{"title":"以关键驾驶为例,应用地形特征识别速度模式","authors":"Antonios Karatzoglou","doi":"10.1145/3423457.3429362","DOIUrl":null,"url":null,"abstract":"Finding the right features represents an essential part when trying to identify patterns in spatiotemporal signals. This paper describes the concept of using the topographic properties prominence and isolation for recognizing critical driving patterns in speed signals. Experiments show that both features can help identify specific driving segments in the users' speed data such as harsh acceleration, abrupt braking as well as over-speeding phases.","PeriodicalId":129055,"journal":{"name":"Proceedings of the 13th ACM SIGSPATIAL International Workshop on Computational Transportation Science","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Applying topographic features for identifying speed patterns using the example of critical driving\",\"authors\":\"Antonios Karatzoglou\",\"doi\":\"10.1145/3423457.3429362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Finding the right features represents an essential part when trying to identify patterns in spatiotemporal signals. This paper describes the concept of using the topographic properties prominence and isolation for recognizing critical driving patterns in speed signals. Experiments show that both features can help identify specific driving segments in the users' speed data such as harsh acceleration, abrupt braking as well as over-speeding phases.\",\"PeriodicalId\":129055,\"journal\":{\"name\":\"Proceedings of the 13th ACM SIGSPATIAL International Workshop on Computational Transportation Science\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 13th ACM SIGSPATIAL International Workshop on Computational Transportation Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3423457.3429362\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 13th ACM SIGSPATIAL International Workshop on Computational Transportation Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3423457.3429362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applying topographic features for identifying speed patterns using the example of critical driving
Finding the right features represents an essential part when trying to identify patterns in spatiotemporal signals. This paper describes the concept of using the topographic properties prominence and isolation for recognizing critical driving patterns in speed signals. Experiments show that both features can help identify specific driving segments in the users' speed data such as harsh acceleration, abrupt braking as well as over-speeding phases.