{"title":"Peephole转向:受限视图尺寸下转向性能的速度限制模型","authors":"Shota Yamanaka, Hiroki Usuba, Haruki Takahashi, Homei Miyashita","doi":"10.20380/GI2020.46","DOIUrl":null,"url":null,"abstract":"The steering law is a model for predicting the time and speed for passing through a constrained path. When people can view only a limited range of the path forward, they limit their speed in preparation of possibly needing to turn at a corner. However, few studies have focused on how limited views affect steering performance, and no quantitative models have been established. The results of a mouse steering study showed that speed was linearly limited by the path width and was limited by the square root of the viewable forward distance. While a baseline model showed an adjusted R2 = 0.144 for predicting the speed, our best-fit model showed an adjusted R2 = 0.975 with only one additional coefficient, demonstrating a comparatively high prediction accuracy for given viewable forward distances.","PeriodicalId":93493,"journal":{"name":"Proceedings. Graphics Interface (Conference)","volume":"1 1","pages":"461-469"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Peephole Steering: Speed Limitation Models for Steering Performance in Restricted View Sizes\",\"authors\":\"Shota Yamanaka, Hiroki Usuba, Haruki Takahashi, Homei Miyashita\",\"doi\":\"10.20380/GI2020.46\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The steering law is a model for predicting the time and speed for passing through a constrained path. When people can view only a limited range of the path forward, they limit their speed in preparation of possibly needing to turn at a corner. However, few studies have focused on how limited views affect steering performance, and no quantitative models have been established. The results of a mouse steering study showed that speed was linearly limited by the path width and was limited by the square root of the viewable forward distance. While a baseline model showed an adjusted R2 = 0.144 for predicting the speed, our best-fit model showed an adjusted R2 = 0.975 with only one additional coefficient, demonstrating a comparatively high prediction accuracy for given viewable forward distances.\",\"PeriodicalId\":93493,\"journal\":{\"name\":\"Proceedings. Graphics Interface (Conference)\",\"volume\":\"1 1\",\"pages\":\"461-469\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. Graphics Interface (Conference)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20380/GI2020.46\",\"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. Graphics Interface (Conference)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20380/GI2020.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Peephole Steering: Speed Limitation Models for Steering Performance in Restricted View Sizes
The steering law is a model for predicting the time and speed for passing through a constrained path. When people can view only a limited range of the path forward, they limit their speed in preparation of possibly needing to turn at a corner. However, few studies have focused on how limited views affect steering performance, and no quantitative models have been established. The results of a mouse steering study showed that speed was linearly limited by the path width and was limited by the square root of the viewable forward distance. While a baseline model showed an adjusted R2 = 0.144 for predicting the speed, our best-fit model showed an adjusted R2 = 0.975 with only one additional coefficient, demonstrating a comparatively high prediction accuracy for given viewable forward distances.