Open AccessA Study on Application of Stochastic Queuing Models for Control of Congestion and Crowding
Author(s) -
Rachna Rathore
Publication year - 2022
Publication title -
international journal for global academic and scientific research
Language(s) - English
Resource type - Journals
ISSN - 2583-3081
DOI - 10.55938/ijgasr.v1i1.6
Subject(s) - traffic congestion , queueing theory , transport engineering , computer science , network traffic control , operations research , control (management) , network congestion , damages , social cost , crowding , economics , computer security , engineering , computer network , microeconomics , artificial intelligence , neuroscience , network packet , law , political science , biology
Traffic congestion is a common day-to-day trouble in many countries, especially large cities. Gradually, even medium-sized and small towns are experiencing such problems and suffering from their negative effects. Importantly, traffic and crowd congestion largely spoils a region's economic and social status. For commuters, traffic congestion gives rise to excess travel costs, duration, and travel discomfort. From a traffic management perspective, traffic congestion leads to more expenses in the traffic system for handling inconvenient road networks. At the social level, traffic congestion causes road accidents, environmental damages and pollution. This article provides an overview of current time's traffic and crowd management system through a review of literature on stochastic queuing models for congestion and congestion control. In particular, we will focus on issues related to tackling the practical need and available features, and alleviation of daily traffic blockages. Dealing in terms of the concepts taken from Operation Research, the most important techniques are analytical queuing model application, stochastic optimality, and robust effective optimal solutions to common road congestion problems.