促进可持续和个性化的旅行行为,同时保护数据隐私

Q1 Engineering Transportation Engineering Pub Date : 2025-03-01 Epub Date: 2024-12-27 DOI:10.1016/j.treng.2024.100237
Cláudia Brito , Noela Pina , Tânia Esteves , Ricardo Vitorino , Inês Cunha , João Paulo
{"title":"促进可持续和个性化的旅行行为,同时保护数据隐私","authors":"Cláudia Brito ,&nbsp;Noela Pina ,&nbsp;Tânia Esteves ,&nbsp;Ricardo Vitorino ,&nbsp;Inês Cunha ,&nbsp;João Paulo","doi":"10.1016/j.treng.2024.100237","DOIUrl":null,"url":null,"abstract":"<div><div>Cities worldwide have agreed on ambitious goals regarding carbon neutrality. To do so, policymakers seek ways to foster smarter and cleaner transportation solutions. However, citizens lack awareness of their carbon footprint and of greener mobility alternatives such as public transports. With this, three main challenges emerge: <em>(i)</em> increase users’ awareness regarding their carbon footprint, <em>(ii)</em> provide personalized recommendations and incentives for using sustainable transportation alternatives and, <em>(iii)</em> guarantee that any personal data collected from the user is kept private.</div><div>This paper addresses these challenges by proposing a new methodology. Created under the FranchetAI project, the methodology combines federated Artificial Intelligence (AI) and Greenhouse Gas (GHG) estimation models to calculate the carbon footprint of users when choosing different transportation modes (<em>e.g.</em>, foot, car, bus). Through a mobile application that keeps the privacy of users’ personal information, the project aims at providing detailed reports to inform citizens about their impact on the environment, and an incentive program to promote the usage of more sustainable mobility alternatives.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"19 ","pages":"Article 100237"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Promoting sustainable and personalized travel behaviors while preserving data privacy\",\"authors\":\"Cláudia Brito ,&nbsp;Noela Pina ,&nbsp;Tânia Esteves ,&nbsp;Ricardo Vitorino ,&nbsp;Inês Cunha ,&nbsp;João Paulo\",\"doi\":\"10.1016/j.treng.2024.100237\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Cities worldwide have agreed on ambitious goals regarding carbon neutrality. To do so, policymakers seek ways to foster smarter and cleaner transportation solutions. However, citizens lack awareness of their carbon footprint and of greener mobility alternatives such as public transports. With this, three main challenges emerge: <em>(i)</em> increase users’ awareness regarding their carbon footprint, <em>(ii)</em> provide personalized recommendations and incentives for using sustainable transportation alternatives and, <em>(iii)</em> guarantee that any personal data collected from the user is kept private.</div><div>This paper addresses these challenges by proposing a new methodology. Created under the FranchetAI project, the methodology combines federated Artificial Intelligence (AI) and Greenhouse Gas (GHG) estimation models to calculate the carbon footprint of users when choosing different transportation modes (<em>e.g.</em>, foot, car, bus). Through a mobile application that keeps the privacy of users’ personal information, the project aims at providing detailed reports to inform citizens about their impact on the environment, and an incentive program to promote the usage of more sustainable mobility alternatives.</div></div>\",\"PeriodicalId\":34480,\"journal\":{\"name\":\"Transportation Engineering\",\"volume\":\"19 \",\"pages\":\"Article 100237\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666691X24000125\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/27 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666691X24000125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/27 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

摘要

世界各地的城市已经就碳中和达成了雄心勃勃的目标。为此,政策制定者寻求更智能、更清洁的交通解决方案。然而,市民对自己的碳足迹和公共交通等更环保的交通方式缺乏认识。因此,出现了三个主要挑战:(i)提高用户对其碳足迹的认识;(ii)为使用可持续交通替代方案提供个性化建议和激励;(iii)保证从用户收集的任何个人数据都是保密的。本文通过提出一种新的方法来解决这些挑战。该方法是在FranchetAI项目下创建的,结合了联合人工智能(AI)和温室气体(GHG)估算模型,计算用户在选择不同交通方式(例如步行、汽车、公共汽车)时的碳足迹。通过一款保护用户个人信息隐私的移动应用程序,该项目旨在提供详细的报告,告知公民他们对环境的影响,并推出一项激励计划,以促进使用更可持续的移动替代方案。
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
Promoting sustainable and personalized travel behaviors while preserving data privacy
Cities worldwide have agreed on ambitious goals regarding carbon neutrality. To do so, policymakers seek ways to foster smarter and cleaner transportation solutions. However, citizens lack awareness of their carbon footprint and of greener mobility alternatives such as public transports. With this, three main challenges emerge: (i) increase users’ awareness regarding their carbon footprint, (ii) provide personalized recommendations and incentives for using sustainable transportation alternatives and, (iii) guarantee that any personal data collected from the user is kept private.
This paper addresses these challenges by proposing a new methodology. Created under the FranchetAI project, the methodology combines federated Artificial Intelligence (AI) and Greenhouse Gas (GHG) estimation models to calculate the carbon footprint of users when choosing different transportation modes (e.g., foot, car, bus). Through a mobile application that keeps the privacy of users’ personal information, the project aims at providing detailed reports to inform citizens about their impact on the environment, and an incentive program to promote the usage of more sustainable mobility alternatives.
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
Transportation Engineering
Transportation Engineering Engineering-Automotive Engineering
CiteScore
8.10
自引率
0.00%
发文量
46
审稿时长
90 days
期刊最新文献
Optimal location of urban land-uses considering transportation systems using genetic algorithm Fully automated road imagery acquisition and pavement distress mapping from Google street view using vision-language models: proof of concept Impact of cooperative autonomous vehicle platooning on highway traffic efficiency and carbon emissions Predicting subgrade compaction curves from sparse moisture-density observations Determination of the visco-hypoplastic material parameters of rolled asphalt
×
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学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
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