• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

BRPVis: Visual Analytics for Bus Route Planning Based on Perception of Passenger Travel Demand.

作者信息

Xia Qiushi, Zhang Huijie, Qu Dezhan, Bai Jinghan, Lv Cheng

出版信息

IEEE Comput Graph Appl. 2024 Nov-Dec;44(6):118-131. doi: 10.1109/MCG.2024.3454645. Epub 2025 Jan 7.

DOI:10.1109/MCG.2024.3454645
PMID:39231050
Abstract

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 multilevel 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.

摘要

相似文献

1
BRPVis: Visual Analytics for Bus Route Planning Based on Perception of Passenger Travel Demand.
IEEE Comput Graph Appl. 2024 Nov-Dec;44(6):118-131. doi: 10.1109/MCG.2024.3454645. Epub 2025 Jan 7.
2
Towards Better Bus Networks: A Visual Analytics Approach.
IEEE Trans Vis Comput Graph. 2021 Feb;27(2):817-827. doi: 10.1109/TVCG.2020.3030458. Epub 2021 Jan 28.
3
TriPlan: an interactive visual analytics approach for better tourism route planning.TriPlan:一种用于更好地进行旅游路线规划的交互式视觉分析方法。
J Vis (Tokyo). 2023;26(1):231-248. doi: 10.1007/s12650-022-00861-8. Epub 2022 Aug 16.
4
An Integrated Multi-Objective Optimization for Dynamic Airport Shuttle Bus Location, Route Design and Departure Frequency Setting Problem.综合考虑动态机场摆渡车选址、线路设计和发车频率设置问题的多目标优化。
Int J Environ Res Public Health. 2022 Nov 4;19(21):14469. doi: 10.3390/ijerph192114469.
5
Design of limited-stop service based on the degree of unbalance of passenger demand.基于乘客需求不平衡程度的有限停站服务设计。
PLoS One. 2018 Mar 5;13(3):e0193855. doi: 10.1371/journal.pone.0193855. eCollection 2018.
6
Traveling by Bus Instead of Car on Urban Major Roads: Safety Benefits for Vehicle Occupants, Pedestrians, and Cyclists.在城市主要道路上乘坐公共汽车而非汽车出行:对车辆乘客、行人和骑自行车者的安全益处。
J Urban Health. 2018 Apr;95(2):196-207. doi: 10.1007/s11524-017-0222-6.
7
Experts' perceptions on the use of visual analytics for complex mental healthcare planning: an exploratory study.专家对视觉分析在复杂精神卫生保健规划中应用的看法:一项探索性研究。
BMC Med Res Methodol. 2020 May 7;20(1):110. doi: 10.1186/s12874-020-00986-0.
8
FSLens: A Visual Analytics Approach to Evaluating and Optimizing the Spatial Layout of Fire Stations.
IEEE Trans Vis Comput Graph. 2024 Jan;30(1):847-857. doi: 10.1109/TVCG.2023.3327077. Epub 2023 Dec 25.
9
RCMVis: A Visual Analytics System for Route Choice Modeling.RCMVis:用于路径选择建模的可视化分析系统。
IEEE Trans Vis Comput Graph. 2023 Mar;29(3):1799-1817. doi: 10.1109/TVCG.2021.3131824. Epub 2023 Jan 30.
10
Optimization of bus stop layout considering multiple factors including passenger flow direction.考虑多个因素的公交站点布局优化,包括客流方向。
PLoS One. 2024 Nov 11;19(11):e0313040. doi: 10.1371/journal.pone.0313040. eCollection 2024.