{"title":"An Adaptive Road Traffic Regulation with Simulation and Internet of Things","authors":"S. Rajendran, S. Chelladurai, A. Aravind","doi":"10.1145/2901378.2901406","DOIUrl":null,"url":null,"abstract":"Traffic congestion is a growing concern in most cities across the world. It is primarily caused by a sudden increase in the number of vehicles in a relatively small number of roads and intersections, while other roads have the capacity to accommodate more traffic. In such situations, distributing traffic to roads in a balanced way could alleviate congestion. With the help of modern technology such as Internet of Things (IoT) and simulation, road users can be encouraged to choose their route on-the-fly, by providing necessary information such as projected travel time on the next leg. In extreme situations, traffic on some critical roads could be adaptively reduced by even introducing levy. A simple solution like providing road traffic information, benefits and penalties, etc., ahead in each intersection would allow travellers to make cognizant choices and therefore could lead to a better, more efficient traffic distribution. To implement the proposed system, simulation and IoT must be brought together by a suitable communication middleware system so that they can work in synchrony. Implementing an actual IoT infrastructure and then testing the cause and effects of traffic congestion with the system in-place is a daunting task. Simulation would help us to test and validate the IoT system for functionality, performance, and scalability. In this paper, we propose a novel framework for integrating IoT and simulation using a message-oriented middleware in the context of an adaptive traffic regulation system and then demonstrate the framework with the help of a prototype implementation.","PeriodicalId":325258,"journal":{"name":"Proceedings of the 2016 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2901378.2901406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Traffic congestion is a growing concern in most cities across the world. It is primarily caused by a sudden increase in the number of vehicles in a relatively small number of roads and intersections, while other roads have the capacity to accommodate more traffic. In such situations, distributing traffic to roads in a balanced way could alleviate congestion. With the help of modern technology such as Internet of Things (IoT) and simulation, road users can be encouraged to choose their route on-the-fly, by providing necessary information such as projected travel time on the next leg. In extreme situations, traffic on some critical roads could be adaptively reduced by even introducing levy. A simple solution like providing road traffic information, benefits and penalties, etc., ahead in each intersection would allow travellers to make cognizant choices and therefore could lead to a better, more efficient traffic distribution. To implement the proposed system, simulation and IoT must be brought together by a suitable communication middleware system so that they can work in synchrony. Implementing an actual IoT infrastructure and then testing the cause and effects of traffic congestion with the system in-place is a daunting task. Simulation would help us to test and validate the IoT system for functionality, performance, and scalability. In this paper, we propose a novel framework for integrating IoT and simulation using a message-oriented middleware in the context of an adaptive traffic regulation system and then demonstrate the framework with the help of a prototype implementation.