{"title":"An intelligent traffic control systems using on-road cameras","authors":"Md Mehedi Hassan, S. Karungaru, K. Terada","doi":"10.1117/12.2589192","DOIUrl":null,"url":null,"abstract":"The main reasons behind the traffic jam and accidents are illegal/double parking, over-speeding, violating signal lights, construction, wrong-way driving, reckless driving, unsafe lane changing, etc. To determines the problems and the solutions, this study proposes a two-step approach. One is data collection and the other is Optimization. In the data collection part, traffic information is obtained from various traffic information units through cameras installed in traffic signals and roads. By analyzing the collected data, the systems can take the next step in the optimization part. In the collected data, it is required to detect vehicles, pedestrians, and lanes. Yolov3 method was used for vehicles and pedestrians’ detection. For lane detection, the Hough transform was used. The main goal of the research is not detecting objects but to determine the intelligent systems which can combine all the collected data and give the optimum solutions to control the traffic signals depending on the situations. The study found that sometimes the vehicles are unnecessarily waiting for the signals. If the unnecessary time could be saved through signals then it would reduce time consumption, oil consumption, and mental impatience. The result would give us opportunities to reduce accidents, pollution, money, and time. Moreover, the systems can measure the speed which helps find out rule violating vehicles. This paper also proposed a method for shortest path calculation. In addition, automatic penalty execution can be carried out through the collected data. For that number plate recognition is included in future works.","PeriodicalId":295011,"journal":{"name":"International Conference on Quality Control by Artificial Vision","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Quality Control by Artificial Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2589192","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The main reasons behind the traffic jam and accidents are illegal/double parking, over-speeding, violating signal lights, construction, wrong-way driving, reckless driving, unsafe lane changing, etc. To determines the problems and the solutions, this study proposes a two-step approach. One is data collection and the other is Optimization. In the data collection part, traffic information is obtained from various traffic information units through cameras installed in traffic signals and roads. By analyzing the collected data, the systems can take the next step in the optimization part. In the collected data, it is required to detect vehicles, pedestrians, and lanes. Yolov3 method was used for vehicles and pedestrians’ detection. For lane detection, the Hough transform was used. The main goal of the research is not detecting objects but to determine the intelligent systems which can combine all the collected data and give the optimum solutions to control the traffic signals depending on the situations. The study found that sometimes the vehicles are unnecessarily waiting for the signals. If the unnecessary time could be saved through signals then it would reduce time consumption, oil consumption, and mental impatience. The result would give us opportunities to reduce accidents, pollution, money, and time. Moreover, the systems can measure the speed which helps find out rule violating vehicles. This paper also proposed a method for shortest path calculation. In addition, automatic penalty execution can be carried out through the collected data. For that number plate recognition is included in future works.