欢迎访问《图学学报》 分享到：
图学学报

图学学报 ›› 2021, Vol. 42 ›› Issue (3): 485-491.DOI: 10.11996/JG.j.2095-302X.2021030485

• 计算机图形学与虚拟现实 • 上一篇    下一篇

可视分析增强的平行智能交通系统框架

  

  1. 1. 浙江大学 CAD & CG 国家重点实验室，浙江 杭州 310058；  2. 湖南师范大学 HPC & SIP 国家重点实验室，湖南 长沙 410000
  • 出版日期:2021-06-30 发布日期:2021-06-29
  • 基金资助:
    国家自然科学基金项目(U1909204)；湖南省教育厅重点基金项目(18A001)

Parallel intelligent transportation system framework enhanced by visual analysis  

  1. 1. State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou Zhejiang 310058, China;  2. State Key Laboratory of HPC & SIP, Hunan Normal University, Changsha Hunan 410000, China
  • Online:2021-06-30 Published:2021-06-29
  • Supported by:
    National Natural Science Foundation of China (U1909204); The Key Fund of Hunan Provincial Education Department (18A001) 

PDF (PC)

74

摘要： 随着人工智能 2.0 时代的到来，可视分析方法作为一种重要的人机耦合方法受到越发广泛的关 注。其是大数据分析的利器，也是理解数据的“导航仪”，能够有效地将三元空间结构(CPH)中的数据转换为知 识系统中的服务与决策，从而进一步提升交通系统智能化水平。为此，提出人工交通系统、计算实验和平行执 行相融合的平行智能交通系统，为智能交通领域提供了一种操控的新机制和新模式。通过分析具体案例，探讨 可视分析在新一代人工智能中的重要性，以及可视分析将数据或信息转换为知识系统的流程。证明将可视分析 与平行智能交通系统的无缝结合，能更好地分析大规模交通数据，更有效地解决交通困扰，从而实现“1+1>2” 的增强效果，据此提出新颖的可视分析增强的平行智能交通系统框架。

关键词: 可视分析, 智能交通系统, 人工系统, 计算实验, 平行执行系统

Abstract: With the advent of artificial intelligence 2.0 era, visual analysis methods have received more and more attention as an important human-machine coupling method. It is a powerful tool for big data analysis and a“navigator”for understanding data. It can effectively convert data in a ternary spatial structure (cyber-physical-human, CPH) into services and decision-making in a knowledge system, thereby further enhancing the intelligent level of transportation system. At the same time, a parallel intelligent transportation system that integrates artificial transportation system, computational experiment and parallel execution is proposed, which provides a new mechanism and new mode of manipulation in the field of intelligent transportation. Through the analysis of specific cases, we discuss the importance of visual analysis in the new generation of artificial intelligence, and the process transforming data or information into knowledge systems. It is proved that the seamless combination of visual analysis and parallel intelligent transportation system can better analyze large-scale traffic data, solve traffic problems more effectively, and achieve the enhancement effect of “1+1>2”. Based on this, a novel parallel intelligent transportation system framework enhanced by visual analysis is proposed. 

Key words: visual analytics, intelligent transportation system, artificial system, computational experiments, parallel execution system 

中图分类号: