{"title":"采用数据挖掘的方法,利用GPS监测车辆速度","authors":"Seror Manea Bahloo","doi":"10.52113/3/eng/mjet/2021-09-02/09-16","DOIUrl":null,"url":null,"abstract":"The suggested effort is an endeavor to regulate the speed of the car using computer software that allows the owner to obtain information about the driver’s position, speed, and activities. To do this, the system must be able to send data in real time. The widespread accessibility of GPS-enabled instruments, as well as the enormous quantities of data collected from them, allows us to get a perfect understanding of the condition of traffic and the road network. The current study was prompted through a sample of “T-Drive GPS” trajectory data made public by Microsoft Research in 2010. The final objective was to estimate the average speeds of the road sections using the supplied trajectory data and therefore obtain a speed overview of the road network. The corrected sensor data are used by Driving Sense to detect three types of hazardous behaviors: uncontrolled speed, driving irregularly and shifting the directions. We test the efficacy of our system in real-world scenarios. Driving Sense can identify the convert of directions through driving and anomalous speed control with 93.95 percent accuracy and 90.54 percent recall, correspondingly, according to the findings. Furthermore, the speed estimate mistake is within an acceptable range of less than 2.1 m/s.","PeriodicalId":431983,"journal":{"name":"Muthanna Journal of Engineering and Technology","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Watching vehicle speed using GPS by using data mining approach\",\"authors\":\"Seror Manea Bahloo\",\"doi\":\"10.52113/3/eng/mjet/2021-09-02/09-16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The suggested effort is an endeavor to regulate the speed of the car using computer software that allows the owner to obtain information about the driver’s position, speed, and activities. To do this, the system must be able to send data in real time. The widespread accessibility of GPS-enabled instruments, as well as the enormous quantities of data collected from them, allows us to get a perfect understanding of the condition of traffic and the road network. The current study was prompted through a sample of “T-Drive GPS” trajectory data made public by Microsoft Research in 2010. The final objective was to estimate the average speeds of the road sections using the supplied trajectory data and therefore obtain a speed overview of the road network. The corrected sensor data are used by Driving Sense to detect three types of hazardous behaviors: uncontrolled speed, driving irregularly and shifting the directions. We test the efficacy of our system in real-world scenarios. Driving Sense can identify the convert of directions through driving and anomalous speed control with 93.95 percent accuracy and 90.54 percent recall, correspondingly, according to the findings. Furthermore, the speed estimate mistake is within an acceptable range of less than 2.1 m/s.\",\"PeriodicalId\":431983,\"journal\":{\"name\":\"Muthanna Journal of Engineering and Technology\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Muthanna Journal of Engineering and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52113/3/eng/mjet/2021-09-02/09-16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Muthanna Journal of Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52113/3/eng/mjet/2021-09-02/09-16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Watching vehicle speed using GPS by using data mining approach
The suggested effort is an endeavor to regulate the speed of the car using computer software that allows the owner to obtain information about the driver’s position, speed, and activities. To do this, the system must be able to send data in real time. The widespread accessibility of GPS-enabled instruments, as well as the enormous quantities of data collected from them, allows us to get a perfect understanding of the condition of traffic and the road network. The current study was prompted through a sample of “T-Drive GPS” trajectory data made public by Microsoft Research in 2010. The final objective was to estimate the average speeds of the road sections using the supplied trajectory data and therefore obtain a speed overview of the road network. The corrected sensor data are used by Driving Sense to detect three types of hazardous behaviors: uncontrolled speed, driving irregularly and shifting the directions. We test the efficacy of our system in real-world scenarios. Driving Sense can identify the convert of directions through driving and anomalous speed control with 93.95 percent accuracy and 90.54 percent recall, correspondingly, according to the findings. Furthermore, the speed estimate mistake is within an acceptable range of less than 2.1 m/s.