使用罗盘传感器来预测即将到来的公共汽车站的路段特征

Danila Chenchik, Jia Chen, S. Yan, S. Nirjon
{"title":"使用罗盘传感器来预测即将到来的公共汽车站的路段特征","authors":"Danila Chenchik, Jia Chen, S. Yan, S. Nirjon","doi":"10.1109/PERCOMW.2017.7917604","DOIUrl":null,"url":null,"abstract":"We devise an inexpensive and intuitive system for bus route navigation for locales where public transportation may serve as a prevalent mode of commute but where technologies that make arrival predictions through tracking vehicles in transit through GPS or other means do not exist. These systems typically require real-time monitoring of traffic variations. We provide a personalized approach where in a world of pervasive smart phone use, users may take advantage of sensor data to learn and personalize their bus routes, and alert them on time when a bus stop is approaching. We accomplish this through the development and implementation of two algorithms: 1) turn detection using on-board compass sensor of a smart phone, and 2) characterizing road segments in terms of turns and thereby predicting approaching bus stops. We conduct field experiments on a route with four selected bus stops in the town of Chapel Hill. Results show that the accuracy of turn detection and detection of approaching bus stops are 95.7% and 83%, respectively.","PeriodicalId":319638,"journal":{"name":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Characterizing road segments using compass sensors to predict approaching bus stops\",\"authors\":\"Danila Chenchik, Jia Chen, S. Yan, S. Nirjon\",\"doi\":\"10.1109/PERCOMW.2017.7917604\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We devise an inexpensive and intuitive system for bus route navigation for locales where public transportation may serve as a prevalent mode of commute but where technologies that make arrival predictions through tracking vehicles in transit through GPS or other means do not exist. These systems typically require real-time monitoring of traffic variations. We provide a personalized approach where in a world of pervasive smart phone use, users may take advantage of sensor data to learn and personalize their bus routes, and alert them on time when a bus stop is approaching. We accomplish this through the development and implementation of two algorithms: 1) turn detection using on-board compass sensor of a smart phone, and 2) characterizing road segments in terms of turns and thereby predicting approaching bus stops. We conduct field experiments on a route with four selected bus stops in the town of Chapel Hill. Results show that the accuracy of turn detection and detection of approaching bus stops are 95.7% and 83%, respectively.\",\"PeriodicalId\":319638,\"journal\":{\"name\":\"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PERCOMW.2017.7917604\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOMW.2017.7917604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

我们设计了一种廉价且直观的公交路线导航系统,适用于公共交通可能是一种普遍的通勤方式,但通过GPS或其他方式跟踪交通工具来预测到达的技术还不存在的地区。这些系统通常需要实时监控交通变化。我们提供了一种个性化的方法,在智能手机普遍使用的世界里,用户可以利用传感器数据来学习和个性化他们的公交路线,并在公交车站即将到来时及时提醒他们。我们通过开发和实现两种算法来实现这一目标:1)使用智能手机的车载罗盘传感器进行转弯检测;2)根据转弯来描述路段,从而预测即将到来的公交车站。我们在教堂山镇的一条路线上进行了四个选定的公共汽车站的实地实验。结果表明,该方法的转弯检测准确率为95.7%,公交进站检测准确率为83%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Characterizing road segments using compass sensors to predict approaching bus stops
We devise an inexpensive and intuitive system for bus route navigation for locales where public transportation may serve as a prevalent mode of commute but where technologies that make arrival predictions through tracking vehicles in transit through GPS or other means do not exist. These systems typically require real-time monitoring of traffic variations. We provide a personalized approach where in a world of pervasive smart phone use, users may take advantage of sensor data to learn and personalize their bus routes, and alert them on time when a bus stop is approaching. We accomplish this through the development and implementation of two algorithms: 1) turn detection using on-board compass sensor of a smart phone, and 2) characterizing road segments in terms of turns and thereby predicting approaching bus stops. We conduct field experiments on a route with four selected bus stops in the town of Chapel Hill. Results show that the accuracy of turn detection and detection of approaching bus stops are 95.7% and 83%, respectively.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Sensitivity to web hosting in a mobile field survey NFC based dataset annotation within a behavioral alerting platform An aggregation and visualization technique for crowd-sourced continuous monitoring of transport infrastructures Trainwear: A real-time assisted training feedback system with fabric wearable sensors Toward real-time in-home activity recognition using indoor positioning sensor and power meters
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1