{"title":"探索新的定性方法来支持一瞥行为的定量分析","authors":"Mauricio Muñoz, B. Reimer, Bruce Mehler","doi":"10.1145/2799250.2799278","DOIUrl":null,"url":null,"abstract":"The work proposes conceptual ways of considering drivers' visual behavior over time as a flow of attention across space. These efforts extend upon previous works (research and regulatory) that focus in greater detail on quantifying attention independent of time. The primary contribution of this work lies in the presented methodology for analysis of glance allocation features. An application of this method is explored as an illustration of its analytic potential. Driver glance allocation data were drawn from a heterogeneous set of drivers. Double coded and mediated glance allocations were used to detail differences between drivers' visual behavior across 3 different task types (baseline driving, visual-manual interaction, auditory-vocal interaction). Glance transition counts were used to estimate glance transition probabilities and significance values. Glance duration features were explored in parallel and used to visualize temporal allocation distribution and significance. Results show that visualization techniques based on these features are well suited for qualitative analysis of visual attention.","PeriodicalId":443866,"journal":{"name":"Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Exploring new qualitative methods to support a quantitative analysis of glance behavior\",\"authors\":\"Mauricio Muñoz, B. Reimer, Bruce Mehler\",\"doi\":\"10.1145/2799250.2799278\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The work proposes conceptual ways of considering drivers' visual behavior over time as a flow of attention across space. These efforts extend upon previous works (research and regulatory) that focus in greater detail on quantifying attention independent of time. The primary contribution of this work lies in the presented methodology for analysis of glance allocation features. An application of this method is explored as an illustration of its analytic potential. Driver glance allocation data were drawn from a heterogeneous set of drivers. Double coded and mediated glance allocations were used to detail differences between drivers' visual behavior across 3 different task types (baseline driving, visual-manual interaction, auditory-vocal interaction). Glance transition counts were used to estimate glance transition probabilities and significance values. Glance duration features were explored in parallel and used to visualize temporal allocation distribution and significance. Results show that visualization techniques based on these features are well suited for qualitative analysis of visual attention.\",\"PeriodicalId\":443866,\"journal\":{\"name\":\"Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2799250.2799278\",\"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 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2799250.2799278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring new qualitative methods to support a quantitative analysis of glance behavior
The work proposes conceptual ways of considering drivers' visual behavior over time as a flow of attention across space. These efforts extend upon previous works (research and regulatory) that focus in greater detail on quantifying attention independent of time. The primary contribution of this work lies in the presented methodology for analysis of glance allocation features. An application of this method is explored as an illustration of its analytic potential. Driver glance allocation data were drawn from a heterogeneous set of drivers. Double coded and mediated glance allocations were used to detail differences between drivers' visual behavior across 3 different task types (baseline driving, visual-manual interaction, auditory-vocal interaction). Glance transition counts were used to estimate glance transition probabilities and significance values. Glance duration features were explored in parallel and used to visualize temporal allocation distribution and significance. Results show that visualization techniques based on these features are well suited for qualitative analysis of visual attention.