{"title":"Visual Data Analysis of Time-Based Transport Optimizations.","authors":"Dragos C Barbu, Torsten Moller, Mike Potel","doi":"10.1109/MCG.2025.3575543","DOIUrl":null,"url":null,"abstract":"<p><p>This article proposes a novel approach to address the need for visual analysis tools in the transportation domain. Transportation planners require a tool to understand the interplay between vehicles, personnel, transported goods, and routes dynamically over time. Existing tools focus on map visualizations and are limited to animations when depicting changes over time in large amounts of data. We propose a design built from three views: absolute, relative, and topological, each showing a different data facet. We show how transport planners' trust in optimization algorithms can be achieved and how the same tool can be used to develop the optimization algorithm further.</p>","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"45 4","pages":"99-106"},"PeriodicalIF":1.4000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Computer Graphics and Applications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/MCG.2025.3575543","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
This article proposes a novel approach to address the need for visual analysis tools in the transportation domain. Transportation planners require a tool to understand the interplay between vehicles, personnel, transported goods, and routes dynamically over time. Existing tools focus on map visualizations and are limited to animations when depicting changes over time in large amounts of data. We propose a design built from three views: absolute, relative, and topological, each showing a different data facet. We show how transport planners' trust in optimization algorithms can be achieved and how the same tool can be used to develop the optimization algorithm further.
期刊介绍:
IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics, visualization, virtual and augmented reality, and HCI. From specific algorithms to full system implementations, CG&A offers a unique combination of peer-reviewed feature articles and informal departments. Theme issues guest edited by leading researchers in their fields track the latest developments and trends in computer-generated graphical content, while tutorials and surveys provide a broad overview of interesting and timely topics. Regular departments further explore the core areas of graphics as well as extend into topics such as usability, education, history, and opinion. Each issue, the story of our cover focuses on creative applications of the technology by an artist or designer. Published six times a year, CG&A is indispensable reading for people working at the leading edge of computer-generated graphics technology and its applications in everything from business to the arts.