Multiple gravity laws for human mobility within cities

IF 3 2区 计算机科学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS EPJ Data Science Pub Date : 2023-12-11 DOI:10.1140/epjds/s13688-023-00438-x
Oh-Hyun Kwon, Inho Hong, Woo-Sung Jung, Hang-Hyun Jo
{"title":"Multiple gravity laws for human mobility within cities","authors":"Oh-Hyun Kwon, Inho Hong, Woo-Sung Jung, Hang-Hyun Jo","doi":"10.1140/epjds/s13688-023-00438-x","DOIUrl":null,"url":null,"abstract":"<p>The gravity model of human mobility has successfully described the deterrence of travels with distance in urban mobility patterns. While a broad spectrum of deterrence was found across different cities, yet it is not empirically clear if movement patterns in a single city could also have a spectrum of distance exponents denoting a varying deterrence depending on the origin and destination regions in the city. By analyzing the travel data in the twelve most populated cities of the United States of America, we empirically find that the distance exponent governing the deterrence of travels significantly varies within a city depending on the traffic volumes of the origin and destination regions. Despite the diverse traffic landscape of the cities analyzed, a common pattern is observed for the distance exponents; the exponent value tends to be higher between regions with larger traffic volumes, while it tends to be lower between regions with smaller traffic volumes. This indicates that our method indeed reveals the hidden diversity of gravity laws that would be overlooked otherwise.</p>","PeriodicalId":11887,"journal":{"name":"EPJ Data Science","volume":"20 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EPJ Data Science","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1140/epjds/s13688-023-00438-x","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

The gravity model of human mobility has successfully described the deterrence of travels with distance in urban mobility patterns. While a broad spectrum of deterrence was found across different cities, yet it is not empirically clear if movement patterns in a single city could also have a spectrum of distance exponents denoting a varying deterrence depending on the origin and destination regions in the city. By analyzing the travel data in the twelve most populated cities of the United States of America, we empirically find that the distance exponent governing the deterrence of travels significantly varies within a city depending on the traffic volumes of the origin and destination regions. Despite the diverse traffic landscape of the cities analyzed, a common pattern is observed for the distance exponents; the exponent value tends to be higher between regions with larger traffic volumes, while it tends to be lower between regions with smaller traffic volumes. This indicates that our method indeed reveals the hidden diversity of gravity laws that would be overlooked otherwise.

Abstract Image

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
城市内人类流动的多重重力定律
人类流动的重力模型成功地描述了城市流动模式中旅行距离的威慑力。虽然我们发现不同城市之间存在着广泛的威慑力,但并不清楚单个城市的流动模式是否也会根据城市中出发地和目的地区域的不同而产生不同的威慑力。通过分析美国人口最多的十二个城市的出行数据,我们根据经验发现,在一个城市内,根据出发地和目的地的交通流量不同,决定出行威慑力的距离指数也有很大差异。尽管所分析的城市交通状况各不相同,但距离指数却呈现出一种共同的模式;在交通流量较大的地区之间,指数值往往较高,而在交通流量较小的地区之间,指数值往往较低。这表明,我们的方法确实揭示了万有引力定律隐藏的多样性,否则这些多样性就会被忽视。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
EPJ Data Science
EPJ Data Science MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
6.10
自引率
5.60%
发文量
53
审稿时长
13 weeks
期刊介绍: EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
期刊最新文献
Comparison of home detection algorithms using smartphone GPS data What relational event models can reveal: Commentary on Thomas Grund’s “Dynamics of Denunciation: The Limits of a Scandal” On the duration of face-to-face contacts Computational social science with confidence Public perception of generative AI on Twitter: an empirical study based on occupation and usage
×
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