrace appropriate activity prototypes. In particular, we have two sorts of activity situations that are considered: free-flow movement and queueing-up activity. We utilize a perceptible traffic model to explore the free-flow activity and examine some parameters, for example, activity thickness, vehicles quantity, and living arrangement time. Likewise, we use the queueing-up hypothesis to demonstrate the queue movement; the line length and the holding up time in the line are investigated. The outcomes will be presented for the customers who got struck in road traffic a common problem in all countries to get rid of traffic conditions. By using this, an alternate route will be predicted for the customer which is traffic free while driving.

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“…According to the ITS approach [4], as well as to the management tasks at each level of the hierarchy, we believe that the traffic control system (TCS) of the intelligent transport system should be based on the principle of multilevel architecture using ring Ethernet technologies that more closely corresponds to the diamond-shaped form of TCS structures. It allows to distribute not only methods of traffic control (TC) for purposes, but also to separate informational (i, n inf ) and technological (i, n T ) elements of the system ( fig.…”

mentioning

confidence: 99%

Structure of transformation of the road motion parameters in the control system

2019

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Over the past decades, the world has witnessed an increase in the number of vehicles. According to the accident analysis and to the existing transport problems, the development of automated traffic control systems using adaptive management methods is the most optimal way to improve road traffic quality. From the technological point of view, the system must function according to the requirements for the traffic flow level and to the assessment of traffic efficiency, so a clear comparison of systems is impossible under the conditions of various principles for identifying managerial impacts and the designation of management system. The authors' analysis of the most commonly used traffic management technologies proves that experts choose the system architecture that affects its functions and the ability to implement one or another method of management. In accordance with the ITS approach and management tasks at each hierarchy level, we believe that the traffic management system of the intelligent transport system should be based on the principle of multi-level architecture using ring Ethernet technologies, which corresponds more to the diamond-shaped system structure; it allows to distribute methods of traffic management for purposes and to separate the informational and technological elements of the system.

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Cloud traffic monitoring and control

Cited by 9 publications

References 3 publications

Using AI for Mitigating the Impact of Network Delay in Cloud-based Intelligent Traffic Signal Control

Using AI for Mitigating the Impact of Network Delay in Cloud-based Intelligent Traffic Signal Control

An optimal Internet of Things–based smart cities using vehicular cloud for smart driving

Structure of transformation of the road motion parameters in the control system

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