{"title":"使用混合优化算法实现道路安全和紧急车辆净空的最优分布式智能交通系统","authors":"Bhavani Sundar Raj, Srimathi Chandrasekaran","doi":"10.1504/ijsoi.2019.10025089","DOIUrl":null,"url":null,"abstract":"Nowadays, the population growth and their choice raise the number of vehicles, which raises traffic congestion in critical condition across the developing Nations like India. In consequence, emergency vehicles are stuck in traffic and waste their valuable time. Many authors focus on traffic problems in terms of intelligent traffic system without the consideration of emergency cases. In this paper, we propose an optimal distributed intelligent traffic system (ODITS) using hybrid optimisation algorithm. The proposed system designed by two phases are collision gathering and decision making. The clustered Jaya algorithm is used to gather the vehicle traffic information, which also differentiate emergency from normal vehicles. Then the modified multiobjective evolutionary based decision-making algorithm is used to compute the best route under the critical conditions. The simulation results shows that the proposed system reduces congestion in traffic, and waiting time of emergency vehicles without compromising normal vehicle speed, waiting time, and number of stopped vehicles.","PeriodicalId":35046,"journal":{"name":"International Journal of Services Operations and Informatics","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimal distributed intelligent traffic system for road safety, emergency vehicle clearance using hybrid optimisation algorithm\",\"authors\":\"Bhavani Sundar Raj, Srimathi Chandrasekaran\",\"doi\":\"10.1504/ijsoi.2019.10025089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, the population growth and their choice raise the number of vehicles, which raises traffic congestion in critical condition across the developing Nations like India. In consequence, emergency vehicles are stuck in traffic and waste their valuable time. Many authors focus on traffic problems in terms of intelligent traffic system without the consideration of emergency cases. In this paper, we propose an optimal distributed intelligent traffic system (ODITS) using hybrid optimisation algorithm. The proposed system designed by two phases are collision gathering and decision making. The clustered Jaya algorithm is used to gather the vehicle traffic information, which also differentiate emergency from normal vehicles. Then the modified multiobjective evolutionary based decision-making algorithm is used to compute the best route under the critical conditions. The simulation results shows that the proposed system reduces congestion in traffic, and waiting time of emergency vehicles without compromising normal vehicle speed, waiting time, and number of stopped vehicles.\",\"PeriodicalId\":35046,\"journal\":{\"name\":\"International Journal of Services Operations and Informatics\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Services Operations and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijsoi.2019.10025089\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Business, Management and Accounting\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Services Operations and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijsoi.2019.10025089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
Optimal distributed intelligent traffic system for road safety, emergency vehicle clearance using hybrid optimisation algorithm
Nowadays, the population growth and their choice raise the number of vehicles, which raises traffic congestion in critical condition across the developing Nations like India. In consequence, emergency vehicles are stuck in traffic and waste their valuable time. Many authors focus on traffic problems in terms of intelligent traffic system without the consideration of emergency cases. In this paper, we propose an optimal distributed intelligent traffic system (ODITS) using hybrid optimisation algorithm. The proposed system designed by two phases are collision gathering and decision making. The clustered Jaya algorithm is used to gather the vehicle traffic information, which also differentiate emergency from normal vehicles. Then the modified multiobjective evolutionary based decision-making algorithm is used to compute the best route under the critical conditions. The simulation results shows that the proposed system reduces congestion in traffic, and waiting time of emergency vehicles without compromising normal vehicle speed, waiting time, and number of stopped vehicles.
期刊介绍:
The advances in distributed computing and networks make it possible to link people, heterogeneous service providers and physically isolated services efficiently and cost-effectively. As the economic dynamics and the complexity of service operations continue to increase, it becomes a critical challenge to leverage information technology in achieving world-class quality and productivity in the production and delivery of physical goods and services. The IJSOI, a fully refereed journal, provides the primary forum for both academic and industry researchers and practitioners to propose and foster discussion on state-of-the-art research and development in the areas of service operations and the role of informatics towards improving their efficiency and competitiveness.