{"title":"BRPVis:基于乘客出行需求感知的公交线路规划可视化分析。","authors":"Qiushi Xia, Huijie Zhang, Dezhan Qu, Jinghan Bai, Cheng Lv","doi":"10.1109/MCG.2024.3454645","DOIUrl":null,"url":null,"abstract":"<p><p>Bus route planning is a complex application problem within the transportation domain, aiming to identify the best route among numerous candidate solutions. Despite existing research significantly reducing the exploration space of solutions, planners still face challenges in further exploring optimal route planning solutions. Specifically, the diversity of route attributes increases the complexity of determining their impact, such as the variety and quantity of reachable points of interest. Therefore, we present BRPVis, an interactive visual analytics system designed to assist bus route planners in exploring optimal solutions through multi-level visualization and rich interaction design. Furthermore, we propose a human-machine collaborative multicriteria decision-making method, which quantitatively analyzes the weights of route attributes while incorporating interactive feedback mechanisms to support personalized route exploration. Based on exploration using real-world traffic datasets, three case studies conducted with domain experts demonstrate that BRPVis effectively provides decision support for bus route planning tasks.</p>","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"PP ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"BRPVis: Visual Analytics for Bus Route Planning Based on Perception of Passenger Travel Demand.\",\"authors\":\"Qiushi Xia, Huijie Zhang, Dezhan Qu, Jinghan Bai, Cheng Lv\",\"doi\":\"10.1109/MCG.2024.3454645\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Bus route planning is a complex application problem within the transportation domain, aiming to identify the best route among numerous candidate solutions. Despite existing research significantly reducing the exploration space of solutions, planners still face challenges in further exploring optimal route planning solutions. Specifically, the diversity of route attributes increases the complexity of determining their impact, such as the variety and quantity of reachable points of interest. Therefore, we present BRPVis, an interactive visual analytics system designed to assist bus route planners in exploring optimal solutions through multi-level visualization and rich interaction design. Furthermore, we propose a human-machine collaborative multicriteria decision-making method, which quantitatively analyzes the weights of route attributes while incorporating interactive feedback mechanisms to support personalized route exploration. Based on exploration using real-world traffic datasets, three case studies conducted with domain experts demonstrate that BRPVis effectively provides decision support for bus route planning tasks.</p>\",\"PeriodicalId\":55026,\"journal\":{\"name\":\"IEEE Computer Graphics and Applications\",\"volume\":\"PP \",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2024-09-04\",\"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.2024.3454645\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Computer Graphics and Applications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/MCG.2024.3454645","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}
BRPVis: Visual Analytics for Bus Route Planning Based on Perception of Passenger Travel Demand.
Bus route planning is a complex application problem within the transportation domain, aiming to identify the best route among numerous candidate solutions. Despite existing research significantly reducing the exploration space of solutions, planners still face challenges in further exploring optimal route planning solutions. Specifically, the diversity of route attributes increases the complexity of determining their impact, such as the variety and quantity of reachable points of interest. Therefore, we present BRPVis, an interactive visual analytics system designed to assist bus route planners in exploring optimal solutions through multi-level visualization and rich interaction design. Furthermore, we propose a human-machine collaborative multicriteria decision-making method, which quantitatively analyzes the weights of route attributes while incorporating interactive feedback mechanisms to support personalized route exploration. Based on exploration using real-world traffic datasets, three case studies conducted with domain experts demonstrate that BRPVis effectively provides decision support for bus route planning tasks.
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.