{"title":"基于物理和数据相结合的飞行器轨迹预测","authors":"Wansik Choi, C. Ahn","doi":"10.1109/ANZCC47194.2019.8945695","DOIUrl":null,"url":null,"abstract":"The physics and data-based methods are used to predict the trajectory of vehicles. To improve prediction performance, we suggest data-based methods using a deep learning model and a simple integration method. The integration method is the weighted sum, and the weights are extracted from the root mean square error of two methods. It shows enhanced results by taking the strength of both methods. The root mean square error of 0 to 3 seconds is less than 3 meter, and 3 to 6 seconds is less than 6 meter.","PeriodicalId":322243,"journal":{"name":"2019 Australian & New Zealand Control Conference (ANZCC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vehicle Trajectory Prediction with Integrating a Physics based Method and a Data-based Method\",\"authors\":\"Wansik Choi, C. Ahn\",\"doi\":\"10.1109/ANZCC47194.2019.8945695\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The physics and data-based methods are used to predict the trajectory of vehicles. To improve prediction performance, we suggest data-based methods using a deep learning model and a simple integration method. The integration method is the weighted sum, and the weights are extracted from the root mean square error of two methods. It shows enhanced results by taking the strength of both methods. The root mean square error of 0 to 3 seconds is less than 3 meter, and 3 to 6 seconds is less than 6 meter.\",\"PeriodicalId\":322243,\"journal\":{\"name\":\"2019 Australian & New Zealand Control Conference (ANZCC)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Australian & New Zealand Control Conference (ANZCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANZCC47194.2019.8945695\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Australian & New Zealand Control Conference (ANZCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANZCC47194.2019.8945695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vehicle Trajectory Prediction with Integrating a Physics based Method and a Data-based Method
The physics and data-based methods are used to predict the trajectory of vehicles. To improve prediction performance, we suggest data-based methods using a deep learning model and a simple integration method. The integration method is the weighted sum, and the weights are extracted from the root mean square error of two methods. It shows enhanced results by taking the strength of both methods. The root mean square error of 0 to 3 seconds is less than 3 meter, and 3 to 6 seconds is less than 6 meter.