O. Santos, F. Ribeiro, J. Metrôlho, Rogério Dionísio
{"title":"利用智能交通灯减少二氧化碳排放并改善交叉路口的交通流量:葡萄牙小城十字路口模拟","authors":"O. Santos, F. Ribeiro, J. Metrôlho, Rogério Dionísio","doi":"10.3390/asi7010003","DOIUrl":null,"url":null,"abstract":"Reducing CO2 emissions is currently a key policy in most developed countries. In this article, we evaluate whether smart traffic lights can have a relevant role in reducing CO2 emissions in small cities, considering their specific traffic profiles. The research method is a quantitative modelling approach tested by computational simulation. We propose a novel microscopic traffic simulation framework, designed to simulate realistic vehicle kinematics and driver behaviour, and accurately estimate CO2 emissions. We also propose and evaluate a routing algorithm for smart traffic lights, specially designed to optimize CO2 emissions at intersections. The simulations reveal that deploying smart traffic lights at a single intersection can reduce CO2 emissions by 32% to 40% in the vicinity of the intersection, depending on the traffic density. The simulations show other advantages for drivers: an increase in average speed of 60% to 101% and a reduction in waiting time of 53% to 95%. These findings can be useful for city-level decision makers who wish to adopt smart technologies to improve traffic flows and reduce CO2 emissions. This work also demonstrates that the simulator can play an important role as a tool to study the impact of smart traffic lights and foster the improvement in smart routing algorithms to reduce CO2 emissions.","PeriodicalId":36273,"journal":{"name":"Applied System Innovation","volume":"13 1","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Smart Traffic Lights to Reduce CO2 Emissions and Improve Traffic Flow at Intersections: Simulation of an Intersection in a Small Portuguese City\",\"authors\":\"O. Santos, F. Ribeiro, J. Metrôlho, Rogério Dionísio\",\"doi\":\"10.3390/asi7010003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reducing CO2 emissions is currently a key policy in most developed countries. In this article, we evaluate whether smart traffic lights can have a relevant role in reducing CO2 emissions in small cities, considering their specific traffic profiles. The research method is a quantitative modelling approach tested by computational simulation. We propose a novel microscopic traffic simulation framework, designed to simulate realistic vehicle kinematics and driver behaviour, and accurately estimate CO2 emissions. We also propose and evaluate a routing algorithm for smart traffic lights, specially designed to optimize CO2 emissions at intersections. The simulations reveal that deploying smart traffic lights at a single intersection can reduce CO2 emissions by 32% to 40% in the vicinity of the intersection, depending on the traffic density. The simulations show other advantages for drivers: an increase in average speed of 60% to 101% and a reduction in waiting time of 53% to 95%. These findings can be useful for city-level decision makers who wish to adopt smart technologies to improve traffic flows and reduce CO2 emissions. This work also demonstrates that the simulator can play an important role as a tool to study the impact of smart traffic lights and foster the improvement in smart routing algorithms to reduce CO2 emissions.\",\"PeriodicalId\":36273,\"journal\":{\"name\":\"Applied System Innovation\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2023-12-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied System Innovation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/asi7010003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied System Innovation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/asi7010003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Using Smart Traffic Lights to Reduce CO2 Emissions and Improve Traffic Flow at Intersections: Simulation of an Intersection in a Small Portuguese City
Reducing CO2 emissions is currently a key policy in most developed countries. In this article, we evaluate whether smart traffic lights can have a relevant role in reducing CO2 emissions in small cities, considering their specific traffic profiles. The research method is a quantitative modelling approach tested by computational simulation. We propose a novel microscopic traffic simulation framework, designed to simulate realistic vehicle kinematics and driver behaviour, and accurately estimate CO2 emissions. We also propose and evaluate a routing algorithm for smart traffic lights, specially designed to optimize CO2 emissions at intersections. The simulations reveal that deploying smart traffic lights at a single intersection can reduce CO2 emissions by 32% to 40% in the vicinity of the intersection, depending on the traffic density. The simulations show other advantages for drivers: an increase in average speed of 60% to 101% and a reduction in waiting time of 53% to 95%. These findings can be useful for city-level decision makers who wish to adopt smart technologies to improve traffic flows and reduce CO2 emissions. This work also demonstrates that the simulator can play an important role as a tool to study the impact of smart traffic lights and foster the improvement in smart routing algorithms to reduce CO2 emissions.