Schematizing car routes with their surrounding street network

IF 2.6 3区 地球科学 Q1 GEOGRAPHY Cartography and Geographic Information Science Pub Date : 2022-11-15 DOI:10.1080/15230406.2022.2125077
M. Galvão, J. Krukar, A. Schwering
{"title":"Schematizing car routes with their surrounding street network","authors":"M. Galvão, J. Krukar, A. Schwering","doi":"10.1080/15230406.2022.2125077","DOIUrl":null,"url":null,"abstract":"ABSTRACT Car drivers can benefit from schematized maps because they require a different level and type of information from different areas of the map. The technical challenge of creating such maps is that a schematic car route map should be optimized for the individual route, and yet simultaneously present the surrounding street network to support orientation. Existing schematization algorithms focus either on routes (without including the surrounding street network) or on the street network (without optimizing the route schematic layout). This paper addresses this lack of methods in schematization research and proposes an algorithm that is able to schematize both the route and the surrounding street network while resolving their conflicting layout criteria. We follow a two-step approach: we optimize the route layout criteria and afterward add the surrounding street network adapting it to the schematic route distortions. Our schematic ‘route + network’ maps aim to satisfy three requirements: (i) better readability of the route with respect to its decision points, (ii) preserving the qualitative characteristics of the surrounding street network while adapting it to route distortions, (iii) better visibility of alternative routes within the street network. A user study with six example maps validates our layout.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"50 1","pages":"20 - 43"},"PeriodicalIF":2.6000,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cartography and Geographic Information Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/15230406.2022.2125077","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 1

Abstract

ABSTRACT Car drivers can benefit from schematized maps because they require a different level and type of information from different areas of the map. The technical challenge of creating such maps is that a schematic car route map should be optimized for the individual route, and yet simultaneously present the surrounding street network to support orientation. Existing schematization algorithms focus either on routes (without including the surrounding street network) or on the street network (without optimizing the route schematic layout). This paper addresses this lack of methods in schematization research and proposes an algorithm that is able to schematize both the route and the surrounding street network while resolving their conflicting layout criteria. We follow a two-step approach: we optimize the route layout criteria and afterward add the surrounding street network adapting it to the schematic route distortions. Our schematic ‘route + network’ maps aim to satisfy three requirements: (i) better readability of the route with respect to its decision points, (ii) preserving the qualitative characteristics of the surrounding street network while adapting it to route distortions, (iii) better visibility of alternative routes within the street network. A user study with six example maps validates our layout.
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
绘制汽车路线及其周围街道网络的示意图
摘要汽车驾驶员可以从示意图中受益,因为他们需要来自地图不同区域的不同级别和类型的信息。创建此类地图的技术挑战是,应针对单个路线优化示意性汽车路线图,同时呈现周围的街道网络以支持定向。现有的示意图算法要么关注路线(不包括周围的街道网络),要么关注街道网络(不优化路线示意图布局)。本文解决了模式化研究中缺乏方法的问题,并提出了一种算法,该算法能够对路线和周围的街道网络进行模式化,同时解决它们之间冲突的布局标准。我们遵循两步走的方法:我们优化路线布局标准,然后添加周围的街道网络,使其适应示意图路线扭曲。我们的示意图路线 + 网络地图旨在满足三个要求:(i)路线相对于其决策点的可读性更好;(ii)保留周围街道网络的定性特征,同时使其适应路线失真;(iii)街道网络内备选路线的可见性更好。一份包含六个示例地图的用户研究验证了我们的布局。
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
CiteScore
5.20
自引率
20.00%
发文量
23
期刊介绍: Cartography and Geographic Information Science (CaGIS) is the official publication of the Cartography and Geographic Information Society (CaGIS), a member organization of the American Congress on Surveying and Mapping (ACSM). The Cartography and Geographic Information Society supports research, education, and practices that improve the understanding, creation, analysis, and use of maps and geographic information. The society serves as a forum for the exchange of original concepts, techniques, approaches, and experiences by those who design, implement, and use geospatial technologies through the publication of authoritative articles and international papers.
期刊最新文献
Dimensions of Uncertainty: A spatiotemporal review of five COVID-19 datasets. Algorithmic uncertainties in geolocating social media data for disaster management A study on the aptitude of color hue, value, and transparency for geographic relevance encoding in mobile maps Trust in maps: what we know and what we need to know Using machine learning and data enrichment in the selection of roads for small-scale maps
×
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