{"title":"Modeling the impact of VANET-enabled traffic lights control on the response time of emergency vehicles in realistic large-scale urban area","authors":"Hamed Noori","doi":"10.1109/ICCW.2013.6649290","DOIUrl":null,"url":null,"abstract":"In the last decade, intelligent transportation systems (ITS) have progressed at a rapid rate, which aim to improve transportation activities in terms of safety and efficiency. Car-to-car and car-to-infrastructure communications are important components of the ITS architecture. Communication between cars and traffic lights is one of the important V2I applications which helps to have dynamic and automatic traffic lights that can create several benefits such as minimizing the traffic jam, reducing fuel consumption and emissions, etc. This paper deals with decreasing the response time of the emergency cars by changing the traffic lights status with employing the communication technologies. The contribution of this paper is twofold: First, the effect of the changing traffic lights status to green for emergency cars is investigated by using traffic simulator (SUMO). Second, this paper uses OMNET++ (Network Simulator) in order to simulate the mentioned scenario as a VANET (with 802.11p standard) by using Veins framework to run SUMO and OMNET++ in parallel. This study has developed the Veins framework by adding a new module to OMNET++ to consider the traffic lights which are simulated in SUMO. Moreover this study has developed a new program written in Python which is connected to SUMO and controls the traffic simulation. This program uses SUMO to simulate a microscopic traffic (by considering every single vehicle movements) and also a city with intelligent traffic lights. Additionally, several statistics about traffic simulation is created for each car such as traveling time, waiting time, emissions, fuel consumption; or complete amount of car emissions in the street during the simulation, fuel consumption, number of vehicles and so on, for each street. This paper uses Manhattan realistic map to describe the mentioned program, then uses realistic map and realistic traffic demand of Cologne, Germany, to obtain a realistic and reliable result.","PeriodicalId":252497,"journal":{"name":"2013 IEEE International Conference on Communications Workshops (ICC)","volume":" 21","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Communications Workshops (ICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCW.2013.6649290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
In the last decade, intelligent transportation systems (ITS) have progressed at a rapid rate, which aim to improve transportation activities in terms of safety and efficiency. Car-to-car and car-to-infrastructure communications are important components of the ITS architecture. Communication between cars and traffic lights is one of the important V2I applications which helps to have dynamic and automatic traffic lights that can create several benefits such as minimizing the traffic jam, reducing fuel consumption and emissions, etc. This paper deals with decreasing the response time of the emergency cars by changing the traffic lights status with employing the communication technologies. The contribution of this paper is twofold: First, the effect of the changing traffic lights status to green for emergency cars is investigated by using traffic simulator (SUMO). Second, this paper uses OMNET++ (Network Simulator) in order to simulate the mentioned scenario as a VANET (with 802.11p standard) by using Veins framework to run SUMO and OMNET++ in parallel. This study has developed the Veins framework by adding a new module to OMNET++ to consider the traffic lights which are simulated in SUMO. Moreover this study has developed a new program written in Python which is connected to SUMO and controls the traffic simulation. This program uses SUMO to simulate a microscopic traffic (by considering every single vehicle movements) and also a city with intelligent traffic lights. Additionally, several statistics about traffic simulation is created for each car such as traveling time, waiting time, emissions, fuel consumption; or complete amount of car emissions in the street during the simulation, fuel consumption, number of vehicles and so on, for each street. This paper uses Manhattan realistic map to describe the mentioned program, then uses realistic map and realistic traffic demand of Cologne, Germany, to obtain a realistic and reliable result.